Data-Driven Growth: How Top GTM Teams Win With Data

Who's excited to talk about Data? I'm a VP of Product here at HubSpot. I've been here for 11 months. My company Clearbit was acquired by HubSpot 11 months ago and we were a B2B data company. Who here was familiar with Clearbit before HubSpot acquired us? Can see some hands? I might need noise instead of hands because I can't see anyone. On that note, who here is marketers Sales less. Woo. How about operations or like revenue ops people? Okay, awesome. Well, today I'm gonna tell you three specific strategies that I've observed some of the best teams in go to market use to win. And those strategies all include using data and some data types that maybe not all of you have heard of and most of you probably haven't used before. My goal is to give three like tactical ways that you can leverage data that exists today to improve your go to market. So why should you listen to me? Well, I co founded this company clearbit and spent 10 years working with these guys. We were incredibly lucky that all of our early customers or most of them were these high growth, super sophisticated, super interesting B2B SaaS companies. And they were all doing really innovative things that most of their companies like either didn't have the resources or didn't have the ingenuity to do at the time. So we got to watch Stripe go From, you know, sub 20 million to where they are now. We got to watch Intercom. We even got to watch HubSpot. HubSpot was an early customer in 2016 and built a couple of their internal products using Clearbit. So today I want to take you through how these teams use data to win. And there's three specific tactics that we're going to run through. And then at the end I'm going to take questions. I tend to talk kind of fast, so if I go too quickly through this, we'll have more time for questions. But we're going to cover what I call Warm Outbound, scaled one to one personalization and bottoms up target account selection. So, so ABM essentially. So warm outbound, taking the cold out of cold calling. So this is what I would say is like outbound that sucks or personalization that sucks. Here's everything about me and nothing about you. So with Warm Outbound the idea is we're trying to find companies that specifically have the problem that we can solve. And that's like the best thing about B2B is all we do is solve customers problems. Like really all we're doing is solving some Business problem or changing some business metric and I guess give me some woos. Who in here runs a cold outbound program or outbound program at all? That was not very many people. Okay. Inbound. Okay. Still not that many. No one's doing sales or marketing. Got it. So warm outbound. There are three ways, three data types that I love for warm outbound. So warm Outbound can be thought of as a trigger for me to send that outbound email. So instead of just taking like, here's the 10,000 accounts that could possibly buy my product and sending them all emails, we're going to filter that by people that are showing intent or showing some signal that they're ready to buy our product. My favorite version of this is by visiting your website. So with IP intelligence data, where you take the IP address of people that are visiting your website, you can reveal what company that IP address belongs to and then you can use that to trigger outbound or to trigger a sequence to someone that's already in your CRM from that company. And HubSpot just said inbound launched our first buyer Intent product that does just this takes your anonymous website traffic and shows you which companies are visiting your website. The next type of buyer intent that I really like is research intent. And so this is things like Bombora or G2 Crowd or any ratings website where you can understand which companies are researching your topic. So say you sell CRM software like HubSpot, you could find out which companies are looking at articles about CRM software, are researching keywords that are, you know, attached to or associated with your category. And then my last and probably favorite is Champion tracking. So the idea with Champion tracking is you're identifying everyone that's purchased your product before or been a champion in one of your deals and then keeping track of them as they change jobs in tech. And in B2B, people change jobs every 18 months to three years. And so it's really, really valuable to know when they move to that next job because it creates two opportunities for you. One, the opportunity with the new company that they've moved to, and two, that like Resell or that save opportunity with the company they were at previously. So I talked briefly about this, but website intent, I'll break it down for you guys here. You take the IP address of the anonymous traffic visiting your website using something like HubSpot, Breeze Intelligence or other products on the market. You can take that IP address and turn it into the company name, the company name, their website, et cetera. Then you can use that to find contacts in your CRM from that company. Or go prospect and find new contacts and enroll them in a sequence in a marketing campaign in your account based marketing advertising campaigns. And you have that signal of their high intent which really helps you write good emails. You can see what pages they visited on your website. So they visited the HubSpot for marketers. You're going to write them an outbound message that's all about marketing use cases and not about sales or operations research intent. Very, very simply it is when someone is researching your category or your keywords. So someone like G2, I think they have 800 different categories and you can understand and buy from them. A data feed of Here are all the companies that are researching specific categories. Again, you can use that for outbound to select contacts that already exist in your CRM and run your sales and marketing campaigns. And