Buying Groups as an Extension of ABM with Alice Walker and Christine Maxey

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Hello everyone and welcome to another episode of OpsCast brought to you by MarketingOpscom, powered by all the more pros out there.
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I am your host, michael Hartman, joined by no one today, at least not my co-hosts.
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So, mike and Naomi, I'm sure will join us again, but I do have guests.
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I have two, so we'll make up for it.
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We have Alice Walker and Christine Maxey, both from Lean Data.
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Alice is currently a senior product and partnership marketing manager at Lean Data.
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Prior to joining Lean Data, she worked in consulting at Shift Paradigm slash LeadMD, where she held several leadership roles focused on marketing and service delivery to clients.
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She also has a background in project and program management.
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Christine is currently vice president of revenue operations at Lean Data, progressing through leadership roles and revenue operations.
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Over the past several years.
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She also spent a few years in solutions consulting at Lean Data, progressing through leadership roles and revenue operations.
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Over the past several years, she also spent a few years in solutions consulting at Lean Data.
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There's a connection between the two of you.
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Between her two stints at Lean Data, christine was the head of customer success at Tackleio.
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Prior to those roles, she held various roles in sales operations and business operations.
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So, alice and Christine, thank you for joining.
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Thanks, we sound smart.
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Yeah, good backgrounds all around.
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Yeah, so it's funny, the lead MD says so.
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I finally met Andrea Lechner Becker for the first time in person at Masa Palooza last week in Anaheim and it was funny because she sent me a message ahead of time.
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She's like I'm tolerated in real life I'm tolerated so and she was so well.
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There you go there you go, living up to the hype.
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That's important yeah, so did you.
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Were you all there when you had the uh the business cards that said doctor?
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i't.
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That was after my time.
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I think it was initially named to be like WebMD, so I spent more time than I would have liked explaining.
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Well, webmd used to be a thing that people did on the Internet, and now it's LeadMD and we're not changing the name because we have great brand recognition.
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So anyhow, let's talk about you.
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Yeah, and now I work for.
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Lean Data.
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So I'm constantly juggling, trying to say the right name every time.
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Yeah, that's so funny.
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Okay, so we're going to spend today talking about the concept of buying groups, so I'm not sure that our whole listener audience will be familiar with that, but it's a term that they may be familiar with if they're familiar with what was I still think of as serious decisions, but now part of Forrester.
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So we wanted to talk to you because not only are you incorporating that concept into some of your products, you're also leveraging it internally, so it might be good.
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Maybe we could start with a definition.
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So, alice, do you think you could start?
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Maybe give us a definition, or your definition, and we'll go from there.
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What is buying groups?
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Yeah, happy to so.
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Buying groups I mean, the great thing about buying groups is it's as simple as it sounds, right, A buying group is a group of buyers.
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The naming is really quite on the nose.
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I think it's helpful to think about buying groups in the context of marketing trends decade over decade, because that's really what we're seeing with buying groups.
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That's why we're talking about it now.
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That's why it's gained in popularity.
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You know, roughly 20 or so years ago, when marketing automation was really just getting started, when marketing automation was really just getting started, you have Marketo's and Eloqua's and the you know, the maps of the world are are being born.
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That really started with demand generation, right, and realizing like, oh my God, we can send an email to a thousand to a hundred thousand people all at once, Right, this is, this is amazing.
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We've never been able to do this before.
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Demand gen was born.
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That got messy really quickly.
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So the MQL came out, the MQL being the marketing qualified lead really focused on just the lead itself, which is really really small, and a lot of problems kind of naturally came out of that.
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And so, 8, 10 years later, as people sort of fall out of love with that first blush of marketing automation and demand generation.
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That's really when you see account-based marketing start to rise in popularity and take over and say, okay, demand gen and the MQL did not solve all your problems.
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It did not make you a million billion dollars.
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Sales and marketing are still fighting about the same things that they've done since the dawn of time.
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Too bad, so sad.
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Let's talk about account-based marketing.
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The MQL is so small, it's just a person, it's a tiny.
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That's not good.
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We need to go big.
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So we're going to talk about the entire account, right, and we're going to market to the account and we're going to work with sales on that account and you'll have the last 8 to 10 years really focused on the accounts.
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That's.
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You know.
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Sixth Sense is born at this time.
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Demandbase comes in.
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You know Engagio.
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At the time you have all of these companies that start really trying to expand to fix the problem that there was in the MQL, and then really, what we've seen now we're about in that same sort of trend timeline 8 to 10 years later.
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Abm solved some of those problems, but not all of those problems.
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Sales and marketing are still fighting about the same thing they've always fought about and what we've seen.
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Is that okay?
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If the MQL is really too small and account-based, maybe that's a little too big.
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Just going to the actual account, Maybe we should start talking about the group of people in the account itself.
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So it's not doing away with people, it's not doing away with accounts.
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It's saying within an account, anybody knows that if you are trying to sell anything with any type of meaningful budget you're selling to multiple people right.
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It's very rare as a day where you get on a call and it's one person and they're the stakeholder, the decision maker, the budget holder and the executive champion.
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It's just not going to happen.
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So buying groups is all about understanding who those people are within the account and then finding out a way to scale and operationalize that so you're not relying on salespeople tracking all that information down, uploading that data into Salesforce and then effectively maintaining that data, because you know, we all know, that's not a realistic solution.
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So I really like the Goldilocks analogy.
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We're really going for a just right approach with buying groups that really incorporates both the people of MQL, the accounts of ABM and centralizes it a little bit more in Salesforce, where people are really living and breathing anyway.
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Yeah, I mean, I think when I first heard about it, it was intuitively it made sense, right it just the idea that, like, yes, when you're buying something substantial, you're typically not doing it on your own.
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There are lower cost things where, yeah, I've been able to put it on a credit card or even do it through a PO or something like that, but it's usually, yeah, I have a certain amount of authority.
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Once I'm over that, which usually happens fairly quickly, you have to get other people involved.
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See, my dog agrees, but I mean, it seems to be too obvious.
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But I think you talked about Salesforce.
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To me there's already a place in Salesforce to capture this stuff.
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Right, it's called opportunity roles, it's really it is, but how many people, how many sales organizations do you know have contact roles filled out for the entire buying group?
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On the opportunity, Right, it's, it's.
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it's quickly approaching zero.
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It's like saying what enterprise organization, or any organization, has clean data in their system and it's so obvious.
