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Speaker 1: (00:00)
Producer. Nice. All right, cool. Uh, so today for this webinar, we're chatting around how to use your c r m, uh, to power product led growth. Um, so what that means, and we have high touch with here, Zack, I'll intro in a second here. Uh, but for what we're discussing today, so we're gonna talk about what is product-led growth, uh, and why you should care about it. Um, why your product data is a critical growth marker. Um, how to actually leverage that data and where to leverage that data in your C R m. And then we'll go through some tactical how to get started and how to actually implement and do this in your role and your organization. And then if we have time here at the end and people have questions that they wanna ask, we'd love to field them for you. Um, so jumping in today, uh, I'm Connor, uh, I'm the c e o and founder of to date. Uh, we are a Roop consulting firm, which if you're here, you may or may not know, uh, we're a HubSpot Elite partner and we do lots of CR r m implementations and custom integrations and help people solve these types of problems. Um, and with us, I'm extremely excited to, uh, welcome Zach Kahn from High-Touch. So Zach, I'll let you do an intro on your side.

Speaker 2: (01:01)
Sweet. Thanks. So, hi, I'm Zach. I run marketing at High-Touch. So High-Touch is the easiest way to get data into your business tools like yours, TM or ad networks, you know, you name it, we probably support it. And prior to High-Touch, I worked as a product manager at Nextdoor, the neighborhood social network. So thought a lot about PLG and how to grow a product, uh, there as well.

Speaker 1: (01:23)
Awesome. Uh, so to get us started sort of on, on the first piece of this is, is what is product led growth? So we're gonna go into kind of a formal definition here, but think about companies that use free trials. If you have software products, if you're using anything where a large portion of that customer engagement, a large portion of that customer journey is happening within a product as opposed to directly in a store directly with a salesperson. And so you have this huge part of your user journey. And traditionally we see these being disconnected from the core crm, the go-to-market strategy, the marketing strategy. And so when we think about product led growth, which is sort of all the rage with plg, is this, uh, trending acronym. Uh, if you check out those Google search history results, but as a strategy in which that customer acquisition and retention are driven primarily by the product itself.

Speaker 1: (02:09)
So super common with tons of SaaS applications. If you think about products like Zoom or Calendly or even HubSpot with some of their starter features and some of these products where you can go and create something and you can interact with that app without necessarily talking to a salesperson. Or when you have people come in and you even sell a first part of that customer journey and then that user's interacting with the application over time and a product led growth strategy. Really the goal here is company wide alignment across teams. So this isn't something that one, uh, individual group is gonna be able to implement on their own. You need alignment from engineering and sales and marketing and what's the strategy and where that data is and how to access it. And that's one of the reasons that we at Aptitude eight with our focus on rev ops love cross organizational alignment. Uh, and this is a reason that this strategy is so key to a lot of the different organizations that we work with. So, jumping into how this actually works, um, I'm gonna hand the mic a little bit to Zach here, uh, as the expert on how to think about, uh, bringing this reality for you.

Speaker 2: (03:07)
Yeah, so like Connor was saying, you know, PLG is really about breaking down these traditional silos that exist across teams. And so everyone is focused on increasing product activation cuz that's for product led growth company the leading indicator of business success. So it's good, maybe you think about it, of a world without PLG and then a world with plg. So without product led growth, everything is kind of treated like a handoff from one team to another. So that, I mean, marketing is involved in getting people into a sales conversation, then sales has their own funnel, moving people from maybe first called a second call until they close a deal. So that's like the non PLG world. But with plg, the lines are blurred. So for example, in a product-led growth world, buying doesn't just happen over the phone. You know, buying can happen online or sometimes without any human interaction.

Speaker 2: (03:53)
So the traditional, you know, first call of a traditional CRM may not make sense in a PLG world. And so companies with a ology strategy like Slack, Calendly, Dropbox, you name it, um, you know, these product led growth companies give users the ability to sign up for a free version of their product. And then the typical adoption path begins with a single user and then expands, you know, to multiple team members that also see value in the product. And then once enough are usually leveraging that tool management will purchase an enterprise license to cover the whole org. And so obviously this model only works if you have a strong product that's compelling enough for more users to join, hence the product led growth name. But, you know, the challenge really comes is that converting for users to paid customer is not easy. And so in most cases, the role of marketing success and sales and PLG companies is to accelerate the adoption cycle.

Speaker 2: (04:44)
So getting customers to use more and more of the product and you know, this usually means delivering highly personalized content messages and offers. And the challenge, you know, compared to a traditional data stack is that nearly all the information about the customers actually captured in your product. It's not happening on a HubSpot form or your website, you know, as much. And so it makes it really difficult to leverage that information because it doesn't exist in native business systems like your crm. So like your Salesforce or HubSpot, where marketers and salespeople live on a daily basis. So it doesn't work out of the box who have to figure that out. And so customers, you know, you need that product data available and accessible in your tools. And so that's what we'll be talking about today.

Speaker 1: (05:29)
Awesome. And I feel like I, I think for this is one webinar I was so excited about cuz we're hearing this come up all of the time. Um, and it's something where I think a lot of organizations are also pivoting from what we'll see is that product led or engineering led companies will sort of avoid CRMs or avoid marketing systems. And they're like, oh, I'll just add it to the app, I'll just build it. And what we're seeing is the companies I think are correctly starting to say, uh, maybe I don't wanna build a whole marketing automation solution and maybe I should be connecting to one that already exists, which is awesome. But then this, I think that this strategy becomes more front and center because ultimately this data is critical to how you're gonna inform your growth strategy because such a huge portion of that customer journey is, is happening in app.

