The B2B buyer’s journey is as complicated as ever. Jon Miller shows the problems in B2B marketing in sales in his presentation and counters those problems with proposed solutions. In this presentation, Jon talks about how 1st party and 3rd party data can be aligned to have a more defined buyer persona. Once data has been collected, it should be analyzed to improve your account-based marketing approach.
Jon is a marketing entrepreneur and thought leader. He is currently the Chief Marketing Officer at Demandbase, the leading account-based marketing platform. Previously, Jon was the CEO and founder of Engagio (acquired by Demandbase) and was co-founder at Marketo (Nasdaq:MKTO), a leader in marketing automation.
“B2B Marketers and salespeople are constantly bombarding their salespeople with spam.”
“A lot of buyer behavior today is hidden from traditional tools like marketing automation.”
- Connect and match 1st party data
- Get and clean 3rd party data
- Maintain the acquired data to ensure accuracy
- Inject data into every step of the buyer’s journey
Hey everyone, this is John Miller. I am the CMO at Demand Base. And today we’re going to talk about how to unpin your brand with account intelligence. So, you know, I joined Demand Base back in June of 2020, when we merged demand based engaging together to create the demand base one platform. I’m really just super proud of how much we’ve evolved the demand base in the 18 or 19 months. You know, since then, you know, I was the CEO and founder at EO before that I’m probably best known as the CMO and co-founder at Marketo. So you know, back in those days of Marketo, there was this real separation between the workflow application i.e. the marketing automation, and the data or the intelligence that fed into it. I think as we’re going to see through today’s presentation, though, buying is much more complicated. There’s more need for AI. And as a result, we’re seeing a convergence or combination between the workflow applications like the ADM platforms, and the data providers.
So that’s a little bit about my background, just another fun fact about me is that I’m a dad. These are my two kids. And I also studied physics. So as a result, I really like nerdy dad jokes, and we’re going to have a couple of those run through today’s presentation. So for example, two atoms were locking across the street when one of them exclaimed, I think I lost an electron. The other one then replied, Are you sure? And the first Adam said, Yep, I’m absolutely positive.
Okay, so with that setup, let’s get into the meat and really talk about the state of b2b Buying today. If you work in the business, you’ve been targeted by the business for business marketing and sales. You know, the world you’ve experienced what today’s b2b marketing playbook looks like, probably many times a day and it’s not pretty. So what’s going on here, something is clearly broken. When you meet marketing and sales people in b2b you can see right away that these people are smart. You have to be in b2b today or you won’t last very long. The thing is, all these like super smart marketers and salespeople, they’re still constantly bombarding their customers and prospects with spam. And that’s not the exception. That’s the current state of b2b. And buyers and b2b are really frustrated. You know, now as consumers, we’ve all come to expect some really smart marketing and E commerce experiences.
Think about the last time you were on Netflix, they know what you watched, and what shows you’re likely to be interested in. And they use all that data, all that intelligence to make your experiences better, more relevant, or personalized. Now that revolution and consumer marketing is finally coming to unspin b2b. Today, most of the typical buying commit journey is happening online. Buyers are in control. They’re researching new products anonymously, before they ever fill out a Contact Me form. Now this means that a lot of the buying behavior today is hidden from traditional tools like marketing automation. At the same time, it’s not a linear single purchase decision. B2b decisions are much more complex because they’re made by groups. So if you see engagement from one person they are likely representing a committee of people who are all conducting their own evaluations on blacks, right? This is a real challenge, but it’s also a real opportunity. Because these interactions that happen online can be tracked and measured, and analyzed and ultimately turned into intelligence to make everything that we do more effective.
There’s this growing volume of data. And if we could just bring it together. We know we could use it to have a smarter market. There’s a real obstacle to doing that. And that’s what we call go to market or fragmentation. All the data that we need ends up sitting across different systems and departments and teams and databases. If we could only bring it all together, we could do something. But when it’s fragmented, it causes some real pains and challenges.
The biggest challenge is account blindness. It’s the inability to really know what’s happening at the accounts, right. It’s that anonymous research that’s hidden to us. It’s the data that we know about the account but fragmented across these different places. We can’t bring it together and really see what’s happening at the buying committee. And as a result, our marketers and our salespeople have to use hunches to make decisions about who to reach out to and what to say. And this is ultimately leading to spam the wrong messages to the right people, the right messages to the wrong people or at the wrong time. And it’s not just unwanted none opt in email. It’s every interaction that’s irrelevant, or not helpful to the buyer. And this is ultimately causing us to miss out on opportunities to create really bad buying experiences. And ultimately cranky CFOs because of lost revenue.
