00:00:00Lessons Learned From Implementing a CDP
00:15:33Overcoming Challenges in CDP Adoption
00:20:28Building a Marketing Data Community
00:35:10Leveraging CDP for Business Success
ABOUT THIS EPISODE
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Today we are joined by Sangeetha Parsan and Mary Wallace from Informa to talk about the lessons learned from rolling out a CDP at a global enterprise organization.
Sangeetha is Vice President, Professional Services at Informa. She has been in IT leadership in various capacities at Informa for several years. Prior to Informa, she was part of IT project management and technology with UBM, which was acquired by Informa. And, her early career was in solution architecture for web/CMS/Ecommerce.
Mary Wallace is Senior Director, Marketing Technology. She has held several leadership roles in Marketing, Marketing Operations and technology at Informa. Before Informa, Mary led marketing technology efforts at UBM before it was acquired by Informa. She has held roles in marketing, marketing services, IT, and project management.
Tune in to hear:
Overview of CDP Implementation: Sangeetha Parson and Mary Wallace discussed their experiences and challenges while implementing a Customer Data Platform (CDP) at Informa, a global enterprise. They emphasized the importance of enhancing customer engagement and operational efficiency through technology, particularly in response to challenges posed by the pandemic.
Strategic Deployment: The rollout of the CDP was strategic, addressing data silos by integrating data to provide a comprehensive 360-degree view of customer interactions. This integration helps in understanding customer behaviors and preferences across different business sectors of Informa, facilitating more targeted and effective marketing strategies.
Adoption and Change Management: Sangeetha and Mary highlighted the critical aspects of ensuring successful adoption of new technologies within large organizations. They underscored the necessity of engaging with different business units individually to understand their specific needs and then scaling solutions. Training, transparency, and trust were identified as key elements to foster acceptance and utilization of the CDP.
Future Outlook and AI Integration: Looking forward, the integration of AI and machine learning is seen as the next significant step to enhance the capabilities of the CDP. This advancement will allow for even more precise data analysis and segmentation, potentially transforming strategic decision-making processes and operational effectiveness at Informa.
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IN THIS EPISODE
SHOW NOTES 🔗
TRANSCRIPT 🔗
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Hello everyone, welcome to another episode of OpsCast brought to you by MarketingOpscom, powered by the MoPros out there.
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I'm your host, michael Hartman, flying solo today.
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Mike and Naomi will both be back soon, I'm sure.
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Today I am joined by Sangeetha Parson and Mary Wallace from Informa to talk about the lessons learned from rolling out a CDP at a global enterprise organization.
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Sangeetha is Vice President of Professional Services at Informa.
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She's been in IT leadership in various capacities at Informa for several years.
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Prior to Informa, she was part of IT project management technology with UBM, which was acquired by Informa, and her early career was in solution architecture for web CMS and e-commerce.
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Mary is Senior Director of Marketing Technology.
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She has held several leadership roles in marketing, marketing operations and technology at Informa.
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Before Informa, mary led marketing technology efforts at UBM, seeing a pattern here.
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Before it was acquired by Informa, she has held roles in marketing, marketing services, it and project management throughout her career.
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So, sangeetha and Mary, thank you for joining today.
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Thank you for having us.
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Very happy to be here.
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Good Thank you for joining today.
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Thank you for having us Very happy to be here.
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Good Thank you myself.
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So I'm looking forward to this because I was looking back, because I'm obsessed with like what's going on with the podcast, past episodes and what's downloaded and in our top 10 is like the one episode we've done about CDPs.
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So this one is going to strike a chord for me.
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I think hopefully it's a chord that our listeners will be interested in again, because it seems like an interesting topic and one that people are interested in and engaged with that we haven't covered much.
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The other is because a lot of the guests we talk to are more from small to medium-sized businesses, and I know that both Naomi and I have a little more of a history in medium to large-sized organizations and I don't think we get enough of that coverage here.
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So I think it hits two birds with one stone, if you will.
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So, yeah, I think what we're going to talk about is that you all have been rolling out a CDP for a little while now, at Informa, among other things, but that's part of it.
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So maybe let's if we could start with a little bit of the history behind the whole project, right?
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Why did Informa want to invest in both the technology, the infrastructure, the people, et cetera, et cetera.
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For a CDP to be a part of the organization.
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Yeah, sure, michael.
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So I think you know, with any transformation of this size, right, the key is to understand the business drivers, the goals and how technology can help drive these two right.
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I think in Informa's case it's customer engagement, because we are B2C and B2B business at the end, right, and data-driven decision-making was another key factor, coupled with the marketing operation efficiency right.
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Especially during the pandemic, it was a very key factor to get more out of less, right, and those were the initial factors that started driving it.
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And also, you know Informa or any company these days, you know there are a lot of data silos that we need to address, right, and a CDP kind of addresses that base goal of bringing everything together, helping the data take shape and tell its own stories, driven by the power of technology, whether it's compute, storage, everything comes together in a CDP to drive that goal.
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Mary, do you have any additional thoughts on that?
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yeah, I think informa understood that it needed to have like, from a strategic perspective, it needed to make a change.
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It wasn't, it couldn't be physical anymore.
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And that came back this with singing said, with the pandemic.
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And so when they understood that they needed to change and move, I think they made a lot of they made a decision that they needed a CDP right.
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We had a ton of warehouses but they weren't enough.
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We needed something to show, to Sangeetha's point, the full customer 360 degree view of the audience, what their needs were, what their wants were, and so I think it was that that kind of led us to where we are today.
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Yeah, you both have been bringing up the point about, like the pandemic and its implication on the business.
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So for our audience that's not familiar.
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Maybe I'll take a little bit of a step back and you guys can see if I get this right.
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So if you're not familiar with the business that inform is in, it fits into I always the way I tell it is to to sort of two parts to it.
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There's events, which is, I think, the big, a big part of it for for different silos or different industry specifics, and many of those businesses also have a call it, a media arm, right, so publishing content and things like that.
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But the events piece obviously is the part that I think was what you were talking about, where the physical activity had to be augmented and so, yeah, so I think that's good context for everybody.
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So the other part to understand is that this is a global company right that has you have.
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I know that when I've worked with you, all that's been in got people in the U?
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S and in Europe and in the middle East and in Asia, so just just where people are located, plus the events are global.
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Um, you know how?
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How is like.
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Do you think that adds another layer to this.
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Like the like, just the global complexities of trying to roll something like this out.
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So I think Informa's vision is to be the best at not only the biggest, but the best at events, right.
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And so I think that Michael laddered into what you were saying and I just want to call that out right, like Informa is growing rapidly, but to be the best, we needed that CDP.
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So just um.
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I know that's not answering your question, but I just want to add that in Um, as far as like rolling it out, we took it business by business, right?
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So we didn't try to do all businesses at one time.
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We looked at a sub-business within Informa, worked through that, understood their requirements, understood their business needs, rolled them out.
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Then we went to the next one.
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We understood their requirements, their business needs, and then we saw a pattern, michael, between the multiple businesses and we realized with that pattern that instead of doing all of them bespoke and separate like different, we realized that we could do them all the same with nuances, right, um.
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And so that's kind of how we approached it.
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Um.
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The last thing I'll say is I think, sangeetha, you and I are looking at like it's Starbucks, right, um.
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So all Starbucks are the same, but not all the chocolate chip cookies in Starbucks are the same.
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Yeah, to add to what Mary said, michael, I think you know the regional differences are.
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Actually they do factor in here.
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Right, there are some products during the pandemic product offerings that were doing very well in certain regions.
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You know, I do remember there was a show in Florida that actually ran during the pandemic right, but it was not the case in some other regions such as, you know, asia and other regions, but there were other product offerings which were doing extremely well in those areas.
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I think the whole concept of the CDP is to bring this insight together so you can look at it as a revenue stream right which is performing well.
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Under what conditions?
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That kind of prepares you for the future too.
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Not saying that it's going to be another event like this kind of prepares you for the future too.
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Not saying that it's going to be another event like this, but it helps you to be hyper-focused on your product offerings and revenue streams, you know to adjust to the market conditions.
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So from a strategic point of view, it sounds like, you know, cdp is like an enabler of an overall strategy to try to get deeper and closer to understanding your customers and prospects across all those lines of business, including things like knowing, like we've got a customer in this one business, they also involved with this other business in some way, is that?
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kind of a fair way of saying it.
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Yep, totally so.
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Some of our customers are attendees at one event and in another event they are a sponsor or an exhibitor, right, and so to understand that and to see those relationships has allowed the marketing teams to better segment right and to better communicate with their audience.
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It has also allowed us to say, okay, well, we didn't understand before or could see before that somebody, believe it or not who is in aviation was also in fashion, right yeah interesting.
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Isn't it Right?
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And so that changes how you communicate, that changes how you personalize, that changes how you understand your audience.
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Love that.
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Yeah, I'm sure that it's uncovered all kinds of unexpected things like that.
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So you also mentioned I think, sangeetha, you were the one who said there's you've got some businesses that are more B2C and some that are more B2B.
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How, again, how does that?
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Because I think most people who might most companies that are doing a CDP would be sort of primarily B2B or primarily B2C, and so they don't have to deal with some of the complexities.
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How have you dealt with?
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Because you talked about sort of bringing all this data together and I'll use my own word normalizing it across these businesses.
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So how do you accomplish that for both B2B and B2C?
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Then?
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It all boils down to the data points, michael.
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What data points are critical to decision-making?
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Whether it is the first-party data that we are collecting from our customers directly through event registration systems, behavioral data that comes get on our event, progress of the event, et cetera right.
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But when you bring all these data points together, like as Mary mentioned, it can go both ways right.
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You're able to understand, okay, who are your customers, who are your customers' customers, right, and who are interfacing with us day in and day out, who are only interfacing us through these events.
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I think it's just about identifying the data points, bringing them together, and then the picture actually starts to emerge by itself.
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All right, when I was working on an initial pre-CDP analysis, it was very interesting to see the bundles, how we do the digital and product offerings, how we bundle different product offerings.
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At one point that granularity was not there.
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It was going in as a bundle.
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So how do you know which product inside that bundle is performing?
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Well, that's how it was going into Salesforce as a bundle.
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But as you start to understand the data and make it more granular and granular now that could go as three different opportunity line items versus one opportunity line item Then you start to see, right, which combination is doing well.
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So I think, yeah, the data points, there could be some variances, but at the end of the day I think they all are very, very similar behavior, demographic product, you know, they fall into those major buckets.
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Got it, yeah, and I think a lot of the challenge people have is getting access to the behavioral data.
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So I know you have a ton of that that is obviously from events but also just from people's digital activity with the media properties and things like that that you now have access to.
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And technology is obviously a big technology project and big lift for that and that is not to discount it, but in my experience, right implementing the technology is one of the easier parts, even when it's complicated technology and just getting the change to kind of make its way through the organization, people to adopt it.
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How did you approach that?
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And you know, what have you learned from that process?
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I think both Sangeetha and I came at this with the background of application development, understanding that there are some keys, no matter what when you're doing an application development project, in order to have a win with the business.