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But in a way, buying groups is really just the technology and the process, kind of catching up to how this has always been done.
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Like salespeople hear about this and they're like no duh, this is how I've been selling, this is how I make my commission.
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This is literally what we've been doing since the dawn of time.
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I'm so glad you finally figured this out and one.
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It's like yes, thank you, we're glad to be here and also the technology wasn't there to be able to build and scale around that.
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And that's really what we're doing at Lean Data is we are building the technology that takes the motion that your very best sales reps do and we automate that so you can scale it across all of your reps who maybe don't have those exquisite habits as one might like.
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Well and I am pretty pragmatic about it, having been in sales myself before when I think about whenever I've talked to salespeople, they get the idea right.
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Buying groups make sense and I go like, yeah, if you put this stuff into salesforce this way, you're it's extra work for you today, but down the road right, it's going to help us better target and help you find your next next account.
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So I think your idea, like the goldilocks analogy, is an interesting one.
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Like you want to make it as easy as possible for them.
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So like what was like.
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But what was the driver of building this into the lean data product set?
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Yeah, yeah, I'll, I'll take first pass of that, and then Christine.
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I think your, your perspective on this is is is really going to be important.
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But I mean, I think all good products come from really acute pain, right, and there has been a lot of pain in trying to understand who orgs are selling to.
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You know, I'm not going to bore you guys with the speech about these economic times, you know, and and unprecedented moments like the ones we've been going through and are going to continue to go through.
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But what we, what everyone knows, what has become common knowledge here it's a cliche at this point is like it is harder to get deals done, especially in the B2B fast world.
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It is harder to get deals done.
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Everyone is asked to do more with less.
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You have a lot, a lot of people involved, and so we have a lot of organizations who are trying to figure out how they can scale and how they can make sure, when they do get in those sales cycles, they are closing them really, really effectively.
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And so we saw that coming from our own clients who had already been turning to us and saying like, hey, we think this is something we can solve with lean data.
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Can you help us get there?
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And we heard it from the market as people were saying hey, wow, the way we've been doing things really doesn't make sense for the way business is and the way that the economy is really demanding, and those two things combined from a product marketer's perspective, it's like yeah, jackpot.
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You guys, there is pain here that we can absolutely solve.
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Sure Christine.
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Any thoughts from you on this too?
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So many.
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I just I want to touch on a few points.
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One is Alice made a really good point and the why now is the technology.
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It always is not really that much has changed.
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I've been in the industry a long time.
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We've always been selling to people.
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People have always been buying.
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It's not.
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If you sell to the enterprise, it's not one person.
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One thing I'll add is we always say it's all these people working together to buy from you.
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Sometimes they're not working together, sometimes they're working in silos at an organization.
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Sometimes I've been in situations where I felt like I was working against people internally as a buyer.
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It's true.
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So there are a lot of nuances to the people that you're selling to.
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There are multiple people and it's the technology that really is the catalyst for these changes, and I think people aren't going to just say, oh, I'm just going to do buying groups, I'm just going to do ABM, I'm just going to do MQL.
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It's going to be a combination of these things because I swear and it doesn't matter how good you are at any one of those things they're going to say I still need more, I need more MQLs, I need more accounts.
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But I'd love to be in a place where they say I need more opportunities, because you've given me so many good opportunities, I need more.
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That is the ideal state, absolutely.
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So what makes Indata in a position to bring this product to market?
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That's, I think, see how the vendor came to market, because their underlying architecture is usually a really good indicator of where they're going to be good and how they can layer on additional products in their roadmap.
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Right and so, because linked data is all about relating data in your system wherever it comes from.
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Whether it's external data, you know company size, internal data data, you only know tickets opened, health of customer products purchased.
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We just relate all this data.
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We're positioned to take that data and do really interesting things with it.
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And signals are great.
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All this information is great, but kind of separating out the noise from the actual interesting moments the signals that matter is one of the things that's going to allow lean data product or really any of the products that you look at for your buying group.
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That's one of the things that's going to be really important to you, not how many signals I have, it's how many important signals do I need.
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Which signals do I need with which people to close a deal?
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That's going to be the differentiator.
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That and clusters Clusters of people.
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What people when?
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What does good look like?
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That's the difference.
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Yeah, it's interesting that you bring up the timing for the technology.
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It reminds me of a couple of things in my career.
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The other thing it's making me realize is we've had several guests on in the last six to nine months, basically most of this year, where we were talking to them about sort of emerging go-to-market approaches that are different, and I think it's part of the same symptom, right, like the ability to get into these accounts and sell to them has been a challenge.
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What's really interesting, as I think about, is some of these just feel like they're actually not new concepts, right.
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The idea of a buying group, like we said, intuitively obvious.
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The idea of using partners, if you're using a partnership based motion right, they all make sense and they've all been used over the past.
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I think it's the ability to do those at scale that seems to be the thing that's really happening now.
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So it's I mean.
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I'm just putting this all together in my head as we talk.
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But one of the other things and maybe, alice, you touched on this a little bit is that you mentioned sort of the link to this in ABM right, which ABM has been a trend here.
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What for, I think you?
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gave us the history, yeah eight to ten years Very good.
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The wave rises and history, yeah, eight to 10 years, very good.
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The wind rises and falls.
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Yes, yes, yes.
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So how does?
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Because I think when we talked before, you said like this is linked to ABM and you touched on it, but can you go a little deeper on that?
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Yeah, absolutely, and this is something that I think is really really important.
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Consultants and analysts and I say this as a former consultant and with all the respect in the world, right, they love to say things like oh, this is dead, you know MQL is dead, the funnel is dead, you know ABM is in a coma.
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There's all of these, really you know, provocative phrases that people like to say around these major trends and major motions that we have in organizations, and I get why.
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But usually the people who are talking about that you know you have there's a little bit of an ivory tower vibe there, right, like it's great in theory and it's great if you're building a company from the start, day one, with absolutely no data or history or past motion, like no problem.
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But for the rest of us, you know, living in the world where we report up to the board on our MQLs and we have a full team that's running ABM programs that has some really impressive metrics that go to it, it just it makes no sense to say you know, all of this is done.
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We're now focused on this other thing.
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If anything, it kind of, you know, feeds into the stereotype right of chasing that shiny object syndrome which you know marketers can perhaps be known for.
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So when you look at buying groups, I think what it really is, when it's done right, is it's an extension of your ABM program, right?
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I don't see.
