How do businesses use buyer intent data to increase the number of sales appointments they set by 6X?
This week on The Inbound Success Podcast, LeadSift Founder Tukan Das breaks down the topic of buyer intent data and provides the best explanation I've ever heard about what it is and how companies can use it to grow the number of sales opportunities.
From who buyer intent data is right for, to where it comes from, what type of data you can expect to receive, how companies are using it, and the results they're getting to how much it really costs, Tukan covers it all in this not-to-be-missed interview.
This week's episode of The Inbound Success Podcast is brought to you by our sponsor, IMPACT Live, the most immersive and high energy learning experience for marketers and business leaders. IMPACT Live takes place August 6-7, 2019 in Hartford, Connecticut, and is headlined by Marcus Sheridan along with special guests including HubSpot Co-Founder and CEO Brian Halligan, world-renowned Facebook marketing expert Mari Smith and Drift CEO and Co-Founder David Cancel.
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Some highlights from my conversation with Tukan include:
LeadSift leverages buyer intent data to help B2B companies understand who is interested in purchasing their products or services.
Tukan believes that buying intent in general is the most important unit in digital commerce.
Buying intent can be measured from online and offline sources and is basically a probabilistic score that indicates the likelihood that a person or company will purchase something.
LeadSift gathers buying intent data by crawling the entire internet and looking at public posts for "signals" - where people are mentioning specific things that LeadSift's customers want to track.
Signals can include a variety of things such as keyword mentions, competitors mentions, conference mentions, and more.
This process is automated and done at scale, and the data is then fed back into LeadSift's data engine and ranked.
When you use LeadSift, you get a ranked list of accounts along with the key contacts that you should be going after because they are the ones that were showing the intent signals.
One common use case for buyer intent data is with account-based marketing campaigns.
Another use case is running audience match ads on Facebook or LinkedIn targeting the buyers that have shown high intent.
There are many types of signals that LeadSift can use to generate buying intent data, but working with their customers they have discovered that signals relating to keywords perform better than signals relating to competitors.
Buying intent data is useful for B2B companies with 50 or more employees and with average deal sizes in excess of $10,000 a year.
Buying intent data is priced starting at $1,000 a month.
Resources from this episode:
Save 10% off the price of tickets to IMPACT Live with promo code "SUCCESS"
I'm your host, Kathleen Booth. Today, my guest is Tukan Das who is the CEO of LeadSift. Welcome Tukan.
Tukan Das (Guest): Hi Kathleen. Nice to be here..
Tukan and Kathleen recording this episode together .
Kathleen: Great to have you. Can you tell my audience a little bit about LeadSift and yourself and what the company does?
Tukan: Sure. My name is Tukan. I'm the CEO and co-founder of LeadSift. LeadSift is a sales intelligence platform that helps other B2B technology companies identify which accounts are actually looking for their solutions at any given time. That's the 30,000-feet view of LeadSift.
One thing that I'd like to add is we have been working on LeadSift for about six and a half years. Our mission at LeadSift, and we have had a few pivots, but our mission at LeadSift has always been the same.
It's around mining publicly available data to predict when a company or a person is looking to buy another product, whether it's a software product or a physical product or something like that. That has been our goal at the company, and in its current iteration, we are helping other B2B technology companies identify and predict which other companies are potentially going to buy their solution.
Kathleen: That's interesting. Coming from the world of marketing, there are plenty of tools available to identify when an individual contact is interacting with your website and showing signs of purchase intent, but it sounds like you're talking about even outside of that, correct?
Tukan: That's correct. What you mentioned is that's more on the first party intent when someone's coming to your website, interacting with your content, downloading the data or filling out a form. What we focus on is the outside world where they're having interesting conversations, which some of them could be potential signals of buying indicators. Those are the ones that we try to pick up and use as predictions.
Kathleen: Now at the risk of getting into the territory of jargon, is this what is commonly referred to as buyer intent data?
Tukan: It is. At a high level, yes, it is.
Kathleen: This is interesting to me, and I was excited to talk to you about it because I have been hearing lots of people talk about this lately. I feel like it's the newest hot buzzword in the world of marketing, but there definitely appears be a lot of confusion around it, and so I would love it if maybe you could just start by demystifying. Every time I've heard somebody talk about this, they say there's all this publicly available data, and they mine it, and then they tell you who's out there.
