ABOUT THIS EPISODE
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In this episode of OpsCast, hosted by Michael Hartmann and powered by MarketingOps.com, we are joined by Chris Golec, Founder and CEO of Channel99, and Emily Gustin, Business Development Manager at LinkedIn. Chris and Emily share how the shift from individual-level to company-level attribution is transforming how B2B marketing teams measure ROI, particularly in social media.
They discuss how LinkedIn and Channel99 are partnering to provide marketers with a privacy-safe approach to connect paid and organic social engagement to website activity and pipeline impact. The conversation explores the implications for ABM and ABX strategies, the evolving landscape of view-through attribution, and how marketing operations professionals can gain deeper insight into brand reach, buyer behavior, and overall performance across the funnel.
In this episode, you’ll learn:
- How company-level attribution is changing B2B social measurement
- The role of privacy-safe solutions in connecting social engagement to pipeline impact
- Insights into ABM and ABX strategies informed by better data
- How MOPs teams can leverage attribution to understand brand reach and buyer behavior
This episode is perfect for marketing operations professionals, B2B marketers, and anyone looking to improve social ROI and attribution strategies.
Episode Brought to You By MO Pros
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IN THIS EPISODE
SHOW NOTES 🔗
TRANSCRIPT 🔗
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Hello everyone.
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Welcome to another episode of OpsCast, brought to you by MarketingOps.com, powered by all the mo pros out there.
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I'm your host, Michael Hartman, joined today by my co-host Mike Rizzo.
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It's been a while, Mike.
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It has been a while, and I am sorry.
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Just been deep in the throes of community building, certification planning, Mopsa Palooza.
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Mopsapalooza.
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Which we'll we, I think we'll touch we'll we'll touch on during the episode today.
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So let's get into it because we've got a lot to tackle.
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So today we are tackling one of the toughest challenges in B2B marketing, provide proving ROI for social.
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For years, much of our traffic and engagement came from that came from social, has ended up lumped into buckets like Direct or other.
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But that's starting to change.
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So joining us today to talk about that are two guests, which is a little bit unusual for us.
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So joining us again is Chris Golick.
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He's the founder and CEO of Channel 99.
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And uh many of you already know him.
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Also joining is Emily Augustin, who is a business development manager at LinkedIn, and she's leading LinkedIn's measurement and attribution partnerships, and she is working directly with Channel 99 on new solutions that provide company level visibility into paid and organic engagement.
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Chris, Emily, welcome.
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Thank you.
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Thank you for having us.
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Thanks for having me.
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All right.
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Well, let's start with some definitions.
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And I think Emily, when we talked before, uh we were talking about you said something like uh view through attribution.
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So why don't we start with that?
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Like definitionally, what does that mean to you and why, especially given your experience having worked with marketers in your previous roles at LinkedIn, like what do you like, why do you think that's relevant for B2B marketers today?
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Sure.
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I mean, I think the definition of view-through uh attribution or view-through uh clickless engagement would be stuff that is not tracked, you know, with a click and not tracked via UTM.
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So if you think about marketing measurement like, I don't know, an iceberg, I'll give that metaphor for today.
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This would be the stuff below the waterline that you oftentimes don't see, but it makes the iceberg what it is.
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And it's very relevant for B2B and for LinkedIn marketing, because in B2B, you have very long sales cycles.
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So it's important to understand more than just the last few clicks.
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Um it's also very relevant with respect to LinkedIn marketing because you're reaching real decision makers.
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You know, you're you're targeting people by the criteria that's on their LinkedIn profile.
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So you know that when you you have viewed through events, they're coming from very real professionals, right?
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This is not traffic that you should just do away with when you're doing your marketing measurement.
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Got it.
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Okay.
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Yeah, I like the iceberg analogy.
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I'm depending on what it is, I use the duck one too, sometimes, you know, all the like all the activity that's happening below the surface, but iceberg seems like a better one for this.
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All right.
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So, Chris, kind of tying this together with what you're you're seeing and hearing from your customers, and you know, what is it that you've been hearing from them that's led to this integration between channel 99 and LinkedIn?
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Yeah, I mean, a big problem for B2B marketers is the fact that 70 or 80% of all their website traffic comes through from an unknown source.
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And so a lot of this is all view-through traffic.
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And a lot of these legacy attribution tools have ignored it.
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And to me, you're not going to get the right answers if you're ignoring the largest customer signal.
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And as it relates to organic social, that kind of attribution or engagement is really high value intent signals.
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And so the integration is really helping us understand, you know, taking that, you know, those that level of engagement out of the direct bucket and properly assigning it to LinkedIn, you know, whether it's organic or paid social.
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Is it I'm just curious because I in my like what I've been noticing lately when I'm working with teams who are trying to grow their their audience, right?
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It feels like social is like the only place where you can do that without running into serious issues with privacy and restrictions.
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So like is it becoming a bigger issue that you're seeing, Chris?
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Emily, you too, like I don't um just because it feels like the growing an audience is becoming harder and harder without going through social.
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Well, I I'll just I'll uh I I do know that people are clicking less.
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So that the amount of view through is actually growing.
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And the level of view through attribution that we see is typically four or five times greater than people clicking.
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And so it it's significant and it changes our OR metrics uh significantly.
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I'll just add on to that.
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I mean, we know that social or LinkedIn or B2B social is a really critical means of reaching a potential buyer.
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We talk a lot in advertising about reaching the right person at the right time with the right message, and that's something that can be done uniquely on social and on LinkedIn if you're trying to drive a B2B purchase.
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And organic social is particularly interesting.
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We've done a bunch of studies at LinkedIn.
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What we've seen is that those who interact with your company page, the brand's presence, organic presence on LinkedIn tend to have higher intent, which makes sense.
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It's sort of of a proxy for, you know, you could think of it almost like a G2 page or some of the other B2B industry spots where you might go and do research.
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So that type of engagement is super relevant.
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It's important to drive if you're a marketer.
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It's also important to understand if you're doing measurement.
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Yeah, it makes sense.
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So um super sorry, I'm gonna jump in right, but it's it's really interesting to like think think about this idea of view through.
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I mean, just from from where I sit, you know, um on the community side, we're constantly trying to engage with our audience in as many ways as we can.
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And and uh I I'm in this, I'm in this little, I don't, we we refer to we have a silly name for this small group of uh founders that we're in.
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There's like four of us.
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We're constantly trying to figure out like how in the heck do we get anyone's attention with the message that we want to put out there, and you know, LinkedIn happens to be our predominant choice uh of social platform to use to do so.
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And you know, and lately like the the sort of like changes in the way LinkedIn's algorithm has been working has certainly had a significant impact on the way we used to perceive and measure the success, quote unquote.
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Uh air quotes for those of you just listening, uh the success of our of our efforts.
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Um and so I'm I'm I'm particularly excited to to hear about like what's going on at LinkedIn and with channel 99 sort of layering on with the two of you kind of uh playing nice together, because it is hard to measure like the success of what's going on, because it is it is completely different than it was just like two years ago, roughly, right?
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Where we were seeing tens of thousands of impressions and all kinds of other interactions on the thing.
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Um, and now if there's a way to actually measure some of this back to your organization, right?
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And obviously for us, it's just about like putting the good message out about the community and getting more community members in.