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I see a lot of companies doing this successfully.
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I don't see any of them doing it as their sole motion.
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It is a hybrid approach where you still have your demand gen efforts going.
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In many, many cases they're still collecting on and reporting on MQLs, they're developing out those parallel metrics so you can start to see how those things are going.
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You're still saying, like the account still really makes a difference when we're talking about selling right the account and where it is and how it's positioned and how you can market effectively and what campaigns you can run against that account.
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Like those are core marketing tenants that aren't going anywhere.
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Buying groups just says we are going to go a level deeper in that account to connect and understand the people in a more systematic way and in a way that unveils context.
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And I know that can sound maybe a little bit, you know, ethereal, but what we're, what we're saying, is we want to pull together all of this data and at this point, with all these different texts, like.
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There's a lot of data out there.
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We are going to aggregate all of that data.
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We are going to put it in the right place in the right format so people can start understanding more about who they're talking to or, crucially, who they're not talking to.
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Right, who's about to come in and sniper their wheel right as they think it's about to get signed, and where they might exist elsewhere in the company.
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Right, where do you have somebody who's a decision maker in one open opportunity and they might exist as an influencer in another opportunity?
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Right, you're going to have a different conversation with that person if you understand what other conversations they're having that you might not be a part of.
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So all of it, I think, is connected.
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I don't think anything in particular is dead.
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Really, I think it's just a reimagining, which is something that we always have to do.
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Right, we have to reimagine and I think we have to get really, really lean and really nimble.
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And I think that's where our approach with buying groups come in, because you can plug into the existing tech stack and you can harness all of that data and you can leverage it in your existing account-based strategies to really amplify what you're already doing and what your salespeople are doing well.
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Yeah, it feels like it's not really a separate thing, it's something that augments.
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What you're probably already doing is the way it sounds like Christine.
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Any additional thoughts on all that?
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Oh, yep, there it goes.
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This is what happens when we're doing a real live recording.
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Yep, there it goes.
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This is what happens when we're doing a live recording.
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Yeah, I do think it is not just turn it on and forget about the old things, because change is not like that.
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That's not how it works.
00:19:44.154 --> 00:19:45.670
Fine, you can have it all.
00:19:45.670 --> 00:19:48.942
You can have MQLs, where you send over leads.
00:19:48.942 --> 00:19:55.578
You can have ABM, where you send over accounts, and you can have buy-in groups where you send over opportunities.
00:19:55.578 --> 00:20:00.279
Everyone loves leads, right?
00:20:00.279 --> 00:20:02.705
They like demo requests.
00:20:02.705 --> 00:20:06.339
Oh, of course, that's not going to stop.
00:20:06.629 --> 00:20:08.537
We all like hand raisers of whatever sort.
00:20:08.537 --> 00:20:08.979
Yeah.
00:20:10.912 --> 00:20:17.156
But MQLs overall, they don't convert very well, yeah, unless you are like who did I talk to the other day?
00:20:17.156 --> 00:20:19.574
Oh, cognizant, because all their MQLs.
00:20:19.574 --> 00:20:21.619
The only way you can MQL is if you raise your hand.
00:20:21.619 --> 00:20:27.171
So I was like, well, that's a different kind of MQL, so will that go away?
00:20:27.171 --> 00:20:29.173
You know that's a different kind of MQL, so will that go away?
00:20:29.173 --> 00:20:46.897
No, but if I send you an MQL versus an opportunity with the contacts already on it and a call scheduled, it feels different and people are going to be asking for that more than they're going to be asking for MQLs.
00:20:47.298 --> 00:20:50.995
The shift is going to be like where's my opportunity, not where's my demo request.
00:20:50.995 --> 00:20:56.939
And maybe if a demo request comes in today, I already create the opportunity and send it to them.
00:20:56.939 --> 00:21:00.701
So for them, when they say a hand raiser, that is an opportunity.
00:21:00.701 --> 00:21:09.863
So there were small things that we've done to be on this buying groups path and we can talk a little bit about that, like what does that change look like and how am I selling it internally?
00:21:09.863 --> 00:21:13.096
But I don't think it will go away either.
00:21:13.096 --> 00:21:14.561
I think it's we can have it all.
00:21:14.561 --> 00:21:15.472
Why can't we have it all?
00:21:16.317 --> 00:21:16.518
Yeah.
00:21:18.191 --> 00:21:20.077
It's easier to measure if it's an opportunity.
00:21:20.077 --> 00:21:34.282
So I will say if everything goes to one object, my Salesforce brain is very happy, my reporting brain is very happy, my metrics are easier, my conversions are much easier to calculate and it's much easier for people to work in one space.
00:21:34.282 --> 00:21:36.915
But I'll automate anything, I don't care.
00:21:37.716 --> 00:22:18.173
And I and I think what's what you just touched on there is really, really important is talking about the opportunity, right, and one of the reasons why buying groups has been such a challenging thing, I think, one of the reasons why the tech hasn't been there in the past is because, of course, you know, as head of RevOps, right, or perhaps as CMO, love, love people operating in the opportunity, and for good reason, right, that is their golden opportunity, that's their source of truth, that's what they're, you know, that's how they get paid.
00:22:18.193 --> 00:22:21.402
That's how they get paid right, that is the most profitable thing.
00:22:21.402 --> 00:22:26.136
So I absolutely understand, like the the the bone deep.
00:22:26.136 --> 00:22:34.200
No, that comes full throated from the sales team when marketing's like oh yeah, and we'll just update your opportunities and it'll be so great.
00:22:34.200 --> 00:22:38.418
And they're like absolutely not, please stay away from everything that we're doing.
00:22:38.418 --> 00:22:47.738
And I think we have to take that really seriously, because nothing is going to get adapted right If you're fighting with people across the board.
00:22:54.869 --> 00:22:56.713
I think sales has some very good reason to be so hesitant.
00:22:56.713 --> 00:23:00.822
You know, to let other departments go in and tinker in this object that is so crucial to their business, to the organization at large.
00:23:00.822 --> 00:23:09.190
And so what we've done is we've created the ability to build out these buying groups in a container, in a custom object container.
00:23:09.190 --> 00:23:14.680
That's pre-opportunity so you can build in Salesforce.
00:23:14.680 --> 00:23:19.935
So think of a buying group object in Salesforce that marketing can start.
00:23:19.935 --> 00:23:23.021
Your MQL is your buying group of one right?