Speaker 1: (06:09)
Um, and in terms of sort of why it's critical, right? So if we jump ahead to some areas that you guys can see this leverage, which is finding more of your actual qualified leads. There's people who are interacting in your app, are taking key actions, they're indicating, and we sort of look at this as like those p qls, right? What is that product qualified lead? Uh, and how are people indicating that they want to work with us? How are we indicating people are a good fit for some of those premium features without them ever hitting a form and saying, Hey, can I do a demo of your enterprise product? How are they engaging with features in a way that indicates they're really good fit for something a little bit more complex? Um, other pieces here are automated and reliable reporting. One of the biggest constraints that we see with customers is folks that need that product data, they want to know, Hey, I just did this big marketing campaign.

Speaker 1: (06:55)
How many trials did I generate? And how many of those trials converted into paid users? How many became sales assisted and pulling that needs c r m an analyst to go pull that information? Then you have to pull out your product data. Maybe if you're lucky you have like a unique ID across those two and your emails match and you maybe can do a v lookup and now you're talking about, you know, three, four days a week later before your teams can pull together this analysis. And it makes it difficult to be able to gain those types of insights, which corresponds to, it's hard to figure out who is, uh, a risk, who's at churn risk, how are you gonna retain those customers? How do you develop those strategies if you can't find and identify those segments and then target those segments. And I think the last piece of this, and Zach I'll let you expand on all of these, but I think especially kind of in this last category as well, which is how do you think about aligning your company around those same goals and same metrics and how do people look at this and say we're all after one funnel as opposed to product is looking at their activation metrics, sales is looking at their conversion numbers, marketing's looking at their MQL numbers and no one's really aligned on how do we get revenue out at the end of the day when so much of that, uh, customer interaction is on the product side.

Speaker 2: (08:00)
Yeah. Uh, plus one, all that. And I think I'll, I'll touch on maybe a few of those points again, really on the first one on uncovering more qualified leads, you maybe have heard the term PQL or product qualified leads, right? Is if you open up your product, you know, for self-serve, you're gonna have tons and tons of users. And so just becomes so much more important then to prioritize which customers are, you know, using your product the most and most likely to convert. And so having product data is, is crucial for that. And then, you know, in terms of reporting, you know, rev ops especially, you know, reporting, you know, let's say it's like, you know, typically the traditional CRM you're waiting on, you know, uh, your sales or success team members to up update fields, right? So your, your data might be, you know, you're, you're reporting in your, in your in CRM traditionally might actually be out of date because someone didn't update a field.

Speaker 2: (08:48)
And so it's crucial, you know, with with automated data that's synced into your crm, you, you, it could be 1:00 AM in the morning and you'll actually have an updated view of your pipeline. Um, and then the last piece, you know, on, uh, aligning your entire company around these same goals. I really wanna touch on that in this presentation too. You know, there's one thing to talk about CRMs, but you know, the more important thing in my opinion is that people behind the CRMs and the teams behind them. So we'll make sure we touch on that too.

Speaker 1: (09:17)
Cool. I wanna go through, uh, a tangible example. So actually where to leverage this product data and some really tangible examples for people and the types of things you can do with this. So this is a recent, uh, project and a customer that we worked with, um, lucid Press. Uh, they're also high-touch customer. Um, and sort of the way that we ended up sort of implementing this is we did a full HubSpot implementation and they have this ultra tight connection between Hubot, which is gonna be their, their C R M and their marketing automation solution and their product. And all of that's really powered by High-Touch. So the three elements in this is they have Snowflake, which is their data warehouse connected to their product. The product team is already generating a lot of that product data. Um, we have a subscription object. So one of the biggest challenges with sort of any software company that we see with C R M projects is that data about who that customer is, data about how that customer is interacting, what plan they're on is is usually really hard to find and get that connected back to that core C R M piece.

Speaker 1: (10:11)
And so High-Touch helps them manage all of those different data points. Um, and the reason for this, uh, is that a lot of lucid presses onboarding and activation strategy is around product data. So someone can come in, you can create a free lucid press account, you should, it's a very cool product. I'd recommend trying it out. Uh, and if you come in, you create a free lucid press account, you can do a whole bunch of different things in the app. And some of those are paywalls, they're blocked. They say, Hey, you can interact with this feature if you have a trial, you start a trial, you can interact with those features. But what they do on those features, do they visit those pages? Do they interact with those pages as critical to knowing how we should be engaging with and communicating with these prospects? And so what we're doing is in order to deliver those hyper-specific contextual elements, we're using the behavioral events, uh, inside of HubSpot.

Speaker 1: (10:57)
So worked with our engineering team, we set some of these up, we're now able to do things like, did this person create a document? How are they two days into their trial and they haven't taken one of these key actions, send them messaging specific to different types of behavior and use cases and driving them to content that tells them, here's how you can create a document. Here's how to activate this. And instead of sending that to every user that creates a trial, we're targeting those users that have not yet interacted with that feature. And all of that's being driven entirely downstream by the, the marketing team as opposed to marketing saying, here's something we want to do. Coming to engineering, engineering has to build and track it. Engineering has to go connect to something like a segment or a, uh, sorry, ascend grid or a mail gun.

Speaker 1: (11:39)
They start sending those emails and then marketing wants to change them, but they're coded. And it all sort of creates this big long iteration cycle that makes it really hard to iterate quickly. And this is sort of where PLG can be so powerful. And I think the additional value out of this is we're also sending in all of the subscription data from Snowflake into HubSpot as custom objects powered by, by high-touch. And that data already exists in Snowflake because it needs to for their product data warehouse. And now the marketing and the sales teams can analyze how effective are we driving people through are we com committing upsells? What's our A C v? Where should we be spending our time? What's that l t V value? And that analysis can happen without ever asking product for data sets, without having to go to engineering and have them pull SQL queries or having data analysts go and parse it. It's all something that could be done using those ultra powerful C r M side analytics tools. And that's really where when that PLG strategy manifests, not only do you get to be, to have way better customer insights, but ultimately what that drives is a more powerful customer experience. So what I wanna do is sort of hand it a little bit to Zach and run through how you guys can do this and how you guys can set this up, uh, if you're using some of these tools now.