What Is Buyer Intent Data?
Kathleen: I think the question I've always had is I want to understand how that really works. What is that data? How specific is it? Where does it come from? Is this GDPR compliance, all the questions that probably you get from of marketers? Maybe you could break that down.
Tukan: Absolutely. I have a interesting philosophical view about buying intent. I personally believe buying intent in general is the most important unit in digital commerce. Basically, buying intent, what it means is identifying a customer in the journey of them buying a product. It is basically a probability of assigning a probabilistic score to a company whether they're going to buy your product or a product. That's all buying intent means.
Now in reality, buying intent is generated both on online sources and even offline sources. It could be someone coming to your website and requesting a demo.
That's a very strong signal of intent, or someone picking up the phone calling you or someone you meet at a coffee shop saying, "Hey, I want to know more about your product, buy from you."
They're all signals of intent, but in reality, a lot of those signals are private to you and your own company, but that doesn't constitute the entire word buying intent.
To reach the scale, you need to pick up signals that are happening on the outside world, but the reality is in a B2B setting, unfortunately, no company goes and waves a flag and says, "Hey, I'm looking to buy a new database or a marketing automation software."
No one talks like that. Life would have been a lot easier.
Kathleen: Well, it would be easier for marketers, but it would be hell for that buyer.
Tukan: Depending if there could be a way to manage the number of requests and all those things. In the absence of that, everybody who is in the buying intent space, what they are trying to do is they're trying to come up with different proxies or signals and then combine all of them to make that prediction of this company likely to be buying a solution.
As with any prediction engine, it can never be 100% accurate. It is a prediction. This is something that we tell all our customers, and I want to clarify this.
I think there's a big misconception about buying intent that it is sort of like a silver bullet, "Oh, you told me this company is good market, 100% they're going to buy." No, they are no. It never works that way. If we could predict every company that was going to buy someone's software, I'd be a lot richer.
Kathleen: I was going to say that we couldn't afford your services.
Tukan: There you go. There you go. I'd be charging money to come into this podcast. With that being said, everybody is trying to look at these different proxies.
There are a few different ways of looking at buying intent. Every company in the space has their own definition. The way I look at it or we look at it at LeadSift at a high level is there could be multiple different signals.
A signal could be if we see someone engaging with my competitor on anywhere that we can publicly get, that could be a signal of intent.
If I see someone engaging with a complimentary company, that could be a signal of intent. For example, our partners are Marketo, Salesforce or even Outreach and SalesLoft. We don't compete with them, but if you see someone using that product or engaging, showing interest about that product, that gives us an indication that they have a tech stack and they are showing interest about outbound marketing, so that could be interesting to LeadSift.
A signal of intent could be someone researching or reading up on topics like account based-marketing. That could be a signal of intent.
A signal of intent could be someone attending a specific event or a trade show. Those trade shows could be big as Dreamforce. It could be Sirius Decision Summit, or it could be niche events like FlipMyFunnel events that are happening or a webinar that is happening. If you're engaging with that content that the webinar's putting out, chances are this is top of mind for you. You might or might not be in the market right now, but you're more aware of this topic.
A signal of intent could be someone growing their team. If I see someone who's hiring for a head of demand gen or someone hiring a lot of SDRs, chances are they are investing on demand generation and outbound marketing is very high.
That's a good point to be. If we see someone announce a new product or launch a new partnership that might need a solution that we are doing, that could be a signal of intent.
Basically, I think there is this myth or misconception around this black box approach around intent is like, "Ooh, we figured out from these publishers or whatever that these guys were researching about this topic, and that's why you should go after them." I think it's a lot simpler than that.
It could be boiled down to all these different signals combining them and then coming up with a final score which are a probability saying, "These are the companies did these different things, and that's why they are more likely to be interested in your product right now." I don't know if I answered that question.
Kathleen: No, those were actually really good examples.
I guess the question that immediately then springs into my mind is you gave specific examples of if I'm engaging with a competitor or attending a certain conference or researching a certain product, and you qualified your definition of buyer intent as drawing from publicly available sources. What I'm trying to wrap my head around is what, and maybe this is the secret sauce, but what are those publicly available sources of information that reveal that data?