Fortunately, though, there can be an answer here, and this is what I call account intelligence. Account intelligence is when we can take all the insights from all the you know information that’s in our databases, and match it and clean it together, and then augment it with really awesome third party information, and then activate that intelligence at every site stage of the buyer’s journey. So that way we can spot opportunities earlier, engage them more effectively, close business faster and ultimately create better experiences. So that setup a quick dad joke. So after the sheep dog chased all the sheep into the pen, he told the farmer all 40 accounted for only 36 sheep, the farmer said, and the sheep replied, yeah, I know. But I rounded them up.
Okay, so let’s dive deeper into this whole idea of account intelligence. And the first piece we just talked about, is you need to collect all your first party data and make sure it matches to the right account. Now easier said than done. Tie into your market automation system and your CRM system and your email and your calendar. You know, and there’s you know, you have all the stuff but there’s still gaps even if you get all the data tied together. Now there’s a gap because your marketing activity like mail opens and campaign responses oftentimes leads and there’s no connection Salesforce between leads and accounts. So you lose that visibility. Plus, as we’ve talked, you know, there’s a ton of the buying happening anonymously, now either on your site but from an unknown visitor or off your site, and there’s a disconnect there to say hey, which accounts are showing interest?
Fortunately, there are technologies to help solve this lead to account matching just really foundational here. And this is just the ability to sort of take a lead look at their email address, for example, and figure out which company they work for. Now, you can use fancy fuzzy logic to make sure you know that you get things right. The real science comes in when you have to break ties, like somebody has a ge.com account. You got to figure out, you know, their location to figure out which GE they work for. And then once you’ve done this, it lets you do pretty cool things like take data from the account record, and actually augment the lead record accordingly so you can route the lead better or score it more appropriately.
On the web activity side, you need to DE anonymize that web traffic using what we call account identification. This is where you’re looking at the cookie and the IP address and to say you not say who the specific person is, but figure out what account they work for. And there’s a lot of data science and machine learning that goes behind this. The real trick, to be honest, is balancing the accuracy of the match with a broad high match rate. You know, I could for example, tell you 100% of the people visiting your website worked at IBM comm that would give me a very high 100% match rate, very low accuracy. So it’s all about the algorithm’s ability to sort of, you know, wait those two factors against each other to come up with a good account identification. Now once we have all this we now have a really complete view of what’s happening with our first party data, you know, at the accounts. So that means it’s time for a nerd joke. I had an argument with a 90 degree angle I lost. Turns out it was right. Now that brings us into a deeper dive into all that awesome third party data, a bunch of different kinds listed out here so that you can see your world in high definition. I’ll walk through each
Of these relatively quickly. The first is you’re just the information about accounts. You know, this is where you’re going to go and find to say you know give me all the accounts that have this revenue, this size, these industries, you know, and so on, or cleaning or taking that same day to to clean the existing accounts that you have. It’s a hierarchy of parent child relationships, and you’re going to use this to find new accounts and score the ones you have built. Segmentations make sure your territories are right, you know, and so on. Now, the data vendors where you’re going to get this data, including Demand Base, you know, we source it by looking at, you know, 1000s of public data sources, we’re looking at public sources websites, regulatory filings. The key is how we triangulate across multiple data sources so that way you get accurate data. Contact data and connections. You know, this is really important because the other day even though it’s account based, you’re still you know, talking to humans, according to Gartner, a given buying committee has 49 people.
So you’re going to want to have access to who are those people in your target personas, what is their name, their title, their contact information, maybe their connections that you have to them? And you can use this to obviously reach out to the right people, but more sophisticated things like following an exact to a new job, and making sure that your email sender scores don’t get blown off by sending to you know, invalid email addresses. Similarly, this is going to be sourced by triangulating against a bunch of different data sources. You’re going to want to avoid scraping or harvesting emails because that can be, you know, not so great. And don’t just think that the vendor with the most contacts is the best vendor because first of all, you want accurate information. And so really focus on you know, who has the best accuracy for the actual contacts you care about? Most likely people who have authority and influence over your buying decisions. News and social insights, you know, this is things like sales triggers, do the company have an expansion or a new acquisition? It’s what you pull from their blogs and their social feeds and you can use this to be more relevant and more timely, it’s pulled from social you know, just by mining, all those, you know, social sources.