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One of those was understanding the requirements upfront, working with the business, getting them to define their requirements and then coming back to them and saying is this exactly what you want?
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I think the next piece is that you need to take the business with you on the development effort.
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Right, you can't talk to them one day and say, okay, this is what we're going to build, and then six months later come back and say, okay, well, this is what we built.
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They have no idea.
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It's kind of like building a house.
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Right, If you're building a house, you want to see the construction as it's happening, because you want to weigh in and say I want the wall to be blue, I want the doorknob to be silver, whatever.
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So we've done that.
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We've taken A overtly defined requirements with the business and got them to commit to them.
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And B, we took the business on the journey on the construction project, on the development effort.
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And then C, we've done a lot in terms of building out documentation explaining how things work.
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We built out training, massive training, where we go in for two and a half days, we work with the business.
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We train them on the tool, we train them on slightly new ways of working, better ways of working and then, last but not least, we're now starting to ladder in change management.
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So what are your expectations, what are you expecting to accomplish and what are your current processes and how you're going to turn slightly on those processes to better use this technology.
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Mary went with her ABCs.
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I'm going to go with three Ts, all right.
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One is transparency, as she mentioned.
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They need to know what the processes, what the problems are.
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If the data is not perfect, it's not perfect, you know.
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Present it as it is right.
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The second T I call it as it is right.
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The second T I call it is the trust right.
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Get them to use the data before they come onto the platform.
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Get them to test the data right, so that way the trust in the data builds from day one.
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And I think the third and final T is what Mary mentioned train, train and train right, so that your confidence also builds up along with you know the trust.
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ABCs and the three Ts.
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I like that.
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So, yeah, I think that's all been good.
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What have been the biggest challenges with that adoption?
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Right, because it sounds like you've got a pretty strong sort of approach in place, but I suspect, yeah, any anything like this.
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Right, people are used to what they're doing and so anything change someone mentioned that said this in a recent other episode, so it's like change is hard, right, and it's like it's a simple thing, but it's true still so.
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How did you have you still?
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So?
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What are your challenges and how have you addressed those?
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I think to me the biggest challenge if I were an end user.
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I've seen my data in a certain way.
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I've seen it in green bucket and pink bucket and purple bucket, going with Mary's analogy.
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And green bucket and pink bucket and purple bucket, you know, going with Mary's analogy, but I've never seen the blocks coming together to you know, build a house per se, right?
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I think that is a change in perspective.
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Right, it's still the same data, it's just that now it is interlinked.
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You know you're getting a new view of it.
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So, I think, getting them to think that through.
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You know what is unification and the next challenge is, I mean, unification is a very key concept in a CDP right Now.
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The next challenge is to agree that it's in-form mass data.
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Right, yes, the brands generate it, the brands maintain it, the brands own it, but at the end of the day, it's in-form mass data.
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So, as Mary mentioned, if a person is in aviation and they are in fashion, our first thought process is something is wrong with the data.
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Right, but it is a different, wider picture that we have to see here.
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Well, nothing's wrong with the data.
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We are just getting an enhanced view of the data, right, understanding that your world has expanded a little bit right?
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I believe those are two.
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You know initial challenges people have to overcome even before you get to the tool right.
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And I'll defer to Mary because she does a ton of training and you know she has seen the struggles that they face on the field.
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So I'll say I'll come back and say there's three challenges.
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I will do circle, square and triangle.
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Okay, since we did the ABCs and the three Ts, now we have circle, square and triangle.
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So I think the first one is we struggled with a lack of ability to show success right.
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First one is we struggled with a lack of ability to show success right.
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We knew there was a success because more people were using it, People were going to it, people were choosing that CDP platform.
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But we struggled with metrics of success.
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I did it the old way and this was my conversion ratio.
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I did it the new way and it was, you know, plus 0.5% or plus 0.1, 0.7% or whatever.
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So we struggled to show that using the CDP actually produced better results.
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Um, I think we struggled with respect at some point, right.
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So it was well, what do you know and why do you know it?
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And all that other stuff.
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I think we had to win over the business and win over that.
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This was this technology solution was producing a business solution.
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It wasn't all about technology.
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We understood the business.
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Trust us, we understand the business.
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And then, last but not least, I think there's in marketing today, I think there's a lot of change fatigue, right, if you look at the metrics, the adoption of technology within marketing, marketing ops, it's not what it was a couple of years ago, right, and so we had to struggle.
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That's the world in general and that's also in Forma in particular, and so I think that change fatigue we had to struggle through.
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Yeah, it's interesting because I think there's no.
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Is there change fatigue?
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It's like I think there's just fatigue in general.
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I think these teams are all moving so fast that anything that, even if they believe that it's going to be helpful, right, that the process of the change feels like it's going to be painful and make things take longer and it may not be quote in quotes, right, right, um, I hear that a lot about data in particular, and my view is that, especially in the B2B world marketing and sales data if you think it's quote right, you've missed the boat.
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It's not right.
00:20:58.632 --> 00:21:01.523
It's just not going to be like financial data in general.
00:21:01.523 --> 00:21:10.667
We don't have the controls, got a lot of humans involved, so it's going to be rife with stuff that doesn't make sense.
00:21:10.667 --> 00:21:20.399
So you're already I think you're fighting an uphill battle when you start pulling it together for multiple businesses where they think they know what's right in their business data but maybe not in the other ones.
00:21:20.399 --> 00:21:23.785
So have you experienced, like is that part of the challenge too?
00:21:23.785 --> 00:21:31.761
Are you just seeing that kind of thing, or is it more of the resistance, because it's just different and you don't know my business?
00:21:33.234 --> 00:21:35.143
I think it's a bit of both, Michael.
00:21:35.143 --> 00:21:36.820
It's human nature, right.
00:21:36.820 --> 00:21:42.387
When something is different, your immediate reaction is is it right, Is it right?
00:21:42.387 --> 00:21:52.976
But I think the more tender, loving care you give, the more connection you have, then it is getting better, which is what we are seeing in the results.
00:21:55.701 --> 00:21:56.081
Gotcha.
00:21:56.081 --> 00:22:08.625
So, Mary, you mentioned about how to measure the impact, right.
00:22:08.625 --> 00:22:21.248
So what are some of the results that you all have seen from rolling out the CDP and I know it's still a work in progress have you evolved how you're measuring it in terms of the overall program?
00:22:27.221 --> 00:22:30.469
I think, michael, it's still a work in progress, to your point right.
00:22:30.469 --> 00:22:33.624
I think we have seen successes.
00:22:33.624 --> 00:22:36.619
We have shouted those successes, right?
00:22:36.619 --> 00:22:46.047
So the other day, somebody said, you know, unique open rates was up by 20 some percent.
00:22:46.047 --> 00:22:51.781
Conversion rates was like astronomical in terms of improvements.
00:22:51.781 --> 00:22:54.156
It was an isolated case that we could show a win.
00:22:54.156 --> 00:23:04.307
And so we took that isolated case and we are shouting it from the rooftops, right, this is, you know, this is what somebody did, this is what is achievable.
00:23:05.494 --> 00:23:06.921
Yeah, it's what's possible, right.
00:23:07.734 --> 00:23:09.096
Yeah, a hundred percent.
00:23:09.096 --> 00:23:29.344
We had one where we were able to, because we're pulling in all this data now and unifying all this data we were able to see, based on IP address, like location, where somebody was at right and we were able to take that data that they never had before.
00:23:29.344 --> 00:23:43.547
And we were able to take that data that they never had before and we were able to convert people, and so that was again a win, because that was something that had never been achievable before and all of a sudden understanding where somebody is based on their location and converting them.
00:23:43.547 --> 00:23:45.057
That was a win.
00:23:45.057 --> 00:23:46.545
So that's, I think, where we're doing.
00:23:46.545 --> 00:24:02.090
It is kind of these isolated cases but then shouting really loud Look what we did, look what we did Kind of like Super Bowl champs, right, they shout for a long time oh, I was the you know XXX Super Bowl champ.
00:24:04.115 --> 00:24:04.995
So using that methodology?
00:24:04.995 --> 00:24:11.625
Yeah, it's, it's storytelling right, which resonates with everybody.
00:24:13.009 --> 00:24:13.471
Storytelling.
00:24:14.240 --> 00:24:28.553
I'm going to talk about the other side of the coin, right, I think, the processing power and the functionality and features that a CDP has brought to us.
00:24:28.553 --> 00:24:34.805
It's opened a whole new set of avenues, right?
00:24:34.805 --> 00:24:43.653
Data that we thought we couldn't process before, connections that we thought we couldn't do before, and those are all happening.
00:24:43.653 --> 00:24:46.297
We can see that coming right now.
00:24:46.297 --> 00:24:58.428
It's about also putting on a new pair of lens and seeing okay, how can we utilize these connections?
00:24:58.428 --> 00:24:59.172
What else can we do with it?
00:24:59.172 --> 00:25:02.201
I think that is where AI comes in, because this is not something a human can process, right?
00:25:02.201 --> 00:25:11.729
So our job is to collect the data, bring the data in a meaningful way, give it to the CDP and then the power comes with the AI and ML capabilities.
00:25:11.729 --> 00:25:18.071
You know that can be built on top of the data that is unified and cleaned up and standardized in the CTP.
00:25:20.360 --> 00:25:39.317
Yeah, so when you tell those stories about the wins, is that helping when you're talking to additional other teams that are kind of maybe just getting started or have been slower to really adopt the technology?
00:25:39.317 --> 00:25:41.001
Has it been helpful with that?
00:25:43.466 --> 00:25:44.649
It 100% has.
00:25:44.649 --> 00:25:47.756
We now have in our toolkit.
00:25:47.756 --> 00:25:51.961
We have 20, 30 different examples of this is what this team did.
00:25:51.961 --> 00:25:53.042
This is what this team did.
00:25:53.042 --> 00:25:54.124
This is what this team did.
00:25:54.124 --> 00:25:55.605
Examples of this is what this team did.
00:25:55.605 --> 00:25:56.326
This is what this team did.
00:25:56.326 --> 00:25:57.768
This is what this team did, and we're not shy, we tout them out.
00:25:57.768 --> 00:25:58.687
We tout them out in training.
00:25:58.687 --> 00:26:02.251
We tout them out when we start, you know, an onboarding process.
00:26:02.251 --> 00:26:18.264
I will say and Sangeeta, I think they're coming to us now, I think it started where we were going to them saying look, you got to do this.
00:26:18.325 --> 00:26:20.168
You got to do this, you got to do this and I think now they're coming to us.
00:26:20.168 --> 00:26:24.238
Yeah, and Mary's team has done an amazing job with taking it to the customers right.
00:26:24.238 --> 00:26:34.903
The marketing forum Every interaction we have is showcasing those wins, bringing awareness and building a community together.
00:26:34.903 --> 00:26:39.866
Right, I think it makes people oh you know what I could try that that situation applies to me.
00:26:39.866 --> 00:26:44.109
Those ideas are bouncing back and forth, which is interesting to see.