last, Champion tracking, we've gone through this already, but this at Clearbit we had a champion tracking campaign that contributed about 15 to 16 new opportunities per month. And for us we were about a 50 million ARR company and that contributed to almost 8% of our close one ops in our last quarter before our HubSpot purchased us. So the big idea here is instead of doing Cold Spring and pray Outbound, you search for intent signals. And every business is different. Every combination of intent signals is different. But these three website Intent, Research Intent and Champion tracking can be used by almost every business once they filter it down to their categories. And one thing I'm going to do here on each of the topics that we cover, I'm going to show off a couple of vendors that I recommend working with. Who here is familiar with G2? Yeah, what about Bombora? Nice. These next three unified GTM, they're relatively new out of San Francisco. They try to automate this entire process. Worth checking out warmly, Lucia. And then I should mention here, HubSpot Breeze Intelligence, newly launched at Inbound about a month and a half ago, we provide a buying intent signal stream from your website. So those anonymous visitors that are coming to your website next, we have scaled one on one personalization. How many folks here have done personalization in their marketing campaigns or on their website? All right. I felt like more people than said they were marketers, so that's great. So the old way of personalization is mostly cookie based, right? It's like once we have identified someone, we could cookie them. Then we can personalize their ongoing and their later website interactions. It usually comes with a lot of manual content creation like static personalization, usually like industry location or Kind of the basics and it's one to many. And for most companies, a lot of work, a lot of human work with a relatively low lift. There's a terrible personalization example. Obviously the congratulations, you survived the Boston Marathon. So the data driven way again is taking advantage of some of the data we talked about earlier. First of all, taking advantage of buyer intent data, so understanding what companies are visiting your website. Second that your niche or your product category. And third, again, tracking the people, tracking those champions. And you'll see these three themes come up over and over today. Personalized landing pages, one for every target account. So this is one of the coolest campaigns I've seen. Brex did this really awesome campaign where they created over 10,000 unique personalized landing pages for every target account that they were going after. And they spun up a personalized website. It had a personalized card asset. You can see there, it's I think Airbnb. And then they had personalized ad campaigns, personalized cold emails going to those accounts and it all matched. And they were able to do this at like very massive scale. And then they would trigger these pages based on the IP data of companies visiting their website. So when someone from Brex or someone from Airbnb visited the Brex website, this is what they would see. And at Clearbit, we actually kind of pioneered a lot of this back in 2016 and 2017. We would personalize the logo that we would show on the page, we would bring in job titles, we would change the color scheme and we ended up getting, I think two or three cease and desists from companies thinking we were using them as like reference customers when we were actually just personalizing the page for their visit. So how do you use this data? I'm really going to focus on the company level, like IP data here. So here's a really good example. We've got two different flows here. We have an enterprise flow and a self serve flow. And Livestorm, a French company, uses the IP data and their cookie data to identify company size. So how many employees does that company have? If it's over 200, they show them the enterprise flow. And if it's under 200, they show them the self serve flow. A couple key differences. One, you can see enterprise and pricing. So instead of showing pricing on the top level nav to large companies, they show them their enterprise page. And then with the small company, they have that self serve flow and straight to pricing. So get started for free. Get your personalized demo. Same below. And then importantly, and then one of the Coolest conversion rate increase like tactics I've seen is this swapping out the logos based on which of those two categories it falls into. So showing your enterprise logos to large companies and your startup logos to small companies. So the big data idea here is use IP intelligence to reveal the companies visiting your website and then power your personalization off that data. Now the plus one idea to this is so you say you're like Brex and you got 10,000 accounts that you care about. You can spin up and create all these personalized landing pages, all these personalized buying flows. But then what do you actually do on the marketing side, on the advertising side? Well, you can take the same lists of companies and take them to LinkedIn, you can take them to Meta, you can take them to Live Ramp and you can run personalized campaigns that are one to one to those domains. And if you go to someone like Liveramp or some of the other DSPs, you can take their list of IP addresses and advertise that way as well. Which lets you do like one to one advertising targeting one to one landing page, one to one email flow, one to one like sales conversion pipeline and really, really start to see the conversion rate impact. Three companies or three tools I would recommend looking at in this space. Mutiny, Intellimize, ninetales Intellimize just got acquired by webflow. So if any of you guys use webflow might expect to see these guys pop up there. All right, bottoms up. Target accounts. How many folks here are running abm? All.

