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Clearbit

Powering sales and marketing initiatives with data requires not only the right attributes, but the freshest data. In Episode 3 of Talk Data to Me – The DataExchange, Ashley Taylor, Head of Partnerships at Clearbit, explains how Clearbit combines real-time lookups, machine learning, and manual QA to ensure data never goes stale, equipping customers with fresh, reliable data that drives results.

Ep 03: Clearbit

With more than 100 attributes to offer, Clearbit provides data for the entire customer lifecycle – aiding businesses in everything from ICP analysis and lead score modeling, to predicting churn and revealing anonymous web visitors. Watch the full clip to learn more about how customers are operationalizing key data attributes like Alexa Ranking to maximize resources and achieve aggressive growth, even during the ongoing crisis.

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John Kosturos:
So let’s get started. Um, Ashley, thank you for joining us today. Uh, today we’re lucky enough to have Ashley Taylor, the head of partnerships from Clearbit to um, go through our fireside chat and answer all the tough questions about all things data. So, Ashley, thank you very much for joining us today.

Ashley Taylor:
Thank you for having me, John. It’s great to be here.

John Kosturos:
Awesome. So let’s just jump right in. Um, I’ve got some questions today and the first one is tell us a little bit about your company’s background.

Ashley Taylor:
Sure. So we got started in about 2015. Um, and we are a tech first platform. In fact, our original name was API hub. Thankfully, uh, we are now clear, but, um, but I think that that really speaks to, uh, you know, all three of our founders are technical. Um, and everything that we do is going to be developer friendly, uh, and uh, and programmatic first.

John Kosturos:
That’s amazing. Um, so how, you mentioned you guys were started in 2015, um, what types of customers do you serve?

Ashley Taylor:
Yeah, absolutely. So, um, we work with B2B customers. All of our data is B to B. Um, and we’ll, we’ll perform best for customers who sell into geos that either speak English or have at least our shared Roman alphabet. We also perform best with customers with an Alexa rank stronger than a hundred K. Um, just because the larger the sample size of visitors, um, kind of the more you can do in operationalizing your data.

John Kosturos:
Great. Um, what are the main problems that you help your customers solve?

Ashley Taylor:
So Clearbit data will integrate into an entire revenue stack. Uh, if, if the platform could accept API connections, uh, we can work with them. But really we provide the data. Our customers need to take action on leads and contacts. As a growth engine, we allow our customers to take action, for example, on intent signals across their website and online properties between visitors and form fills, um, in any ways that prospective customers could be engaging with them online.

John Kosturos:
Wonderful. Okay. Are there specific verticals that you focus on serving? Obviously B2B is where your, your, your focus. But within that B2B, um, vertical, are there industries or, or, or verticals within the BDB vertical that you really focus on?

Ashley Taylor:
I think because of, as I said before, the sort of tech first approach that we’ve taken, we tend to do well in B2B SAS, however, that’s certainly not a requirement. Any B2B company, especially those with a lot of inbounds or those with maybe a bifurcated sales process. Um, you know, they have both a self serve and an enterprise sales motion, um, tends to be the most successful. But really we, we could serve just about any B2B company.

John Kosturos:
Okay. Are there specific geographic locations that you focus on?

Ashley Taylor:
So it’s less about where the customer is located and more about where their customer base is located, so where they’re selling into. But companies that sell into, uh, geos that speak English primarily will perform really strong. And then companies that sell into geos that don’t necessarily speak English but use our shared Roman alphabet will also perform well. Um, companies that sell mostly into GOs that don’t use our shared alphabet. We just, our, our data quality will not be there.

John Kosturos:
Okay. Um, and what would you categorize your data as? I think you’ve answered this already, but we’ll, we’ll let you go again.