00:23:23.021 --> 00:23:29.541
And then you work with sales and you say, okay, how many people would you want in this buying group before you would want to jump on a call with them?
00:23:29.541 --> 00:23:30.844
How many people would you need to have?
00:23:30.844 --> 00:23:32.211
And who are those people?
00:23:32.211 --> 00:23:33.114
You know.
00:23:33.114 --> 00:23:37.062
And sales says you know I want six people.
00:23:37.062 --> 00:23:38.492
I don't think you're ever going to do that.
00:23:38.492 --> 00:23:42.272
You know, get me six people and make sure the decision makers on the call and then I'll pay attention Right.
00:23:42.854 --> 00:23:49.224
And now, what marketing has is they have an understanding of who those those people need to be, what those roles are.
00:23:49.224 --> 00:23:57.142
They have the ability, through all of these new, through all of these technologies and the stack that they were already doing, to find all of those people.
00:23:57.142 --> 00:24:12.500
Through lean data, we have the ability to associate them into this unique container that we can track so that we see exactly how we've been touching them and what they've been doing and what they're engaging and all of that fun, contextual, great data.
00:24:12.500 --> 00:24:34.100
And then, when it gets to that point, we can turn to sales and say, great, here it is, it's ready to go, and then that is something that sales can then create the opportunity and associate, and that can be done manually, it can be done automatically, but it gives marketing the ability to play in that sandbox without saying I'm going to stomp on your sandcastle to make it happen.
00:24:34.100 --> 00:24:37.644
We have two sandcastles Building a bridge between them.
00:24:37.644 --> 00:24:40.106
If you'll, let me belabor that analogy.
00:24:45.609 --> 00:24:47.770
Sorry, now I'm thinking about the beach.
00:24:47.770 --> 00:24:56.075
Yeah, it's interesting because I've had similar experience, but I think I just want to clarify something.
00:24:56.075 --> 00:25:00.037
So I think you said like, oh, we need to understand the six people.
00:25:00.037 --> 00:25:07.100
It feels like it's really like if we say we typically win when we have these six roles involved, right, and whoever those people are.
00:25:07.100 --> 00:25:12.583
But it also feels like maybe it could be a self-validating model, right?
00:25:12.583 --> 00:25:18.586
So we think, based on historical data, that we win when we have these six people, but what we find is okay.
00:25:18.586 --> 00:25:23.208
So now we get a new opportunity, we've got the three people and we actually win, right?
00:25:23.208 --> 00:25:26.769
Does that change the model?
00:25:26.769 --> 00:25:28.596
I see Christine's like nodding.
00:25:28.615 --> 00:25:36.818
I'm like, yeah, okay, yeah, of course, all right, yeah and I think there's reporting that comes with it, right, and I mean, this is like anything else.
00:25:36.818 --> 00:25:42.865
You're going to need to run models off of it, you're going to need to track performance, you're going to need to see how these things go.
00:25:42.865 --> 00:25:55.800
That's what our clients are doing.
00:25:55.800 --> 00:26:15.330
Typically, what we see with buying groups is people will run a pilot or a smaller rollout with one product or one segment and then they start seeing results and they start to see those numbers and all of a sudden, people start paying a little bit better of attention, right, because your conversion rates start going up and in some cases, the total opportunities are going up in pretty large numbers, and so once that starts happening in a small space, then you start getting the buy in Right.
00:26:15.411 --> 00:26:23.023
A lot of what this is, you know, from my perspective, is building back up, in some cases, marketing's credibility with sales.
00:26:23.023 --> 00:26:33.336
Having that executive champion, that executive stakeholder yeah, having that executive champion, that executive stakeholder Ideally it's the CMO and the CSO are working really closely together and the CSO is kind of blessing all of this.
00:26:33.336 --> 00:26:43.362
And you have, you know, we have a product that will run all of the analysis on what those numbers should be and what those titles are.
00:26:43.362 --> 00:26:49.066
Many organizations might already have that and then you report on that and it's like any other program, right?
00:26:49.066 --> 00:26:50.866
You iterate once you have the data.
00:26:51.488 --> 00:26:56.074
Yeah, no, it makes sense, maybe shift gears a little bit.
00:26:56.074 --> 00:27:05.125
So you've been developing the product and then, christine I think I don't want to use the previous sort of analogy but you drink your own champagne now.
00:27:05.125 --> 00:27:09.673
Right, so you're using this internally.
00:27:09.673 --> 00:27:09.854
How, like?
00:27:09.854 --> 00:27:14.432
How do you approach this kind of stuff, like when you're because this is not just a technology change?
00:27:14.432 --> 00:27:24.061
Right, this is a it's not even a process change, like it's, it's kind of a mindset change, because I was talked about, right, you, you have to build this trust as a along the way too.
00:27:24.061 --> 00:27:27.734
So just how do you approach that when you're doing something like this internally?
00:27:28.316 --> 00:27:28.856
This was.
00:27:28.856 --> 00:27:32.722
This is kind of funny, it's we're not unique.
00:27:32.722 --> 00:27:35.291
I had to sell our own product internally.
00:27:35.291 --> 00:27:41.903
So I the thought was, you know who is the best fit for buying groups?
00:27:41.903 --> 00:27:43.753
Is it enterprise?
00:27:43.753 --> 00:27:45.116
Is it commercial?
00:27:45.116 --> 00:27:47.320
Is it anyone selling to the enterprise?
00:27:47.320 --> 00:27:51.517
Is it anyone who has a product that sells into a buying group?
00:27:51.517 --> 00:27:52.759
What does that look like?
00:27:53.240 --> 00:28:03.094
So we talked a lot about that and, you know, finally convinced them like, let me be our guinea pig.
00:28:03.094 --> 00:28:38.478
And so I had to pitch this internally to our internal stakeholders and convince them that I wanted to do the historical analysis that we provide and our partners guy and our CEO and found our partner, opsfocus, and we ran the blueprint.
00:28:38.478 --> 00:28:55.000
The product's called Blueprint, but we ran the historical data and we're just about to go through the analysis and so for us, the thought is we will run, like Alice said, this just for our enterprise segment of our business.
00:28:55.000 --> 00:29:05.712
I do think we're going to find that the commercial business is going to start wanting it to when I start sending opportunities to the enterprise, they're going to want it to.
00:29:05.712 --> 00:29:08.682
So we are just in the middle of our rollout.
