Customer data platforms are just one of the most recent innovations in the way AI is used to propel sales to a whole new level. Jim Hopkins of Leadspace joins Chad Burmeister to talk about some of the latest developments in using AI to gain a competitive advantage in sales. Leadspace is a B2B customer data platform that helps big companies become more data-driven with efficient data management systems. Inspired by the sports statistics at the back of the baseball cards he played with as a child, Jim found innovative ways to leverage data to succeed in sales. Listen in as he details the process of how CDP works and gives us the lowdown on some of the most recent innovations in AI in sales and marketing.
AI For Competitive Advantage With Jim Hopkins From Leadspace
I’m here with Jim Hopkins from Leadspace. I am excited to have him. I met him at the Dr. Howard Dover UT Dallas event in Dallas, Texas, or Richardson. We had a great conversation. I love his presentation and we get to have him here on the conversation. We’re going to be talking about AI for competitive advantage, how to profile intent and engagement enables personalization at scale. Jim, welcome to the show. Thanks for being here.
Thanks for having me, Chad.
Where are you quarantined?
I am quarantined in my little office cubby in the East San Francisco Bay Area. I’m out in the suburbs. Luckily, we have a yard. When it’s nice outside, we can send the kids outside to get the wiggles out. We’re pretty lucky, I feel pretty blessed during this time.
For those of you who are not familiar with AI For Sales or this is your first episode, we did write the book, AI For Sales, in 2019. Throughout an entire year, we interviewed about 21 different leaders from all different companies that use AI in their platforms. Leadspace is one of the leaders in that area. Jim, tell us a little bit about Leadspace. You provide artificial intelligence for your customers through your data, how do you leverage AI internally at your own company?
Leadspace is a B2B customer data platform, CDP, you might have heard those acronyms. We’re a CDP specifically for B2B companies. We work with big enterprise companies to help their go-to-market teams get better with data, get more data-driven, and take back control of their data. Whether that’s for inbound, outbound, ABM efforts, or whatever it might be. There are a lot of data that is involved in all those processes. We help out across the board.
Our marketing team and our sales team as well are excited users of our own platform. We try to drink our own champagne or eat our own dog food, whichever you prefer. We have a three-pronged approach to the way that we describe how our platform works that we also follow as well. We talk about to get healthy, get smart, and get busy. The get healthy part of that is about data management, data unification, and making sure your data is the best quality possible. We do that whether it’s in our CRM system to clean up the account and contact records that are in there or our marketing automation system as leads come in, enriching them with data so that we have the best quality data possible.
Get smart is about using AI to uncover the hidden treasures in that data to help you prioritize and segment the right audiences. When a lead comes in, we’re applying the predictive models or the AI models to those leads to help signal to us whether they should be in a nurture campaign for this or that, or whether our SDRs should take immediate action, whatever it might be. Those are helpful. Getting busy is about activating it in the correct channels. AI activation at scale. Being able to push that data to the right systems, whether it’s personalization on a website or out into ad platforms so that you can target and serve advertising to the right targets or accounts. We’re doing a little bit of all of that. There are more that we can be doing. There are some of our sophisticated customers that are doing some cool things. They are enterprise companies. They have the whole team that’s helping execute on that, but we try to do as much as we can on our own platform.
Get healthy, get smart, and get busy. I talked to one of the data scientists and one of your customers. That large unified communications as a service organization. Those who followed my background, they’ll know who I’m talking about. What I thought was neat was that they would leverage this level of AI to tell them which types of customers were the best ones to go after and which ones weren’t. Before this analysis, if you look at a T-Chart, all customers were created equal or treated the same. That shouldn’t be the case. If a customer has the propensity to buy and they’re going to be a five-year customer versus somebody who’s likely to go out of business in three months, there’s AI for that. That one goes in the red bucket and that one goes in the green bucket. It’s interesting to see how this technology is. At the base of everything is data. If you don’t have clean data, then you don’t have a good business model.
That helps to feed the right behavior too. Sometimes you get into this mode of FOMO or the fear of missing out. You want to try to do everything. You want to try to go down the list like a phonebook. Having data that tells you what to prioritize first and why that’s key.