00:26:44.109 --> 00:26:47.048
At some point, I don't think we don't even have to be in the middle.
00:26:47.048 --> 00:26:53.413
The community has gotten that powerful that they are starting off themselves on experimenting things.
00:26:54.740 --> 00:26:56.228
That's interesting, the idea of a community.
00:26:56.228 --> 00:26:59.047
Now there's these people.
00:26:59.047 --> 00:27:09.833
It's like proof points because this podcast is part of more of a public community, but I see the power every day of people helping each other from that standpoint.
00:27:09.833 --> 00:27:22.375
So internally, it almost sounds like one of the byproducts of doing this now has been the sort of building of that community of marketers across all these businesses who now have a place.
00:27:22.375 --> 00:27:29.854
Maybe it wasn't intentional but right, but it's a place now where they can all communicate and share ideas that they may or may not have had before.
00:27:29.854 --> 00:27:35.712
I mean, I'm sure there were internal relationships one on one in small groups, but not in a broader sense like this.
00:27:35.712 --> 00:27:39.590
Has that been a surprise that you've been able to do that with this?
00:27:42.000 --> 00:27:43.587
I think we intentionally did it, Michael.
00:27:44.903 --> 00:27:48.771
Ah, okay, I think we fostered the community.
00:27:49.559 --> 00:27:57.222
No, no, but I think we fostered the community right and we knew that we needed that groundswell and we knew that we needed.
00:27:57.222 --> 00:28:07.311
If one marketer is saying it's good to another marketer who's afraid, it's far more powerful than me saying that you need to do it.
00:28:07.311 --> 00:28:10.068
So we did it with intention.
00:28:12.661 --> 00:28:14.385
I think it's the IT 101, michael People process and technology.
00:28:14.385 --> 00:28:15.008
In that order right.
00:28:15.008 --> 00:28:17.194
That's the it 101 michael people process and technology.
00:28:17.194 --> 00:28:18.317
In that order right.
00:28:18.317 --> 00:28:21.243
That's the formula absolutely.
00:28:22.165 --> 00:28:39.922
Yeah, it's funny because when I've when I've struggled with getting people to adopt or go through a change process, one of the things I've learned is to find the people who are the most um, the ones who are least interested in it, and I always know if I can get them convinced that it's going to be useful and beneficial.
00:28:39.922 --> 00:28:44.748
My job is basically mostly done because then they'll be the ones who convince everybody else.
00:28:47.100 --> 00:28:51.833
I'm sneaky like that yeah, so all right.
00:28:51.833 --> 00:28:54.321
So more to come on that.
00:28:54.321 --> 00:29:02.367
So you mentioned you know additional things that you get.
00:29:02.367 --> 00:29:04.690
What are some of the big next steps that are coming up?
00:29:04.690 --> 00:29:10.074
I know it's like it sounds like like how far into the whole rollout process are you of?
00:29:10.074 --> 00:29:14.257
You know all the different businesses and then beyond that?
00:29:17.626 --> 00:29:18.570
what do you see in the long run?
00:29:18.570 --> 00:29:23.743
I think, in terms of coverage, we are making really really good progress.
00:29:23.743 --> 00:29:26.951
Like, as Mary mentioned, it's a slow and steady progress, right, bringing people along with us.
00:29:26.951 --> 00:29:37.174
For some of the divisions in Informa again, there are multiple for people who don't know Informa, but for some of the divisions, we covered more than 60 percent ground.
00:29:37.174 --> 00:29:40.210
You know some are between 40 to 50 percent.
00:29:40.600 --> 00:29:51.350
I think the major shift is coming in 2025 because our people and our processes are now very aligned and you know we are free to move with the technology change.
00:29:51.350 --> 00:30:02.514
All right, so as to what is exciting that is coming next, like I mentioned, all right, so far it's been about data collection, data transformation.
00:30:02.514 --> 00:30:04.923
Right now we are going to see the power of ai.
00:30:04.923 --> 00:30:11.561
Um, because you know we are going to the cdp world soon and in the previous cdp world we attended.
00:30:11.601 --> 00:30:16.393
I think one of the things that caught our eyes was LLM-based segmentation.
00:30:16.393 --> 00:30:22.172
Right, you don't have to say, okay, pull in the country, pull in the consent.
00:30:22.172 --> 00:30:26.126
You just have to say give me all the people in the country with this consent.
00:30:26.126 --> 00:30:30.506
You know, right, the one-liner and the tool is able to build that for you.
00:30:30.506 --> 00:31:02.270
I think that is really really exciting, right, as a marketer that opens up the arena for experimentation, and think that is really really exciting, right, as a marketer that opens up the arena for experimentation, and it's going to be a cool technology to see, mary, anything else on your radar that you want to bring on for the next steps, yeah, so I'm going to go back to you mentioned AI and I think we had to take this step and get the data organized, get good quality data and I think, with that good quality data, then the AI agents will sit on top of it.
00:31:02.681 --> 00:31:07.311
I think if we hadn't done this, I think the AI thing would have been like all over the place.
00:31:07.311 --> 00:31:26.923
So I think that's one piece in terms of next steps, and I think the other thing, michael, is to continue to roll out data maturity and like how the business and marketers use maturity right or, excuse me, mature in their use of data.
00:31:26.923 --> 00:31:29.932
I think that's a next step that we need to take.
00:31:32.721 --> 00:31:36.016
When you say that, what do you mean by that data maturity?
00:31:36.016 --> 00:31:37.642
Is it like understanding data?
00:31:37.642 --> 00:31:45.947
Is it identifying issues with data that can go be addressed through, like upstream processes and technology, or is it it might?
00:31:45.947 --> 00:31:47.112
Is it something completely different?
00:31:47.413 --> 00:31:48.475
it's so.
00:31:48.475 --> 00:32:00.187
It's understanding the point that a data collection is where you have the most control and the marketers are the ones that are at the data collection, collecting the data initially.
00:32:00.187 --> 00:32:07.330
So how that gets organized, how that gets structured, getting them to understand that is point one.
00:32:07.330 --> 00:32:15.743
Point two is how do you take the data you've collected, whether it's express data and somebody typed it in, or whether it's implied data and it's.
00:32:15.743 --> 00:32:37.061
Back to the Sangeetha's website that she talked about earlier and how you take that data and run analytics across it to be smarter and to predict what somebody wants and to be able to say, okay, what's the next best action and what is my key audience and how do I continue to like excite them.
00:32:37.061 --> 00:32:44.694
All that requires a maturity in data that I think we kind of need to like usher forward.
00:32:46.200 --> 00:32:57.672
Yeah, and to add to what Mary said previously right, proving the ROI, proving the results, has always been a problem, especially in digital marketing.
00:32:57.672 --> 00:33:02.511
Right, because you have several channels, several campaigns, several touch points.
00:33:02.511 --> 00:33:03.740
How do you know?
00:33:03.740 --> 00:33:11.013
You know, in a multi-touch environment like this, how do you know which one is converting better if you don't track in a certain way?
00:33:11.013 --> 00:33:18.734
Right, and I think you know, in terms of lessons learned, that is something we have to be focusing on to see how can we track.
00:33:18.734 --> 00:33:27.019
All right, every activity we do, every campaign we do, you know we have to think about okay, is there a mechanism to track it?
00:33:27.019 --> 00:33:30.729
Is there a mechanism to bring that data back into the CDP?
00:33:30.729 --> 00:33:35.970
And if we did, I think that's an area where we really need to improve on going forward.
00:33:36.881 --> 00:33:49.561
So the tracking of the results of things either done via the CDP and the other tools that are part of the ecosystem there, or if they're done separately, right, how do you capture those after the fact?
00:33:49.561 --> 00:33:51.305
Okay, that makes sense.
00:33:51.305 --> 00:33:55.652
It's interesting, mary, you talked about the that data maturity.
00:33:55.652 --> 00:33:57.375
My head went immediately to.
00:33:58.461 --> 00:34:02.132
I hear people regularly say oh, like our data, everyone's data is crap.
00:34:02.132 --> 00:34:08.711
Right, everyone says their data is crap, salesforce data is crap, marketing data is crap, and they're hesitant to do reporting.
00:34:08.711 --> 00:34:16.492
And I was like just know it's crap, right, do the reporting anyway, because that will uncover and expose where stuff is broken.
00:34:16.492 --> 00:34:41.490
And yeah, I've got a number of scenarios in my career where I've seen like doing reporting is identified oh, there's a problem with the way that you know the marketing team is deploying assets to the market, or the sales team is recording stuff in Salesforce or like whatever it is, and like it feels like that could be a big part of this by itself.
00:34:41.490 --> 00:34:42.862
Right, just getting that insight.
00:34:42.862 --> 00:34:44.508
Are you also looking at?
00:34:44.508 --> 00:34:46.014
You mentioned predictive.
00:34:46.014 --> 00:34:56.522
So are you really like are you trying to put on top of this things like predictive modeling tools to help drive other parts of the business, whether it's website interactions or I don't even know what else.
00:34:56.522 --> 00:34:57.644
So many things.
00:34:59.268 --> 00:35:01.093
I don't think we can be competitive if we don't.
00:35:01.093 --> 00:35:07.121
I think we need that AI, I think we need that predictive, you know, the modeling and all that other stuff.
00:35:07.121 --> 00:35:10.449
If we're not, we're not going to be competitive.
00:35:10.449 --> 00:35:12.682
I can see Sangeetha wants to say something.
00:35:14.250 --> 00:35:16.562
And yes, absolutely, mary, you were spot on.
00:35:16.562 --> 00:35:22.523
And it also goes to a deeper understanding of what our customers are doing right Intent and all that.
00:35:22.523 --> 00:35:28.782
The more we know, the better we can position ourselves, the better we can write content right.
00:35:28.782 --> 00:35:40.444
It's going to have a full-on effect, as we we know their behaviors, not just oh, you went to this page, but what were you actually looking for on the page?
00:35:40.444 --> 00:35:43.752
Is there a pattern as to where you went yesterday, right?
00:35:43.752 --> 00:35:50.905
I think that's where we need to go, uh, for the next step interesting and you've talked a lot about doing stuff with marketing.
00:35:50.945 --> 00:35:55.762
Are there, like, are there other teams that you see where this is going to be valuable down the road as well?
00:35:55.762 --> 00:36:03.967
And when you said marketing, I assume it's mostly been with, like I'll call it demand gen, right People doing promotional activity mostly.
00:36:03.988 --> 00:36:07.274
I think, content sales.
00:36:07.274 --> 00:36:14.833
We are trying to extend into those areas, mary, anything you wanted to add from the new use cases that are emerging?
00:36:21.340 --> 00:36:22.465
I think it's content and sales, michael.
00:36:22.465 --> 00:36:23.167
How can we better create content?
00:36:23.167 --> 00:36:24.673
How can we create content that's personalized?
00:36:24.673 --> 00:36:25.918
How can we create content that resonates better?
00:36:25.918 --> 00:36:29.027
So I think that's one, and then how can sales use this data better?
00:36:29.027 --> 00:36:31.292
I think that's the second one.