Ashley Taylor:
Yeah. So it’s, it’s very much B2B data. Um, so if you’re, if you’re purely a B to B B2C shop, we won’t be a good fit. Um, if you’re a hybrid B2B, B to C, um, if you have a strong go to market motion for your B2B side, we could be a strong fit. Um, and then of course if you’re a B to B, um, that said, if, if clear it is something that you’re interested in, our sales process pretty much always involves a data test, um, so that you can validate for yourself how strong our data actually is for what you are specifically looking to accomplish.

John Kosturos:
Wonderful. Um, do you guys consider yourselves enrichment providers solely or do you also provide lists of net new contacts or companies?

Ashley Taylor:
Yeah, so we’re, we’re very much an enrichment provider. Um, again, kind of coming back to you being tech first, we don’t really sell lists. Um, that said, if, if you’re, if you do have a list that you’re looking to get in rich, you can set up an account@clearbit.com um, and, and do a onetime batch in Richmond. However, um, you know, to really, really get the power of Clearbit. Um, you’ll want to actually have ongoing, recurring, real time enrichment used in conjunction with your CRM, with your marketing automation platform, uh, orchestrated through a platform like RingLead.

John Kosturos:
Well, I, I agree. I mean the one time cleanse it’s, it’s always, it’s never cost-effective to clean data as opposed to prevent or have ongoing maintenance happening. Um, data cleanup projects are never fun. So, um, how many business in person records are in your database?

Ashley Taylor:
Yeah, this is, this is actually a really hard question to answer because of the way that we approach gathering data. We actually don’t think about things in terms of database size. So what do we mean by this? If you were to go to Clearbit and try to enrich an email address for the first time that no one has ever tried to use Clearbit to enrich this email address before, um, we actually won’t error out. What we’ll do instead is try to look it up in real time. So we’ll crawl the web, we’ll leverage our give to get model, we’ll leverage the machine learning that we’ve built behind the scenes. So it’s very unlikely that you’ll get a complete error, but that also means that it’s really hard to tell you how many records are in our database when theoretically, you know, any email address ever at least any B2B email address ever could be, um, could be a candidate for enrichment.

John Kosturos:
Yeah, I think that’s a very unique approach. And, and I think it’s, it’s, it’s refreshing because, you know, I interview all a lot of data vendors and I see the landscape in a lot of them, you know, buy information from each other, slap it in a big file and cross reference the file to try to do enrichment rather than doing the real time crawl aggregation and having any models set up in the back to make sure that the quality is there. I think that gives you guys a lot of flexibility and it’s a, it’s a pretty cool, um, it’s a pretty cool strategy.

Ashley Taylor:
It does. And I think that that, you know, one of our value props too is the ongoing enrichment. So people get promotions, companies grow, companies raise funding funding, um, data can go stale. And so with our customers, we offer not just, you know, enrichment at the moment that you implement Clearbit, but an ongoing every 30 day refresh. So that data is never more than 30 days old. Um, and then of course, enrichment upon creation of a lead or a contact or an account.

John Kosturos:
So can I ask about that? Actually? Um, do you, if I’m a customer, do I pay one time for an enriched person? Uh, and then again and again as a refresher, do you have a motto where you pay once and you get the refreshed as long as you’re a subscriber?

Ashley Taylor:
Yeah, absolutely. So, um, we are a SAS platform, so you’ll, you’ll sign up for the year, um, and that will include keeping your database up to date, uh, every 30 days. Um, so you know, there’s a little bit of nuance to it, but typically pricing will be based on the size of your database. Um, uh, so that we can make sure that we can do things like offer, um, ongoing enrichment.

CLEARBIT LOOKS UP DATA IN REAL TIME – charge by database size – Part 2

John Kosturos:
That’s also really cool. So because you do size of database, you don’t necessarily have to worry about how many enrichment calls you’re going to make. If you’re a customer, you can kind of use it wherever so that you can get the best, uh, value. I think that’s cool. And so if you’re using RingLead and you enrich a web form with RingLead and that data makes it into Salesforce, then does your tool pick it up because it recognizes that enriched ID or is there like a unique identifier where then your system can pick it up and make sure that that’s always in that refresh cycle?