We had a quarter in February, March of 2019. Gabe Larsen, who used to be with InsideSales.com, he called us out and said, “We don’t think AI is the way. That’s not going to replace humans. It’s going to augment human behavior.” There’s this big battle that ensued through social media. It drove about 42 inbound closed-one deals in the month. I was high-fiving their CEO, Dave, and Gabe, and saying, “Thank you, guys.” I saw him at a conference, I was like, “This is a great fight you guys picked because I think we won.” Maybe we both won, but a large percentage of those inbounds were small companies that were not funded, that weren’t an ICP, and they churned a lot faster than the rest. It looked good because our spike in the quarter went up, but at the end of the day, the long-term tale of those bookings wasn’t as good as when you’re proactively reaching out to ICP.
In a SaaS business especially, that ends up costing you more because the cost to acquire a customer and the cost in the first year of a customer can be a lot greater if you don’t retain them over multiple years and make your money back. Having that data and feeding it into the AI to tell you these are the customers that last for many years and these are the kinds that you want to go after more.
The data is available. There are tools like Leadspace. I don’t know why companies are so far not signing up by the thousands, but I guess they are.
Little by little people are being converted. It can be complicated, sometimes. It can be hard to understand, but it’s definitely worth it.
In this day and age, it’s more important than ever, because why go spend time on companies that aren’t going to convert because you have finite resources? In this weird market that we’re in, I’m seeing companies like yours are seeing an increase in demand and not a decrease because it’s more important than ever. Before we dive deeper down the rabbit hole, how did you get into this? I’m curious how did you get a passion for data. Some people could look at it as cut and dry and boring. Other people look at it as, “This is amazing.” I would think you’re probably in the “This is awesome” camp.
You have to be a little bit of a nerd to love data. I’m a marketer by background. I’ve been a marketer for many years, but I’ve always been passionate about technology and data. Being in the Bay Area, being in San Francisco, there are a lot around us. There are lots of opportunities to be exposed to technology and data. I spent some time early in my career at a couple of media companies. In both of those instances, I was adjacent. I reported to the director of marketing research at one of them. I got exposed to marketing research. I started to learn more about how to tell a story with data and information, and how to draw stories out of analysis and research. That unlocked a new language for me. I found opportunities moving forward in my career to do that more.
As I got opportunities to work in technology, data became more important over time. Data has always been important but it’s become increasingly important to technology. I spent some time at Salesforce. I spent some time at one of the ABM leaders, Demandbase. Data is critical in each of those technologies. I have gotten more opportunities to be surrounded by data and see the importance of data. I became passionate about it. I became a storyteller as it comes to data.Get healthy. Get smart. Get busy. Click To Tweet
We can go way back to my childhood. I grew up in the Golden Era of Bay Area sports with the Bash Brothers. I don’t know if you remember the Bash Brothers and the Oakland Athletics, Jose Canseco, Mark McGwire, and Rickey Henderson. The 49ers were doing well, Joe Montana and Jerry Rice. All of these guys were chasing records or breaking records. Kids who are fanatics back in those days were checking the sports pages and looking at the stats. We’re tracking stats every day to see what was the next record that’s going to be broken, who’s the leader in home runs, ERA, and all that stuff. That fueled the passion for me for numbers and data. I was always pretty good at math. What’s weird about me, I was good at that side but I was also passionate about art and music, and then the sports junkie side of me. I’m a weird mix. A nerd music geek jock. It’s a little of everything. Maybe that’s why I became a marketer. It’s part art, part science, and then there’s that competitive angle to it as well. It was a good fit for me. That’s led to my path.
I remember when I was with Riverbed Technology in the Bay Area, I would commute from Belmont to the city every day. We also opened an office further south on the peninsula. I grew the team from ten people up to well over 100 between me and MJ, the VP. I was a director. We’d go to these dinners and we would award some of the reps with, “Here’s a bottle of champagne.” We toast with everyone. It started with the top five, then it went to the top twenty. There were 40 out of the 100 at dinner.