00:36:31.740 --> 00:36:32.843
Do salespeople know how to do that?
00:36:32.843 --> 00:36:35.531
I'm kidding, I'm only half kidding.
00:36:35.531 --> 00:36:37.176
Actually they do.
00:36:37.336 --> 00:36:42.552
Yeah, some of them are really sharp, really smart, and they understand how to use the data to sell.
00:36:45.181 --> 00:36:52.975
Some of the people that were so excited when looking at the insights that were coming out of the CDP data were actually the salespeople, Michael.
00:36:52.975 --> 00:36:57.646
They saw the potential that opens up, you know, for them with this kind of insights.
00:36:58.327 --> 00:36:58.749
That's great.
00:36:58.749 --> 00:37:03.248
You may have talked about this, but others so.
00:37:03.248 --> 00:37:06.263
Are you also like?
00:37:06.263 --> 00:37:18.950
Are you identifying and sharing sort of general insights about your audience as well across, like different parts of the business, sort of separate from what we'll call the tactical, like go-to-market activities themselves?
00:37:18.950 --> 00:37:23.089
Like you know, this is what the profile of our typical customer looks like.
00:37:23.089 --> 00:37:28.246
They're, you know, they're engaged with multiple these two businesses on average.
00:37:28.246 --> 00:37:35.170
Like that kind of that kind of stuff, or are you really focused on more of the go-to-market activity stuff?
00:37:37.545 --> 00:37:41.354
so I think, michael, we're starting to transition.
00:37:41.354 --> 00:38:03.969
I think, um, it was scott vaughn right who talked about understanding the customer, understanding the audience and creating an audience strategy, and I think that is kind of that is where we're going right, and so I guess I think that's the key getting that data, understanding it, understand the audience and then building the strategy on top of that.
00:38:05.601 --> 00:38:11.313
And I would like to add that you know there are standard dashboards that are built on this data right.
00:38:11.313 --> 00:38:13.849
Are we doing enough to bring that to light?
00:38:13.849 --> 00:38:14.324
Yes, we data right.
00:38:14.324 --> 00:38:15.215
Are we doing enough to bring that to light?
00:38:15.215 --> 00:38:15.580
Yes, we are right.
00:38:15.580 --> 00:38:22.388
There are personal dashboards where you can build a segment and, you know, find out whatever you need about those uses.
00:38:22.388 --> 00:38:29.114
So that level of awareness is created as part of our training sessions that Mary mentioned.
00:38:29.114 --> 00:38:33.412
But I think you know we can do a better job of following up on how are they using it.
00:38:33.412 --> 00:38:35.568
You know what are they doing with this data they get.
00:38:35.568 --> 00:38:38.126
So there is definitely room for improvement there.
00:38:39.307 --> 00:38:40.973
Got it All right.
00:38:40.973 --> 00:38:44.571
You mentioned CDP World, which is, I think, coming up.
00:38:44.571 --> 00:38:47.459
We're recording this mid-late September 2024.
00:38:47.459 --> 00:38:50.507
And it's about a month away, if I remember right.
00:38:50.507 --> 00:38:51.611
Maybe not quite.
00:38:51.611 --> 00:38:54.086
What are you all going to be talking about there?
00:39:05.501 --> 00:39:11.321
How we drove adoption across a global company, what the steps were um, how we excited, how we shouted the wins um and how we thought you know, a couple years ago we didn't think we're going to make it.
00:39:11.321 --> 00:39:12.122
Here we are, we're making it.
00:39:12.122 --> 00:39:17.310
So you didn't think we were going to make it, and here we are, we're making it so you didn't think you were going to make it.
00:39:17.551 --> 00:39:37.315
I don't believe that well, there were times I remember what was it like n73 or something like that way back when it was like one one time we wanted to push out and and do an activation and it was months to do that one activation.
00:39:37.315 --> 00:39:39.664
Now they're doing them many a day.
00:39:41.027 --> 00:39:45.198
Amazing Right Well, so I'm glad you shared it.
00:39:45.198 --> 00:39:49.805
It sounds like we got a little preview for our audience, or for those who can't make it to CDP World.
00:39:52.449 --> 00:39:54.271
And for whoever want to make it.
00:39:54.271 --> 00:39:56.194
I believe the registrations are still open.
00:39:57.035 --> 00:39:57.436
They are.
00:39:57.436 --> 00:39:59.565
I checked today they're still open.
00:39:59.585 --> 00:40:00.267
I was looking, it's in.
00:40:00.287 --> 00:40:02.272
Vegas, las Vegas.
00:40:02.272 --> 00:40:04.165
See, that's the reason for me not to go.
00:40:06.050 --> 00:40:06.672
Michael.
00:40:08.484 --> 00:40:13.543
I'm not a Las Vegas fan, you know.
00:40:13.543 --> 00:40:21.284
It's all right, it's all good, like it's just not my cup of tea, right so?
00:40:21.284 --> 00:40:25.490
But I'm sure that content is going to be great.
00:40:25.490 --> 00:40:31.827
Um, we covered a lot of ground here already, but is there anything that we didn't talk about that you want to make sure our audience heard about?
00:40:33.711 --> 00:40:35.374
Yeah, I do have one thing right.
00:40:35.374 --> 00:40:40.168
I know CDP is a new toy, new technology right.
00:40:40.168 --> 00:40:46.346
Before anybody wants to dive into it, right, just think through that right.
00:40:46.346 --> 00:40:51.240
First thing I believe you should think about is your data ready for this right?
00:40:51.240 --> 00:40:53.687
That's something that I'm very passionate about.
00:40:53.687 --> 00:40:57.544
Just because you can get a new toy, don't get a new toy right.
00:40:57.544 --> 00:41:02.074
Be prepared and also choose a good partner, which is very crucial.
00:41:02.074 --> 00:41:04.771
You know some people have in-house development teams.
00:41:04.771 --> 00:41:11.089
If not, if you're looking for a partner, make sure there is a skill set match, make sure there is a business buy-in.
00:41:11.089 --> 00:41:14.443
Then go into it right.
00:41:14.443 --> 00:41:19.282
That would be your surefire way to get success with the CDP implementation.
00:41:19.282 --> 00:41:24.450
Mary.
00:41:24.771 --> 00:41:26.954
I think it's being in it for the long haul.
00:41:26.954 --> 00:41:34.512
You can't be in it for a short term when you have to be in it for the long haul and I think you have to be in it with a win in mind.
00:41:34.512 --> 00:41:48.289
Right, this is what you want to accomplish and go after that North Star versus being in it because, hey, CDP is the new cool buzzword and everybody understands maps are.
00:41:48.289 --> 00:41:55.648
They are good, but they are not what they used to be, and so, understanding that it's not about the technology but about a business win.
00:41:58.172 --> 00:41:59.535
Love it Awesome.
00:41:59.535 --> 00:42:03.731
Well, it's been fun both of you, so thanks for joining.
00:42:03.731 --> 00:42:08.512
I know it's a late evening for some of us, so thank you.
00:42:08.512 --> 00:42:17.146
If folks want to keep up with what y'all are doing or reach out to you or learn more about CDPs, what's the best way for them to do that?
00:42:19.581 --> 00:42:30.550
First off, thank you for giving us this opportunity, Michael, you know it was very insightful, thought-provoking questions, I think Mary and I are both on LinkedIn.
00:42:30.550 --> 00:42:33.590
We are happy to share our profile links.
00:42:33.590 --> 00:42:41.728
That's probably the best way to ping us and reach us, and we'll be happy to share our journey in depth if needed.
00:42:44.252 --> 00:42:45.414
Mary, anything else from you?
00:42:47.821 --> 00:42:50.069
Thanks, michael, this has been fun, this has been great.
00:42:51.200 --> 00:42:59.224
Oh, good, well, and I know, maryary, you do write occasionally on linkedin, so and so I've seen those articles, you, or what do they?
00:42:59.224 --> 00:43:00.186
What does linkedin call them?
00:43:00.186 --> 00:43:01.811
They call them contributed articles.
00:43:01.811 --> 00:43:02.421
Is that what it is?
00:43:02.421 --> 00:43:05.170
I can't even remember what they call it now, I don't I don't know.
00:43:05.290 --> 00:43:05.981
I think it changed.
00:43:05.981 --> 00:43:15.019
I'm too lazy to do those once a quarter is my goal yeah that's good, all right well she's your editor.
00:43:18.426 --> 00:43:20.350
Well, good, well, thank you both appreciate it.
00:43:20.350 --> 00:43:23.582
Thanks to our listeners for continuing to support us, as always.
00:43:23.582 --> 00:43:33.131
If you have ideas for guests or topics that you want to share, or if you want to be a guest, reach out to mike naomi or me, and until next time, bye, everyone, okay, bye.
00:00:23.771 --> 00:00:29.094
Hello everyone, welcome to another episode of OpsCast brought to you by MarketingOpscom, powered by the MoPros out there.
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I'm your host, michael Hartman, flying solo today.
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Mike and Naomi will both be back soon, I'm sure.
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Today I am joined by Sangeetha Parson and Mary Wallace from Informa to talk about the lessons learned from rolling out a CDP at a global enterprise organization.
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Sangeetha is Vice President of Professional Services at Informa.
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She's been in IT leadership in various capacities at Informa for several years.
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Prior to Informa, she was part of IT project management technology with UBM, which was acquired by Informa, and her early career was in solution architecture for web CMS and e-commerce.
00:01:02.509 --> 00:01:05.530
Mary is Senior Director of Marketing Technology.
00:01:05.530 --> 00:01:11.376
She has held several leadership roles in marketing, marketing operations and technology at Informa.
00:01:11.376 --> 00:01:15.858
Before Informa, mary led marketing technology efforts at UBM, seeing a pattern here.
00:01:15.858 --> 00:01:22.117
Before it was acquired by Informa, she has held roles in marketing, marketing services, it and project management throughout her career.
00:01:22.117 --> 00:01:24.658
So, sangeetha and Mary, thank you for joining today.
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Thank you for having us.
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Very happy to be here.
00:01:27.858 --> 00:01:28.581
Good Thank you for joining today.
00:01:28.600 --> 00:01:29.826
Thank you for having us Very happy to be here.
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Good Thank you myself.
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So I'm looking forward to this because I was looking back, because I'm obsessed with like what's going on with the podcast, past episodes and what's downloaded and in our top 10 is like the one episode we've done about CDPs.
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So this one is going to strike a chord for me.
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I think hopefully it's a chord that our listeners will be interested in again, because it seems like an interesting topic and one that people are interested in and engaged with that we haven't covered much.
00:02:00.790 --> 00:02:15.737
The other is because a lot of the guests we talk to are more from small to medium-sized businesses, and I know that both Naomi and I have a little more of a history in medium to large-sized organizations and I don't think we get enough of that coverage here.
00:02:15.737 --> 00:02:18.879
So I think it hits two birds with one stone, if you will.
00:02:18.879 --> 00:02:33.219
So, yeah, I think what we're going to talk about is that you all have been rolling out a CDP for a little while now, at Informa, among other things, but that's part of it.