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But for B2B organizations, you know, driving that traffic back to your website with real intent and signal, like that's really, really exciting.
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So I I don't know.
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I'm just like I'm excited to hear that there's kind of a obviously something's been cooking underneath the water that I am gonna use the duck analogy.
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The duck's feet have been moving very quickly over at LinkedIn, it sounds like.
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And and I'm just I'm excited to hear it.
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So yeah, anyway.
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Yeah, I think that's a fair segue to, you know, what the heck are we launching with channel 99?
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Um, and I'll just say that I think for a long time, platforms like LinkedIn didn't really provide a ton of engagement data to fit in with the source of truth platforms that we know that advertisers are using for measurement.
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Um, things have changed and we're able to provide that data in a privacy-first you know, way by looking at things at a company level.
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And so whether you're thinking about organic engagement that you're driving or uh interactions with your paid ads, we now pipe you know LinkedIn engagement data into B2B analytics and attribution platforms like channel 99 so that you can get that full picture of the buyer journey.
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You can see below the waterline, you can, you know, ducks feed, whatever you want to use there, um, night vision goggles, whatever you want, right?
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How you can actually get a picture of how a company moved from, let's say, organically engaging with your brand to perhaps engaging with your paid ads, but they weren't yet, you know, a company you might have been calling on or you might have pipeline tracked in your CRM for all the way through into that kind of close one, you know, final conversion event that everybody is trying to measure.
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And just to like be clear about what we did not do in the past, which is the change that we're making here, is we didn't provide that full suite of uh of touch points at the company level.
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We'd let you look at LinkedIn uh paid marketing data by top X number of companies you reached or engaged, but we never gave you the full pipeline of every engagement event at the company level.
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And since ViewTroop is so important, since the B2B sales cycle is so long, we felt like it was about time to give marketers that visibility that they deserve and that will help to you know make their efforts a lot more successful if they can use the intelligence.
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That's really cool.
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Sorry, uh I want to double click, and I apologize to take us off off script just a little bit.
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I want to double-click on um uh because I I know we have really good questions we want to ask you, but I want to ask this question.
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Um the the idea of company level data, and I don't know if that's like Chris or Emily or both, can we sort of unpack that just a little bit?
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Like and and more specifically, I think if I was a Mo pro, marketing operations professional, RevOps professional, very familiar with using data, attribution, all kinds of things in these in these various products.
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Um, if there's now uh a data layer that we have access to and you're calling it this company level information, my next immediate question is do you mean the employees who are associated to said company?
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And then it rolls up in aggregate.
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So the compliance piece is basically protected in that way.
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So like I now work at okay, cool.
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I'm seeing head nods.
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So I'm gonna stop asking the question and just ask that.
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Yes.
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Um, that is the answer to your question is uh we aggregate, you know, individuals' member profiles up to a company that they belong to.
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Um and we share this data for marketing measurement purposes explicitly and only in a way that would be you know extremely privacy compliant.
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So we won't report out on engagements unless there's a certain minimum number of those engagements, and we won't report them out until companies are a certain size.
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So you're never able to de-anonymize the traffic, even when combining it with other data sources.
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What this meant to do is provide an input to measurement that is accurate because we know that user-level signal is sparse, uh, that actually makes sense for B2B marketing because we know that it's not just an individual that drives a purchase.
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It's a, you know, more like a buyer group of several individuals at a company and signal that can be gathered from other places that are not just LinkedIn, right?
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Like this practice has been going on for a while in the world of account-based marketing.
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I think LinkedIn's seeing the industry shift more toward that approach to marketing, and we are able to provide a signal into it that we hope can just make advertisers more successful while being privacy, you know, first.
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I think Mike, uh second part to your question though, it it does make attribution and kind of turns it on his head because quite often what happens, people will read a you know, organic post and then they'll search on Google and then come to the website and paid search gets the credit, when in fact the first touch was organic social.
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So you got to be able to map that whole journey.
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Well, it's interesting, Emily, that you you I was gonna I actually was thinking in my head, this is like sounds like something that would tie in with the concept of buying groups in ABM.
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So I think I think um again, just going into like how hard it is to reach people individually now, like I think that's really powerful.
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So if you can target that based on the the person and what they their role may be in whatever it is your uh service or product is gonna provide, right?
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And where they'd be an important piece of that buying group or decision making group is huge.
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So um, yeah.
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So so Chris, maybe like what is it like Emily, you've kind of hit a little bit on like what are some of like from a marketplace standpoint, what has changed, but like is there like from a technology standpoint, Chris?
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Like what else is like what other changes have you seen out there that are like have have you excited about what this what this has to offer?
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Well, well, number one, I think view-through attribution happens across all channels, you know, email, display, uh, content syndication.
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Uh social is one of the most important to solve because it is one of the higher intent signals.
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Um and you know, I obviously came up through account-based marketing, but at the end of the day, it's it's the same thing.
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It's company level.
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And I would say, you know, CRM systems are all architected based on companies and accounts.
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Sales teams are all organized around companies and accounts, so it really helps align sales and marketing team together.
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Yeah, it's like for me, it feels like going back to the old school way, right?
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Named accounts and selling and and all that.
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That is I I I I deal with this all the time uh with marketing and sales teams where we talk about attribution in terms of people, but sales I think this is part of the disconnect between sales teams and and marketing teams when it comes to attributions because at the end of the day, salespeople think about accounts and opportunities.
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They don't think of people are sort of come along for the ride, right?
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So this is helping to bridge that that gap, it feels like.
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So um maybe talk about this a little bit, maybe Christy first and then Emily, but like how how is company level attribution shift?
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Like how how's that going to change, do you think, or are you already seeing a change in how people think about influence, reach, impact, kind of all like up and down the funnel?
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It's a good question.
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I mean, I think we're everything is becoming account centric.
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It doesn't necessarily mean ABM, because it's more of a strategy of measuring everything at the account level and really understanding yes, pipeline impact and revenue is number one, but there are a lot of other measures along the way of looking at channel efficiency.
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Like what does it cost to engage a target account channel by channel?
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And how do I look at that on a level playing field that's unbiased?
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And um, and so that's why you know our partnership with with LinkedIn helps us do that for the customer.
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And it's a great leading indicator to get to Pipeline.
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I would just add, I mean, I think a few points that this all helps you kind of refine your audience-based strategy.
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Um, I think what we've been seeing for the past few years is B2B marketers have moved toward really centering around the count as source of truth versus an individual, right?
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So, you know, from planning to activation to measurement, there is now this pretty clear flywheel, right?
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Where company or account, whatever you want to call it, is at the center, right?
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It's that currency that's transacted, then bought, and then measured upon.
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And so this makes the flywheel even tighter.
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Now, this is the norm for B2B, which makes execution a lot smoother.
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Um, I think for the industry, it improves the focus on reaching the right audience.
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There's always kind of that concept of spraying and praying and marketing where any impression or any unique individual that you reached is equal.
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Um this may be true for some brands in B2C, though even there, I don't know that it works that well, but it's certainly not true for B2B.
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You know, you need to find companies that are actually a fit for your product or that are in market or could be in market for your product, for that impression to be, you know, impression that you want to spend a dollar on.
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And so I think how this all comes together, if we are focusing from planning to activation to measurement around, you know, a priority audience of accounts, is it makes everybody work better together, right?