The SVP at the time, Dave Peranich, because there’s a federal outbound rep, an ISR, quota-carrying, lead gen, and all these different roles. He would always say, “Chad, what’s the one number that’s the single version of the truth that tells me who’s the best in this room?” When you were talking about the baseball cards and football cards, I started thinking about the back of the baseball card stats of who the best seller is. That can be applied whether you’re trying to hire the right person and who you’re calling into. There’s so much where you can leverage this data and information to be successful in sales these days. I can’t even imagine what’s 12, 24, 36 months out.
What’s interesting about that is you could probably draw parallels and watch the movie Moneyball or whatever. Look at the sabermetrics that has developed in sports and in baseball, in particular. Other sports have tried to do it as well. I know the Warriors here in the Bay Area are analytic-driven. A lot of what’s happening with this sabermetrics is they combine multiple individual stat categories into one uber score. It’s like wins over replacement or whip for pitchers or whatever it might be. I’m not that good at that stuff, but I know that they’re combining those because ERA doesn’t necessarily tell you the whole story about how good a pitcher is, or home runs doesn’t necessarily tell you how good a hitter is. They developed these metrics that were a combination of walks plus hits, plus this, plus that to give you that full picture. There are some of that happening in sales and marketing as well.
This is interesting, a little off topic but still in the AI realm. If you think of ExecVision, Gong, Chorus, they capture a call recording and a day later or an hour later, you can go back and do what this company calls post mortem analysis. The call is already done. You can’t resuscitate a bad call. The new way that AI is being deployed is that in your Chrome extension browser window, you move the screen to a three-quarter screen, that’s your core app. You then got this tool sitting over there on the right-hand side that listens to every part of the conversation, and it pops up a window, “We’re in the objection handling part, you mentioned my competitor. Let me make sure to ask you some good questions and check on those.”
It’s where man meets machine. We’re going to have such augmentation. I’m getting a feeling that as a result of these quarantines, a lot of companies are going to come out and go, “Maybe we can do the four-day workweek. Maybe we should get Friday, Saturday, and Sunday off like a lot of Europe does.” We have powerful technologies and tools that can let us do more in four days than we used to do in four weeks.
Then you get the more social distance. Not to kill this baseball analogy, but the scandal that’s happened with the Astros if you followed it all. They were using technology to tell them what pitch was coming. They won a World Series because they had advanced intelligence to tell them how to behave and how to win. That’s definitely applicable to sales.
I have heard in the military, I don’t know which branch, there’s a term, “If you’re not cheating, you’re not trying.” You could ask Tom Brady about that one too, but he’s on a new team. I wish I had a piece of pie here to finish out the analogy. PIE is what we’re talking about. If we think of the three sides of the stool, P stands for Profile. Let’s dig into that because a record is not just a record. That’s the old way. Here’s the phonebook, call them all. Let’s peel into what does this whole PIE stands for?
We came up with this acronym because when you talk about data for AI and for sales, there’s a ton of ground you can cover. Data is a general term, you could talk about all kinds of information that could go by the name data. There are lots of parts of the go-to-market process where different pieces of data become important. PIE helps to bring some organization thought to this. P is for Profile. The profile is about who that person is or that company is. It’s from a seller’s perspective or from a vendor’s perspective. You want to be able to filter the targets, whether thats accounts or people. Who could even qualify to be potential customers at the top level? What makes them a potential customer?
These are usually relatively consistent attributes. Who they are doesn’t change quite as often as some of these other pieces of data. If you think about company size, company industry, location, people data like a job title. These things do change but they’re key to you targeting them in the first place. The profile is critical. Without knowing that profile data, you’re just reading the phonebook. You could be calling a director of IT, but you could be calling him at the SMB down the road that does vacuum sales versus some enterprise company. If you’re selling a server load balancing software, you’re not selling it to the SMB, you’re selling it to a large company. You want to know who they are and what makes them a potential customer.