00:29:09.309 --> 00:29:21.310
And it is interesting because what we're trying to do is not only drink our own champagne but gain empathy for the change management parts of the process, and not just the change management from a people.
00:29:21.310 --> 00:29:23.835
But what does the system need to do?
00:29:23.835 --> 00:29:26.798
What changes am I going to need to make to the system Now?
00:29:26.798 --> 00:29:50.241
Thankfully, we've already done some of the things that I think set us up for success, and I presented on this and I'll share some of the things that I think anyone can do today to kind of set the groundwork for buying groups and really just for I don't know preparing for the.
00:29:50.241 --> 00:29:52.392
Sometimes I call them the robots.
00:29:52.392 --> 00:29:54.840
I don't know what that robot will be whether it's.
00:29:55.162 --> 00:29:59.994
AI or your buying group or whatever next piece of technology there is.
00:29:59.994 --> 00:30:16.106
So you've got to know who you're talking to, right, and so one of the gaps that I do know is that, regardless of what engagement tool you're using, there are people that your reps are talking to that are not in the system.
00:30:16.106 --> 00:30:17.510
Oh a hundred percent.
00:30:18.132 --> 00:30:22.360
The biggest what I when I ran um I I ended up using Nectar.
00:30:22.360 --> 00:30:22.682
You can.
00:30:22.682 --> 00:30:25.094
There's lots of vendors out there Um.
00:30:25.094 --> 00:30:30.470
What I found actually were our biggest offenders were our customer success side of the business Interesting.
00:30:30.470 --> 00:30:35.822
Which is interesting because one of our bigger term risks are loss of a point of contact.
00:30:35.822 --> 00:30:38.196
And if I don't even know who that point of contact is.
00:30:38.196 --> 00:30:44.116
I don't know when they've left and I do use software to know when people leave, but if I don't know the person, I won't know that they left.
00:30:44.499 --> 00:30:44.699
Right.
00:30:47.174 --> 00:30:50.351
So one of your risks and won't know that they left.
00:30:50.351 --> 00:30:53.019
So, um, so you're, you're one of your risks, um, and I don't know how buying groups will play into renewals.
00:30:53.019 --> 00:30:53.180
That's.
00:30:53.180 --> 00:30:54.483
That's the next piece of where I want to go with.
00:30:54.483 --> 00:31:11.019
Buying groups is not just new business enterprise maybe commercial, but definitely renewals, because, um, keeping up with relationships and existing accounts is actually harder than it is in the buying and the selling process because you're actively engaged where the renewals is a whole nother thing.
00:31:11.079 --> 00:31:15.713
So, not only know who you're talking to know who you don't know.
00:31:15.713 --> 00:31:21.232
So scrape all that data and, while you're at it, get all of your activities and meetings.
00:31:21.232 --> 00:31:26.894
But, but beware of duplicates, because you're going to get it from something like outreach or sales loft.
00:31:26.894 --> 00:31:29.160
How do you get those other pieces without duplicates?
00:31:29.160 --> 00:31:30.824
Because you're going to get it from something like outreach or sales loft.
00:31:30.824 --> 00:31:32.007
How do you get those other pieces without duplicates?
00:31:32.007 --> 00:31:32.969
And do you need all of the data or just the?
00:31:32.969 --> 00:31:34.011
Is it an email on the subject?
00:31:34.011 --> 00:31:35.837
You probably don't need all the data and attachments.
00:31:35.837 --> 00:31:51.716
Be careful what you bring in, but bring it in, because if you want to know who you're talking to, you gotta kind of know, when you're talking to them who you're talking to, what type of what it is, so that if it's meaningful, you've captured it, so you can repeat that type of.
00:31:51.716 --> 00:31:54.211
You have that data to understand what meaningful is.
00:31:54.211 --> 00:31:56.597
You don't need you probably don't need all of the text.
00:31:57.158 --> 00:31:58.590
That's one thing, so can I.
00:31:58.590 --> 00:32:02.060
So I want to interrupt real quick a couple of questions that popped into my head.
00:32:02.060 --> 00:32:03.510
Let me do the first one.
00:32:03.510 --> 00:32:06.512
So one I don't think we've talked about this who do you what?
00:32:06.512 --> 00:32:09.274
Who do you roll up to Christine in the organization?
00:32:10.055 --> 00:32:12.175
I roll up to um the CSO.
00:32:12.175 --> 00:32:14.798
Okay, so you're on this.
00:32:14.958 --> 00:32:15.979
Okay, all right.
00:32:15.979 --> 00:32:19.987
Um, the second question.
00:32:19.987 --> 00:32:21.411
I don't know how you approach this.
00:32:21.411 --> 00:32:45.145
So when I've done pilot stuff and I like the idea of finding a small group building some success and some momentum snowball effect, if you will, Did you go after people who were actively receptive to it, or did you go over people who felt like they were almost antagonistic to the idea first and try to convince them, because I've done both and they both work, but I've, I've, I've.
00:32:45.145 --> 00:32:48.740
The second one is harder, but I found it ultimately more successful.
00:32:49.020 --> 00:32:55.693
so this time I went after the people who were well for it.
00:32:55.693 --> 00:33:04.472
To be honest, okay, um, I it's not that we had people who were against it, but I was was just like, hey, we have this opportunity.
00:33:04.472 --> 00:33:07.510
I really want it to be ready by 2025.
00:33:07.510 --> 00:33:21.629
And I think we have an opportunity in the enterprise and you know, I don't have a lot of people saying no when it comes to our own product internally, but the thing was more about time constraint.
00:33:22.180 --> 00:33:23.705
They're like it's Q4.
00:33:23.705 --> 00:33:25.481
Do you have the time?
00:33:25.481 --> 00:33:27.968
We have a lot going on.
00:33:27.968 --> 00:33:29.550
We have a lot of marketing initiatives.
00:33:29.550 --> 00:33:44.792
We have a lot of sales planning to do and I kind of looked left, looked right and was like let's do it, because I really want to do it and yeah, the historical analysis is really no lift.
00:33:44.873 --> 00:33:54.905
For me it's a very little lift, but I think the readout is going to put us in a really good position to give them enough information to make the right decision.
00:33:54.905 --> 00:34:11.552
So it's the and some companies offer this and some don't, but I think I don't have enough information to make a good recommendation without the historical analysis and I have enough data for the robot.
00:34:11.552 --> 00:34:13.347
So I need the data.
00:34:13.347 --> 00:34:15.246
Give me the readout.