Ashley Taylor:
Yeah, I think, I think it would pick up what you’re asking with our Salesforce integration, every contact, every lead and every account will be enriched. Um, so while you could work with an orchestration platform like RingLead to be able to do this in more sophisticated ways, to be able to do things like pre-assigned territories, do lead scoring, making sure that your routing is, um, you know, is accurate and going to the right reps. Once the lead hits Salesforce or the contact or the accounts, um, the Clearbit package will automatically enrich it. Now it may already be enriched because it’s gone through RingLead, which is also integrated with Clearbit. However, if for any reason it’s not, um, we, we don’t need any sort of unique identifier to say that this is a clear, friendly record. Your CRM only works if everything is accurate and up to date.

John Kosturos:
Yeah. I guess that goes back to the point that you’re in. Just enriching everything and not like, I’m not scared that I have to pay for another credit or something. That’s, that’s,

Ashley Taylor:
yes, exactly.

John Kosturos:
Um, do you offer any other services outside of providing data to the customer?

Ashley Taylor:
Yeah, we absolutely do. So the Clearbit platform empowers our customers to operationalize data. So for example, serving personalized ads to target accounts based on website behavior or alerting the team when a prospect that they’re working with visits. Um, so I think historically we’ve been seen as a very tech forward data vendor and that’s certainly still true. But as our company’s evolved, we’ve started building our own product so that you’re not just using Clearbit in other systems like your CRM or your marketing automation or, um, you know, your, your orchestration platform like RingLead, but also allowing our customers to, um, again, to be their growth engine and let them immediately take meaningful action based on, uh, you know, coming from a place of data first. So understanding who’s visiting by the IP address and allowing them to then take action on those intent signals.

John Kosturos:
Very cool. So, uh, earlier in the call we, we mentioned Alexa ranking and I, you know, and I enriched data with Clearbit. I love seeing the, uh, Alexa rank of the companies or people at companies that I’m enriching. And so I’m wondering, I know that the Alexa 1 million is publicly available. It’s, I hate working with files. Do you guys, when you’re enriching the Alexa score onto a record go deeper than the Alexa 1 million?

Ashley Taylor:
Yes. Um, I don’t know if we have a cutoff, but I’ve definitely seen much, much, much higher numbers than 1 million.

John Kosturos:
Wonderful. Um, yeah, we, we recommend all the time that customers, because we focus a lot on tech companies as well. And, and, um, understanding the Alexa rank is, is a big part of the analysis for ideal customer profile. Um, it can even be in the routing rules, right? Like a company could be 10 million in revenue, but being the Alexa, you know, 1 million and you maybe want to route it a little bit differently. I think that’s a, a very cool, uh, data point.

Ashley Taylor:
I go for it. I was just going to say I completely agree. We actually using our own Clearbit data, um, we have reasonably embarked on a very, very in depth, uh, journey to understand what our ideal customer profile is and what our most successful customers look like versus those who we see are less successful. And you know, with, with a few basic assumptions like they’re a B to B company, you know, they, they sell into, uh, into geos with that shared alphabet. Um, Alexa rank is actually the strongest indicator for us, um, of whether or not a customer could be successful. Um, so it’s, I think we’re starting to see more and more companies use that as a parameter for routing, for ICP analysis. Um, and, and that, that resonates with what we have found to be true. We very much eat our own dog dude. Um, and everything that we worked on an understanding our ICP, what was powered by Clearbit and we found Alexa ranks be incredibly important.

John Kosturos:
Yeah. One customer that we both worked with in the past, they won’t mention their name. They, uh, they really use the Alexa ranking. Uh, um, and they had us do an exercise, uh, pull the Alexa 3 million and see how many unique companies were inside of that, um, database because a lot of those high ranking pages are for like product pages or landing pages or blog posts. So like if you mash up the Electra 3 million, you end up getting like 60,000 total companies, which to me was wild because, you know, people are always spending so much time building their home pages and I’m like, you don’t need to do that. You just build awesome. Like funnel pages, landing pages, product pages, and pay for traffic to get there. Right. That was a pretty good eye-opener.