00:02:33.219 --> 00:02:39.756
So maybe let's if we could start with a little bit of the history behind the whole project, right?
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Why did Informa want to invest in both the technology, the infrastructure, the people, et cetera, et cetera.
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For a CDP to be a part of the organization.
00:02:53.890 --> 00:02:54.663
Yeah, sure, michael.
00:02:54.663 --> 00:03:10.061
So I think you know, with any transformation of this size, right, the key is to understand the business drivers, the goals and how technology can help drive these two right.
00:03:10.061 --> 00:03:27.699
I think in Informa's case it's customer engagement, because we are B2C and B2B business at the end, right, and data-driven decision-making was another key factor, coupled with the marketing operation efficiency right.
00:03:27.699 --> 00:03:38.723
Especially during the pandemic, it was a very key factor to get more out of less, right, and those were the initial factors that started driving it.
00:03:38.723 --> 00:04:03.621
And also, you know Informa or any company these days, you know there are a lot of data silos that we need to address, right, and a CDP kind of addresses that base goal of bringing everything together, helping the data take shape and tell its own stories, driven by the power of technology, whether it's compute, storage, everything comes together in a CDP to drive that goal.
00:04:07.070 --> 00:04:09.254
Mary, do you have any additional thoughts on that?
00:04:09.615 --> 00:04:20.686
yeah, I think informa understood that it needed to have like, from a strategic perspective, it needed to make a change.
00:04:20.686 --> 00:04:23.230
It wasn't, it couldn't be physical anymore.
00:04:23.230 --> 00:04:26.375
And that came back this with singing said, with the pandemic.
00:04:26.375 --> 00:04:36.486
And so when they understood that they needed to change and move, I think they made a lot of they made a decision that they needed a CDP right.
00:04:36.486 --> 00:04:41.341
We had a ton of warehouses but they weren't enough.
00:04:41.341 --> 00:04:54.341
We needed something to show, to Sangeetha's point, the full customer 360 degree view of the audience, what their needs were, what their wants were, and so I think it was that that kind of led us to where we are today.
00:04:55.971 --> 00:05:00.591
Yeah, you both have been bringing up the point about, like the pandemic and its implication on the business.
00:05:00.591 --> 00:05:03.437
So for our audience that's not familiar.
00:05:03.437 --> 00:05:06.875
Maybe I'll take a little bit of a step back and you guys can see if I get this right.
00:05:06.875 --> 00:05:13.620
So if you're not familiar with the business that inform is in, it fits into I always the way I tell it is to to sort of two parts to it.
00:05:13.620 --> 00:05:27.998
There's events, which is, I think, the big, a big part of it for for different silos or different industry specifics, and many of those businesses also have a call it, a media arm, right, so publishing content and things like that.
00:05:27.998 --> 00:05:40.883
But the events piece obviously is the part that I think was what you were talking about, where the physical activity had to be augmented and so, yeah, so I think that's good context for everybody.
00:05:41.309 --> 00:05:46.533
So the other part to understand is that this is a global company right that has you have.
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I know that when I've worked with you, all that's been in got people in the U?
00:05:50.553 --> 00:05:58.455
S and in Europe and in the middle East and in Asia, so just just where people are located, plus the events are global.
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Um, you know how?
00:06:00.880 --> 00:06:02.303
How is like.
00:06:02.303 --> 00:06:04.815
Do you think that adds another layer to this.
00:06:04.815 --> 00:06:08.984
Like the like, just the global complexities of trying to roll something like this out.
00:06:10.571 --> 00:06:18.465
So I think Informa's vision is to be the best at not only the biggest, but the best at events, right.
00:06:18.465 --> 00:06:32.793
And so I think that Michael laddered into what you were saying and I just want to call that out right, like Informa is growing rapidly, but to be the best, we needed that CDP.
00:06:32.793 --> 00:06:35.259
So just um.
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I know that's not answering your question, but I just want to add that in Um, as far as like rolling it out, we took it business by business, right?
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So we didn't try to do all businesses at one time.
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We looked at a sub-business within Informa, worked through that, understood their requirements, understood their business needs, rolled them out.
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Then we went to the next one.
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We understood their requirements, their business needs, and then we saw a pattern, michael, between the multiple businesses and we realized with that pattern that instead of doing all of them bespoke and separate like different, we realized that we could do them all the same with nuances, right, um.
00:07:15.981 --> 00:07:17.971
And so that's kind of how we approached it.
00:07:17.971 --> 00:07:18.874
Um.
00:07:18.874 --> 00:07:24.734
The last thing I'll say is I think, sangeetha, you and I are looking at like it's Starbucks, right, um.
00:07:24.734 --> 00:07:31.884
So all Starbucks are the same, but not all the chocolate chip cookies in Starbucks are the same.
00:07:35.030 --> 00:07:41.058
Yeah, to add to what Mary said, michael, I think you know the regional differences are.
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Actually they do factor in here.
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Right, there are some products during the pandemic product offerings that were doing very well in certain regions.
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You know, I do remember there was a show in Florida that actually ran during the pandemic right, but it was not the case in some other regions such as, you know, asia and other regions, but there were other product offerings which were doing extremely well in those areas.
00:08:09.289 --> 00:08:21.355
I think the whole concept of the CDP is to bring this insight together so you can look at it as a revenue stream right which is performing well.
00:08:21.355 --> 00:08:22.899
Under what conditions?
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That kind of prepares you for the future too.
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Not saying that it's going to be another event like this kind of prepares you for the future too.
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Not saying that it's going to be another event like this, but it helps you to be hyper-focused on your product offerings and revenue streams, you know to adjust to the market conditions.
00:08:43.730 --> 00:09:04.331
So from a strategic point of view, it sounds like, you know, cdp is like an enabler of an overall strategy to try to get deeper and closer to understanding your customers and prospects across all those lines of business, including things like knowing, like we've got a customer in this one business, they also involved with this other business in some way, is that?
00:09:04.350 --> 00:09:05.151
kind of a fair way of saying it.
00:09:05.151 --> 00:09:07.336
Yep, totally so.
00:09:07.336 --> 00:09:29.745
Some of our customers are attendees at one event and in another event they are a sponsor or an exhibitor, right, and so to understand that and to see those relationships has allowed the marketing teams to better segment right and to better communicate with their audience.
00:09:29.745 --> 00:09:43.958
It has also allowed us to say, okay, well, we didn't understand before or could see before that somebody, believe it or not who is in aviation was also in fashion, right yeah interesting.
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Isn't it Right?
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And so that changes how you communicate, that changes how you personalize, that changes how you understand your audience.
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Love that.
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Yeah, I'm sure that it's uncovered all kinds of unexpected things like that.
00:10:01.680 --> 00:10:10.362
So you also mentioned I think, sangeetha, you were the one who said there's you've got some businesses that are more B2C and some that are more B2B.
00:10:10.362 --> 00:10:15.274
How, again, how does that?
00:10:15.274 --> 00:10:25.909
Because I think most people who might most companies that are doing a CDP would be sort of primarily B2B or primarily B2C, and so they don't have to deal with some of the complexities.
00:10:25.909 --> 00:10:28.251
How have you dealt with?
00:10:28.251 --> 00:10:36.538
Because you talked about sort of bringing all this data together and I'll use my own word normalizing it across these businesses.
00:10:36.538 --> 00:10:41.160
So how do you accomplish that for both B2B and B2C?
00:10:41.160 --> 00:10:41.380
Then?
00:10:43.141 --> 00:10:47.084
It all boils down to the data points, michael.
00:10:47.084 --> 00:10:50.247
What data points are critical to decision-making?
00:10:50.247 --> 00:11:13.659
Whether it is the first-party data that we are collecting from our customers directly through event registration systems, behavioral data that comes get on our event, progress of the event, et cetera right.
00:11:13.659 --> 00:11:20.870
But when you bring all these data points together, like as Mary mentioned, it can go both ways right.
00:11:20.870 --> 00:11:34.597
You're able to understand, okay, who are your customers, who are your customers' customers, right, and who are interfacing with us day in and day out, who are only interfacing us through these events.
00:11:34.597 --> 00:11:43.646
I think it's just about identifying the data points, bringing them together, and then the picture actually starts to emerge by itself.
00:11:48.209 --> 00:11:59.625
All right, when I was working on an initial pre-CDP analysis, it was very interesting to see the bundles, how we do the digital and product offerings, how we bundle different product offerings.
00:11:59.625 --> 00:12:04.260
At one point that granularity was not there.
00:12:04.260 --> 00:12:06.398
It was going in as a bundle.
00:12:06.398 --> 00:12:10.812
So how do you know which product inside that bundle is performing?
00:12:10.812 --> 00:12:14.558
Well, that's how it was going into Salesforce as a bundle.
00:12:14.558 --> 00:12:31.312
But as you start to understand the data and make it more granular and granular now that could go as three different opportunity line items versus one opportunity line item Then you start to see, right, which combination is doing well.
00:12:31.312 --> 00:12:45.113
So I think, yeah, the data points, there could be some variances, but at the end of the day I think they all are very, very similar behavior, demographic product, you know, they fall into those major buckets.
00:12:48.179 --> 00:12:53.991
Got it, yeah, and I think a lot of the challenge people have is getting access to the behavioral data.
00:12:53.991 --> 00:13:03.150
So I know you have a ton of that that is obviously from events but also just from people's digital activity with the media properties and things like that that you now have access to.
00:13:03.150 --> 00:13:25.930
And technology is obviously a big technology project and big lift for that and that is not to discount it, but in my experience, right implementing the technology is one of the easier parts, even when it's complicated technology and just getting the change to kind of make its way through the organization, people to adopt it.
00:13:25.930 --> 00:13:30.524
How did you approach that?
00:13:30.524 --> 00:13:33.644
And you know, what have you learned from that process?
00:13:38.155 --> 00:13:53.175
I think both Sangeetha and I came at this with the background of application development, understanding that there are some keys, no matter what when you're doing an application development project, in order to have a win with the business.
00:13:53.175 --> 00:14:04.999
One of those was understanding the requirements upfront, working with the business, getting them to define their requirements and then coming back to them and saying is this exactly what you want?
00:14:04.999 --> 00:14:12.209
I think the next piece is that you need to take the business with you on the development effort.
00:14:12.209 --> 00:14:21.586
Right, you can't talk to them one day and say, okay, this is what we're going to build, and then six months later come back and say, okay, well, this is what we built.
00:14:21.586 --> 00:14:22.797
They have no idea.
00:14:22.797 --> 00:14:24.302
It's kind of like building a house.
00:14:24.302 --> 00:14:34.567
Right, If you're building a house, you want to see the construction as it's happening, because you want to weigh in and say I want the wall to be blue, I want the doorknob to be silver, whatever.
00:14:34.567 --> 00:14:36.250
So we've done that.
00:14:36.735 --> 00:14:41.266
We've taken A overtly defined requirements with the business and got them to commit to them.
00:14:41.266 --> 00:14:46.126
And B, we took the business on the journey on the construction project, on the development effort.