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Your brand and demand team, organic team, as well as sales and marketing, right?
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Because you're marching toward the same goal.
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So everyone can be trying to kind of like move the ball forward together, playing their own role versus kind of like finger pointing about why didn't this group do this or do that, or could we be doing better here or there?
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You're architecting your strategy around one common goal, one common set of metrics, which at least makes the strategy and the execution easier.
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Yeah.
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No, I mean, I think it's what's unfortunate is I still think spray and pray, although nobody like it's still, I still run into teams where I really try to guide them to you know narrow the aperture of their target so that it's a better match for what they're doing.
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But then they get concerned about the volume, right?
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Because I think they're so trained into it's a it's a volume game, in quotes, right?
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So and I think everyone's bought into the idea, like I can't I I don't hear a lot of people arguing against the idea of whether you call it ABM or account focused, right, or like that.
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But it does feel like we're at a maybe this is a tipping point.
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We actually had a uh another episode recently about MQAs, right?
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Which is kind of aligns with this.
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And it feels like like do you think this is like maybe the beginning of the end for individual level lead attribution kind of stuff?
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Like I Emily, you've worked a lot with different marketers, like what's your sense for what people are thinking about that these days?
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Well, first I would just say, you know, with respect to like a targeting or or audience strategy, um, you know, we don't need to think even as literally as you need to have a priority account list of a thousand or a hundred thousand accounts, right, that you're going after.
00:19:09.529 --> 00:19:10.649
It could be a type of company.
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Yeah, I think the focus is on finding the type of business that would be well suited for you to sell into.
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And that might mean actually broadening your aperture, right?
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Like thinking about like who is the ideal customer profile here, and then what are the myriad of companies that they could work at or types of companies?
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Um, so I think you could actually end up getting even broader, but just smarter and broader using, you know, a company uh-based strategy.
00:19:34.970 --> 00:19:40.889
And in terms of lead level attribution, listen, I don't think that it will ever go away.
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Um, but I think that B2B marketing and sales will evolve for the better, which is always the hope.
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I mean, for marketing, you know, MQLs, MQAs, they're not the only metric that matters and they they never should have been.
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Um, but similarly, like events that are tracked in your CRM, even if it's a closed one deal, aren't the only metrics that matter, right?
00:20:00.569 --> 00:20:08.889
It's important to understand the full journey because that's where you where you can recognize where am I wasting spend, where am I not driving efficiency?
00:20:08.889 --> 00:20:12.970
And each point matters to get the thing that you want in the end, right?
00:20:12.970 --> 00:20:18.649
So I think the MQL, the MQI, whatever you want to call it, is just one step along that process.
00:20:18.649 --> 00:20:26.329
Um, and I think for sales, you know, there's an understanding now that like this is not just an individual that you're trying to reach, right?
00:20:26.329 --> 00:20:38.009
So whether it's a marketing qualified lead or a sales qualified lead, it's important to be marketing and to be selling into a buyer group and then to probably update if you really care about the tracking, your CRM hygiene accordingly.
00:20:38.009 --> 00:20:44.009
So you're not just focusing on one person at the target company that you want to sell into, right?
00:20:44.009 --> 00:20:47.210
So I think lead metrics will never go away.
00:20:47.210 --> 00:20:49.849
They're an important middle stage of the funnel.
00:20:49.849 --> 00:20:57.369
But I think it's about not only focusing on that metric, understanding the full journey, and not thinking that it's only about one individual.
00:20:57.690 --> 00:20:57.849
Yeah.
00:20:58.009 --> 00:20:59.129
It's an and, not an or.
00:20:59.129 --> 00:20:59.849
I love.
00:20:59.849 --> 00:21:00.250
Yeah.
00:21:00.490 --> 00:21:00.809
Yeah.
00:21:00.809 --> 00:21:01.210
Yeah.
00:21:01.210 --> 00:21:02.970
I love, I love all this.
00:21:02.970 --> 00:21:16.329
Like I would love to see a world where, you know, uh, there's a, for lack of a better term, a dashboard, a report, a moment in time where the team has said, guess what?
00:21:16.329 --> 00:21:24.250
Here was our goal to uh lay a foundation of coverage to reach these sort of ICP accounts.
00:21:24.250 --> 00:21:27.049
And here's what we did, and here's how many impressions we got.
00:21:27.049 --> 00:21:35.609
And oh, look at how many net new connections our sales team got with people at these companies.
00:21:35.609 --> 00:21:37.769
Those connections are now in place.
00:21:37.769 --> 00:21:50.889
They may not actually be names in our database, but just the the fact that there's a one-on-one connection with, you know, 10% of our total sort of effort right now is headed the right way.
00:21:50.889 --> 00:21:51.450
Right.
00:21:51.450 --> 00:21:54.089
Like that is just a huge win.
00:21:54.089 --> 00:22:00.089
And like never once have I had a conversation with a group of people that's that brought those two things together, right?
00:22:00.089 --> 00:22:06.089
Like if our sales team is making a connect on LinkedIn with somebody, right?
00:22:06.089 --> 00:22:19.769
Because we're able to sort of see view through, and and then we just like aggregate some new data together, says, Oh yeah, Chris is now a first degree connection with whatever 20 people across our 150 accounts.
00:22:19.769 --> 00:22:22.490
That wasn't there before, right?
00:22:22.490 --> 00:22:27.769
We'd have to guess that that's not just because they thought Chris looked like a really cool guy, even though he is, right?
00:22:28.490 --> 00:22:33.609
Yeah, I think it bolsters a case for organic, it also bolsters a case for brand advertising as well, right?
00:22:33.609 --> 00:22:40.329
Because if you're able to link like somebody saw a brand advertisement, they're an account that I care about, we know how we move them down the funnel.
00:22:40.329 --> 00:22:43.129
We've always known that brand was important and that brand worked, right?
00:22:43.129 --> 00:22:46.250
But we never knew how to justify it or really how to measure it.
00:22:46.250 --> 00:22:53.450
So I think it, you know, whether it's organic, whether it's brand, it makes a case that again, each of these things are critical and they all pass to the next.
00:22:53.450 --> 00:22:55.129
Um, I don't know, Chris, what you think about that.
00:22:55.450 --> 00:23:02.889
Yeah, I mean, the the number of times I've heard customers ask, I want to target just the CIOs at the Fortune 500.
00:23:02.889 --> 00:23:05.690
I'm like, you're gonna target your way out of business.
00:23:06.329 --> 00:23:07.849
You and everyone else.
00:23:08.970 --> 00:23:17.210
Yeah, so I think I think this notion of buyer groups is really exciting and compelling, especially for like pipeline acceleration.
00:23:17.210 --> 00:23:22.329
And um it's just the innovations are just getting tighter and tighter.
00:23:22.730 --> 00:23:30.009
Well, and it's just it's nice to see the the sort of pendulum swing a little bit back toward, you know, to your point, Emily, right?
00:23:30.009 --> 00:23:34.649
Like back toward brand and the importance of getting that coverage, right?
00:23:34.649 --> 00:23:45.210
And and we've all now sort of come to fruition with the idea that not every CIO or CTO is gonna be actively on LinkedIn waiting for that email to come in.
00:23:45.210 --> 00:23:48.889
And um, and then you know but they want your nurture email.