00:34:15.365 --> 00:34:15.586
Right.
00:34:17.084 --> 00:34:17.827
And we'll go from there.
00:34:17.827 --> 00:34:32.081
So I needed data to be really compelling, and so the thing that they worried about was my time, and for me they didn't need to know, but it really didn't take any time for me to roll out Interesting.
00:34:32.262 --> 00:34:34.667
Okay, so you talked about this historical data.
00:34:34.667 --> 00:34:37.814
What types of data?
00:34:37.814 --> 00:34:45.811
I imagine opportunities was a part of it, and if you had contact roles, that would be part of it too, but what other things did you include in that analysis?
00:34:46.732 --> 00:34:53.304
Yep Opportunities, contacts, leads, tasks, events.
00:34:53.304 --> 00:35:02.513
If you have OCRs, ocrs Campaign data, I think so Let me grab it.
00:35:02.513 --> 00:35:07.722
Yes, campaign data You're right, got it.
00:35:07.762 --> 00:35:15.153
Was there anything that you actually intentionally excluded, that other people were like we really should include this?
00:35:15.153 --> 00:35:15.735
I'm curious.
00:35:15.735 --> 00:35:17.326
I'm throwing a curveball at you here.
00:35:20.481 --> 00:35:29.352
I generally exclude some marketing stuff, um email sends like lists.
00:35:29.352 --> 00:35:42.896
I exclude any type of email ins that are um and I do this for all of my analysis email ins that are automatic replies out of office, um sure, anything that I I do a lot of.
00:35:42.896 --> 00:35:53.064
I keep data that's duplicate sometimes, but I mark it as a duplicate, so duplicate data Um, what else do I exclude that?
00:35:53.064 --> 00:35:59.321
Um, I don't exclude unqualified people because they may not have been unqualified at the time.
00:35:59.321 --> 00:36:01.024
So generally I exclude unqualified.
00:36:01.044 --> 00:36:02.026
But for this analysis.
00:36:02.086 --> 00:36:09.800
I did not exclude unqualified, so that's that's one of the reasons I don't always delete unqualified people from the system.
00:36:09.800 --> 00:36:14.071
If they have any relationship to anything that is relevant, I keep them.
00:36:14.071 --> 00:36:27.352
It's part of my data destruction policy, but so so in this scenario I would analyze unqualified where normally I wouldn't.
00:36:28.033 --> 00:36:30.401
Interesting, alice.
00:36:30.401 --> 00:36:37.888
Um, as you're taking this out to customers, are they doing like, are they using sort of a similar pattern of stuff they're looking at?
00:36:37.888 --> 00:36:38.501
Um?
00:36:39.022 --> 00:36:45.923
yeah, so we have two different, um, two different offerings that we have around buying groups, and one is called Buying Groups Blueprint.
00:36:45.923 --> 00:36:52.646
That does essentially what Christine just itemized, and so we would do that in the same way.
00:36:52.646 --> 00:37:24.762
Right, we're already going through that process at our organization, the same as we would roll it out for anyone else, and that's providing them with not only what your buying groups should look like, what those meaningful events are, the titles, roles or personas that you would want to base your buying groups around but also more of a holistic assessment of overall readiness between the system, your tech stack, your business process, the change management, kind of a holistic approach to getting started with buying groups.
00:37:24.762 --> 00:37:38.833
So it's same same, but in some cases we have, you know, a number of organizations that have, you know, really robust data science departments, frankly, and really robust ways of analyzing the data.
00:37:38.833 --> 00:37:41.160
That's not something that they need the support on.
00:37:41.361 --> 00:38:03.704
Some people do, just because it's easy to build out as a proof of concept, to kind of really jumpstart the motion, and so, you know, in some of those cases where they're using our product, it's going to look exactly as Christine just identified and for those who already have their information, you might see some variance, but across the board it's pretty much always the same of you know.
00:38:03.704 --> 00:38:07.702
Really, going back to just the, the obvious fundamentals, you have to know who you're talking to.
00:38:07.702 --> 00:38:09.791
You have to know what they care about.
00:38:09.791 --> 00:38:12.522
You have to know how they want to digest information.
00:38:12.522 --> 00:38:15.391
You have to know the role that they play in the sales cycle you're in.
00:38:16.140 --> 00:38:19.967
That sounds a lot like personas, so it's a little bit of personas.
00:38:20.067 --> 00:38:21.169
It's a little bit of personas.
00:38:21.169 --> 00:38:22.612
It's a little bit of attribution.
00:38:22.612 --> 00:38:27.048
It's a little bit of um, you know, full cycle reporting.
00:38:27.048 --> 00:38:28.211
It's um.
00:38:28.211 --> 00:38:37.586
None of these past trends in marketing or past things that have just kind of the names have gone out of vogue but none of them ever really fully went away because they were created for a reason right?
00:38:37.707 --> 00:38:42.307
no, I, I think so, and that's why I was like this sounds very familiar if you've done any of that kind of work.
00:38:42.307 --> 00:38:49.101
Yes, so, so, christine, you've done this analysis or you're in the final stages, I guess.
00:38:49.101 --> 00:38:54.008
Right, has there been any anything that has surprised you about it?
00:38:54.008 --> 00:39:02.267
Right, like, were you, like, have you been able to say, oh, this opportunity we really have, we have this one point of contact, but we really need these other two or three or four, whatever the number is.
00:39:02.267 --> 00:39:03.429
Like what?
00:39:03.429 --> 00:39:08.702
What kinds of interesting things have you uncovered that you might not have otherwise expected?
00:39:10.046 --> 00:39:36.928
not yet, because we're just about to do our readout, um, but what I will say is um, we know that multi-threading works, um, this is kind of a little off topic, but I do want to make sure I cover this, because multi-threading is super interesting, right, and not because we don't do it, but because we don't pay anyone to do it.
00:39:36.928 --> 00:39:45.990
And I thought this was interesting in that I was talking to an organization the other day and they said they pay their SDRs on multithreading.
00:39:47.282 --> 00:39:49.487
So just for my own notification, maybe your eyes.
00:39:49.487 --> 00:39:51.893
When you say multithreading, what do you mean?
00:39:52.701 --> 00:40:00.214
Making sure that they have multiple people at the account and paying them to reach out to more than one person on the account.
00:40:00.214 --> 00:40:07.843
Reach out to more than one person on the account, and so what we did?