Where Does Buyer Intent Data Come From?
Tukan: Exactly. To give you an example, let's say you are interested in tracking a competitor or a specific partner of yours, and anytime you see someone engaging with them, that could be an interest. What we would do is we would look at the competitors that companies that you're interested tracking all their digital channels, whether it's social blogs, their forums, their YouTube channels, anything that is out there, and we would see when people are commenting, asking question or anything about them on those channels or on Quora or Reddit, ProductCon, Twitter, LinkedIn, anywhere they're mentioning something about that company or maybe they posted a webinar and they are sharing the link to the webinar, which maps to the domain of the companies.
That's a signal. That's how we would figure it out. The way we do it, and there is no crazy secret behind it. If in reality all of the data that we're getting is public as I said, if you had 10,000 interns or researchers that are annually going over the entire internet, they could get the same exact signals. We just do it at scale and automate the whole process.
Kathleen: You're basically finding a way to scrape all of that and then process it-
Tukan: That's it.
Kathleen: ... and put a formula behind what is a meaningful level of interaction.
Tukan: Absolutely. Yes.
Kathleen: That is a great explanation. That is the best explanation that I've heard yet about how this actually works. I feel like sometimes the people who are in the business of buyer intent data almost intentionally make it seem like this black box, but thank you for clarifying that.
Tukan: Not a problem. I think there is a problem. I'm actually writing a LinkedIn post about it. I think there is a challenge there where on purpose, there is this misconception and there's a level of complexity that's added when it's not needed. Maybe they do hide some things. I don't know, but for us, it's purely crawling. It is literally crawling the entire public works for you at scale, and then getting this information.
Kathleen: It makes sense. I agree with you that there is a problem because I think that the natural instinct when you feel like something's deliberately being presented as mysterious is either you don't trust it. Like, "Are you getting this data from an untrustworthy source," or that it's possibly too good to be true. I feel like a lot of people have shied away.
Now, you go out and you crawl all of these sites. You look at all the interactions that are happening. You're able to synthesize that into meaningful insights for your clients.
What Kind of Data Is Included With Buyer Intent Data?
Kathleen: If I am somebody who is purchasing buyer intent data, what does that look like? Am I just getting a list of company names? Am I ever getting down to the individual contact level? How granular can you get?
Tukan: No, that's a great question. Because of how we get the data, how we collect the data, we are probably the only company in the entire intent data ecosystem that can provide intense signals the level of a contact.
When we give you an information, we would actually tell you, "You should go after Dell as a target account because their head of marketing was recently engaging with your competitor's content."
That's what you get. You get a ranked list of accounts along with the key contacts that you should be going after because they are the ones that were showing the intent signals.
When we, I guess, score or rank these accounts, we take into account who was the person that was showing interest in an IT services solution, a head of marketing, showing interest about the topic is okay versus if the IT director showed an intent signal. Their score will go up, so we incorporate all of that and present that data to you.
Kathleen: You mentioned account based marketing earlier, and I wonder when you then return that data, you're able to get to the individual contact level. Let's say you mentioned Dell. Let's say there's 10 different influencers or decision makers at Dell who are showing intense signals. Are you able to package that together and say it's not just like a laundry list and there happens to be 10 people from Dell somewhere in the list? Is it, "Dell is the company. Here are the 10 people?"
Tukan: That's exactly it. The way we presented it would say, "Here is Dell. These are the 10 people, and these are the different things they did."
Kathleen: That's really interesting. I can see that being very useful because I've spoken to other companies that have pitched me on buyer intent data, but really all they're selling is a list of company names. It's better than nothing, but I wasted a lot of time marketing to the wrong contacts in those companies.
Tukan: You asked a question earlier on about GDPR compliance and things like that. There is a confusion in the market because one of the things that clients tell us is, "How do you get contact level data?" If someone saw an ad on Forbes, they have an IP data that you reversed mapped to a company, but how the hell do you know who that person was?
That's how we are able to provide not just Dell but the key contacts that you should be talking to. All of this data is publicly available, so if your SDR was manually researching, he or she would have found this information. We just made it that much easier for them using technology.