00:23:48.889 --> 00:23:51.849
But they definitely want your nurture email.
00:23:51.849 --> 00:24:06.490
Um, and and you know, on top of that, I think it's just nice to see that um we've we've I don't know, the whole tech sector has had this re-equating with, you know, it's not growth at all costs, right?
00:24:06.490 --> 00:24:14.250
And you know, we're talking about sort of uh an expanding and narrowing of aperture for your target accounts and all those things.
00:24:14.250 --> 00:24:21.930
And I think all of that is in the vein of you're you're doing your best to not spray and pray anymore, to Michael's you know, point.
00:24:21.930 --> 00:24:29.609
Um but like the heart of the shift is like the funding changed in the market, right?
00:24:29.609 --> 00:24:39.769
The buyer behavior has changed, and then on top of that, technologies like this are now enabling us to do things that are fundamentally different, which is really, really, really cool.
00:24:39.769 --> 00:24:46.730
If I could just like I'm gonna just share a nugget from our state of the mo pro research from this year for this for the listeners, right?
00:24:46.730 --> 00:24:50.009
Early preview sneak peek, little early preview.
00:24:50.009 --> 00:24:59.450
So uh key finding number six from our data says that AI and attribution tools are the top investment priorities for the next 12 months.
00:24:59.450 --> 00:25:11.129
We had over 61% of the teams say that they're planning to invest invest in AI or machine learning-based tools, and 45% of them are gonna invest in marketing, attribution, or reporting tools.
00:25:11.129 --> 00:25:14.490
And it's saying that the it's reflecting sort of a broader trend.
00:25:14.490 --> 00:25:19.690
About 68% of our RevOps teams are also planning to invest in advanced analytics and AI.
00:25:19.690 --> 00:25:27.769
So, like everybody's honing in on this idea of how do I understand what's going on through the data layers that I have access to now.
00:25:27.769 --> 00:25:31.930
And they're thinking about, you know, this attribution problem, right?
00:25:31.930 --> 00:25:33.690
This account-based targeting problem.
00:25:33.930 --> 00:25:39.690
I think it's very, very clear from our well, uh it's interesting because I mean I was like struck by your idea.
00:25:39.690 --> 00:25:46.490
Like, I I agreed with the idea, like you don't have to have a tar prioritized targeted set of accounts to target.
00:25:46.490 --> 00:25:55.129
Like, I that's one of the pushbacks I've always given to sales teams or other marketing teams who've come to me and said we need to do ABM because what they're thinking about is buy technology, right?
00:25:55.129 --> 00:26:07.210
So I I love that idea that like you don't have to that, and I'm I hadn't really thought about like you could open the aperture that there on your targeting, uh, especially when you've got technology that enables you to do it.
00:26:07.210 --> 00:26:17.289
It's it's almost like it's like I think I was realizing in the mo after that you said that that I'm still thinking in the model of I'm targeting people as opposed to companies or accounts.
00:26:17.289 --> 00:26:31.609
It's like even I, even though we've been talking about like even for me, it's like it's hard to break out of some of these habits and and and get into that mindset that that it's you know to get into the a combination of the two, to your point, right?
00:26:31.609 --> 00:26:33.210
The the lead stuff is never gonna go away.
00:26:33.210 --> 00:26:35.129
I think that's also true.
00:26:35.769 --> 00:26:58.009
Yeah, I I mean, I also think, I mean, for for for the sake of what uh channel 99 and LinkedIn are doing, enabling you to find those targets in new ways and measure them in new ways, um, I think is just I mean, that's a win on the alignment side of your sort of broader go-to-market strategy, right?
00:26:58.009 --> 00:27:15.289
And then educating your sales team on here's who we're sort of going after, let's try to make connections into these accounts, but it never replaces the fact that there's a very important step of the being like myopically focused on a particular account and its particular journey, right?
00:27:15.289 --> 00:27:21.450
If it had just had funding rounds and all this other stuff, they're hiring, they're firing, they've just acquired new tools.
00:27:21.450 --> 00:27:34.649
Uh, the person graduated from USC, like stuff like that will make the difference in building the relationship and being able to like use the specific right language, which is exactly what a salesperson wants to go do.
00:27:34.649 --> 00:27:41.129
But if we can like a good sales a good salesperson simple companies across the way.
00:27:41.129 --> 00:27:43.289
Yeah, a good salesperson.
00:27:43.289 --> 00:27:44.089
Exactly.
00:27:44.089 --> 00:27:46.250
Anyway, yeah, sorry, I'm rambling.
00:27:46.250 --> 00:27:50.089
And so far, this has been a fun thought experiment to go through.
00:27:50.730 --> 00:27:56.889
Well, I just think to your point, Mike, on the rise of attribution tools or marketing measurement over the next few years.
00:27:56.889 --> 00:27:57.930
One, that's exciting.
00:27:57.930 --> 00:28:00.410
Chris and I are probably both pumped to hear that.
00:28:00.410 --> 00:28:09.609
Um, two, uh those types of tools allow you to abstract the like higher level finding of what type of businesses should we be going after?
00:28:09.609 --> 00:28:11.930
How should marketing be connecting with sales?
00:28:11.930 --> 00:28:22.410
Like, how do we make this actionable so that we generate demand and then revenue for our business, which is the goal of B2B marketing, if not all marketing.
00:28:22.410 --> 00:28:34.649
Um, and so I think the the rise of Gen AI has made marketing measurement actually really exciting because measurement is nothing if it can't be actioned on and then used to improve your performance.
00:28:34.649 --> 00:28:49.849
So I think the technology that we already have in place in the last few years, what's coming down the pike in the next few, along with the data that's available via solutions like this, allows you to get those like higher level findings for how should my business orient sales and marketing, right?
00:28:49.849 --> 00:28:51.690
This isn't just about measurement for measurement sakes.
00:28:51.690 --> 00:28:53.849
Like what type of accounts should we go after?
00:28:53.849 --> 00:28:55.529
Who could be a fit for our brand?
00:28:55.529 --> 00:28:57.849
Those are super important questions to ask.
00:28:58.170 --> 00:29:02.329
And then once you know those accounts, you know, what are the the best channels?
00:29:02.649 --> 00:29:03.289
Yeah, right.
00:29:04.250 --> 00:29:05.529
You shouldn't guess.
00:29:05.529 --> 00:29:08.329
It should be right in front of you.
00:29:08.569 --> 00:29:10.250
I'm trying to try to rack my brand.
00:29:10.250 --> 00:29:31.690
I like I know of examples that I've run across that camera where where you know you think of your business as this is our target audience, and then if you're paying attention to data, you get surprised that these people in this other industry that we never thought about, or these roles that we never thought about, or looking at our tool, and it like it could open up a new possibility for where you're taking your product or service, right?
00:29:31.690 --> 00:29:34.730
And so I think that's because sorry, Mike, I cut you off.
00:29:35.129 --> 00:29:35.849
Oh, no, no.
00:29:35.849 --> 00:29:38.490
It's uh it was it that's yeah, no, I I agree.
00:29:38.490 --> 00:29:56.889
I've uh you know just to that, just to that point, it's it is hard for organizations that you know, I I think of Mavenlink, for example, when I was there, like there were countless moments that the founder would come over and like be like, all right, we're gonna be da-da-da for da-da-da-da-da-da.