Speaker 2: (12:50)
Yeah. So you know, really what we'll touch on now is how to set up your C RM for product-led growth. And so, you know, high level question might be, you know, what is a CRM CRM for anyways, right? So, you know, textbook definition of a CRM is, you know, it's by Salesforce is to, you know, it's, it's a, it's a tool for managing all of your company's relationships, interactions with customers and potential customers. So it's called a crm, but actually most of CRMs say are more like an L r m, like a lead relationship management tool cuz most of today's CRMs are actually primarily optimized for pre-sale. Uh, and that's usually because of this rigid structure of, you know, first call, second call. And you know, the customer journey typically ends around when the M MSSA is signed and you know, the best, at best, maybe you get a notification for a contract renewal, but traditional CRM is usually missing that product data that we talked about that one would indicate the health of a customer post close and two, help surface upsell opportunities based on usage.

Speaker 2: (13:49)
But fortunately, you know, PLG or product led growth CRMs deliver on the promise of managing the entire customer relationship. And so how we define PLG CR r M is any CRMs that can be your current, you know, HubSpot or or Salesforce instance, that one contains data on how your customer is using your product. And two has workflows built around your product journey rather than just your sales journey. And so with plg C R M product usage data helps determine the stage that a customer is in and not, you know, it's not necessarily how many calls they've had with your sales team. And so a key difference here is that, you know, we believe that it's much easier to get started with your existing C R M and adding data and workflows there to unlock product led growth instead of buying another tool because I'm sure we've all experienced this before, you know, who needs another tool to look at. So we really believe in, you know, fixing what's in front of you already.

Speaker 1: (14:46)
Something that I also love, uh, about your guys' approach to that. Cause I think that those existing, existing C R M technologies, like PE people are latching onto PLG and, and they're building good products. Um, and and by no means are we saying that anyone who has a PLG C R M that that's not a product worth looking at. But I think the main value here is that rather than saying, Hey, this is this new trend, let's build a C R M product tailored for it, you guys are really looking at this and saying, how can we take what you already have and how can we leverage the power of existing technology, uh, and make it more useful for those end users?

Speaker 2: (15:18)
Yeah. And, and, and there is a place for these, you know, purpose-built PLG CRM solutions, right? They, they do things that are, you know, very custom and, and important for a product led growth company. Uh, but I think it's really about, you know, what can you get, you know, adoption for internally quickly? And that definitely is these, you know, the CRMs your team's already using. Um, but we can touch more on, on this versus off the shelf CRMs later too, if people are interested. Um, let's

Speaker 1: (15:45)
Jump to, to how to, and I think, uh, one more forward from here. So reverse E T L is sort of where you guys tag this. What might be helpful is a starting point would be, uh, what, what is an ETL and what are traditional ETLs? Uh, I know that there are sort of situations where folks are, uh, we might have think we might be skipping one or two, which is okay, we'll go back. Uh, but in terms of how you guys think about e TL and what ET TL does and sort of what traditional ways you guys see this and how you guys differ from that.

Speaker 2: (16:12)
Yeah, so really maybe taking a step back, like why is this, why are you even talking about this EPL L term, right? Like, you know, one of the biggest blockers product led growth is this data accessibility, right? So when business teams are waiting on data, they can't experiment, you can't learn, you can't iterate. And so all that time is wasted. And so, you know, you don't wanna be blocked by engineering teams cuz you know, compounded growth comes from compounded learning and then compounded learning comes from having the data to run experiments, right? And of course, you know, e TL typically is basically the process of getting data into a data warehouse, which is basically a central place to house all your data. And typically, you know, there are e TL tools, um, like, you know, five tran or other tools that, you know, get data into your warehouse. But that data usually is used for dashboards, uh, you know, like a look or dashboard for example. And, and dashboards are great, you know, don't get me wrong, you know, they provide visibility, they're great, you know, to see how you're doing, but they don't automatically

Speaker 1: (17:07)
Use dashboards ,

Speaker 2: (17:09)
But they don't automatically drive action, right? You know, they're, you know, you, you don't look at a, you know, dashboard and immediately, you know, create a workflow or automate different things, right? Data really is primarily most useful to business teams when it's available in their specific tools like your C R M. And so that's the key difference, right? So reverse e TL is about putting data into the tools that you use every day to run your business. And so ET TL is about putting it into the warehouse. Uh, and then so, you know, we support, you know, we, you know, et TL is, is necessary as a to, to make reverse et TL happen and I'll walk through the steps, but really the, what reverse et TL is, is basically the fastest way to send a complete 360 degree view of your customers, like how they're using your product, whether they paid their bills last week, what blog, what articles in your blog did they read, send all that, you know, comprehensive data combined into your C R M without having to rely on your engineering team.

Speaker 2: (18:05)
And the key part about reverse et TL is that it connects to your data warehouse. Uh, and that's where all your customer data lives because you're already using your warehouse primarily for, you know, dashboards and you know, you're already et TLD a bunch of data into your warehouse with all there for you to use. And, uh, right now it's only being used primarily for dashboards, but it can be used for so much more. Um, and so I'll walk you through the steps next on, um, how to send product data to your C R M. I'm not sure of anything else you wanted to add Connor there.