00:40:07.843 --> 00:40:09.986
Because I don't know exactly who yet, but I'm going to approach it in two ways.
00:40:09.986 --> 00:40:18.142
Once I know the exact two, I started automating bringing in the right people on the account.
00:40:18.142 --> 00:40:23.548
So I think I'll know soon exactly who those people are the account.
00:40:23.548 --> 00:40:25.631
So I think I'll know soon exactly who those people are.
00:40:25.631 --> 00:40:29.036
I think I need two RevOps, two marketing ops, depending on the size of the company, could be one or two.
00:40:29.036 --> 00:40:39.005
If they don't have it, I send it out to Sixth Sense or User Gems and I pull in those people and add it on.
00:40:39.025 --> 00:40:56.322
Now I don't pay the SDRs today by multi-threading, but I'm looking into it for next year because we know and again maybe I'll automate it through buying groups but we know you have to be talking to X number of people and soon I'll know the number and soon I'll know the personas.
00:40:56.322 --> 00:41:04.675
But why not pay someone to do that if I know that it's going to improve the win rate?
00:41:04.675 --> 00:41:12.973
And talking to it was again, it was Cognizant the other day the co-founder there.
00:41:12.973 --> 00:41:23.594
He said they actually that's how they comp their SDRs on multi-threading and they found it to be very successful not even on you know number of meetings booked multi-threading.
00:41:23.594 --> 00:41:28.854
So I don't know the output yet of the analysis.
00:41:28.854 --> 00:41:30.579
It's going to give us a few things.
00:41:30.579 --> 00:41:43.753
It's going to give us the personas, the clusters that we call it, alice, the persona clusters that are important Not only it's what it looks like in a one deal and a closed lost deal.
00:41:43.773 --> 00:41:47.514
That's the other thing that I would analyze, that I don't always analyze.
00:41:47.514 --> 00:42:10.432
In some of my reporting I'm going to also look at what lost and bad looks like, the clusters of titles that make up each of the personas, the number of people in those personas needed to close deals and the number of personas, and then figure out what we either automate versus what we have.
00:42:10.432 --> 00:42:13.565
A human do we're still going to have humans.
00:42:13.565 --> 00:42:16.004
Yeah, at least next year.
00:42:16.004 --> 00:42:18.439
At least next year, guys, we're still going to have humans.
00:42:18.439 --> 00:42:21.410
So big promises from Christina.
00:42:22.701 --> 00:42:23.644
So that's what I do with the output.
00:42:23.724 --> 00:42:24.526
AI is dead.
00:42:26.351 --> 00:42:26.752
Big word.
00:42:26.752 --> 00:42:29.470
That's the title of this episode.
00:42:30.942 --> 00:42:43.129
So that's what I do with the output, even though I don't have it yet is really focusing on identifying the gaps and risks and closing them with automation and people.
00:42:43.129 --> 00:43:00.950
And if that moves the needle, I'm going to keep repeating automating, paying people, closing the gaps and then hopefully rolling it out to the other segments, not only for commercial but renewals, which is super interesting to me.
00:43:01.612 --> 00:43:01.812
Yeah.
00:43:02.281 --> 00:43:05.365
And I think the whole concept of the sdr is a really like.
00:43:05.365 --> 00:43:08.172
We could probably spend another hour talking about it here.
00:43:08.172 --> 00:43:13.351
It's super juicy, um, and it's something that I think is going to continue to evolve.
00:43:13.351 --> 00:43:16.043
I don't know that anyone has a nice, neat, pat answer.
00:43:16.043 --> 00:43:22.448
You know, for what do you do in this environment with the sdrs, or you know the bdrs or whatever you want to call them.
00:43:22.448 --> 00:43:31.827
Right this, moving fully to this model, it's part of why, you know, as Christine alluded, there's such a huge change management aspect associated with this.
00:43:31.827 --> 00:43:37.262
It's fundamentally a large scale process change across the entire organization.
00:43:37.262 --> 00:43:56.294
That has comp impacts, right, um, real, real finances that need to be accounted for and the idea of, okay, if marketing is putting together a buying group pre-opportunity that's ready to go to sales and start selling it, how does that work for the bdr?
00:43:56.294 --> 00:43:57.036
What does that mean?
00:43:57.036 --> 00:43:57.397
What are they?
00:43:57.740 --> 00:43:58.903
getting what are they doing?
00:43:58.944 --> 00:44:09.452
then, um, I think you're going to see it done in a lot of interesting ways TechTarget, for anyone wanting more information, john Steinhardt has got a really, really good approach.
00:44:09.452 --> 00:44:15.403
He recently wrote a blog about it that's up on the Lean Data website, palo Alto Networks.
00:44:15.403 --> 00:44:28.113
You'll see, marketing is just working really closely with the BDRs and when marketing fills that out for pre-opportunity, they send it to the BDR and then the BDR is comped on building that out even further and doing those initial calls.
00:44:28.113 --> 00:44:36.004
So there's a lot of different ways it can go and I think it's good that there's no prescriptive one size fits all flavor to it.
00:44:36.004 --> 00:44:39.393
Right, because these companies and systems are so complicated.
00:44:39.393 --> 00:44:43.551
Anyone who says they've got the solution is, you know, selling you snake oil.
00:44:44.560 --> 00:44:46.425
Well, I mean, this is what I always talk about.
00:44:46.425 --> 00:44:49.152
Is the sort of fallacy of best practices, right?
00:44:49.152 --> 00:44:51.024
Because, like it's not.
00:44:51.024 --> 00:44:54.393
I mean there's not a one-size-fits-all place.
00:44:54.393 --> 00:44:56.942
I mean there's too many nuances, and I think.
00:44:57.923 --> 00:45:14.277
What I do believe, though, is that, like these kinds of technologies, ai, whatever I still think there's going to be a place for that human element, no matter what, in all seriousness, but people will need to adapt, and it will change the nature of the work that they do, and they need to be able to adapt to that.
00:45:14.277 --> 00:45:18.863
And if you can't adapt to that, that's and in some ways, it could be way more interesting, right?
00:45:18.863 --> 00:45:37.121
If you're, if you're spending your time like oh, now, I know I'm not just completely throwing darts at a big ocean of people at this account and I can target because I get specific people right I can imagine that being way more interesting and less, you know, soul crushing.
00:45:37.121 --> 00:45:45.275
If you're just doing that kind of outbound stuff, it is hard to do that and get hung up on and cursed out or whatever, right?