00:29:56.889 --> 00:29:59.210
And it would just like change, you know, in the early days.
00:29:59.210 --> 00:30:08.009
And so the reality is like, as you know, there's probably a time and a place where technology like this is really, really strong.
00:30:08.009 --> 00:30:11.049
It it can give you the right signal along the way.
00:30:11.049 --> 00:30:21.849
If but if you haven't quite probably figured out like what your you know, target market like buyer fit actually looks like, you might you might struggle just like any other startup.
00:30:21.849 --> 00:30:34.089
Um, but I think I Think where that takes me next, and Emily, and uh forgive me for being totally ignorant to some of the capabilities that that LinkedIn is um unleashing with with Cho 99 here.
00:30:34.089 --> 00:30:43.769
Um when I think about demand gen, which I appreciate that you said generate demand, it is not leads, and that is a fundamentally different thing.
00:30:43.769 --> 00:30:54.970
Um when I think about those sort of like relationships between demand gen teams that are often doing ad campaigns, and uh conversion usually ends up being like a core focus, right?
00:30:54.970 --> 00:30:59.369
So the conversion pixel fires when the form is submitted or something like that.
00:30:59.369 --> 00:31:09.210
Is there, uh, or maybe this is for Chris, uh, is there a version of that where like LinkedIn learns a little bit about what is converting through channel 99's integration?
00:31:09.210 --> 00:31:20.490
Like there's like a conversion pixel pixel, so to speak, a success metrics that's passed back that helps uh this new capability find more, I guess.
00:31:20.970 --> 00:31:22.329
So I think that's the hope.
00:31:22.329 --> 00:31:35.529
Um, right now, the way that this integration works is we provide our engagement data at the company level to a platform who's an expert in measurement and also has you know CRM outcomes synced to the platform like channel 99, right?
00:31:35.529 --> 00:31:43.930
And they're able to sew this together to say basically, okay, all these company engagements from LinkedIn, and then these company level, you know, tracked outcomes in the CRM.
00:31:43.930 --> 00:31:46.730
We believe there's a certain correlation between the two.
00:31:46.730 --> 00:31:48.170
That's attribution, right?
00:31:48.170 --> 00:31:58.490
In the future, what we'd like to enable is for some of the aggregate information about that attribution that would be in channel 99 to be passed back to LinkedIn.
00:31:58.490 --> 00:32:22.329
So we would have some understanding of, you know, what were the largest deals driven or the campaigns that contributed to those deals where LinkedIn, you know, favorably uh, you know, won credit, let's say, so that we can keep our machine oriented toward driving more of those deals, toward the you know, most performant campaign types and assets and all of that stuff.
00:32:22.329 --> 00:32:24.410
So good question.
00:32:24.410 --> 00:32:35.210
I think it's it's a good one to now have out there in the in the industry because hopefully it'll get things moving uh a little bit to be able to cover that full circle.
00:32:35.529 --> 00:32:35.930
Yeah, yeah.
00:32:35.930 --> 00:32:50.170
It's just an it's I think I I think any any fairly um versus technical marketer who's dealt with these conversion metrics, like might end up in a place where they're like, well, how do I, how can I tell it what is success?
00:32:50.170 --> 00:33:01.690
But I think the abstraction layer, so to speak, uh where all this data comes together from the data pipe that is that is linked in in channel 99, I feel like that's a really sweet spot for for channel 99.
00:33:01.690 --> 00:33:16.730
Like you guys, I know you guys are working on tying all that stuff together and giving the end user the ability to sort of make those decisions themselves anyway, which doesn't, you know, then you then you pipe back data right into like here's here's my more of my targets that I'd like to go after.
00:33:16.730 --> 00:33:18.730
So um, but that's cool.
00:33:18.730 --> 00:33:21.369
It's it's good to it's good to know that there's thoughts around it.
00:33:21.369 --> 00:33:29.609
It's that definitely naturally where my brain went, like as we were thinking of like success, measuring success around uh this motion in the market.
00:33:30.009 --> 00:33:41.289
Yeah, I think there will be a lot more interoperability with MCP servers and the ability to execute campaigns automatically and optimize campaigns.
00:33:41.289 --> 00:33:53.609
And it's not always just pipeline, it could be you know targeting efficiency, like what percentage of my impressions are reaching the right accounts and what does it cost me to engage a target account?
00:33:53.609 --> 00:33:57.369
These are all great leading indicators of pipeline influence.
00:33:59.129 --> 00:33:59.609
Yeah.
00:33:59.609 --> 00:34:14.329
So okay, I I I I know this is we're still in the early days of this kind of being rolled out, but I'm curious, like what um do you have any examples uh or stories where you maybe two twofold, like where you've seen success, right?
00:34:14.329 --> 00:34:22.570
Where companies, uh your club customers um or members are seeing success for this or anything that's been a surprise.
00:34:24.170 --> 00:34:28.970
I'll just start by hitting kind of some of the findings from the beta and then takeaways.
00:34:28.970 --> 00:34:31.050
And Chris, I'll I'll pass to you.
00:34:31.050 --> 00:34:40.970
Um, but to help you know the listeners understand kind of the magnitude of the change of the type of data that we're sharing over and the results that we're seeing.
00:34:40.970 --> 00:34:54.970
Um, when we uh egress this company intelligence uh data to the five partners that we're launching uh this solution with, they were able to see almost 300% more companies that have been reached by LinkedIn.
00:34:54.970 --> 00:35:06.170
Um and what that connected to was almost 100%, 96% more sales qualified leads across, again, all of those five partners using a range of different attribution models.
00:35:06.170 --> 00:35:13.050
81% more close one deals that were touched by LinkedIn, and 43% then lower cost for acquisition.
00:35:13.050 --> 00:35:20.330
So essentially LinkedIn's cost at driving a deal to close halved uh with this data incorporated.
00:35:20.330 --> 00:35:25.530
So that's like the magnitude of the change, which I think was not surprising to us.
00:35:25.530 --> 00:35:28.330
We see or hear from our customers a lot.
00:35:28.330 --> 00:35:37.210
Like, listen, I know that you are working because if I take you out of the mix, things pretty much stop, but it's hard for me to actually prove that.
00:35:37.210 --> 00:35:44.810
And I think by giving out these company level touch points to be included in measurement, we've seen is yeah, there's a lot more coming from LinkedIn than people thought.
00:35:44.810 --> 00:36:01.769
Um, the biggest takeaways or most interesting things that I heard when speaking with a bunch of our, you know, beta customers were one, kind of the agility that these marketers had being able to optimize kind of in real time toward what was performant, right?
00:36:01.769 --> 00:36:12.810
So wanting to go and create, let's say, new audiences or refine the audience that they're currently targeting so they can try to drive deals from pipeline to close with this type of intelligence.
00:36:12.810 --> 00:36:22.090
And the other was, you know, a little unexpected for me, which was the impact for let's call it like brand marketers or those with upper funnel goals.
00:36:22.090 --> 00:36:26.170
So I expected that like this is going to be a hit with demand gen marketers.
00:36:26.170 --> 00:36:26.730
Great.
00:36:26.730 --> 00:36:33.690
You can see how stuff is converting to these CRM outcomes and you can drive, you know, your campaigns being more efficient from there.