Speaker 1: (18:35)
No, I I think that's great. I think the other thing to, to emphasize as well is I think that there's elements where people on the business team may not know that these products already exist. And what we find the majority of the time is that if your, if your, if you have a product and if you have a product team, uh, it is very likely that they're already doing some sort of a data warehousing. And we typically see that process exists long before it gets in front of that business team. And so ma ask this question as opposed to saying, Hey, we, we need to start from scratch. It's exceedingly likely that you're further down this process, um, if you're on sort of the sales or marketing side and you guys have a robust product already.

Speaker 2: (19:09)
Yeah, I think the, the good limits test is like, do you have a BI tool? Like do you have a look or do you have any of these like BI tools like Tableau and, you know, BA basically to, for those products to work, you need a data warehouse technically. So generally speaking, you know, it it is, you know, most companies are, are moving towards this model anyways. So, um, steps one and two in that we'll go through now are, you know, most likely good chance your company's already gone through it. Um, but basically, like we said before, you know, first thing you need is a data warehouse, but, um, which is basically a central place to store all your customer data. And that means all meaning like from different sources, right? Maybe that's how they're using your product, right? What they click, what buttons did they click, um, and from, from your website.

Speaker 2: (19:52)
But also it could be billing data, you know, it could be, um, marketing data about like what they saw on your site. And so you may have heard of things like Snowflake or Google, big Quarter, Amazon, Redshift, those are examples of just different, um, data warehouses. And the main benefit, you know, for a business and why you need a data warehouse is really two things, consistency and completeness. So your business one needs a single source of truth that everyone, um, can look at that basically provides consistent metrics, right? So you don't want, you know, you know, one team, that marketing team to have a definition of a R R and L T V and the sales team to have a different one, which you know, would happen if you didn't use the same source. That's a key part. And the second thing is, you know, you will also want it to be complete.

Speaker 2: (20:35)
You want to have one place that has all of the data about a customer. And so the challenge of other data tools and why the data warehouse is so important is, you know, other data tools can help send data from like one tool directly to another, like sending HubSpot leads to Salesforce, but they don't let you combine multiple sources of data about a customer. And that data is raw. And so you really need to combine multiple sources of data to get that 360 view that, that you care about. Um, and so I can give an example for like point to point solutions that makes it impossible to, let's say, calculate something like a arr, you know, annual recurring revenue or LTV for a customer. You'd have to just send individual purchases, you know, which, uh, you know, I don't think anyone wants to be looking at each individual purchase. They wanna see synthesized information, right? So the benefit of the warehouse is you can combine data prevents information overload, and you can see synthesized information instead, like seeing ARR instead of just a list of purchases.

Speaker 2: (21:38)
Uh, next, so then the second piece is, you know, okay, you have a warehouse, how do you get data? Um, you know, your data, your warehouse is only useful if it has data in it, right? So you need to actually send data using e ETL tools like five Tran that are super easy to use. Literally you just click a few buttons and they connect to your tools and send all your data into a warehouse. And so this, this, you know, happens very quickly. And then the fun stuff happens is when you can actually combine all that data together, so you can use your warehouse to, you know, create useful definitions and insights for each customer. For example, you can calculate things like lifetime value or L T V, you know, P Q L scores, you know, marketing qualified lead scores, like depending on how much intent they showed on your website, you know, propensity to purchase score, customer health scores, you know, the list goes on, right?

Speaker 2: (22:29)
Once your data is in one place, there's so much you can do with it. And it's likely that if you already have a data team, they already created these key definitions on top of your data warehouse. So literally all you, you're, you're missing is basically sending those definitions to the tools that you use. Um, and, and, you know, there's so many unique ways to combine data from meaningful insights. And I think one key part that I think gets missed is like, you know, typically if you, if you have your data scattered everywhere, you, it makes it really hard to ask like the fun questions that are unique to your business. Um, because it, it just takes so much more work to do that, you know, of course, you know, everyone's gonna ask, what was our, our a r R last month? And that kind of stuff. You know, you need, you need to get done. But you know, sometimes it's, there's more interesting questions that can only be answered when you combine data sources, right? Like, let's say we're Slack and, you know, what's the correlation between the number of emojis sent and long-term retention in Slack? Like, this is like a very specific business question that's related, you know, to combining product data and use, you know, and sales data. And, and these are the questions that only a data warehouse can help you answer.

Speaker 2: (23:37)
And so now you have this model data, the last piece is, okay, so you have your LTV scores, et cetera. How do you actually send that data to your crm? And that's what reverse ET TL does. And so with reverse et tl, you have full control over how you want your data to appear in over 60 different tools. So not just CRMs, but also, you know, email tools, add tools, et cetera. So all you need to do is define the data you want to send from your warehouse. And then you can see on the left screenshot here, you just map which fields to update in your crm. So for example, in this screenshot here, you know, this is, uh, some information about products ordered by a user. And so we're just, you know, matching them by email can send, you know, this, the skew number for a product and then update, you know, the product ordered skew number on contacts in HubSpot. So literally just, you know, really simple mapping ui and you press send and your data's automatically synced. So it's super easy to use. And the, and the, you know, most important part is that you don't have to rely on engineering. So you're, you know, a, as a business team, as a rev ops team, you are, you know, able to run free iterate, um, with, and so you, you're able to just move much faster.

Speaker 1: (24:45)
Something that I also, I love about that, and one of the things that I think is, uh, becoming more common in a, in a really positive way, uh, across all of these different kinds of tools is that, uh, you guys are building something for the ops person who like has an understanding of data as an understanding of the product, knows how they maybe want to use it at the end of the day, but they aren't in a position where they are gonna go be interfacing with those direct product databases. And maybe they can dabble in some sequel and they can pull it out. But really using these types of tools is something where someone who's not a direct engineer, you don't need that product in the software team. Uh, and that fundamentally changes the, the speed with which, but you also keep your product team focused on the things that matter most to them, which is shipping new features to customers.

