Using Intent Data for Product Marketing

Oct 23, 2020 | Author Ed Marsh

Tl;dr - It's common for marketers to think of third party buyer intent data primarily as a demand gen tool. This leads to missed opportunities for data mining, and valuable and creative product marketing and content marketing insights as well.

Intent Data - Marketing Bonanza Beyond Demand Generation

It's common for third party intent data to be silod in the demand gen or ABM groups in marketing departments. 

This misses large opportunities for content teams, competitive marketing and product marketers to use data in effective ways which compliment traditional uses of intent data for marketing, and creative marketing use cases such as PR (predictive™ media scan).

Teams can use intent data creatively in various ways:

  • Track what kind of content competitors are publishing and monitor other aspects of their businesses
  • Track the major areas of interest among their ideal customer profile (ICP) to create content in response
  • Understand "share of engagement" as a compliment to "share of search"
  • Visualize market level trends (problem to solve, outcome to achieve, competitor engagement, job function and seniority, geography, etc.

Let's unpack these.

Track Competitors' Content and Operations offers the capability to closely observe target account / account-based marketing targets for a variety of signals which sales can use as conversation starters or trigger alerts. (This is similar to ZoomInfo's Scoops.) 

That same capability can be used for competitive monitoring. If a competitor is hiring for certain job roles, sponsoring events, recently funded, opening a new office (does anyone do that anymore!?), or publishing significant new content, for instance, you might want to know.

It's an easy campaign to build - but probably not one you'd want to automatically integrate into your CRM unless you created a custom object - perhaps "competitor insights" - that would let you surface and report on it.

This info is a perfect example of material of potentially great interest to your product marketing team - and essentially no value to your demand gen group.

It's a good example of why you ned to think creatively about how you configure and use third party intent data - and why specific key terms and competitors are so much more powerful than opaque "topics."

Understand Your ICP

We all think we understand our ICP pretty well. Personas and journey maps are increasingly nuanced and sophisticated, and often based on 3rd party research rather than assumption.

Nevertheless, we don't really know for sure what content is particularly important to them.

Solving for this requires a bit more creativity and experimentation.

The solution is to build and maintain an algorithm that tracks engagement with social and business topics beyond your normal business scope. While we don't know what we don't know, and therefore have to start with some guesses, it is possible to add and remove topics based on current trends, events and news.

This approach would help the content team, for instance, identify areas of active engagement among the ICP that are adjacent to the specific product/problem content topics they normally consider, and give them an opportunity to try some content designed to drive engagement and activity - maybe even active social shares - for awareness and branding purposes.

Stack Rank Your Industry Engagement

SEO folks sometimes provide share of search information to other marketing colleagues for its value in predicting market share changes. (Interesting article here on that topic.)

Share of engagement is another interesting way to look at a current view that might provide some future predictive ability.

How does that work? Again, it's a simple execution of purchase intent data that just takes some creativity of vision. Here's how you'd build that.

Build an intent data campaign that captures the relevant brand and competitor key terms and along with competitor domains, and details of your ICP. That narrow scope helps to ensure that the signals are indicative of meaningful engagement.

Then, as you aggregate the resulting signals over time, you'll be able to parse out the incidence of engagement, by competitor, to build a profile. Be prepared to be surprised.

Take it a step further and look at the job function and seniority that engages with each to discern differences in how they are perceived by the market.

Track High Level Trends

Markets evolve. The key problems buyers are trying to solve, the outcomes they're trying to achieve, the seniority level and composition of complex buying teams, and even the locations and industries of active buyers all shift over time.

But how can you observe that dynamically? Of course you could invest in extensive, ongoing market research, and that might be appropriate. But if that's not in your budget, or even if you want a quick, agile view of changes, intent data can provide that as well.

How? As with the other applications above, it's a matter of creating a campaign that looks at information with the right parameters and from the right angle. For instance, a simple pivot table of aggregated data from some months or years will let you observe changes (or consistency) in seniority engaging at different stages in the buying journey (as inferred from specific key terms that can be associated with stages in the buying journey), geographical distribution of engagement, and even industry engagement.

An interesting example of the latter was the observation by many companies that higher education activity surged throughout Q2-Q3 as colleges and universities looked at a wide range of tech solutions to solve problems with the sudden shift to remote.

Sometimes trends like this can be sniffed out via diligent feedback from BDRs and sales, and observation of form submissions and first party anonymous data. But dynamic analysis of large volumes of broad market data can illuminate changes more quantitatively.

Contact Details - The Rosetta Stone

If you've never thought of using purchase intent data for these applications, there's probably a simple reason why.

If you only have anonymous account level data, then it's really hard to connect the dots on many of these forms of engagement. You could track industry, and perhaps geography in some cases, but much of the insight comes from understanding job titles and function (and therefore seniority, etc.) 

And that requires the rare Contact Level™ Intent Data approach in combination with a solution that provides granular insight (specific key term, competitor, etc.) that allow you to make inferences about what happening.

Do you have the right intent data for the full range of applications that would benefit your business?



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