00:14:46.126 --> 00:14:55.889
And then C, we've done a lot in terms of building out documentation explaining how things work.
00:14:55.889 --> 00:15:04.581
We built out training, massive training, where we go in for two and a half days, we work with the business.
00:15:04.581 --> 00:15:17.587
We train them on the tool, we train them on slightly new ways of working, better ways of working and then, last but not least, we're now starting to ladder in change management.
00:15:17.587 --> 00:15:31.367
So what are your expectations, what are you expecting to accomplish and what are your current processes and how you're going to turn slightly on those processes to better use this technology.
00:15:33.795 --> 00:15:35.643
Mary went with her ABCs.
00:15:35.643 --> 00:15:37.742
I'm going to go with three Ts, all right.
00:15:37.742 --> 00:15:40.403
One is transparency, as she mentioned.
00:15:40.403 --> 00:15:44.044
They need to know what the processes, what the problems are.
00:15:44.044 --> 00:15:46.755
If the data is not perfect, it's not perfect, you know.
00:15:46.755 --> 00:15:48.702
Present it as it is right.
00:15:48.702 --> 00:15:49.841
The second T I call it as it is right.
00:15:49.841 --> 00:15:51.793
The second T I call it is the trust right.
00:15:51.793 --> 00:15:56.586
Get them to use the data before they come onto the platform.
00:15:56.586 --> 00:16:01.985
Get them to test the data right, so that way the trust in the data builds from day one.
00:16:01.985 --> 00:16:13.286
And I think the third and final T is what Mary mentioned train, train and train right, so that your confidence also builds up along with you know the trust.
00:16:17.254 --> 00:16:18.559
ABCs and the three Ts.
00:16:18.559 --> 00:16:19.062
I like that.
00:16:19.062 --> 00:16:24.533
So, yeah, I think that's all been good.
00:16:24.533 --> 00:16:29.185
What have been the biggest challenges with that adoption?
00:16:29.185 --> 00:16:37.649
Right, because it sounds like you've got a pretty strong sort of approach in place, but I suspect, yeah, any anything like this.
00:16:37.649 --> 00:16:48.957
Right, people are used to what they're doing and so anything change someone mentioned that said this in a recent other episode, so it's like change is hard, right, and it's like it's a simple thing, but it's true still so.
00:16:48.957 --> 00:16:51.802
How did you have you still?
00:16:51.802 --> 00:16:52.004
So?
00:16:52.004 --> 00:16:55.228
What are your challenges and how have you addressed those?
00:16:56.914 --> 00:17:02.447
I think to me the biggest challenge if I were an end user.
00:17:02.447 --> 00:17:04.943
I've seen my data in a certain way.
00:17:04.943 --> 00:17:10.556
I've seen it in green bucket and pink bucket and purple bucket, going with Mary's analogy.
00:17:10.556 --> 00:17:18.278
And green bucket and pink bucket and purple bucket, you know, going with Mary's analogy, but I've never seen the blocks coming together to you know, build a house per se, right?
00:17:18.278 --> 00:17:20.299
I think that is a change in perspective.
00:17:20.299 --> 00:17:24.862
Right, it's still the same data, it's just that now it is interlinked.
00:17:24.862 --> 00:17:27.023
You know you're getting a new view of it.
00:17:27.023 --> 00:17:29.983
So, I think, getting them to think that through.
00:17:30.003 --> 00:17:37.846
You know what is unification and the next challenge is, I mean, unification is a very key concept in a CDP right Now.
00:17:37.846 --> 00:17:42.869
The next challenge is to agree that it's in-form mass data.
00:17:42.869 --> 00:17:50.613
Right, yes, the brands generate it, the brands maintain it, the brands own it, but at the end of the day, it's in-form mass data.
00:17:50.613 --> 00:18:01.341
So, as Mary mentioned, if a person is in aviation and they are in fashion, our first thought process is something is wrong with the data.
00:18:01.341 --> 00:18:04.248
Right, but it is a different, wider picture that we have to see here.
00:18:04.248 --> 00:18:06.298
Well, nothing's wrong with the data.
00:18:06.298 --> 00:18:13.705
We are just getting an enhanced view of the data, right, understanding that your world has expanded a little bit right?
00:18:13.705 --> 00:18:15.402
I believe those are two.
00:18:15.402 --> 00:18:20.301
You know initial challenges people have to overcome even before you get to the tool right.
00:18:20.301 --> 00:18:29.484
And I'll defer to Mary because she does a ton of training and you know she has seen the struggles that they face on the field.
00:18:31.995 --> 00:18:35.326
So I'll say I'll come back and say there's three challenges.
00:18:35.326 --> 00:18:38.869
I will do circle, square and triangle.
00:18:38.869 --> 00:18:43.774
Okay, since we did the ABCs and the three Ts, now we have circle, square and triangle.
00:18:43.774 --> 00:18:51.269
So I think the first one is we struggled with a lack of ability to show success right.
00:18:51.269 --> 00:18:56.623
First one is we struggled with a lack of ability to show success right.
00:18:56.623 --> 00:19:01.196
We knew there was a success because more people were using it, People were going to it, people were choosing that CDP platform.
00:19:01.196 --> 00:19:05.046
But we struggled with metrics of success.
00:19:05.046 --> 00:19:09.057
I did it the old way and this was my conversion ratio.
00:19:09.057 --> 00:19:16.064
I did it the new way and it was, you know, plus 0.5% or plus 0.1, 0.7% or whatever.
00:19:16.064 --> 00:19:22.757
So we struggled to show that using the CDP actually produced better results.
00:19:22.757 --> 00:19:29.004
Um, I think we struggled with respect at some point, right.
00:19:29.165 --> 00:19:33.211
So it was well, what do you know and why do you know it?
00:19:33.211 --> 00:19:34.096
And all that other stuff.
00:19:34.096 --> 00:19:39.406
I think we had to win over the business and win over that.
00:19:39.406 --> 00:19:44.903
This was this technology solution was producing a business solution.
00:19:44.903 --> 00:19:46.687
It wasn't all about technology.
00:19:46.687 --> 00:19:48.355
We understood the business.
00:19:48.355 --> 00:19:49.916
Trust us, we understand the business.
00:19:49.916 --> 00:20:10.931
And then, last but not least, I think there's in marketing today, I think there's a lot of change fatigue, right, if you look at the metrics, the adoption of technology within marketing, marketing ops, it's not what it was a couple of years ago, right, and so we had to struggle.
00:20:10.931 --> 00:20:21.608
That's the world in general and that's also in Forma in particular, and so I think that change fatigue we had to struggle through.
00:20:23.735 --> 00:20:25.701
Yeah, it's interesting because I think there's no.
00:20:25.701 --> 00:20:26.805
Is there change fatigue?
00:20:26.805 --> 00:20:29.339
It's like I think there's just fatigue in general.
00:20:29.339 --> 00:20:57.770
I think these teams are all moving so fast that anything that, even if they believe that it's going to be helpful, right, that the process of the change feels like it's going to be painful and make things take longer and it may not be quote in quotes, right, right, um, I hear that a lot about data in particular, and my view is that, especially in the B2B world marketing and sales data if you think it's quote right, you've missed the boat.
00:20:58.050 --> 00:20:58.632
It's not right.
00:20:58.632 --> 00:21:01.523
It's just not going to be like financial data in general.
00:21:01.523 --> 00:21:10.667
We don't have the controls, got a lot of humans involved, so it's going to be rife with stuff that doesn't make sense.
00:21:10.667 --> 00:21:20.399
So you're already I think you're fighting an uphill battle when you start pulling it together for multiple businesses where they think they know what's right in their business data but maybe not in the other ones.
00:21:20.399 --> 00:21:23.785
So have you experienced, like is that part of the challenge too?
00:21:23.785 --> 00:21:31.761
Are you just seeing that kind of thing, or is it more of the resistance, because it's just different and you don't know my business?
00:21:33.234 --> 00:21:35.143
I think it's a bit of both, Michael.
00:21:35.143 --> 00:21:36.820
It's human nature, right.
00:21:36.820 --> 00:21:42.387
When something is different, your immediate reaction is is it right, Is it right?
00:21:42.387 --> 00:21:52.976
But I think the more tender, loving care you give, the more connection you have, then it is getting better, which is what we are seeing in the results.
00:21:55.701 --> 00:21:56.081
Gotcha.
00:21:56.081 --> 00:22:08.625
So, Mary, you mentioned about how to measure the impact, right.
00:22:08.625 --> 00:22:21.248
So what are some of the results that you all have seen from rolling out the CDP and I know it's still a work in progress have you evolved how you're measuring it in terms of the overall program?
00:22:27.221 --> 00:22:30.469
I think, michael, it's still a work in progress, to your point right.
00:22:30.469 --> 00:22:33.624
I think we have seen successes.
00:22:33.624 --> 00:22:36.619
We have shouted those successes, right?
00:22:36.619 --> 00:22:46.047
So the other day, somebody said, you know, unique open rates was up by 20 some percent.
00:22:46.047 --> 00:22:51.781
Conversion rates was like astronomical in terms of improvements.
00:22:51.781 --> 00:22:54.156
It was an isolated case that we could show a win.
00:22:54.156 --> 00:23:04.307
And so we took that isolated case and we are shouting it from the rooftops, right, this is, you know, this is what somebody did, this is what is achievable.
00:23:05.494 --> 00:23:06.921
Yeah, it's what's possible, right.
00:23:07.734 --> 00:23:09.096
Yeah, a hundred percent.
00:23:09.096 --> 00:23:29.344
We had one where we were able to, because we're pulling in all this data now and unifying all this data we were able to see, based on IP address, like location, where somebody was at right and we were able to take that data that they never had before.
00:23:29.344 --> 00:23:43.547
And we were able to take that data that they never had before and we were able to convert people, and so that was again a win, because that was something that had never been achievable before and all of a sudden understanding where somebody is based on their location and converting them.
00:23:43.547 --> 00:23:45.057
That was a win.
00:23:45.057 --> 00:23:46.545
So that's, I think, where we're doing.
00:23:46.545 --> 00:24:02.090
It is kind of these isolated cases but then shouting really loud Look what we did, look what we did Kind of like Super Bowl champs, right, they shout for a long time oh, I was the you know XXX Super Bowl champ.
00:24:04.115 --> 00:24:04.995
So using that methodology?
00:24:04.995 --> 00:24:11.625
Yeah, it's, it's storytelling right, which resonates with everybody.
00:24:13.009 --> 00:24:13.471
Storytelling.
00:24:14.240 --> 00:24:28.553
I'm going to talk about the other side of the coin, right, I think, the processing power and the functionality and features that a CDP has brought to us.
00:24:28.553 --> 00:24:34.805
It's opened a whole new set of avenues, right?
00:24:34.805 --> 00:24:43.653
Data that we thought we couldn't process before, connections that we thought we couldn't do before, and those are all happening.
00:24:43.653 --> 00:24:46.297
We can see that coming right now.