But, um, can you, uh, or actually, do you sell the data mostly for sales and marketing purposes or are there also cases where you sell to app builders and other, you know, just general use cases?

Ashley Taylor:
Yeah, great question. Um, historically it’s been sales and marketing. What we’re finding as, as part of the ICP analysis that I mentioned is, um, a lot, oftentimes our, our marketing use cases tends to make for the most successful customers. Not, not always true. Um, but there, there tends to be a pretty, pretty strong overlap in looking to Clearbit for marketing use cases. Like I mentioned for example, actioning website intense, um, over sales use cases of just, you know, enriching Salesforce data that that’s an important part of it. But I think for the, for the whole picture, um, you know, oftentimes we’ll see that marketing is involved as for, um, as for your question about app filters and other use cases, we do have, um, some strategic partners that incorporate our data into their product functionality. Um, generally we engage in when there is, um, when it is both a use case where Clearbit can add value to that partner’s offering. And we can also tell a bigger story and really win joint customers together. Um, and, and just ultimately start with it. Much like, you know, we have with RingLead start with the customer experience and work backwards to figure out the best ways to bring that to life.

John Kosturos:
Yeah, I’ve seen a, we use drift and I see the Clearbit off option inside of drift and you know, I think it’s a really helpful integration and I really think it’s smooth and you know, it does, it adds a ton of value. I mean immediately when somebody pops up in a chat if, if, if you know what company it is, it’s like popping up the logo. So I think it’s pretty cool.

Ashley Taylor:
Yeah. Thank you.

John Kosturos:
Um, can you tell us a little about how you guys use reverse IP lookup to pair person with business data?

Ashley Taylor:
Absolutely. So, uh, we actually don’t use reverse IP look up to pair person with business data. Reverse IP lookup is purely going to return company level data. Um, we call this our reveal API and we can resolve an anonymous IP address into a full firmographic and technographic company profile. Very similar to, if you try to pitch a domain via our enrichment API will return all the same data. But it will be company level only where the user, the actual person might come into play is um, using our enrichment API in conjunction with a form. So imagine that an anonymous visitor comes to your website, they don’t really engage in anything they click around and leave. That would be the reveal API, understanding the IP address and tying it back to a company. But should that site visitor engage with the form, once they enter their email address in the form, that’s where the enrichment API would come in and we can return the same full firmographic and technographic profile of the company as well as specific data points about that person in regard of their role. So we can return things like seniority, title, job function, um, to give you a picture of not just about the company that they’re coming with, with attributes like we talked about before of Alexa rank or funding or employee head counts, but also who that person is in the org. Um, so that you can make sure you get it to your right contacts, that they can have a more, I’m sorry, your right reps so that they can have a more educated conversation and, and better predict what pain points they might have.

John Kosturos:
Yeah, I think you guys have really kind of solved the problem a lot better than any of the other form builder technologies I’ve seen on the market because you emphasized really reducing the fields down to a single field on a form which is email. And then if the email doesn’t match against the real time crawl, um, then you’re gonna ask and progressively profile them for more information. But if the email does match, all the user has to do is fill out one field which increases number of leads submitted and then you don’t lose functionality on the backend. Like, you know, the routing, the, the ability to score and segmented properly because you’re actually filling that data in behind the scenes. So that’s a really cool feature. Anybody who is looking at Clearbit should definitely check out.

Um, do you find that your customers are more interested in firmographic or contact data or is it like kind of the same?