Kathleen: That makes sense. That was a great explanation. Thank you, very, very helpful. Now, if somebody is hearing this and they're thinking, "Okay, this is really interesting," can you talk through some specific use cases of how companies might use this kind of data to fill their sales funnels?
Use Cases For Buyer Intent Data
Tukan: I'll give a couple of examples, one more from a marketing perspective, the other more from a sales perspective how it can be used.
One of our customers, they're fast growing in endpoint security space, highly competitive. Everybody in that space is super well funded, and it's a massive problem. One of the things they did was they had a list of target accounts that they wanted to book meetings with, basically try to get engagements on. They came to LeadSift, and they gave us that big list of target accounts along with it.
They gave us a list of keywords and competitors that are of interest to them or topics. We work in this case was we were crawling the web picking up signals and contacts and pushing them directly into Marketo. A certain percentage of the signals were on target accounts that they were interested in during conversation into, and some of them were just green field or white field accounts or whatever they call them that fit the ICP but it's not in their target account list. We are pushing the data into Marketo, and they have it sync with Salesforce typically. That's the typical flow.
When we pushed it into Marketo, they score them. Once the score reaches a certain score, they pass it over to the SDRs to go ahead and try to book a meeting with the contact that we picked up on that target account. Not just saying, "Hey, go after Dell because Dell is showing interest or talk to these three people within Dell because they were talking about these topics that you care about." That's how they did.
I'll talk a little bit later about how they used interest in scoring techniques, but the result that they got was they had this started off with 100 accounts, target accounts to have discussions with.
Within three months because of this contact and the signals we picked up, they had meetings with 60 of them. That was great, and over a period of six months, they got... I forget the number. It's high six figure in pipeline that they generated from those 100 accounts plus the new ones we identified.
That's an example of how someone needs to think 10 signals into Marketo, push to Salesforce coupled with their account based strategy into booking meetings and creating opportunities from there.
Kathleen: That's great.
Tukan: One thing that we found out from them they were sharing was in the scoring mechanism, they actually found out when companies were engaging with specific keywords versus when companies were engaging with competitors, the key word engagement were actually giving them better results than competitors, which is interesting because my initial gut would have said, "If someone is engaging with my competitor, that's the hottest one I should go after."
They found it opposite. It makes sense, but after, I thought, "Maybe some of them might be already too far in the buying journey.
Kathleen: Too far down the funnel.
Tukan: Yup. That was an interesting thing, so they adjusted the score in Marketo accordingly based on the kind of triggers. The other thing they also did was they were also looking at how many unique people within one of those target accounts were engaging.
If one person engages three times, that's not as valuable as three people within the target they're gonna engage in one time each. They were using that because one person engaging multiple times might give you a false positive.
They might have some prior relation, but if three people engage or like x number of people engage with this same trigger events or competitors, that's a better signal. Those were some interesting insights that we saw a customer use our data from a marketing perspective and being very successful.
Who Is Buyer Intent Data Right For?
Kathleen: That is really interesting. Now, in terms of the types of companies that are using this data, it sounds like it is very useful for B2B companies and companies that have a high transaction sales values or considered purchases, if you will, where more than one decision maker is involved. Is that accurate?
Tukan: Yup, that's very accurate. In terms of our buyer persona, and when you look at our ICP and clients who have been most successful, so we look at companies in the small to medium sized enterprise, so 50 to 500 employees. Those are the ones. In B2B technology, 100%, and the other is their deal size needs to be meaningful. If their average deal size is, let's say, $1,000 a year, then they don't really need intent signals are even an outbound sales team, but if typically their deal size is at least $10,000, $12,000 annually, in that case, it makes sense for them. That's a sweet spot we have seen.
Then there is another group of companies that we work not directly but through our partners. Those are more the large enterprises, so those 5,000, 10,000 employees. You have the HPs and the Oracles and Adobes of the world where we work with our partners. In their case, they do truly a multichannel or omnichannel marketing strategy where they take our data. They would do media buys, contents indications, email nurture, and things like that, but our sweet spot is those 50 to 500 companies that are heavy on driving sales revenue pipeline and things like that.
How Much Does Buyer Intent Data Cost?