What I always liked about how Leadspace uses this and the fuzzy logic around titles. If I were to go out and search in a Dun & Bradstreet, I’d have to type in “vice president of sales.” If I missed, “vice president of VP, sales, SVP sales,” it could be 500 different variations of the term VP of sales. That’s just one level. It also seems to me that there’s, “We need the person who’s responsible for this.” That title might be VP of sales in one company. It might be something completely different. I always found with the way you’re able to profile people that are unique from anything else that I’ve ever seen out there is that it’s down to those bucketed groups of titles.
That’s a critical piece. That’s our proprietary persona data. We have a persona library of over 100-plus different clusters of personas. There is some fuzzy logic involved there. We’re taking the things that you would expect to know about a person like their job title, department, company, some of the account attributes of their industry, or whatever. We then go even further. We go beyond the job title because we’re looking across the social and open web. We’re gathering all kinds of data from all kinds of sources and using AI to blend it and unify it.
We’re looking at things like skills and expertise. We’re gathering in technology as well. We’re using all these data points to then create clusters where signals are high, medium, or low. We can then say, “This is an IT director who’s focused on cloud software,” versus “This is an IT director who’s focused on security.” Just knowing that they’re an IT director doesn’t get you in either direction, you’re marketing to both of them. That persona data is critical when it comes to targeting. It’s knowing who you want to go after and as I said, profile data is about your perspective as a seller. Who do I want to target in the first place?
I remember going to lunch in Denver, Colorado some years ago. It was with your head of customer success, maybe a VP. You’ve got some high-level data science skillset and if I’m not mistaken, it’s Israeli. If you’re trying to find someone in the field of battle, and you need to figure out when and where they’re going to be so that you can target the enemy. That’s the level of deep understanding machine learning AI that is built into this platform.
Our founder, Amnon Mishor, worked in the 8200 Division of the Israeli Defense Force, that’s their Intelligence Division. He did a lot of stuff there, but one of the main things he always talks about is he was using data and signals to identify terrorist threats and terrorist activity. Applying that AI to then find B2B personas is a little less life or death situation but it still applies.
That’s the Profile level. Hopefully, our readers can see that it’s a deep understanding of who the persona is. There’s a way to bucket these people. Now that you know who the person is and the target is, the next big thing that we’ve heard over the last months is, “When should I call those people?” Not all 100 are entering into a buying cycle. I expect this has to do with, “How do we find out which people we should call and when?”
It’s a timing issue. If you don’t have this component, you’re likely hard selling. You’re trying to convince that person or that company that they should buy this, which is a much harder sell. When they’re in the market, they’re looking for something. You want to be in front of the people who are in the market to buy. If you notice, in the picture is the perspective of the buyer’s point of view. It’s what they’re looking for and what they’re interested in. Intent data has become more popular, more in use, and more advanced in the last few years.
It’s has a lot to do with their digital behavior. As we’ve all heard, a lot of buyers are going through the buying process digitally long before they ever reach out to a salesperson. It’s capturing a lot of that digital behavior and those digital signals that would indicate that there’s a buying process happening. It’s outside of your realm of knowledge, outside of your garden. They’re searching out on the web. They’re reading topics related to your solution. They’re even maybe looking or searching your brand name, which is a key indicator. The intent is critical in filtering the companies or the people who are ready to buy.Get the kind of data that tells you what to prioritize first and why. Click To Tweet
Part of this is what’s the baseline? If you’re with Boeing and there’s a baseline of searches for that keyword and it doesn’t go above the baseline, that’s just normal day-to-day. If all of a sudden, there’s a little bit of a surge, one of my customers said that it was a detriment if there was too much intent. I’ve seen this with certain data providers when they put out a trigger or whatever those things are called. In most cases, we would buy those triggers and that intent was way too high. They’ve already bought whatever the product is. They’ve installed it and now everyone’s researching, “We just moved over to RingCentral it looks like. This is going to surge.” You missed it. You’re six months late to the party. How do you decide one standard deviation above the baseline? Has that got to be built into the black box on the back or do you give the customer some configurability in those areas?