Speaker 2: (25:27)
A hundred percent. And, and you know, the, the magic here is, you know, we think everyone at a company is a data user, not just data teams, right? And they have just different ways of, of using data. And so we think, you know, our vision is that everyone should be able to do it and whatever way they're able to. And so, uh, the next slide talks on, you know, a new product that we recently launched, uh, called Audiences that lets, you know, rev op or any, any, you know, business team member to, you know, visually query and filter their data. Like, you know, if I wanna find all users who abandoned their shopping cart, for example, so they added a product to the cart but then didn't purchase, I can do that visually without having to know any SQL or upload any. So, you know, that that's, that's the vision for High Touch to let anyone, you know, put their data into action. And another key part is that, you know, we talk about Data Warehouse, but we also support other data sources outside the warehouse, like spreadsheets, you know, um, production databases and more. So we really support any data source that you want.

Speaker 2: (26:31)
And so that's really talking about, you know, how to get product data into a crm. Next question that's natural is like, you know, what does a PLG CRM actually look like? And so we can give a live example here. You know, like, like we said, there's really two components of a PLG crm. One is the data, and two is the workflows. So as you can see on the left here, this is, this is what our CRM setup looks like on high touch. We're syncing, uh, fields that show where a customer is at in their adoption cycle. So we show, for example, whether a customer has connected the data warehouse, but they've connected a, a tool to send data to, uh, they've created a query so they can know, you know, how, how activated they are in the funnel. And then we also have an actual, you know, our deal stages are set up to be around those stages in the adoption cycle. So, you know, these are, these X number of customers have, you know, not set up the data warehouse, you know, and, uh, these customers have set up the data warehouse, but then haven't actually set up a tool like HubSpot to send data to. And so that helps us prioritize and think about, you know, the marketing campaigns, the sales campaigns we wanna run to help increase adoption.

Speaker 2: (27:39)
And so now we can touch more on that second piece, but how to use PLG CRMs. These are the workflows and you know, the human part about how you would actually use, uh, CRM for product-led growth. And so the goal for any PLG model is basically to drive product adoption and activation. So therefore, we think that your CRM should be aligned with those same goals. And so to achieve this, you have to basically identify your activation point in which a customer has fully adopted your product. And of course, this is specific to every company. So you'll wanna search for that point in which a customer typically continues to use the product after reaching that threshold. So basically any point where retention is consistently higher after that point. So that's why you can team as looking up with the activation point for your product. And so I can give some examples, uh, of like some known PLG companies like Slack for example, they focused on, um, getting customers to send 2000 plus key messages in the first 30 days.

Speaker 2: (28:34)
And so they knew when customers reached that point, they were basically very sticky and they were willing to pay. And, you know, the retention curves stayed consistently high for Dropbox. That was like 85% of customers upload one file in one folder on one device within one hour. And then HubSpot focused on 80% of customers using five features out of 25 features in the platform within 60 days. And so these are very tractable things that, you know, the whole company can get around and thinking about how do we get every single customer that comes in, ideally to reach the activation point. And so once you have that activation point, you want to basically work backwards from that point to identify other points of heavy friction that potential customers get stuck around before reaching that activation point. And this can either be specific events in the product onboarding process or, you know, an aggregation of events.

Speaker 2: (29:25)
So one example is like, you know, if users get stuck at a certain onboarding task, like for us, for example, at High-Touch, we revolve everything around, you know, the onboarding steps, right? Cause the user has to first connect their data warehouse and maybe they don't have access to the data warehouse. And so we have different campaigns to help people around that. And, um, one piece, um, really is that, you know, by the time a customer, you know, our, our activation point at High-Touch is basically having a sync of data from one source. So let's, from Data warehouse, let's say, to any tool. And, um, by that point, you know, we believe the customers already understood and received the value of high-touch, and we see that they're much more likely to become a paid customer after they've completed that one sync. Um, and so the next part piece of this is actually modeling your deal stages, um, around these activation points, right?

Speaker 2: (30:19)
So we defined what those activation points, we think that data to the crm, and now we actually want to, you know, use these deal stages or, um, but focus them instead around, you know, instead of using the traditional sales pipeline of discovery demo decision pending and closed one, we have this, you know, product led, uh, pipeline or self-serve pipeline, and we replace the stages of the seller journey, like instead of demo, et cetera, with stages of the customer journey. Like whether they've connected their warehouse, they've connected their, um, they've made a query, they've sent data to a tool. Um, and so the, you know, instead of closed one, you know, we have like fully activated essentially. And so, um, this is, you know, a different way of thinking about it and aligns everyone on these shared goals.

Speaker 1: (31:07)
And I think to, to your point, Zack, on this one, right? Because we see a lot of organizations where, and it depends on your, your price point, are you targeting enterprise? Like where, how, like where reasons they want to use a PLG strategy is because that PLG strategy is effective and and cheaper at, at converting those customers. Um, and that makes a lot of sense for lower dollar dollar value customers. But as you sort of climb that stream, you want more personal touches, you want more engagement, you want more interaction. And so what we typically see is people splitting those pipelines. So I think we're, we're one side ahead here, but for the two pipelines, which is, do you have one that is a self-serve product driven type of pipeline and experience, and one that's more of that traditional sales pipeline, and you can even move people in between.

Speaker 1: (31:54)
So knowing someone is completely self a self-serve on that kind of step three on the next slide, which is if you have someone moving through that self-serve pipeline, they could be taking those actions that indicate they are somebody who should be sales assistant, they are somebody who should be enterprise targeted, and you can move them over. And similarly we see folks who, hey, someone came in their enterprise demo flow, but we don't necessarily think that we want to touch them as heavily, and so we're gonna move them to that other side. And both of these can exist in harmony.