00:36:33.690 --> 00:36:49.290
Brand, we have so many verbatim from customers saying, like, this makes the case for my brand investment, because rather than just looking at like impressions and reach as kind of my standards for success, I can now think about the concept of like on target, you know, reach and engagement, right?
00:36:49.290 --> 00:36:52.970
Did I get in front of a priority account that I wanted to?
00:36:52.970 --> 00:36:55.130
And how much did it cost to do so?
00:36:55.130 --> 00:37:03.850
So being able to win new budgets, you know, kind of within the month that this data was provided for brand advertising, which was crazy exciting to me.
00:37:04.250 --> 00:37:04.810
Interesting.
00:37:05.130 --> 00:37:06.090
Chris, how about you?
00:37:06.090 --> 00:37:07.210
Oh, sorry.
00:37:07.210 --> 00:37:09.690
No, no, it's not a Chris go.
00:37:10.010 --> 00:37:18.810
No, just reflecting, and it's like I I think I approached LinkedIn about 18 months ago because we had this tracking pixel to solve for view through attribution.
00:37:18.810 --> 00:37:26.490
And my whole message was obviously preaching to the choir, I'm like, you guys are generating so much engagement and not getting credit for it.
00:37:26.490 --> 00:37:29.610
Nobody's getting credit for it because it's sitting in this direct bucket.
00:37:29.610 --> 00:37:40.730
And while the the a tracking pixel was uh you know wouldn't work for various privacy reasons, um there was discussions around an API in development.
00:37:40.730 --> 00:37:44.330
So that's that's how this all all came to be.
00:37:44.330 --> 00:37:52.970
And um, you know, solving view-through attribution, you can't just do it with one channel, it has to be solved across all channels, so that it is kind of a source of truth.
00:37:53.210 --> 00:37:53.370
Right.
00:37:53.610 --> 00:38:04.010
But you know, to Emily's point, that the factors we're seeing are like three or four X when you consider view through and the other key factor is targeting efficiency.
00:38:04.010 --> 00:38:08.810
Like what percentage of these companies are in my addressable market?
00:38:08.810 --> 00:38:19.690
And you'll see huge differences of looking at LinkedIn social versus uh Paid Search, for example, which is also a an a great intent signal.
00:38:19.690 --> 00:38:27.769
But if 80% of those clicks aren't from companies that will ever buy anything, you got to factor that into your cost per target account.
00:38:28.570 --> 00:38:28.810
Yeah.
00:38:28.810 --> 00:38:33.290
Well, I think it's it's interesting, uh Emily, you brought up two things that really caught my attention.
00:38:33.290 --> 00:38:39.450
One was the ability to like speed and agility, like is this gives these teams who are prepared for it.
00:38:39.450 --> 00:38:44.490
I'm not sure that everyone is, but they can move quickly, like they can see results and move quickly.
00:38:44.490 --> 00:38:46.650
It's one of the like that's huge.
00:38:46.650 --> 00:38:53.930
And then I'm I'm sort of blown away about this, like to you, like I'm surprised about the connection to brand.
00:38:53.930 --> 00:39:02.250
Um, like how how is are you expecting that now as you go into like start talking about this with other people?
00:39:02.250 --> 00:39:05.769
Like, are you expecting this to help with like budget?
00:39:05.769 --> 00:39:08.330
Especially if we're going into like budget season, right?
00:39:08.330 --> 00:39:09.610
People are planning for next year.
00:39:09.610 --> 00:39:14.490
Like, how are you are people starting to use this for their budgeting, both for brand and demand stuff now?
00:39:16.010 --> 00:39:23.690
Yeah, we've seen so for demand, you know, that's kind of again where I expected this to hit and to be a super budgeting.
00:39:23.690 --> 00:39:27.850
Um, so what we've seen is people want to make quick optimizations, right?
00:39:27.850 --> 00:39:31.850
And that normally looks like shifting budgets around from channel to channel based on this data.
00:39:31.850 --> 00:39:36.330
The other would be deploying net new audiences or refining, you know, an existing audience.
00:39:36.330 --> 00:39:41.050
Those are both kind of like demand-centric budgeting um, you know, approaches.
00:39:41.050 --> 00:39:49.130
For brand, what we've seen is like, you know, brand tends to be forecasted how much budget do I need based on region frequency.
00:39:49.130 --> 00:40:05.290
Um, and so now rather than just thinking about again, an eyeball is an eyeball is an eyeball, where that's the way you're forecasting how many total individuals can I reach, we've seen the concept of like on target reach being used as the baseline for brand budgets, right?
00:40:05.290 --> 00:40:10.890
So the first movement that I saw was people saying, oh my gosh, brand is working better than I thought it was.
00:40:10.890 --> 00:40:13.769
Okay, I should be dedicating some more budget here.
00:40:13.769 --> 00:40:21.530
The second was I'm gonna plan around this with this data as like the seed of my forecasting and my budgeting, right?
00:40:21.530 --> 00:40:23.769
How large should my audience be?
00:40:23.769 --> 00:40:26.330
Who should I be trying to get in front of?
00:40:26.330 --> 00:40:28.650
And then how much of that audience do I need to reach?
00:40:28.650 --> 00:40:33.769
What type of frequency do I need to reach them with in order to eventually drive them down funnel?
00:40:33.769 --> 00:40:37.530
So, I mean, this launched in beta earlier in the summer.
00:40:37.530 --> 00:40:56.090
It's been, you know, just a few months, but seeing both the immediate and then the longer term budgetary movement from both brand and demand-focused advertisers, I think is a testament to how different this type of intelligence is from what existed before and how helpful it is to a marketer.
00:40:56.410 --> 00:40:56.810
Yeah.
00:40:56.810 --> 00:41:01.210
The other factor there, Emily, too, is it's not just the reach.
00:41:01.210 --> 00:41:14.250
It's, you know, given the contextual relevance of the LinkedIn platform, the the level of engagement for that same audience also is way higher versus kind of a broad-based, you know, display type platform.
00:41:15.850 --> 00:41:17.050
Yeah, interesting.
00:41:17.050 --> 00:41:24.890
Um okay, so let's maybe shift gears a little bit to the marketing ops professionals who are out there listening or watching.
00:41:24.890 --> 00:41:30.170
Um if they were like, oh, this is something that would peak interest with our teams, right?
00:41:30.170 --> 00:41:36.970
What like what should they be doing to prepare for for taking advantage of this, Chris?
00:41:36.970 --> 00:41:43.210
Maybe you know, with whether it's with travel 99 or something else, but like how what are the like what should they be thinking about?
00:41:43.210 --> 00:41:53.530
Um, and maybe what could they, what would you advise them to be like how to talk about this with their marketing leaders, with their sales leaders?
00:41:54.010 --> 00:41:54.330
Yeah.
00:41:54.330 --> 00:42:09.130
Well, I'll I'll tell you the number one thing when they can show their CMO or their marketing leaders that spend a lot of time putting out thought leader content that it's influencing and turning in the pipe, and these are the companies, the rubber hits the road.
00:42:09.130 --> 00:42:11.610
And so, and everybody gets that.
00:42:11.610 --> 00:42:14.570
And you know, the CMOs love to see that.
00:42:14.570 --> 00:42:16.410
And they haven't been able to see that before.
