What Google, Facebook, and B2B Media Companies Don’t Want You to Know
When I first heard about third-party intent data five years ago, I loved the idea. While I still encourage the use of this data source, I have a feeling the hype train might be steaming you off the edge of a steep cliff. To be sure, intent data should be one of many signals marketers use to identify when companies are in market. Other signals might include a job posting, a leadership change, a round of funding, new legislation, good or bad press, just to name a few.
First, what is intent data?
The Intent Data You Already Use
If you have a marketing automation platform — like Marketo, Oracle Eloqua, HubSpot, or Pardot — then you are probably using intent data. Intent data can include the email opens and clicks of your customers and prospects, the pages your customers visit on your website, the webinars they register for and attend, the e-books they download, their social likes and shares, and similar behavioral activity. Ideally, you are using this intent data, among other things, as an input to your lead scoring model.
Third Party Intent Data You Can Buy
Companies like Bombora and The Big Willow have arrangements with numerous B2B publisher sites to license this same behavioral data on those sites. Page views, email opens, white paper downloads, site search strings, and so on. You can select a topic area and get that data at the account/domain level, not the contact level. The basic idea is that if an account is more active around a topic, chances are they are in market for the solution. Sounds reasonable, right?
Intent Data Is Nothing New. Just Ask Google.
Search data is another type of intent data. Google doesn’t sell the data (as far as I know). They do let you bid for clicks, though, one contact at a time. The Google advantage is speed and relevance. As soon as someone enters a search, advertisements pop up. And those ads are specific to the person who did the search.
Unlike data from Bombora and The Big Willow, Google ties the search to the individual typing in the search string. Marketers can try to gain first page ranking through search engine optimization or pay for clicks through Google, Bing, or other search engines.
The weakness of Google search is that you have to bid for top ranking, and it’s pretty expensive, especially when you do the downstream math. Cost per click multiplied by the small percentage of people who fill out your lead form and multiplied again by the small number of people who convert into a customer. Acquisition costs in B2B can easily be $3k to $5k and more per closed-won deal. That’s fine if you’re selling a $100k product or a lower cost product with a $100k lifetime value. It’s not so great for most B2B scenarios.
The Truth Intent Vendors Don’t Want to Talk About
With the hype cycle at full throttle, maybe a little straight talk would help. First, we use intent data as an input into the predictive models we build. So we’re not against it. But it’s not a cure for cancer, the way some would have you believe.
Problem #1: Bad Fit
None of the intent data vendors or the publishers, social media companies, or search engine companies want you to ask yourself whether the people and the companies they work for are a good fit for your product or service. Let’s say someone really is in market for a solution. Does that mean your solution is the right one for that individual? Of course not. If you are marketing an enterprise CRM, for example, and you reach a small business who needs a simple CRM, then chances are there is not a good fit between the intent and your solution. In that case, your enterprise CRM sales person will likely waste time talking to that prospect. Worse, the sales person might convince the small business owner to buy the enterprise solution. Before long, you have a very unhappy customer and possibly an unprofitable customer, one who is posting negative comments on social forums and review sites and consuming lots of sales and support time.
So fit matters. A lot.
Problem #2: Decay Rate of Intent Data
Intent data has a short shelf life. If you don’t act on that behavior quickly, you’ll often lose the opportunity to do so. Google has built a $95B search business by understanding the need for speed. You do a search. You see results in sub-seconds. You don’t come back in a few minutes, a few hours, tomorrow, or next week. If that were the case, Google would probably be a small company.
And that’s the first big problem with third party intent data. The lack of immediacy. Do you know what blog posts or articles you read last week? I don’t. I read a lot of blogs and articles. Sadly, I don’t have a photographic memory. Some of the articles I don’t finish. Others are interesting but not actionable. A few can help me immediately and I may want to learn more. But I don’t remember specific blogs, unless they are unusually insightful. So referencing something I read a week ago (or longer) is not likely to be effective.
Still, intent data can help you figure out areas of interest so that you can be more relevant in future interactions. In theory, intent data can potentially reveal depth of interest, helping you with lead scoring. But interests change. Right now I may want to learn more about short-form video. Next week, my interest might be on email deliverability. Only a few of my passing interests turn into a bigger time commitment in which I go deep on that topic.
Problem #3: Invisibility of Individuals
Unlike Google, the intent data offered by Bombora and The Big Willow doesn’t tell you who the person or people are who have interest in the topic. Instead, you just know the account has an interest. Now, knowing the account has value, but not nearly the value it would have if you knew who the people were that a topic is engaging. So you are left with reaching out to people who may not have expressed the interest at the account.
Problem #4: The In-Market Fallacy
The big promise of intent data vendors is that these companies are “in market.” SiriusDecisions even validated the importance of this idea by creating a new funnel stage in the latest Demand Waterfall. Their Active Demand stage has no doubt inspired a lot of marketers to search for such data, and the intent vendors and a few large B2B media companies are happy to step forward.
There are several problems.
Problem #3a: No Intention
First, not all content within a topic has predictive value. You’ve probably read about lots of topics and never purchased anything related. Let’s say you are in marketing. If you read an article on how to write better email subject lines, does that mean you are looking for a new marketing automation platform? Probably not. What about if you read about how to do better lead scoring? Well, yes, maybe you are unhappy with your current lead scoring capability within your existing marketing automation platform, but not necessarily.
Last week, I read about a rich guy who owns an island with a landing strip for his private jet and helicopter. Sadly, I won’t be buying my own island any time soon.
Problem #3b: No Influence or Authority
IBM has about 376k employees. Most them, no matter what they read, have absolutely no influence on any purchase above $10. And the bigger the purchase, the lower the number of people at IBM who get to vote on what IBM buys.
Traditional media, social media, search engines, and demand side platform companies like Ziff Davis, Facebook, Google, and Demandbase don’t want you to spend much time thinking about that reality, but you should. You’re paying to reach that audience, regardless of whether they influence the purchase of your product.
Problem #3c: Late to the Party
For many products and services, it’s crucial to talk to the customer early enough to help shape the buying vision. Get in too late, and you are often responding to an RFP your competitor helped craft, an RFP that highlights your weaknesses relative to areas of advantage for your competitor. Obviously, there is intent. You just got there too late.
All these problems with intent data should not give you the idea that intent data has no value. It does. But it is only one type of signal in an ocean of signals that lets you know which companies are in market and a good fit. So use a broad set of signals, not just one.