Ashley Taylor:
I think it depends on the use case. Um, I think that, you know, if a lot of times with the sales use case, the contact data will be incredibly important because these are the people that are actually going to be having the conversations with the sales team. Um, with the marketing use case. That’s, that’s certainly also important for, for, you know, remarketing and email nurture and, and email personalization. Um, I think that where we’re company data becomes available is for lead routing and territory assignment. And then for things like website personalization or, uh, or chat personalization is a huge, huge use case. Conversational marketing. Um, and then just understanding things like, like I said before about the ICP analysis. Um, so it depends on the use case, but I think that both are generally pretty important.

John Kosturos:

Yeah, I would say so as well. Um, have, are there any specific attributes in your data catalog that have traditionally been the most popular for you?

Ashley Taylor:
Probably so we, um, we, we turned out some nickel and dime by saying, Oh, you want this attribute but not that one. It’s just you get the full payload. Um, but I think that the ones that we tend to see ourselves and our customers use the most to operationalize, um, would, would sort of be what you expect, right? It would be the company name as well as things like employee head count, Alexa, rank funding raised revenue, location. Um, and then at the person level, um, you know, their, their job function, their seniority as well as, um, we, we haven’t alerted someone leaves their job, um, that we can typically surface long before they update LinkedIn. Um, so I think, you know, the, those are some of the ones that I see operationalized most often, but I mean we’re returning over a hundred data points per contact that we’re enriching. So, um, there’s a lot that you could add that you could do. Um, I will say if, um, where we haven’t seen things, excuse me, go as well as B to C companies. Try to like do a weird hack to get some social data from our API. You know, in that case it’s probably better to just use a B to C provider. Um, but you know it with the B2B use case, you get the full payloads so you’ll, you’ll have a lot of options to choose for how you want to operationalize.
companies are investing more in finding the right customers that will have lifetime value”

John Kosturos:
That’s awesome. And have any of those attributes become more popular during this pandemic or have you offered any new type of data to, you know, help with anything going on?

Ashley Taylor:
Yeah, I think, I think it’s less that we’ve seen certain attributes become more popular and more that we’ve seen them used differently. So having a really full robust data backed picture of who your customers and your prospects are can help teams become more efficient, help teams, make sure that they’re only spending ad spend on those leads that are most likely to be the best fit and have shown the strongest buying signals. Make sure that you’re only investing in those opportunities that are most likely to give you the highest lifetime value. And so I think that, you know, as far as I’ve seen, I don’t necessarily know that the importance of attributes has changed. I think it’s just the way that they’re operationalized. It’s going from, you know, grow at all costs to become more efficient, become more conservative, figure out how we can, um, you know, be most effective with fewer resources.

John Kosturos:
Yeah. I’m seeing kind of a similar thing is that, you know, during these times it’s less about demand gen and getting in front of people and it’s more, it really is that spring cleaning raw, okay, let’s bring it back. Let’s clean it up, let’s find out where we really should target the business, let’s get better focused. Um, so in a way that data almost becomes more strategic. Yes. During a time like this because you know, people outside of just that normal demand gen unit start to take notice of the information.

Ashley Taylor:
Yes, completely agree.

John Kosturos:
Okay. So the last question, I think you, you gave us a, uh, an answer, but you said about a hundred or over a hundred. So how many data attributes do you have in your catalog? And it can be a ballpark figure.

Ashley Taylor:
The ballpark figure would be a little over a hundred. Um, if you actually go to our listing on the RingLead data exchange, I think, uh, your team has listed out every single one of them. Um, you can also go to clearbit.com/attributes but yeah, it’s, it’s a little bit over a hundred if you include, um, you know, all the firmographic, all the technographic and all the, uh, you know, job role, functions, seniority, uh, data points that we return.

John Kosturos:
Okay. Wonderful. Well, I really appreciate you coming on with us today. Um, I think you’ve given us a wealth of information and I’m clear it’s got an amazing solution. Um, they’ve got amazing technology and amazing team. Um, Ashley and her team are very knowledgeable and, and we’ll make it very easy for you to be able to connect with them. Um, but we really enjoyed having the conversation, having you on the show today. So thank you so much.

Ashley Taylor:
Thanks for having me, John.

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