00:42:16.410 --> 00:42:18.010
So that's number one.
00:42:18.010 --> 00:42:24.890
I think the other piece is you know, really taking the focus on quality of what's being generated, not volume.
00:42:24.890 --> 00:42:36.810
Um, and that's where I keep on harping on, you know, targeting efficiency and making sure you look at view through attribution because it the the all the KPIs change by three or four X.
00:42:36.810 --> 00:42:41.530
So completely different than what the numbers were last year.
00:42:42.810 --> 00:42:43.930
I just add on to that.
00:42:43.930 --> 00:42:48.170
I mean, I think there's always been an issue doing full funnel marketing, right?
00:42:48.170 --> 00:43:12.490
And so if you're able to be that kind of change agent that's able to help link different groups so that you can actually have a full funnel approach from brand to demand, tracking against the same metrics, moving companies from, you know, an engaged account to pipeline to revenue with greater efficiency than you did before, to Chris's point, something that will actually speak to dollars in and dollars out.
00:43:12.490 --> 00:43:17.769
That's a really, really powerful place to be if you can be that person.
00:43:17.769 --> 00:43:21.690
So, plus one, too, that you know, impact on revenue always matters.
00:43:21.690 --> 00:43:31.290
I think being able to bring together teams around this type of data is what makes it actionable and also makes you kind of the hero internally.
00:43:31.290 --> 00:43:39.370
And I'll just plug for those, you know, especially practitioners who are interested in getting a sneak peek at what this looks like and how to use it.
00:43:39.370 --> 00:43:43.530
Um, we have kind of a bite-sized version available in the LinkedIn campaign manager tool.
00:43:43.530 --> 00:43:48.650
It's called companies, and you can look at, you know, much of this data in an abbreviated form.
00:43:48.650 --> 00:43:52.570
You don't get as much of it as you do via the API in the campaign manager tool.
00:43:52.570 --> 00:43:56.490
So if you're wondering, like, what is this account level signal that I can see?
00:43:56.490 --> 00:44:09.690
How might I want to think about it for measurement, for activation purposes, go ahead and play around in the campaign manager tool as long as you have an ad account and you've spent a little bit on marketing, then you can get access to this today.
00:44:09.690 --> 00:44:28.250
And then, you know, partners like channel 99, who are really like what's needed in order to zoom out, look at things across channels, incorporate all the signal that you need to in order to get a correct answer about what's driving what, you take it from there and you can make things even stronger.
00:44:28.810 --> 00:44:35.050
Yeah, I I again forgive me for being ignorant on product capabilities.
00:44:35.050 --> 00:44:53.610
Uh, and and Chris, I think this fodes for uh we need to do a no bullshit demo uh uh with our with our community so they can really see what's going on uh you know in the product and and what it what it does when we're talking about across multi, you know, multiple channels and touch points, right?
00:44:53.610 --> 00:44:55.210
At the channel 99 level.
00:44:55.210 --> 00:45:00.250
Where my head is going around this idea of like I I was I heard you say it, right?
00:45:00.250 --> 00:45:13.690
Like, hey, when when your thought leader is making a post, I can tell we can sort of start to understand is that making an impact and an impression on the individuals who work at the accounts that we want to be selling to.
00:45:13.690 --> 00:45:26.970
And so, you know, that means my CMO, my CEO, my CRO, they're the ones creating content, which I think, you know, ideally they're the ones creating content, or they have somebody helping them to create content to put it out there.
00:45:26.970 --> 00:45:33.450
And I think this starts to change the, you know, well, over a decade ago, we saw this like rise of the social media marketer.
00:45:33.450 --> 00:45:45.050
Um, this is a totally new sort of uh opportunity, I think that's gonna come up, backed by data, enabled by an API layer and and and what channel 99 is doing.
00:45:45.050 --> 00:46:00.730
Um and and I'm I'm wondering though, like, and this is probably just better suited for like an offline conversation or maybe a no bullshit demo, but I'm like, I really want the ability, not every post is gonna be about the company, right?
00:46:00.730 --> 00:46:19.210
And so I kind of want to get to a place where I imagine channel 99 can fit in, and I could say, hey, when my SVP of sales is posting, I can tag different sort of engagement types or uh efforts as like brand focused versus just personally focused or whatever.
00:46:19.210 --> 00:46:25.210
And then I can actually go back and say, hey, which one of these two is sort of making a bigger impression in the market?
00:46:25.210 --> 00:46:27.769
Because I think that stuff matters, right?
00:46:27.769 --> 00:46:40.570
Where this this lay this data layer is coming in from LinkedIn, and you've got these capabilities coming in from channel 99, and we're saying, hey, you're gonna be doing all these different kinds of things.
00:46:40.570 --> 00:46:48.490
And just to start, we're gonna be able to uncover something that is totally, totally new to be able to roll that up in a new way.
00:46:48.490 --> 00:46:53.769
But you're probably gonna want to start going like layers deeper to be able to segment out, right?
00:46:53.769 --> 00:46:59.290
Like, uh, well, not every post obviously is just gonna be promoting the company's capabilities, right?
00:46:59.290 --> 00:47:02.730
Um, and and I kind of want to understand the difference uh between that.
00:47:02.730 --> 00:47:11.050
We're seeing like technologies out there that are scratching at this idea, uh, like this influencer marketing type of type of play, right?
00:47:11.050 --> 00:47:20.330
Um so anyway, I would just love to get to a place where like our audience starts to think about oh, well, how could I report back on this stuff, right?
00:47:20.330 --> 00:47:25.610
And um, and Chris, I don't know if you like from John 99th perspective, where you guys are at.
00:47:25.610 --> 00:47:28.250
Um we had getting a little nerdy here.
00:47:28.490 --> 00:47:28.970
That's okay.
00:47:28.970 --> 00:47:42.330
I mean, we did a fairly limited pilot, but it was very clear the companies that were active at in thought leadership content were by far the most efficient in generating pipeline versus their spend.
00:47:42.330 --> 00:47:47.690
It wasn't it wasn't the companies necessarily just spending the most that were going to generate the highest returns.
00:47:47.690 --> 00:47:52.410
It was the ones that were also very active in putting out thought leadership content.
00:47:52.410 --> 00:47:59.130
And we're measuring this just to be clear at an aggregate level for the company versus individual by individual.
00:47:59.130 --> 00:48:00.170
Right, right.
00:48:00.170 --> 00:48:00.810
Yeah.
00:48:00.970 --> 00:48:01.290
Right.
00:48:01.690 --> 00:48:13.530
Is it also sorry, sorry, does it like really point like is that include though at the company level the individuals who are part of that company who are posting about that or can it can it vary?
00:48:14.170 --> 00:48:15.210
I'll hit that one.
00:48:15.210 --> 00:48:24.250
So what we report on now is um paid and organic engagement at the company level.
00:48:24.250 --> 00:48:29.530
For organic, it would be interactions with you as an advertiser's company page post.
00:48:29.530 --> 00:48:34.730
So if your CMO from his personal LinkedIn page is posting, right?
00:48:34.730 --> 00:48:40.730
And it's not sponsored by the brand and ties back to the brand's company page, that action is not going to be tracked.
00:48:40.730 --> 00:48:45.290
And again, organic, this is stuff is only at the company level.