The key to think about is you know, can you get custom trackers and keywords so that the alerts are going to be relevant to your business. Just a couple things: quick dad jokes at the right time. Why do teenagers travel groups of three and five all because they can even buy two more data types with a little bit more detail on these because they’re really important. Technographic data is data about the technologies that a company has installed. And then any kind of patterns you can, you know, come up with based upon you know, that dataset. You know, what we found is that for technology companies, this is often the number one most important data source for which account is going to be a good fit for the ideal customer profile.
You can also use it to identify which companies are using your competitors or perhaps partners. And you can and there’s interesting patterns that said here you can sort of start to predict when a competitor contract might be up for renewal, or what is the next technology somebody might buy based upon patterns that we see and therefore reach out at the right time. So this kind of couple ways you can get this data, the sort of most common way is to get the stuff that you can basically see off of a website, because different vendors will put a tracking code on the site, but that’s fine for some technologies, but if you want lots of other technologies, you have to be a little bit more sophisticated, and do some natural language processing and mining of like job boards, you know, what skills are people talking about when they’re hiring, they’re hiring, or looking at resumes of people who work or have worked at that company to see what kind of technologies they talked about using.
Alright, so the last datasource I want to talk about is intent data. This is probably the coolest, the hottest one that’s getting the most buzz in b2b today because it’s really all about tracking what topics people are reading out on the open web, not your website. And using that to find what you know, topics they’re interested in, and when there’s spikes that show they might be in the market, make a new purchase. It can help you identify if one of your existing customers or open ops are flirting with the competition. It can let you use the actual words that that account uses in their research to be more personalized and relevant when you reach out. So let’s talk about where this data comes from. It’s kind of a mystery to some people. There are lots of intent providers demand base Bombora Jeetu, you name it. What they all have in common is that they start by getting a signal from a visitor on a particular webpage. You know, and so, hey, this cookie with this IP address is reading this article.
At DemandBase. We get that from the b2b bid stream Jeetu gets it from people on their own website. Once we have that bid stream, the first thing we do is that account identification. So we know that this person, this visitor, we don’t know who they are, but we know they work at IBM or Tesla or Nike. And then we can do content extraction with natural language processing to see what that page is about. So we can see maybe this is a page about digital security or something like that. Now any one article doesn’t tell us intent. You know, but when we start to see a pattern of lots of articles, you know, articles that maybe are older and therefore more about research rather than news, and this person is reading a lot of articles. That’s when we can find a you know, a spike that says that his intent is going up, it’s time to kind of reach out or do something.
That’s where this data kind of comes from. Now Garner’s on some research here and like lots of people are interested in 10 data, but almost to the theater, a little more than two thirds of companies who have it say that their biggest challenge is actually using the intent data. So make sure you’re thinking about how this gets into your ABM platform or your CRM? How will the sales team and the SDR get alerted or know which accounts are showing intent? How does it get incorporated into your predictive analytics? How can housing tend to drive your advertising, your direct mail programs and understanding where accounts are in the buying journey? These are all important questions to ask using your intent data. Final piece of your account intelligence is maintaining the data because it doesn’t stand still. Even if you’ve gone and pocket data, which you know most people haven’t necessarily, your database on any given time is probably at least 25% inaccurate. According to Forrester because employees get promoted, they change jobs companies grow and shrink and acquire other companies. So you need some process to make sure your emails are accurate, that your CRM is clean and enriched without duplicates, and that anything out of date, no date gets cleaned up. That is your account intelligence foundation.
So second to last nerd joke. Why is six afraid of seven because 789 you probably heard that one? But why did 79 because you’re supposed to eat three square meals a day. So the last thing I want to just touch briefly on is what you do with all this account intelligence. Once you have it? Well, you want to take it and use it to inject that you want to inject intelligence into every step of the buying journey. You want to see opportunities sooner, engage with them more intelligently and close deals faster. So for example, you want to use this in your Account Based Marketing account based experience programs. You know, to orchestrate interactions to know where accounts are, you know and so on. You want to use it to make your advertising more effective, you know targeting the right accounts with the right messages, the right people in the right accounts and so on. You want to use it to make your sales team more effective. So think about how you are going to put your intelligence into their hands inside the CRM, email alerts in Slack, you know in LinkedIn, all that kind of stuff. And last but not least, don’t just how are you going to use this account intelligence in all your other systems? Do you want to use it in your application? Do you want to put it into your data lake, you know, or your tableau analytics to really again, make sure that everything that you’re doing is smarter, more intelligent,
And less spammy? Do you want to learn a lot more about account intelligence or how to use it? To activate your smarter go to market checkout my 250 Plus page book called The cleaning company guide to smarter GTM you can get it for free at demand base comm slash guide that let’s wrap with one big thank you. You know you are the best. Have a great day