00:45:45.275 --> 00:45:48.649
So well, why don't we do this?
00:45:48.649 --> 00:45:57.188
So, we've covered a lot of ground and we're kind of tight on time here, but maybe can you give us a quick rundown Like what's next, christine, in this rollout?
00:45:59.101 --> 00:46:01.469
The readout, which I'm super excited about.
00:46:01.469 --> 00:46:10.077
It should be like I said we ran the data, so we should have it in the next few weeks while they run the analysis.
00:46:10.077 --> 00:46:11.883
Again, if you have your own data science team, you can do it.
00:46:11.883 --> 00:46:24.188
I don't have the luxury of having that, so I worked with our partner and I plan given that I can have it rolled out, the analysis in the next, you know, two weeks.
00:46:24.188 --> 00:46:46.543
I plan to have a proposal to the executive staff for a 2025 rollout for the enterprise team and, even if that seems too big for them to roll out or if they're a little uncertain, I have two reps that are really anxious to participate and I'm going to propose that.
00:46:46.543 --> 00:46:49.851
I know that everyone's going to want to do it.
00:46:49.851 --> 00:46:50.232
Anyway.
00:46:50.232 --> 00:46:54.227
I think maybe my biggest hurdle might be marketing.
00:46:54.227 --> 00:46:54.769
I don't know.
00:46:54.889 --> 00:47:02.188
I'm curious to see how this plays out, not that that would be a hurdle.
00:47:02.188 --> 00:47:06.875
They're going to ask me the tough questions, the questions of how are we going to report?
00:47:06.875 --> 00:47:08.647
What does success look like?
00:47:09.080 --> 00:47:09.421
What are the?
00:47:09.521 --> 00:47:15.644
metrics that you're going to be able to provide for me to feel comfortable, um, understanding.
00:47:15.644 --> 00:47:18.653
Month over month, year over year, week over week.
00:47:18.653 --> 00:47:22.249
Do we have historicals to understand data like this and that?
00:47:22.249 --> 00:47:23.592
So those are the things.
00:47:23.592 --> 00:47:36.324
We have a very analytics-minded CMO who, I think, is not going to say no, he's just going to ask me the tough questions.
00:47:36.324 --> 00:47:37.782
Sales is going to be like oh, that looks good.
00:47:38.570 --> 00:47:42.823
I think they're going to see good numbers Make my job easier, right, right, and so I don't think marketing is going to say no.
00:47:42.761 --> 00:47:43.582
I think good, yeah, I think I think they're gonna see, like good, make my job easier, right, right and so, and so.
00:47:43.582 --> 00:47:44.685
I don't think marketing is going to say no.
00:47:44.846 --> 00:48:04.052
I think they're going to ask me the tough questions that are going to make me think yeah I can imagine I'm going to automate it all yeah, yeah, I mean, I can imagine, coming coming from a marketing perspective, how this would be maybe seen as maybe a little bit of a threat, but also I think, like I think it's a potential opportunity too.
00:48:04.052 --> 00:48:06.264
So I think it really depends on the details.
00:48:06.264 --> 00:48:14.911
Gosh, I wish we could go on longer because I think we didn't even cover everything we had hoped to cover, but this has been really fascinating to me.
00:48:15.842 --> 00:48:17.215
We'll just have to come back on again.
00:48:17.215 --> 00:48:17.700
We'll do a part two.
00:48:17.700 --> 00:48:18.120
There you go.
00:48:18.521 --> 00:48:18.921
There you go.
00:48:18.921 --> 00:48:20.483
There you go, love it.
00:48:20.483 --> 00:48:22.025
Well, thank you.
00:48:22.025 --> 00:48:32.797
So if there's anything like if folks want to keep up with what's going on with either of you or learn more about buying groups, what's going on with lead data, what's the best way to do that, one of you go first.
00:48:33.260 --> 00:48:35.026
Yeah, you can connect with me on LinkedIn.
00:48:35.026 --> 00:48:40.324
Just a maxi, and there is a LinkedIn buying groups leadership group.
00:48:40.324 --> 00:48:40.725
Do you have?
00:48:40.785 --> 00:48:41.365
it Really there Buying Groups.
00:48:41.385 --> 00:48:42.266
Leadership Group.
00:48:42.767 --> 00:48:44.008
Do you have it Really there?
00:48:44.008 --> 00:48:45.810
Sure is, yeah, so, likewise, connect with me.
00:48:45.810 --> 00:48:47.572
I'm on LinkedIn.
00:48:47.572 --> 00:48:49.994
It's a great, great place to be.
00:48:49.994 --> 00:48:55.201
Connect, alice A Walker is my URL Pretty easy to spell?
00:48:55.201 --> 00:49:02.314
And then come join me in our Buying Group Leaders group that I am a member of.
00:49:02.314 --> 00:49:13.842
The name of the group is literally buying group leaders A lot of good people from from all across different company sizes and industries and verticals.
00:49:13.842 --> 00:49:18.022
Lots of great thought leadership in there, lots of great conversation happening in there.
00:49:18.022 --> 00:49:20.836
So, yeah, if you want to learn more, you want to follow along.
00:49:20.836 --> 00:49:21.217
That's a.
00:49:21.217 --> 00:49:26.512
That's a really great resource, as well as, of course, you course, following along with what we're doing at Lean Data.
00:49:26.512 --> 00:49:30.368
And, if you're interested, everybody loves a hand raiser, that's right.
00:49:30.729 --> 00:49:32.614
Amazing.
00:49:34.321 --> 00:49:39.053
We'll have to get that LinkedIn group from you so we can share it in the show notes.
00:49:39.053 --> 00:49:41.647
Absolutely Great stuff, alice.
00:49:41.647 --> 00:49:42.871
Christine, thank you so much.
00:49:42.871 --> 00:49:44.065
It's been a great conversation.
00:49:44.065 --> 00:49:49.127
I truly do wish we had more time, so thank you again.
00:49:49.127 --> 00:49:51.982
Thanks to our audience for continuing to support us, as always.
00:49:51.982 --> 00:50:03.871
If you have ideas for a topic or a guest, or want to be a guest and want to join us, reach out to Naomi Mike Rizzo or me, linkedin or the marketingappscom Slack group.
00:50:03.871 --> 00:50:06.044
Until next time, everyone Bye now.
00:50:07.267 --> 00:50:08.389
Bye, bye.
00:50:08.429 --> 00:50:08.810
Thank you.