Speaker 2: (32:23)
Exactly. I think it puts a really important call out and, and, um, thank, thanks for bringing that up first. Um, really is a, not that this self-serve product led funnel is not for everyone, right? And there's some, these are even some customers on enterprise side with a longer sales cycle. Like you actually want to start maybe in a traditional sales pipeline. And so, you know, we believe, you know, kind of moving on to kind of talking about these two pipelines, everyone in your company is, you know, marketing success support product should have access to a P G C R M. So not just the sales team. And typically, you know, non P L G world sales is the main team that's tracking customers before they sign a contract. And maybe customer success is mostly post-sale after a contract gets signed. But this of course doesn't work with product led growth.

Speaker 2: (33:08)
And so with plg, we believe that customer success, you know, product et cetera, should be pre-sale starting from the moment a customer signs up for the product and helps see them through the onboarding process and post-sale. And so this challenge is like, you know, if if sales customer success should be involved, how does ownership work, right? And so we believe, you know, this like, like you were saying, Connor in two pipelines, right? A sales assisted pipeline and then a, you know, self-serve slash product led pipeline. And so we believe most customers, right, especially the lower a c v customers should fall into the self-serve pipeline where they use the product themselves to gain value and they receive, you know, lifecycle marketing emails or helpful emails or nudges that's gonna be automated or personalized, um, along the way. And we see, you know, in terms of ownership, customer success and product teams can own that self-serve pipeline.

Speaker 2: (33:59)
And, you know, product and marketing can also own that pipeline on an aggregate basis. So by sending lifecycle emails to a set of accounts, and then success can own this, you know, pipeline on an individual and personalized basis. So success might be instead of, you know, sending a bunch of emails, they're actually hopping on onboarding calls and debugging issues with customers. And so that's really about this self-serve pipeline. And you can even give success and solutions like KPIs, like number of successful onboardings in order to align their incentives with customer activation. And so that's, you know, again, this PLG focus, but you know, it's, you know, you, you can't ignore the sales assisted pipeline that still needs to be there, and that's reserved for customers that likely need an extra hand with understanding the product. Or, you know, maybe enter as enterprise customers that prefer demos or users that, you know, require a bit more help, um, evaluating decisions.

Speaker 2: (34:51)
And then, you know, this sales assisted pipeline, it can be owned by the sales team and customers should have the option at any time that are in the self-serve pipeline to talk to sales, right? That you should, the customer should have control or what, how they want to basically onboard the product. Do they wanna talk to a salesperson? Uh, they should have that option. Um, but also, you know, they, if they wanna just go through and experience the product themselves, they they should feel completely free to do so and not be blocked by talking to, you know, sales. And so I also

Speaker 1: (35:19)
Think that what we see here is, right, like it varies by persona too. To your point of sort of like self election is that we see if we jump to kind of the next slide here, we have like the, uh, examples of kind of what this looks like. But I think we see a vary by persona where, uh, folks on the engineering or the product side are like, I don't wanna talk to anybody unless I have something very specific and I like, don't wanna have a, a demo or a sales conversation. Like, I just want to ask you like, Hey, I'm trying to do this. How do I do that? Uh, and like, don't show me it, I've already kicked the tires. Whereas on the flip side, you have a lot of the folks that we typically see more from like a, a marketing or a sales background that are coming in and saying, Hey, I'd love for somebody to really show me how this works and I have an idea of what I'm trying to do. And getting somebody to help me understand how to connect those two is key. And the value here is that you can really serve both of those audiences in both of those journeys and let people kind of move in between them.

Speaker 2: (36:08)
Yeah. And so like, one, one thing we do tactically to make that happen is that at the, you know, bottom of all of our emails that we send across the customer onboarding journey, we do say, Hey, like, wanna talk to us? Here's our Calendly, right? And so customers are always, you know, have flexibility to talk to us, um, and talk to our sales team. Um, and so, you know, this, this is onto the last piece. So you know, now that we've, you know, set up the deal stages, we've, you know, have the data in our crm, uh, and we have the different pipelines, um, now we can talk about the fun stuff around automations and things that we can actually do to move customers through the product funnel. And so this final step is really about adding nudges and touch points that move a customer through and help 'em increase their product adoption.

Speaker 2: (36:51)
So the first thing to do is figuring out how to automatically move customers into the next funnel stage when they complete any activation event. So let's say for example, if we're Slack and a customer send 2000 plus emails or sorry messages, we wanna mark them as fully activated. And you know, usually CRMs like HubSpot has HubSpot workflows, or each CRM has their own solution that helps you automate, you know, okay, this customer did this action, now they should be moved to the next stage in the funnel. So that helps, you know, with the, the value prop of automatic and reliable reporting. But, okay, so we talked about reporting. Let's say our, you know, our deal stages are automatically updated when customers take certain actions. Now let's talk about what else we actually can automate. So you can leverage your, your tech stack basically to it's full potentials.

Speaker 2: (37:37)
So let, let's someone gets stuck on an onboarding task, let's say for high-touch, someone is stuck on connecting their data warehouse, you can send them a personalized help article so that it can help move on to the next stage. And that's what we do ourselves. And you can see an example of an email on the right that we send. Um, and sometimes customers need, you know, human interaction for some things. Like you can actually trigger Slack messages, tasks, and, and Asana or any kind of, you know, tool that you need to make sure customers get the right experience. And so how we do this internally, like I said, we have this email that's sent to customers based on this different stage they're in, um, that gives them helpful tips and articles and things to help them out. That's all automated. But we also have, you know, uh, internally we have Slack, uh, messages that are sent to our customer success rep reps when certain customers take actions in their product. So we know, oh, finally, you know, this customer finally, um, added their destination or added HubSpot and they finish the sync, that means I can reach out to them and, and talk to them about this.