Kathleen: Let's talk about the numbers then, because I'm curious. If somebody is listening and they're like, "This sounds amazing. I need to do it," what should they expect to spend, and how is the spend calculated? Is it based on the number of leads you're delivering? How does that work?
Tukan: No. This is very interesting because it's not a cost per lead or ad spend or media spend type model. It's a purely subscription-based set up where you pay a flat fee, an organization wide license for your entire company, which is dependent on the number of triggers you're tracking. A trigger could be a name of a competitor or a name of a keyword or a topic or an industry event that you're interested in tracking. Based on that, they pay that fee and we push the data directly into the system.
In terms of exact dollar value, it starts at around $1,000 a month. It's not crazy, but that's the price point that we charge, and it's a subscription model.
Kathleen: Is there any general sense you can provide us to like if I'm spending $1,000 a month, what should I expect in terms of value?
Tukan: Absolutely. Absolutely. That number changes, to be honest with you, Kathleen, based on how niche or how broad they're targeting, but on an average, all our customers get around 200 signals, intent signals a week, so roughly 800 to 1000 signals a month. That's the average. Our model is not capped on the number of signals you get. Some of our customers get a 1000 signals a day. For example, if someone is attending an event or sponsoring an event and they want to track people that are likely going to that event, they might get 400 or 500 accounts a day when the event is happening, but on an average, I would say between 800 to 1000 signals every month on unique accounts.
Kathleen: I want to make sure I understand correctly. 800 to 1000 signals a month, that's 800 to 1000-
Kathleen: ... in full contact level?
Kathleen: Really, if you're saying that you started $1,000 a month, that's for all intents and purposes about a dollar per contact. I know you don't want to call it.
Tukan: No, but yeah. Sometimes you can do the ROI calculation if you do want to look at it that way.
Kathleen: I mean, to me that sounds like a no brainer. I'm not being paid to say this, but it sounds like a no brainer only because if I do Facebook ads or something like that, a $1 costs to acquire a new contact, and this is a much more qualified contact, I would argue, that's pretty darn reasonable.
Tukan: The way some of our customers would use the data and look at it is let's say you use it for a 90-day period, and in the 90-day period, that's a good enough period for you to then activate the data. One is us providing you the data. These are not inbound leads. Excuse me, you still need to nurture them, but assuming you ae following up with the data. Within 90 days, you should be booking 10 to 20 meetings, and then you can do the math from there on. Out of those 20 meetings you're booking, you should be having these many opportunities, and from there, they'll close. It's very easy to do the ROI from that perspective.
What Kinds of Results Can You Expect?
Kathleen: No, that makes sense. That's really interesting. Are there any averages in terms of results that you see your clients getting?
Tukan: Yup. Few things. This is another example that I thought of is from a sales perspective. We are working with a digital marketing agency actually out of New York. They're national. They obviously do Facebook ads and different ads and inbound paid to drive leads. Reference is a big thing, but outbound is also a channel for them to generate leads. What they were finding is the number of meetings that they were generating through outbound was trying down because the way they were doing outbound is as everyone does is by static list of companies that fit our criteria and just hit them.
They came to LeadSift to help them identify companies that are showing intent, potential companies that they can brand, I guess, in this case that they might be interested. They ran an email nurture campaign. That's what they're running.
On an average, they're getting about 6% of the people that they're reaching out to are booking meetings with them. That is a very, very high number of people that are booking. The industry average is less than 1%, so they have tripled the number of people they're having meetings with in a month using the intense string.
On an average, 6% is very high. That's of the outlier. This is not replies or positive replies. These are people that are actually booking meetings with them. On an average, we see... Assuming you have some baseline. You have an outbound process, whether it's email coupled with social and things like that.
The average is at least you have twice the number of hit rate or connect rate or meetings rate than. That's the average that we see assuming you have a baseline, you already have a process set up.
Kathleen: Well, and if you're not doing outbound sales, because there are plenty of companies that don't have really robust outbound sales programs, I imagine you could still take this data and create a custom audience for your paid advertising. You could do a look alike audience from that. There's a lot of different ways that if you didn't want to do direct outreach to the contacts, you could still pull them into your orbit in a subtler fashion.