Right.

In account based marketing? Most of the time where I've seen companies executing here, they come up with a relatively static list of accounts. Either their sales leadership or their sales reps just pick a list of accounts. They're like these feel like good fits. You're slightly more sophisticated teams. Maybe you have a rev ops person or a strategy person that's picking that list. But really what you want to do when you're building this target account list is, is capture every possible company that's facing the problem that your product or service solves. It really shouldn't just be like employee count, location, job title. That's not specific enough. And we have enough data today where you can go much further down. You can go down to what topics are they interested in, where are they spending time, what problems are they facing as a business? What are they hiring for, what are they publishing on their blog? All of these become signals to help you do target account selection. So the data driven way is to create a dynamic like live list. It's not static, it's not 50 accounts, it's not 500 accounts. It's a ever changing segment of accounts based on the activities of those underlying businesses. So you can start with the firmographics. So say it's like I, I want to sell it to marketers at 50 plus person companies that are based in the United States and Western Europe that use HubSpot. Okay, that's a great starting point. And maybe that gives me 14,000 accounts. Now I want to filter that and I only have the sales reps to go after the top 500 of those. So how am I going to filter? Going to filter with additional data with intent signals. Gonna bring in things like again, website visits, I'm gonna bring in things like job postings, Are they mentioning my category? I'm gonna bring in research, intent data sets. I'm gonna bring in that champion tracking that we talked about. And any other data set or any other data point that you can think of could even go as far as like, I'm gonna scrape those 15,000 websites and I'm gonna look for specific phrases or I'm gonna look for specific topics being mentioned on their blog. There are so many different ways to cut this. And if any of you have individual questions about your own business, I'm happy to chat through. And then once you have that, you can run AI lookalikes. Has anyone using lookalike audiences or run AI lookalike type campaigns before? This has gotten so much easier and so much cooler with LLMs and vector embeddings. So lookalikes used to be based just on activity and firmographics. Now you can base them based on the knn similarity of a vector embedding. And what I mean by that is you can take all of the text that we know about a company and then compare it to all of the text that we know about another company. And you might find things in there that are not based on company size or location or job title, but you'll find things that are more based on like how they talk about their customer base. You know, are they selling to the enterprise, are they selling to financial services? And you can do that in like a much more nuanced, interesting way. So the big data idea here is let's combine fit plus intent plus AI to cast this like wider net and prioritize with, with intent signals and have this like live dynamic bottom bottoms up target account list. One vendor I really recommend checking out here is Keyplay. They just do target accounts. Super valuable, super cool. And then I'll plug myself again here, HubSpot, Breeze Intelligence. There is a account selection tool there too. So the top three ways, data driven ways, top three ways to use data to win jet lags, cat catching up, warm outbound, scaled one to one personalization and this bottoms up Target account selection. And I have talked relatively fast. We're gonna have extra time for questions. I think we've got some mics to run around. I'll throw it to questions. Hello there.

So quite often with reverse IP that we've seen in the past, you struggle to actually end up seeing the individual company. And quite often you see Cloudflare or Verizon or someone like that. How is HubSpot sort of actioning that with Breeze Intelligence? And are you able to use the cookie data from the tracking code in order to be able to help that across all portals?

So we don't use cookie data. The question is like basically IP intelligence, when you've tried it in the past, hasn't been very Good. How is HubSpot tackling it? So Clearbit, my former company, we built an IP intelligence product that was completely based on like the individual IPs and not the IP blocks and was sort of a dynamic list of best guess of what company each IP belongs to. And that was a big part of what drove the acquisition. This was a pretty unique data set. And then we've expanded that into the HubSpot world. But we don't return things like, you know, Cloudflare or ISPs, it's only the individual companies. So if you haven't tried it yet, give it a try. I think you'll be pleasantly surprised.

How do you know as a company if focusing more on quality like this approach is suggesting works better than focusing on quantity? And once you have this hypothesis, how do you show internally that it's going to pay off? Because it's sort of higher investment and higher return, but you need to make the investment and you need to wait to see the return.

Yeah, I mean, it's an interesting question. Almost always in my experience, focusing on quality does better than focusing on pure quantity. But it's like a unique equation for every business. Like, how many reps do you have? What's their efficiency? Now it's all about like, how can you improve your current flow? So if you're doing true like, I doubt you are, but true like spray and pray, cold outbound, and it's working really well, maybe you don't need intent.

Right.

But if you are trying to increase the efficiency of those teams or increase the outcomes of Your current marketing campaigns, that'd be the place to start in terms of measuring it. I mean the simplest is like the before and after. But you're gonna have to take a little bit of a leap of faith and give yourself three months to prove out the efficacy. I'm not sure that's helpful, but hey.