Speaker 2: (38:42)
And so last piece is, you know, this like proof points, right? Of customers that have actually had, you know, success particularly with this use case, right? Of, of using HubSpot or using Salesforce to companies like Retool for example, increase their email response rate by over 32% using, you know, personalized outreach. So what they did is they, they, you know, send product data to HubSpot showing about basically telling how each customer was using the product and then use that messaging, right? So, oh, I, I see that you're using this part of our product, here's some tips. And that increased their response rate. And overall, you know, conversion by 32%, similar with Go Site, we did the same thing, but with billing data to help them cuz they're a financial product. And then Zeppelin has used it for improving sales productivity by prioritizing product, uh, leads. So, you know, they have millions and millions of users, so how do they prioritize the customers that are actually using the product the most?

Speaker 1: (39:40)
And I think, we'll, we'll jump into questions. I know I've already seen a, a couple come through, so I'll pick those up. But if you have anything that, that you guys wanna ask either on strategy approach, things on, on the high-touch side, uh, please let us know in the q and a or in the chat, uh, and we'd love to touch on them in the next sort of 10 minutes or so here. And then before we jump into questions, also, if we jump forward, one, um, if you guys have to jump or you wanna sort of get in touch, uh, feel free to email me directly on any of these things, more than happy to set up time with the folks on our side. Uh, and then LinkedIn is always a good place too. Um, we do lots of these webinars with lots of different partners and so we'd love to have you, uh, and then Zach, I I'm assuming that's fine on your end, but you tell me the best way people to, to contact your follow.

Speaker 2: (40:22)
Yep.

Speaker 1: (40:23)
Cool. Um, so I have one question, uh, from Michael here, which is, um, around I is PLG the new A B M, um, something that's been happening for a while and has been made into a movement as content marketing for, uh, PLG type companies. Uh, is there anything new here? And he admits that it's a leading question, uh, but I think honestly my answer here is I don't think so. And the reason that I think that that's the case is that, um, and I'm, I'm a, I'm a pretty strong speaker around ABM stuff and thinking that ABM is just like another word for marketing in a lot of situations. Um, I think PLG is actually very different. Um, and the reason that I think that that's the case is I, five years ago when we were doing these types of projects, um, there were, you had all these different sort of things like Segment or Mail Gun or SendGrid, and they sort of had these audiences of, oh, you'd connect SendGrid to your application, and then they tried to go and build sort of this like marketer centric UI and journey builder, but it didn't really work because it, it fundamentally missed out on a lot of the actual sales side data, right?

Speaker 1: (41:26)
Which is like, oh, I don't want to send this person that messaging if they're already talking to a sales rep. And I think a lot of companies have tried to sort of build stuff in this space. And I think that what has changed and, and just like a technology layer is one, the prevalence of people tracking and managing this data, uh, and, and this data being readily available, right? Like you had five, 10 years ago is like, unless you're Facebook or Google, like you just didn't have a data warehouse with all of this data in a structured way. And that's just become so much more accessible and so much easier to do that really small scale companies like, or, or early stage software companies are building really robust data warehousing and data analytics, uh, platforms and tools and getting value out of them. And I think that's been a significant change.

Speaker 1: (42:09)
Um, the other change is sort of this like wide scale embrace of C R M and and marketing technology and that also being something that smaller organizations are using earlier. And I think those two things combined have sort of opened the window for this to be a strategy. Whereas if you said like, oh, is PLG new? Like, maybe not, right? Like, I mean, Amazon's been doing it for 15 years, 20 years, but the reality is, is that this being something that companies without hundreds of analysts and product managers and marketers that are focused specifically on activating product data, uh, can now access this. And that's something that becomes a strategy other folks can implore instead of only sort of really big organizations with lots of firepower. Um, Zach, I'll let you expand if there's anything else on that, but

Speaker 2: (42:51)
Yeah, I, I think I totally agree. I think another piece is like really about like consumer expectations, right? Customer expectations. Like I think, you know, you mentioned developers for example. There's, there's certain types of customers that are given, you know, this trend of product led growth, you know, expecting self-serve, expecting these things, right? Um, that adds on to the pressure to, to meet that need, um, as well. So I think that's something that's also changed is like, as more and more self-serve products have common to the market, um, that also means that, you know, um, if you're, let's say in a competitive space and there's a self-serve product and a non self-serve product, you know, that that's a big difference. And, and customers, you know, let's say especially technical customers, but I think increasingly, you know, any kind of savvy, you know, many savvy customers are just like wanting to try out a product themselves first before paying.

Speaker 1: (43:41)
I, I think it to that point too, like the tech savviness of users has increased, like across the board full stop, right? Like, it's not, it, it used to be if you were like, oh, like does it have an api? Can I connect to it? And like, unless you were a pretty advanced software engineer who is doing web applications, like you didn't know what that meant, like most business users and are like, oh, cool, like it has an api and I, I have a rough idea of like what that means. Um, and that means that people are just in general, far more technical, far more willing to kick the tires on stuff, and they prefer to do that as opposed to, I have to fill out a form, I have to do a demo, I have to talk somebody, like I really just want to click around and like see if this works.

Speaker 1: (44:16)
Um, and that's sort of a, an a global trend, uh, across all of technology. Um, no, another question in the q and a for Michael, I'll do q and a once first. So if you're throwing stuff in the chat, uh, I may not see it first, but if you have anything, feel free to throw it into the q and a, um, which is getting started with P L G before sort of massive user data and events. And so his questions largely dictate, I'm gonna let you sort of take this one Zack, but about like, uh, high touch and versus segment versus like workado or other tools in the space and sort of how to think about, um, this piece of the tech stack and where both high-touch fits in, but also where you see other products fitting into.