Tukan: Absolutely. We are seeing people doing that Facebook custom audience, Linkedin ads. That's also one of the things is to do paid media to drive people in there. Absolutely.
Kathleen: Interesting. Wow. Well, that is really cool. I love hearing the details of how the sausage is made. It's the first time anybody's explained it really well to me, so I appreciate it.
Tukan: No problem.
Learn More About LeadSift
Kathleen: If somebody's interested in learning more about either the company and its products or about this topic, and they want to connect with you, what's the best way for them to do that?
Tukan: Couple of things. The best way is to go to leadsift.com. We have a pretty simple website. There's quite a bit of... We produce a lot of content and webinars and things like that, so do check it out.
Kathleen: I'll put the link in the show notes for that.
Just reach out to me. I'm deeply passionate about this whole idea of mining intent from unstructured web. I believe there is no single source of truth for intent. There's different ways to look at it. If you want to know anything more about LeadSift or just a general idea about intent-driven marketing and sales, hit me up.
Kathleen's Two Questions
Kathleen: Love it. I'll put all those links in the show notes. Now, we can't wrap up without me asking you the two questions that I always ask my guests. First of those is we talked a lot about inbound marketing on this podcast. Is there a particular company or an individual that you think is really killing it right now with inbound marketing?
Tukan: That's a good question. I think I'm going to give altruistically different answer. I think one company, one person that is absolutely killing it is Jason Lemkin with SaaStr. I think they are doing a phenomenal job with inbound marketing, creating content that startups find valuable from early stage to growth stage or scale up. Unbelievable content they're getting. They have podcasts. They have the SaaStr show. I think Jason has probably written 100,000 answers on Quora and things like that and his LinkedIn post. I think they're doing a phenomenal job with inbound marketing.
Kathleen: That's a really interesting one that I've not heard before.
Tukan: I thought so.
Kathleen: I might actually just then tweet Jason and see if I can get him to come on the podcast.
Tukan: You would be amazing because you ask any startup founders, CEO or anybody in a tech startup space, everyone knows about SaaStr. SaaStr itself is becoming the go-to conference for all SaaS companies to go, and it is all because of Jason creating content every day and they're doing a phenomenal job.
Kathleen: I love it. Well Jason, if you're listening, I'm coming for you.
Now the second question is the biggest challenge that I hear marketers talk about is that the world of digital marketing is changing at such a lightning fast pace, and it's really hard to keep up with current best practices, new technologies and developments. How do you personally stay educated? What do you do for yourself?
Tukan: Again, this also might be a different answer compared to what everyone else has said. Maybe because I'm not a marketer by trade. It might be a bit of a cheesy answer, but the best source for me to learn is actually talking to customers who are all marketers. When we talk to customers, we do the first five minutes of a sales call, we ask them. It's what's their process? What are they using? We get unbelievable amount of insights into what this entire world's looking like. They actually literally educate us, which we then use for other customers to get ourselves better and all that. That's one source that I think is phenomenal.
The other is actually, I'm part of a few groups in Facebook and LinkedIn. One of them particularly is called SaaS Growth Hacks. It's from early stage companies, super active. There, I get a ton of insights into latest marketing trends, cool hacks and crawl tracking stories or things like that that people are trying out. There's a lot of discussion. People ask questions. People comment. I skim through it at least once a day to get some cool insights into what's going on, what's working, what's not working, what to be aware of. Those would be my two big sources of learning about the latest marketing trends.
Kathleen: Those are good ones. I'm going to have to hunt down that SaaS Growth Hacks.
Tukan: Absolutely. It's a great Facebook group.
Kathleen: Good. All right. Well, there you have it. I will put the links for all of those things in the show notes.
Now you know how to reach Tukan if you're interested in learning more about LeadSift or buyer intent data. If you have been listening and you learn something new or you liked what you heard, I would love it if you would leave the podcast a five star review on Apple Podcasts. That makes a huge difference.
If you know somebody else who's doing kick ass inbound marketing work, tweet me at Work Mommy Work, because I would love to interview them. Thanks Tukan.
Tukan: Thank you Kathleen.
Kathleen: It's great having you.
Tukan: Same here. It was a pleasure.
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