00:24:46.297 --> 00:24:58.428
It's about also putting on a new pair of lens and seeing okay, how can we utilize these connections?
00:24:58.428 --> 00:24:59.172
What else can we do with it?
00:24:59.172 --> 00:25:02.201
I think that is where AI comes in, because this is not something a human can process, right?
00:25:02.201 --> 00:25:11.729
So our job is to collect the data, bring the data in a meaningful way, give it to the CDP and then the power comes with the AI and ML capabilities.
00:25:11.729 --> 00:25:18.071
You know that can be built on top of the data that is unified and cleaned up and standardized in the CTP.
00:25:20.360 --> 00:25:39.317
Yeah, so when you tell those stories about the wins, is that helping when you're talking to additional other teams that are kind of maybe just getting started or have been slower to really adopt the technology?
00:25:39.317 --> 00:25:41.001
Has it been helpful with that?
00:25:43.466 --> 00:25:44.649
It 100% has.
00:25:44.649 --> 00:25:47.756
We now have in our toolkit.
00:25:47.756 --> 00:25:51.961
We have 20, 30 different examples of this is what this team did.
00:25:51.961 --> 00:25:53.042
This is what this team did.
00:25:53.042 --> 00:25:54.124
This is what this team did.
00:25:54.124 --> 00:25:55.605
Examples of this is what this team did.
00:25:55.605 --> 00:25:56.326
This is what this team did.
00:25:56.326 --> 00:25:57.768
This is what this team did, and we're not shy, we tout them out.
00:25:57.768 --> 00:25:58.687
We tout them out in training.
00:25:58.687 --> 00:26:02.251
We tout them out when we start, you know, an onboarding process.
00:26:02.251 --> 00:26:18.264
I will say and Sangeeta, I think they're coming to us now, I think it started where we were going to them saying look, you got to do this.
00:26:18.325 --> 00:26:20.168
You got to do this, you got to do this and I think now they're coming to us.
00:26:20.168 --> 00:26:24.238
Yeah, and Mary's team has done an amazing job with taking it to the customers right.
00:26:24.238 --> 00:26:34.903
The marketing forum Every interaction we have is showcasing those wins, bringing awareness and building a community together.
00:26:34.903 --> 00:26:39.866
Right, I think it makes people oh you know what I could try that that situation applies to me.
00:26:39.866 --> 00:26:44.109
Those ideas are bouncing back and forth, which is interesting to see.
00:26:44.109 --> 00:26:47.048
At some point, I don't think we don't even have to be in the middle.
00:26:47.048 --> 00:26:53.413
The community has gotten that powerful that they are starting off themselves on experimenting things.
00:26:54.740 --> 00:26:56.228
That's interesting, the idea of a community.
00:26:56.228 --> 00:26:59.047
Now there's these people.
00:26:59.047 --> 00:27:09.833
It's like proof points because this podcast is part of more of a public community, but I see the power every day of people helping each other from that standpoint.
00:27:09.833 --> 00:27:22.375
So internally, it almost sounds like one of the byproducts of doing this now has been the sort of building of that community of marketers across all these businesses who now have a place.
00:27:22.375 --> 00:27:29.854
Maybe it wasn't intentional but right, but it's a place now where they can all communicate and share ideas that they may or may not have had before.
00:27:29.854 --> 00:27:35.712
I mean, I'm sure there were internal relationships one on one in small groups, but not in a broader sense like this.
00:27:35.712 --> 00:27:39.590
Has that been a surprise that you've been able to do that with this?
00:27:42.000 --> 00:27:43.587
I think we intentionally did it, Michael.
00:27:44.903 --> 00:27:48.771
Ah, okay, I think we fostered the community.
00:27:49.559 --> 00:27:57.222
No, no, but I think we fostered the community right and we knew that we needed that groundswell and we knew that we needed.
00:27:57.222 --> 00:28:07.311
If one marketer is saying it's good to another marketer who's afraid, it's far more powerful than me saying that you need to do it.
00:28:07.311 --> 00:28:10.068
So we did it with intention.
00:28:12.661 --> 00:28:14.385
I think it's the IT 101, michael People process and technology.
00:28:14.385 --> 00:28:15.008
In that order right.
00:28:15.008 --> 00:28:17.194
That's the it 101 michael people process and technology.
00:28:17.194 --> 00:28:18.317
In that order right.
00:28:18.317 --> 00:28:21.243
That's the formula absolutely.
00:28:22.165 --> 00:28:39.922
Yeah, it's funny because when I've when I've struggled with getting people to adopt or go through a change process, one of the things I've learned is to find the people who are the most um, the ones who are least interested in it, and I always know if I can get them convinced that it's going to be useful and beneficial.
00:28:39.922 --> 00:28:44.748
My job is basically mostly done because then they'll be the ones who convince everybody else.
00:28:47.100 --> 00:28:51.833
I'm sneaky like that yeah, so all right.
00:28:51.833 --> 00:28:54.321
So more to come on that.
00:28:54.321 --> 00:29:02.367
So you mentioned you know additional things that you get.
00:29:02.367 --> 00:29:04.690
What are some of the big next steps that are coming up?
00:29:04.690 --> 00:29:10.074
I know it's like it sounds like like how far into the whole rollout process are you of?
00:29:10.074 --> 00:29:14.257
You know all the different businesses and then beyond that?
00:29:17.626 --> 00:29:18.570
what do you see in the long run?
00:29:18.570 --> 00:29:23.743
I think, in terms of coverage, we are making really really good progress.
00:29:23.743 --> 00:29:26.951
Like, as Mary mentioned, it's a slow and steady progress, right, bringing people along with us.
00:29:26.951 --> 00:29:37.174
For some of the divisions in Informa again, there are multiple for people who don't know Informa, but for some of the divisions, we covered more than 60 percent ground.
00:29:37.174 --> 00:29:40.210
You know some are between 40 to 50 percent.
00:29:40.600 --> 00:29:51.350
I think the major shift is coming in 2025 because our people and our processes are now very aligned and you know we are free to move with the technology change.
00:29:51.350 --> 00:30:02.514
All right, so as to what is exciting that is coming next, like I mentioned, all right, so far it's been about data collection, data transformation.
00:30:02.514 --> 00:30:04.923
Right now we are going to see the power of ai.
00:30:04.923 --> 00:30:11.561
Um, because you know we are going to the cdp world soon and in the previous cdp world we attended.
00:30:11.601 --> 00:30:16.393
I think one of the things that caught our eyes was LLM-based segmentation.
00:30:16.393 --> 00:30:22.172
Right, you don't have to say, okay, pull in the country, pull in the consent.
00:30:22.172 --> 00:30:26.126
You just have to say give me all the people in the country with this consent.
00:30:26.126 --> 00:30:30.506
You know, right, the one-liner and the tool is able to build that for you.
00:30:30.506 --> 00:31:02.270
I think that is really really exciting, right, as a marketer that opens up the arena for experimentation, and think that is really really exciting, right, as a marketer that opens up the arena for experimentation, and it's going to be a cool technology to see, mary, anything else on your radar that you want to bring on for the next steps, yeah, so I'm going to go back to you mentioned AI and I think we had to take this step and get the data organized, get good quality data and I think, with that good quality data, then the AI agents will sit on top of it.
00:31:02.681 --> 00:31:07.311
I think if we hadn't done this, I think the AI thing would have been like all over the place.
00:31:07.311 --> 00:31:26.923
So I think that's one piece in terms of next steps, and I think the other thing, michael, is to continue to roll out data maturity and like how the business and marketers use maturity right or, excuse me, mature in their use of data.
00:31:26.923 --> 00:31:29.932
I think that's a next step that we need to take.
00:31:32.721 --> 00:31:36.016
When you say that, what do you mean by that data maturity?
00:31:36.016 --> 00:31:37.642
Is it like understanding data?
00:31:37.642 --> 00:31:45.947
Is it identifying issues with data that can go be addressed through, like upstream processes and technology, or is it it might?
00:31:45.947 --> 00:31:47.112
Is it something completely different?
00:31:47.413 --> 00:31:48.475
it's so.
00:31:48.475 --> 00:32:00.187
It's understanding the point that a data collection is where you have the most control and the marketers are the ones that are at the data collection, collecting the data initially.
00:32:00.187 --> 00:32:07.330
So how that gets organized, how that gets structured, getting them to understand that is point one.
00:32:07.330 --> 00:32:15.743
Point two is how do you take the data you've collected, whether it's express data and somebody typed it in, or whether it's implied data and it's.
00:32:15.743 --> 00:32:37.061
Back to the Sangeetha's website that she talked about earlier and how you take that data and run analytics across it to be smarter and to predict what somebody wants and to be able to say, okay, what's the next best action and what is my key audience and how do I continue to like excite them.
00:32:37.061 --> 00:32:44.694
All that requires a maturity in data that I think we kind of need to like usher forward.
00:32:46.200 --> 00:32:57.672
Yeah, and to add to what Mary said previously right, proving the ROI, proving the results, has always been a problem, especially in digital marketing.
00:32:57.672 --> 00:33:02.511
Right, because you have several channels, several campaigns, several touch points.
00:33:02.511 --> 00:33:03.740
How do you know?
00:33:03.740 --> 00:33:11.013
You know, in a multi-touch environment like this, how do you know which one is converting better if you don't track in a certain way?
00:33:11.013 --> 00:33:18.734
Right, and I think you know, in terms of lessons learned, that is something we have to be focusing on to see how can we track.
00:33:18.734 --> 00:33:27.019
All right, every activity we do, every campaign we do, you know we have to think about okay, is there a mechanism to track it?
00:33:27.019 --> 00:33:30.729
Is there a mechanism to bring that data back into the CDP?
00:33:30.729 --> 00:33:35.970
And if we did, I think that's an area where we really need to improve on going forward.
00:33:36.881 --> 00:33:49.561
So the tracking of the results of things either done via the CDP and the other tools that are part of the ecosystem there, or if they're done separately, right, how do you capture those after the fact?
00:33:49.561 --> 00:33:51.305
Okay, that makes sense.
00:33:51.305 --> 00:33:55.652
It's interesting, mary, you talked about the that data maturity.
00:33:55.652 --> 00:33:57.375
My head went immediately to.
00:33:58.461 --> 00:34:02.132
I hear people regularly say oh, like our data, everyone's data is crap.
00:34:02.132 --> 00:34:08.711
Right, everyone says their data is crap, salesforce data is crap, marketing data is crap, and they're hesitant to do reporting.
00:34:08.711 --> 00:34:16.492
And I was like just know it's crap, right, do the reporting anyway, because that will uncover and expose where stuff is broken.
00:34:16.492 --> 00:34:41.490
And yeah, I've got a number of scenarios in my career where I've seen like doing reporting is identified oh, there's a problem with the way that you know the marketing team is deploying assets to the market, or the sales team is recording stuff in Salesforce or like whatever it is, and like it feels like that could be a big part of this by itself.
00:34:41.490 --> 00:34:42.862
Right, just getting that insight.
00:34:42.862 --> 00:34:44.508
Are you also looking at?
