John Buten and Iris from Explorium explain how their platform enriches sales data and builds predictive models. They cover lead scoring in two steps: rule-based scoring from win-loss analysis, then machine-learning models. Explorium tracks over 1.133 million small businesses, helping sales teams identify which prospects actually matter.
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1, 2, 3, 4.
Sales, marketing, and RevOps. It's sink or swim out there, and yesterday's strategies and tactics won't help you today. This is Revenue Today, and I'm your host, Jared Robin. Join me as we interview revenue leaders in our community to learn what steps we could take right now to help you scale yourself and your company. Revenue Today is sponsored by Rev Genius, and we're on a mission to bring inspiration and creativity to all revenue professionals in the world. Want to shout out our sponsor Demandbase. Demandbase is smarter GTM for B2B brands. They help marketing and sales teams spot the juiciest opportunities earlier and progress them faster by injecting account intelligence into every step of the buyer journey and orchestrating every action. For more information about Demandbase, visit demandbase.com.
Let me just share with you some of our customers that you can see, some big names here, and we're very proud of them. And there's many more, and we'll definitely continue to tell you some stories about our customers moving forward. And with that, let's move on to the last section of the webinar, questions and answers. Before we go into that, I want to mention a few things that you can look at right now or immediately after the webinar, and we'll be sending you them in an email as well. Obviously, come to our website or try our free trial. You can also see some examples of the data that we provide over there on the website and the free trial. We also have an exclusive offer for Rev Genius Community, and we can offer you a free 30-minute consultation with one of our data scientists to discuss your segmentation needs and maybe show you a quick demo of what this might look like for you. And we can also create a list of up to 5,000 net new SMB contacts for you that map to your ideal customer profile to show you again what the platform can do for you. So that's an exclusive offer for Rev Genius Community. And again, we'll be sending that in an email later on. And like I said, the Forrester 2023 Planning Guide for Sales Ops, a great piece of content. We'll be sharing that with you in an email later on. after the webinar. So I think great deliverables that you will get from us later on. Definitely go ahead and use them. And with that, let's get started with the questions. You ready, John? Absolutely. Great. So let's go ahead and let me see. The questions are coming in, and I want to remind everyone to go to your question tab and submit your questions. as we still have some time to take some questions. Let me take the first question that came in. The question is, how do you upload your data into your platform and where is all the data manipulation and prediction taking place? Is it in Excel? Is it in your platform? Is it in my BI system? That's the question. It's a very good question because I didn't get into the specifics of how the platform works, but the idea is that the platform is And there are many ways to get the data. But a typical way will be to upload the data from wherever it is. It could be in Excel. It could also be Salesforce CRM or any other CRM. Upload it to our platform, do all the manipulation, enrichments, and even, I call it exploration on the platform, build some prediction or scoring models on the platform, and then export it back to where it really needs to live. So if it's for the salespeople, You export it back to Salesforce. If it's for BI, we have APIs that connect you to your BI systems. If it's for marketing, we can bring it back to HubSpot. So many APIs and connectors allow us to be very, very flexible, upload the data from anywhere, manipulate it, and send it back to wherever it needs to be. Good. So great question. The next one is for you, John. And let me read it. The question is, how do you do market sizing when you go outside traditional segmentation by vertical or company size?
Well, yeah, market sizing is always looked at as more of a science than an art, but it's a little bit of both. You know, there are great data providers that can help you understand the nature of the market. So if you have something like— I thought the example that you gave, Iris, was really interesting, that Shopify users are a good target for a customer. Well, how many are there? And how big is that market? You know, you might look just at them, you might look at all the e-commerce providers and say, if we sold to people using e-commerce, what does that look like? What's important is to not necessarily get to the right dollar figure, but to get a good estimate of the relative size. And so you can use a variety of data sources to get some good estimations, you know, in terms of the number of customers for Shopify or for some of the other companies. Maybe some of the other companies aren't public, so it's harder to get at, but you can do some rough estimates based on who's bigger. This one's 2 times bigger than that one. And get to a good, a reasonable estimate. And that's what's most important usually for market sizing is getting to an estimate. We have good estimation techniques for doing it top-down as well as bottom-up, and often that's the best practice is to do 2 of them, and that way you can meet somewhere in the middle with something that's reasonable, a reasonable approximation. So don't let the perfect be the enemy of the good in terms of market sizing.
Yeah, thank you. We have time for a couple more questions, so I'll take the next one. How, how do companies typically get started with a lead scoring project? So yes, I mentioned lead scoring throughout the presentation, and it's actually very similar to how you get started with segmentation. So again, you need to start looking at the data, you need to start looking at the win-loss analysis, see what attributes are actually meaningful and relevant in that sense. Then typically what we see customers do is build a rule-based scoring mechanism that collects the data from the different places and connects it all together in a rule. The next step is to build a real statistical machine learning model that will really learn from your win-loss analysis and accurately predict and prioritize new accounts as they come in. Okay, we have time for a few more. So the next one, let me give it to you, John. As we're growing, we're facing a lot of pressure to verticalize our marketing. How should we think about adding a vertical?
This is a good one, I think. You know, we talked about vertical. Vertical could be the way you're looking at segmenting your marketing. I think Too often, people look at delivering products to market and then putting vertical on top, or we see large companies do vertical marketing. And it's important to understand whether the vertical makes a real difference for your product. I think we are seeing a— we've seen a little bit of a pendulum swing away from some of the vertical marketing because it didn't make as much sense all the time to just take the same solution and talk about how it applied to healthcare or financial services. You know, if it's CRM, it might be very similar ways that they use it. But what people, you will still need to do is at certain phases in the marketing cycle to be able to support companies always wanna know, can companies like mine use this? And vertical is one of the hooks into that. So being able to provide vertical-oriented case studies and be able to maybe micro-segment, you know, as people go through that buying journey to be able to support the sales model with some things that are specific to their use cases, whether that's demonstrations or case studies. So we see less of that vertical marketing layered on top, but if you have a solution that's very different for for healthcare or financial services. That's something that, you know, is right in our traditional segmentation that we see that companies go to market differently for different customer groups.
That makes sense. Okay, one more question here to me that I will take is around SMBs. Do you also cover private companies and specifically SMBs? Absolutely, we do. And like I said, it's hard to find information about SMBs. They're very dynamic. nature. They don't offer too much information about them. They're private. They don't have to issue reports. And they are very dynamic. They might move often. It's very hard to know if— think about a restaurant chain, a pizza chain. Is there a headquarters and subcompanies? How do you really understand the structure of that beast? That's difficult. But we actually excel in that area specifically. We cover— our database covers over 1 133 million small businesses, and we provide reliable information about them, and that's a unique point for us. Okay, I think we are running out of time, John. So I'd like to thank you for joining me today and thank everyone for joining us for this webinar. We'll be very, very happy to be in touch with you and show you our, how our Explorium platform can be used for segmentation and for other go-to-market techniques. Thank you very much, and I hope to see you in our next webinar.
Thanks, Iris, and thanks for the opportunity, and thanks everyone for your time.
Whoa, another great episode of Revenue Today. For show notes, links, and mentions, visit revenue today dot live. For all my friends and RevGenius community, thank you. It's been awesome to spend this time with you. Please DM me any feedback and ideas in our Slack channel or on LinkedIn. If you're not in RevGenius, join us at revgenius.com. It's free and it only takes like 2 seconds and you'll be joining a group of 27,000 revenue professionals strong. We've got it all. Looking forward to seeing you there. Catch you on the flip side.