We do have some standard scoring methodology that we use to make sense of an intent scoring. The partners that we work with, they’ll give a score. Bambora is a leader in this space. They do talk about that surge. They have a surge score that comes with their data. That’s one way to understand it. We do some simplification. There’s a high, medium, and low methodology that we’ll employ to certain intent topics. We can do more advanced intent scoring. We work with companies like the ones you’ve talked about already, to do some more advanced things or to even combine the intent with some other things. There’s more work to be done in this area. We’re exploring that with a lot of customers as well. There are different intent signals that would indicate early in the buying process versus late. A hand raised like an inbound lead, they’re late in the cycle. We know that from research that they’re probably 2/3 of the way through their buying cycle. You don’t want to wait for that. That’s the key.
I remember one of the best salespeople that I ever worked with, Steve. We both worked at Airborne Express right out of college, 1st or 2nd job out of school. He went down the path of hardware, I went down the path of the software. In hardware, it’s all about I want to find that 11th-hour hand raiser. I want to go create a relationship with that person. I’m going to sell you emotionally at that moment because you’re already all the way down the buying process. I need you to flip over to Cisco or to whatever hardware he was representing. In software, it’s different. I need to create the vision of what it is you’re building. There are some overlaps in both of these areas. I’m sure it not all or none. Generally speaking, if you’re selling something that’s more of a software, Microsoft, Selling Air, I remember I have that book early on. It’s not a physical hard product. I would tend to think you probably want to catch them a little early in the cycle.
Any salesperson, sales leader, or even marketer, if you would ask, “Do you want to be involved earlier or later?” They would opt for earlier, but who knows? Maybe that’s a strategy like a swoop in late and steal the cheese.
What’s next? This is outside the four walls. We’re listening to the market. That is on the internet search and all that. The last piece of the PIE is the Engagement piece. If I’m not mistaken, this is more of your own internal triggers and alerts.
It’s straightforward. How they’ve interacted with you, website activity, content, email, understanding the history of engagement with them, and up to the minute real-time engagement. It all helps to tailor the message, tailor the pitch, personalize what you’re showing, and personalize the proposal whatever it might be.
Those are the three biggies that we covered. You see a lot of technology. You’ve worked for companies that use technology. When I go into a lot of companies, they have a CRM. They have LinkedIn navigator. They might have an email platform/dialing platform. They have a data source. That’s maybe four. What do you see as the next tier of sales or marketing tech that within 12 to 24 months, you’re going to say that is the next most important strategic item you need on your list?
Selfishly, customer data platforms will fit in there and vie for that spot. It’s going to be critical.
To be clear, it’s not a database. It’s a smart CDP.
The key here is that it runs across the silos of systems that we have, whether it’s sales, marketing, maybe even customer success, finance, or whatever. It’s ingesting and unifying data from across the customer journey to then give you a better picture of individual customers and give you the whole pie versus just a slice of it. CDPs are vying for that spot. We’ve talked about conversational intelligence. That’s an interesting technology for salespeople. That’s also another interesting source of data that could be added to the pie to help you in that engagement bucket. To help you understand the signals that they’re sending, maybe even the subversive signals or that subconscious signals they’re sending through what they’re talking about.
Crystal Knows is a data set that helps you figure out what the personality is. Leadspace column Z says, “This is their personality, therefore the messaging should be slightly different than it is.” That’s another layer.
I’ve heard about those. Those are cool. There’s the analytics part of this and sales leaders have traditionally been the reports and dashboards type of power user. That will become even more important to frontline salespeople, marketing teams, sales ops. Analytics is critical and there’s more that we can do there. Especially from our perspective, as you unify data, as you bring it all together, there will be more data to handle. There will be different views that you can show, especially in that PIE construct. You want to surface that.
You want to surface the combination of those different things, each individual thing on its own. You want to visualize the customer journey for a sales rep or for any customer-facing representative to have the full picture, to be able to know what to do, what to say. Analytics will be critical. Salesforce has signaled the importance of that with their acquisition of Tableau. Other tools are continuing to innovate. We use a tool called InsightSquared that is cool. There are lots of analytics and BI tools like your Domo and your Tableau.