Speaker 2: (44:53)
Yeah, so I, I see this question as, I see this as before having massive user data and events, right? So I'll, I can touch on that piece first. I think really what it comes down to is what we were talking about earlier around point to point integrations versus, you know, being able to put together this holistic 360 view of your customer, right? And so let's maybe talk about, you know, there's like two different kind of solutions here, or three, I'd say one would be the, you know, CDPs, so customer data platforms like segment second, there's like IPA solutions like Workato and Trey, and then third are like other reverse ETL solutions, right? So I'll talk about, maybe we'll talk about the C D P first, like things like segment. And so the real, the really big challenge with things like Segment really comes down to this rigid data model, um, you know, segment, everything has to be around users and accounts or an event.

Speaker 2: (45:44)
And you know, it's not as easy to stitch together, you know, in similar first both segment and CDPs, but also any kind of IPAs solution, you know, that holistic, you know, view of like L T V or a r r or you know, churn scores or all these things, right? Because of their rigid data model and the fact that everything is an event, right? And so that makes it just really difficult for you to actually do what you need to do, um, to unlock product like growth and have these more predictive churn models and things like that. And, you know, in terms of, you know, if you're starting from scratch as well, you know, um, one thing you will always need is, is event tracking. So that that's one thing that CDPs are very helpful for, you know, but outside of that, you know, you know, your data is already living in a warehouse, right?

Speaker 2: (46:30)
So you're, you are the implementation time of like now sending all of your data to, you know, segment as well, which again, is storing your data. It's not your data, you know, they're actually storing it. And so that also has PII concerns too, is just more duplicative work, right? Why, you know, you are basically creating two sources of truth for your business, A P D P, and then you're creating your data warehouse and you, and you definitely need your data warehouse for BI tool and visualization as well. And so it just creates a lot, like in terms of not just being limited in terms of functionality because of, you can't combine multiple data sources. It's also just duplicative work cuz you're gonna have to send everything through segment two as well as, um, you know, your warehouse and you have less control of the data structure.

Speaker 2: (47:12)
And it also, you, you, your data is being sent to a third party service. And if you're in a, in a, you know, that's why many companies and regulated industries choose us as well because it's in their warehouse. They have, they have full control and we don't store any data. And then I think, so that's really like, you know, about CDPs and, uh, you know, the lack of flexibility and it's kind of like, you can think of using your warehouse as almost like unbundling A C D P and you can really have more control and, you know, um, in, in terms of what you can actually do with it. Um, and so that, that, that's, that's on, on the CDP side. And then in terms of, you know, solutions like an IPA solution like acado, you know, really it's a similar point about, you know, the point to point integrations that that, um, you know, you just can't send every, get this 360 profile.

Speaker 2: (47:58)
That's really important. Um, but also a thing that does happen as a company grows is that, you know, these iPASS solutions and also Segment as well, they're all event based. So like as soon as an event happens, it's going to, you know, send something to your API and those hit rate limits very quickly. Um, and so with the, the key difference with something like Reverse et TL is that, you know, we batch the data. We diff we, we, we look at, you know, differences in data and only send data that's different and we automatically retry and, and back up and make sure that, you know, your data does get sent. Reliability is crucial. A lot of our customers that, you know, are coming from segments or IPA solutions like Trader Workato are hitting rate limits. And that's, they're not, you know, these aren't like Amazon's style companies.

Speaker 2: (48:40)
These are like, you know, mid-market companies or small mid-market companies because of the realtime aspect. You know, you know, your data needs are gonna increase. And so these companies hit rate limits very, very quickly. And so we, we provide that so we automatically handle that out of the box. Um, and then another piece that, that's pretty crucial too is, you know, just complexity, right? So, you know, IPAs solutions like Treya, Workato where are great for workflows in certain, in certain ways, but they aren't made to handle data, right? So for example, if you wanna match, uh, let's say a HubSpot user and a, um, Salesforce user off of like email, it's actually a lot of like custom if L statements you're gonna have to write in an IPAs solution. Um, cuz it's, it's like it's not made for data transfer, whereas high touch, it's literally two clicks nash.

Speaker 2: (49:31)
So like we, there's just all these things that, you know, if you are using an iPad solution like a Tray Workato to send data, you're really kind of like hacking a solution that's more made for workflows and not necessarily for se data transfer integration. And then the last piece about segment, or sorry, census or other reverse ETL solutions is really just like the difference in terms of like functionality and, and really fun. Fundamentally the difference is, you know, high-touch is really thinking about enabling the whole business. So we launched the audience product, for example, recently, um, that enables marketers to now also selfer data. And so, uh, but we also have features like, you know, our, we have a live debugger, so you can literally click on and see each row, what APIs are we sending, you know, um, and when alerts happen, you know, when errors happen, we alert you in Slack, et cetera. So we both go deeper on the data engineering stakeholder, but also help data engineers better serve their, you know, know their partners on marketing. And so those are the fe these just basically in terms of like robustness of this vision of data democratization, it's just, you know, you know, we're, we see ourselves as the leaders in this space because of these things that we're paving forward that haven't been caught up at all yet. So.

Speaker 1: (50:44)
Awesome. Thanks so much Zach. Wealth of information. Uh, we're gonna go ahead and, uh, and wrap. I know we're sort of at, at near the top of the hour here, but everyone who joined us live, thank you guys so much for attending. Um, for those of you who are seeing this on demand, uh, we hope that we're able to answer some of your questions, but if you have ones that we didn't answer, feel free to reach out to us directly. We'd be happy to chat. Uh, and thank you guys so much for, uh, for coming and we'll see you on the next one.

Speaker 2: (51:12)
Thanks so much.

Speaker 1: (51:13)
Bye everybody.