00:34:44.508 --> 00:34:46.014
You mentioned predictive.
00:34:46.014 --> 00:34:56.522
So are you really like are you trying to put on top of this things like predictive modeling tools to help drive other parts of the business, whether it's website interactions or I don't even know what else.
00:34:56.522 --> 00:34:57.644
So many things.
00:34:59.268 --> 00:35:01.093
I don't think we can be competitive if we don't.
00:35:01.093 --> 00:35:07.121
I think we need that AI, I think we need that predictive, you know, the modeling and all that other stuff.
00:35:07.121 --> 00:35:10.449
If we're not, we're not going to be competitive.
00:35:10.449 --> 00:35:12.682
I can see Sangeetha wants to say something.
00:35:14.250 --> 00:35:16.562
And yes, absolutely, mary, you were spot on.
00:35:16.562 --> 00:35:22.523
And it also goes to a deeper understanding of what our customers are doing right Intent and all that.
00:35:22.523 --> 00:35:28.782
The more we know, the better we can position ourselves, the better we can write content right.
00:35:28.782 --> 00:35:40.444
It's going to have a full-on effect, as we we know their behaviors, not just oh, you went to this page, but what were you actually looking for on the page?
00:35:40.444 --> 00:35:43.752
Is there a pattern as to where you went yesterday, right?
00:35:43.752 --> 00:35:50.905
I think that's where we need to go, uh, for the next step interesting and you've talked a lot about doing stuff with marketing.
00:35:50.945 --> 00:35:55.762
Are there, like, are there other teams that you see where this is going to be valuable down the road as well?
00:35:55.762 --> 00:36:03.967
And when you said marketing, I assume it's mostly been with, like I'll call it demand gen, right People doing promotional activity mostly.
00:36:03.988 --> 00:36:07.274
I think, content sales.
00:36:07.274 --> 00:36:14.833
We are trying to extend into those areas, mary, anything you wanted to add from the new use cases that are emerging?
00:36:21.340 --> 00:36:22.465
I think it's content and sales, michael.
00:36:22.465 --> 00:36:23.167
How can we better create content?
00:36:23.167 --> 00:36:24.673
How can we create content that's personalized?
00:36:24.673 --> 00:36:25.918
How can we create content that resonates better?
00:36:25.918 --> 00:36:29.027
So I think that's one, and then how can sales use this data better?
00:36:29.027 --> 00:36:31.292
I think that's the second one.
00:36:31.740 --> 00:36:32.843
Do salespeople know how to do that?
00:36:32.843 --> 00:36:35.531
I'm kidding, I'm only half kidding.
00:36:35.531 --> 00:36:37.176
Actually they do.
00:36:37.336 --> 00:36:42.552
Yeah, some of them are really sharp, really smart, and they understand how to use the data to sell.
00:36:45.181 --> 00:36:52.975
Some of the people that were so excited when looking at the insights that were coming out of the CDP data were actually the salespeople, Michael.
00:36:52.975 --> 00:36:57.646
They saw the potential that opens up, you know, for them with this kind of insights.
00:36:58.327 --> 00:36:58.749
That's great.
00:36:58.749 --> 00:37:03.248
You may have talked about this, but others so.
00:37:03.248 --> 00:37:06.263
Are you also like?
00:37:06.263 --> 00:37:18.950
Are you identifying and sharing sort of general insights about your audience as well across, like different parts of the business, sort of separate from what we'll call the tactical, like go-to-market activities themselves?
00:37:18.950 --> 00:37:23.089
Like you know, this is what the profile of our typical customer looks like.
00:37:23.089 --> 00:37:28.246
They're, you know, they're engaged with multiple these two businesses on average.
00:37:28.246 --> 00:37:35.170
Like that kind of that kind of stuff, or are you really focused on more of the go-to-market activity stuff?
00:37:37.545 --> 00:37:41.354
so I think, michael, we're starting to transition.
00:37:41.354 --> 00:38:03.969
I think, um, it was scott vaughn right who talked about understanding the customer, understanding the audience and creating an audience strategy, and I think that is kind of that is where we're going right, and so I guess I think that's the key getting that data, understanding it, understand the audience and then building the strategy on top of that.
00:38:05.601 --> 00:38:11.313
And I would like to add that you know there are standard dashboards that are built on this data right.
00:38:11.313 --> 00:38:13.849
Are we doing enough to bring that to light?
00:38:13.849 --> 00:38:14.324
Yes, we data right.
00:38:14.324 --> 00:38:15.215
Are we doing enough to bring that to light?
00:38:15.215 --> 00:38:15.580
Yes, we are right.
00:38:15.580 --> 00:38:22.388
There are personal dashboards where you can build a segment and, you know, find out whatever you need about those uses.
00:38:22.388 --> 00:38:29.114
So that level of awareness is created as part of our training sessions that Mary mentioned.
00:38:29.114 --> 00:38:33.412
But I think you know we can do a better job of following up on how are they using it.
00:38:33.412 --> 00:38:35.568
You know what are they doing with this data they get.
00:38:35.568 --> 00:38:38.126
So there is definitely room for improvement there.
00:38:39.307 --> 00:38:40.973
Got it All right.
00:38:40.973 --> 00:38:44.571
You mentioned CDP World, which is, I think, coming up.
00:38:44.571 --> 00:38:47.459
We're recording this mid-late September 2024.
00:38:47.459 --> 00:38:50.507
And it's about a month away, if I remember right.
00:38:50.507 --> 00:38:51.611
Maybe not quite.
00:38:51.611 --> 00:38:54.086
What are you all going to be talking about there?
00:39:05.501 --> 00:39:11.321
How we drove adoption across a global company, what the steps were um, how we excited, how we shouted the wins um and how we thought you know, a couple years ago we didn't think we're going to make it.
00:39:11.321 --> 00:39:12.122
Here we are, we're making it.
00:39:12.122 --> 00:39:17.310
So you didn't think we were going to make it, and here we are, we're making it so you didn't think you were going to make it.
00:39:17.551 --> 00:39:37.315
I don't believe that well, there were times I remember what was it like n73 or something like that way back when it was like one one time we wanted to push out and and do an activation and it was months to do that one activation.
00:39:37.315 --> 00:39:39.664
Now they're doing them many a day.
00:39:41.027 --> 00:39:45.198
Amazing Right Well, so I'm glad you shared it.
00:39:45.198 --> 00:39:49.805
It sounds like we got a little preview for our audience, or for those who can't make it to CDP World.
00:39:52.449 --> 00:39:54.271
And for whoever want to make it.
00:39:54.271 --> 00:39:56.194
I believe the registrations are still open.
00:39:57.035 --> 00:39:57.436
They are.
00:39:57.436 --> 00:39:59.565
I checked today they're still open.
00:39:59.585 --> 00:40:00.267
I was looking, it's in.
00:40:00.287 --> 00:40:02.272
Vegas, las Vegas.
00:40:02.272 --> 00:40:04.165
See, that's the reason for me not to go.
00:40:06.050 --> 00:40:06.672
Michael.
00:40:08.484 --> 00:40:13.543
I'm not a Las Vegas fan, you know.
00:40:13.543 --> 00:40:21.284
It's all right, it's all good, like it's just not my cup of tea, right so?
00:40:21.284 --> 00:40:25.490
But I'm sure that content is going to be great.
00:40:25.490 --> 00:40:31.827
Um, we covered a lot of ground here already, but is there anything that we didn't talk about that you want to make sure our audience heard about?
00:40:33.711 --> 00:40:35.374
Yeah, I do have one thing right.
00:40:35.374 --> 00:40:40.168
I know CDP is a new toy, new technology right.
00:40:40.168 --> 00:40:46.346
Before anybody wants to dive into it, right, just think through that right.
00:40:46.346 --> 00:40:51.240
First thing I believe you should think about is your data ready for this right?
00:40:51.240 --> 00:40:53.687
That's something that I'm very passionate about.
00:40:53.687 --> 00:40:57.544
Just because you can get a new toy, don't get a new toy right.
00:40:57.544 --> 00:41:02.074
Be prepared and also choose a good partner, which is very crucial.
00:41:02.074 --> 00:41:04.771
You know some people have in-house development teams.
00:41:04.771 --> 00:41:11.089
If not, if you're looking for a partner, make sure there is a skill set match, make sure there is a business buy-in.
00:41:11.089 --> 00:41:14.443
Then go into it right.
00:41:14.443 --> 00:41:19.282
That would be your surefire way to get success with the CDP implementation.
00:41:19.282 --> 00:41:24.450
Mary.
00:41:24.771 --> 00:41:26.954
I think it's being in it for the long haul.
00:41:26.954 --> 00:41:34.512
You can't be in it for a short term when you have to be in it for the long haul and I think you have to be in it with a win in mind.
00:41:34.512 --> 00:41:48.289
Right, this is what you want to accomplish and go after that North Star versus being in it because, hey, CDP is the new cool buzzword and everybody understands maps are.
00:41:48.289 --> 00:41:55.648
They are good, but they are not what they used to be, and so, understanding that it's not about the technology but about a business win.
00:41:58.172 --> 00:41:59.535
Love it Awesome.
00:41:59.535 --> 00:42:03.731
Well, it's been fun both of you, so thanks for joining.
00:42:03.731 --> 00:42:08.512
I know it's a late evening for some of us, so thank you.
00:42:08.512 --> 00:42:17.146
If folks want to keep up with what y'all are doing or reach out to you or learn more about CDPs, what's the best way for them to do that?
00:42:19.581 --> 00:42:30.550
First off, thank you for giving us this opportunity, Michael, you know it was very insightful, thought-provoking questions, I think Mary and I are both on LinkedIn.
00:42:30.550 --> 00:42:33.590
We are happy to share our profile links.
00:42:33.590 --> 00:42:41.728
That's probably the best way to ping us and reach us, and we'll be happy to share our journey in depth if needed.
00:42:44.252 --> 00:42:45.414
Mary, anything else from you?
00:42:47.821 --> 00:42:50.069
Thanks, michael, this has been fun, this has been great.
00:42:51.200 --> 00:42:59.224
Oh, good, well, and I know, maryary, you do write occasionally on linkedin, so and so I've seen those articles, you, or what do they?
00:42:59.224 --> 00:43:00.186
What does linkedin call them?
00:43:00.186 --> 00:43:01.811
They call them contributed articles.
00:43:01.811 --> 00:43:02.421
Is that what it is?
00:43:02.421 --> 00:43:05.170
I can't even remember what they call it now, I don't I don't know.
00:43:05.290 --> 00:43:05.981
I think it changed.
00:43:05.981 --> 00:43:15.019
I'm too lazy to do those once a quarter is my goal yeah that's good, all right well she's your editor.
00:43:18.426 --> 00:43:20.350
Well, good, well, thank you both appreciate it.
00:43:20.350 --> 00:43:23.582
Thanks to our listeners for continuing to support us, as always.
00:43:23.582 --> 00:43:33.131
If you have ideas for guests or topics that you want to share, or if you want to be a guest, reach out to mike naomi or me, and until next time, bye, everyone, okay, bye.
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