Those are an interesting category. You talked about sales engagement. That’s becoming even more critical. We’ve seen it in our own company. It’s interesting how that interplay works between sales engagement like the sales life and outreach with marketing automation. The bigger scale nurture programs versus the smaller scale cadences and where that line is, we’ve had some conversations internally.
It’s all coming into a single line is what it feels like to me.
How important is the automation part of this versus the more personalization, the smaller, more targeted cadence or interaction? That will develop in the future too. We’re definitely keeping an eye on that, both for internal purposes and for marketability. The other critical category that I’ve thought about is collaboration and communication. It’s critical especially as we become more work from home and more digital. We’ve seen Zoom take off and go through the roof and other unified communication platforms have gotten lots of attention and are going to have to innovate quickly. There will be some cool innovation that happens with voice and with video. We’ve all become heavy users of Slack. A lot of us have a chat. How that converges will be interesting.
Slack plus Zoom equals an interesting peanut butter and jelly combo. I’m waiting to wake up one day and say, “Okay.”
The real forcing function here for sales, in particular, is how do you reach somebody that’s working from home? How do you communicate with them? How do you get them to connect when they’re probably not picking up their phone? The email has become inundated. You don’t have their home address, you can’t send them a direct mail.
We were about to do a direct mailer right at the beginning of all this. What we are seeing that’s working well is that if we do an analysis of a person’s LinkedIn network and who they’re connected with at my top target prospects, and I reach out to people in my network and say, “Remember, we did that webinar together. It looks like you know Mr. Fred Smith from FedEx, could you make an intro?” “Okay,” then Fred knows you. We’re seeing that as a big lift in our ability to book meetings with prospects.
Those connections will become important. The digital connections are all we have now. We don’t have face-to-face anymore. We can’t go to events and just meet people.
There you go. There’s a product for you. Who’s connected to who? You listed out 8 or 10 different technologies. Some companies may say, “We already have all those.” Most would probably say, “We have two of them.” You’ve bought technology and you’ve sold technology. If you’re on the buying side or in the handshake side of that picture, how do you stack rank the investment in technologies?
I’m a corporate shell. I’m an old Salesforce. I have CRM high on the list. We’ve gone through a reboot of our Sales Cloud instance or CRM instance. We’ve seen how powerful it can be to do it the right way and have technology aiding the sales process and helping to automate a lot of that. It’s important. The next piece of that becomes the data part of it. Making sure the data is right, you understand and it’s coming in clean. Selfishly, customer data platforms are critical there.
As a marketer, I always think that marketing is key. Marketing automation platforms are a priority. Whether or not you want to be more targeted and personalized versus more mass and automated, then it dictates whether or not you might go with a more sales engagement tool versus an automation tool. It’ll be interesting to see how this data space evolves, maybe the data can dictate some of that a little more so than it has in the past. Maybe you need email delivery and you can become more intelligent with the data. We’ll see how that goes. Collaboration is key too.
Leadspace is a cool company. Four of my favorite people, Stu Schmidt runs the sales organization. Stu was an ex WebEx leader that I knew from many years ago and one of the most trustworthy and amazing people that I know. Natalie Kolody works for Stu. She is a top-notch sales leader. Jennifer Piehl worked with me at a prior organization. When it comes to data, I’ve seen some companies are used-car sales. CDP with Leadspace, this company has so much knowledge and so much understanding. CDP is the Customer Data Platform. If you’re looking for a fresher way to buy data and leverage artificial intelligence in your customer, I highly encourage you to check out Leadspace. Jim, it’s great to talk with you. I appreciate it.
Thank you, Chad. I appreciate it.
Thank you so much. We will catch you on the next one. The Sales Experts Channel, we are out.
- AI For Sales
- Riverbed Technology
- Amnon Mishor
- Selling Air
- Crystal Knows
About Jim Hopkins
Many people may call themselves marketers. They may have taken all the classes, worked at the best companies, and in the hippest of agencies. They build a mean spreadsheet, track all the best KPIs, and bleed the budget to the last drop. But if they can’t tell a story…one that resonates with customers…and architect the ways to deliver on the promises of that story, they’ll never be able to build brands that have real relationships with people.
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