So probably some of the folks here that are doing ABM may be using something like six sense. We invested in that a year ago. And with HubSpot, to what extent would Breeze Intelligence the combination of your new capability, do we get the same value? If we're combining Six Sense which is obviously third party tool integrated into HubSpot, to what extent can you still get the same same value and outcome from a third party integration versus Breeze Intelligence?

6 Sense is great. The question is like can you get the same outcome using 6Sense as using HubSpot directly? Like yes. And I would be honest with all of you. Six Sense is a more feature fully featured and developed product today. Similar IP intelligence data sets, ours will be a little bit stronger but you can use them together. Back in Clearbit days we had a lot of our most sophisticated customers would use both and the Venn diagram overlap was, was real. But there was enough on the outsides that it was valuable to have both and then six Sense for their advertising capacity and their cold outbound prospecting. Super valuable. So check it out, see how much of it they can like complement each other. But if you're really relying on six Sense and getting a lot of value, I wouldn't recommend like wholesale switching. So when you launched the highly personalized.

Landing pages that had job titles and these things on it, I mean what was the finding from testing that? Did you find it? It really worked for some people and.

It really didn't work for others. Yeah, absolutely. So the company that I've seen, I'll come back to like Clearbits findings. But the company that I've seen be most successful with this was actually Rippling. So Rippling was an early Clearbit customer and they personalized like their entire website to their. I think it was, I think they had like just over 5,000 accounts that they focused on for their first three.

Years.

And their personalized versus non personalized was like a 30ish percent increase to open Opportunity. Intercom saw something similar and the company Mutiny kind of formed out of those early experiments. They saw that working for companies and then like tried to productize it with Clearbit. Because we were selling the data, we got to, we just got to have fun showing off as much data as we could. We never did a like non personalized version to test as a baseline. But we like our anecdotal evidence and qualitative evidence was that it was like very attention grabbing and increase people's interest.

How do you do data validation? You do a lot of breeze intelligence enrichment. At what point do you draw the line and say okay this is legit data versus this is the next or the best guess. Basically quality control in general for that.

Yeah. So question about data quality and data validation. So with breeze intelligence we try to only return Data that were 90% plus us confident is correctly matched and like accurate and up to date. So in company and contact data we're refreshing the data set at least once every 30 days so bringing back the latest information that we can on every company and contact record. And then if we're not confident or we don't have that much data, we just don't return anything. And that's not the same with all other data vendors. There's some out there that let you set like a threshold. I want 60% accuracy, 70%, 80. We just go kind of the binary, bad data is harmful and so we don't want to inject that into your system.

Just that question from someone over there made me think of this. So in terms of quality versus quantity, you know you've got like I call it a turn off rate but that is definitely not the right term. But like the step before your unsubscribe rate of a mailing list if you're doing both. So you're testing the hypothesis of cold outreach versus this target list. Could you cross reference the IP of your unsubscribed and use that to filter your target list further.

So to pull people out of your target list.

So to kind of. Yeah. To prove that one informs the other.

You could. The thing with that is your, the IP is it's at the company level so you might not know who the individual contact is. And if it's a large company, say you're you know, BMW or something, someone might have unsubscribed from BMW but someone else might still buy. Right. So I wouldn't recommend filtering out your unsubscribes like because it's a one to many relationship versus a one to one relationship.

Yeah. Nice. Thanks.

Yeah.

I'm going to ask you a little bit of a more zoomed out question Matt, because obviously getting rid of cookies is more of like a practical thing that we kind of have to do in business world because people hate cookies. But do you see like a future where we can respect both privacy and do this, like super targeted marketing and actually present what people want without them having to, you know, go through a lot of hoops?

Yeah, I mean, everyone loves those cookie pop ups, right?

Right.

It's a really good question. There's a reason that we focused on like the company level for our level of targeting. Like, we don't go down to the person level because we can do that in a very privacy, safe and compliant way and it gets you 80% of the way there. Like knowing that the company's visiting is a strong signal even without knowing who the person is. I don't know where privacy regulation is going to go. The US is going to follow Europe along. Like, we're pretty sure we're gonna have a federal, our version of GDPR within the next 18 months to two years, or at least it will have been proposed. I think that in general, the selling of personal PII and personally identif identifiable information is gonna continue to get harder. Candidly, it's like part of what motivated us to join up with HubSpot too was like this. The industry was getting more challenging. But I think if you focus on like inbound data where you already have rights to that individual and company level intent or personalization data, like it's a safe place to play and you can still get a lot of value. Not sure that fully answered your question, but that's the best I got. Amazing. Thank you all so much. Have a great rest of your grow.