00:48:45.290 --> 00:48:54.730
Our intention from LinkedIn is never to give um data out about people, you know, individuals engaging, especially with your organic content.
00:48:54.730 --> 00:49:02.810
You know, people are not on LinkedIn to be tracked so that their, you know, organic comments, for example, get put into a bunch of paid reports.
00:49:02.810 --> 00:49:12.570
But I think we're trying to do with this tool is help you like think about a two by two where you're able to kind of put brands into a few quadrants.
00:49:12.570 --> 00:49:19.450
One would be like brands that are engaging with our organic, um, but we're not targeting them with any paid.
00:49:19.450 --> 00:49:24.170
You know, brands that you're engaging with organic and you are targeting with paid, but they're not in your CRM.
00:49:24.170 --> 00:49:27.130
There's no maybe sales isn't calling on them, there's no open pipeline.
00:49:27.130 --> 00:49:32.490
Then you have ones that are engaging across both, and there is, you know, kind of some open pipeline against.
00:49:32.490 --> 00:49:36.090
And then you might have those that are in your CRM, but you're not marketing to at all, right?
00:49:36.090 --> 00:49:43.610
So it's that type of intelligence, which lets you steer your paid and organic marketing ship to its best effect.
00:49:43.610 --> 00:49:56.890
We don't want to go kind of poking around on Emily's individual post or individual comment because our goal is to give businesses intelligence in a way that protects the LinkedIn member experience.
00:49:57.370 --> 00:49:57.530
Sure.
00:49:57.530 --> 00:49:58.890
And that makes sense.
00:49:58.890 --> 00:50:20.810
Well, and it to me, what I my head goes to is like the implications, even with the metrics you described, right, in terms of understanding LinkedIn's effect on pipeline revenue, like if you assume that it that there's also individuals within that company who are both posting their own content, but also content about the company where they're at, right?
00:50:20.810 --> 00:50:23.530
Those numbers are only gonna go up, right?
00:50:23.530 --> 00:50:27.610
So um I think that's and that's that's kind of where I was going.
00:50:27.610 --> 00:50:34.890
Well, as you kind of hinted at this like a little bit, like both of you like, but why we end with like where do you see this going?
00:50:34.890 --> 00:50:41.690
Like what's kind of what's the do you have any plans or vision for where the where the these products and solutions are gonna go?
00:50:41.690 --> 00:50:46.490
Uh whatever, pick your time frame, six months, 12 months, 18 months beyond.
00:50:46.490 --> 00:50:49.290
Emily, you want to go first?
00:50:49.290 --> 00:50:50.650
Yeah, yeah.
00:50:50.650 --> 00:50:51.850
Sure.
00:50:52.410 --> 00:50:57.450
Um, I think you know, an ideal state, and we're already seeing this start to happen today.
00:50:57.450 --> 00:51:02.250
The measurement and activation bits will become, you know, much closer connected, right?
00:51:02.250 --> 00:51:20.490
So being able to take this intelligence and then look at who's engaging with your brand and automatically make updates to your audience, LinkedIn audiences so that you can either address, you know, those that you haven't in the past with pay that you probably should be, or optimize your audience, maybe trim some names out that you don't want to target anymore.
00:51:20.490 --> 00:51:23.210
That's kind of the first horizon, I think, for this thing.
00:51:23.210 --> 00:51:51.769
And I think longer term, where we'd love to go with it, is you know, the the topic that Mike brought up earlier, which is, you know, we're bringing all this account level, company level data into a platform like channel 99, who does great measurement, then bringing back some of that signal to LinkedIn, again, at the company totally aggregate level, so that we can optimize our machine to be most efficient at driving those outcomes for the buyer.
00:51:51.769 --> 00:52:01.690
Um I think that's in everybody's best interest, so long as it can be done in a in a privacy protected way, which is you know the core of this of this solution.
00:52:02.650 --> 00:52:10.570
Yeah, and just to, I was just gonna say almost the same thing, like audience activation and having audiences that are dynamic by nature.
00:52:10.570 --> 00:52:23.210
So if an account is in my addressable market but not in my um pipeline, I may want to push that audience or that list of companies to my SDR team to call into.
00:52:23.210 --> 00:52:28.890
Versus if they are on my pipeline, I might want to retarget to the buyer groups on LinkedIn.
00:52:28.890 --> 00:52:44.890
And these audiences change daily, especially if you're a large company and have you know hundreds of thousands of people per month coming and to set it and forget it and have all this stuff automated is it's you know, that's gonna be amazing for for marketers.
00:52:44.890 --> 00:52:54.730
And the other the other piece to Emily's point, like pushing other signals back to LinkedIn so it further refines their their engine, so uh all the better.
00:52:55.370 --> 00:52:56.250
Terrific.
00:52:56.250 --> 00:53:02.010
Well, uh, it feels like we just scratched the surface, but I think we're gonna have to call it call it a day.
00:53:02.010 --> 00:53:04.970
Um, so first off, Mike, thanks for joining again.
00:53:04.970 --> 00:53:07.610
I'm looking forward to to this.
00:53:07.610 --> 00:53:10.010
Uh Emily, Chris, thank you so much.
00:53:10.010 --> 00:53:10.810
It's been fun.
00:53:10.810 --> 00:53:19.290
If folks want to, this is gonna be, I know where this question is gonna go, but if folks want to keep up with what you all are talking about or what you're doing, what's the best place for them to do that?
00:53:19.690 --> 00:53:20.570
It would be LinkedIn.
00:53:20.570 --> 00:53:20.890
Yeah.
00:53:20.890 --> 00:53:24.570
They're interested in joining the partner program as well.
00:53:24.890 --> 00:53:25.210
Got it.
00:53:25.210 --> 00:53:27.769
And I would say channel99.com.
00:53:27.769 --> 00:53:34.410
And I'd also say that Emily and I are gonna be presenting at the MOPSA conference later this month.
00:53:34.410 --> 00:53:36.810
So love to have you guys attend.
00:53:37.530 --> 00:53:37.930
Awesome.
00:53:37.930 --> 00:53:39.210
We're looking forward to that one.
00:53:39.210 --> 00:53:41.050
Uh, thank you both for joining today.
00:53:41.050 --> 00:53:42.250
Uh, it was fun to talk to you.
00:53:42.250 --> 00:53:45.769
And uh we'll go a little deeper at MOPSA on on some of these capabilities.
00:53:45.769 --> 00:53:48.730
I think um some sneak peeks are in order and all that stuff.
00:53:48.730 --> 00:53:51.050
So if you haven't registered, folks, uh grab your ticket.
00:53:51.050 --> 00:53:51.850
It'll be a good one.
00:53:52.090 --> 00:53:52.730
That's right.
00:53:52.730 --> 00:53:53.290
All right.
00:53:53.290 --> 00:53:54.730
Thanks to you again, everyone.
00:53:54.730 --> 00:53:57.210
Uh, thanks for our audience for continuing to support us.
00:53:57.210 --> 00:54:04.170
If you have ideas for topics or guests or want to be a guest, as always, you can reach out to Mike, Naomi, or me, and we'd be happy to talk to you about it.
00:54:04.170 --> 00:54:04.970
Until next time.
00:54:04.970 --> 00:54:06.250
Bye, everybody.