Infer blog – Q&A with Bombora Co-Founder Mike Burton about intent data

There’s a lot of buzz in the marketing community around 'intent data' — and following an article on this topic on VentureBeat the team at Infer continue the discussion with Mike Burton.

Infer: It seems like the place that 3rd-party Intent data has gotten the most early traction is with email personalization and targeted advertising. Can you explain that use case?

Enabling programmatic targeting compared to email is relatively simple. We build targetable sets of cookies that have very high consumption against specific B2B topics. We also create account-based segments, which plays very well together with predictive.

Email is trickier, because Marketing Automation is built to market to contacts, and the monitoring of the B2B web mostly takes place on a company + location level. So, we created a product called 'Frog DNA' (a Jurassic Park reference), which looks at each contact’s company, location, and department and appends fresh intent data to every record every month. If we cannot use company level data we’ll fill in the gaps with overall B2B topics that are surging across broad topics like tech, sales/marketing, etc. Marketers then use that data to reactivate leads, alter nurture paths, etc. Probably my favorite use case is aggregating all of the most popular topics and using it to create relevant new content with a data-driven approach.

Infer: Can you share a customer success story that highlights how companies can measure the ROI of Intent data?

We’re always measured by lift in engagement. Whether it’s email, site personalization, inside sales, content creation, or advertising, the use of intent data is measured based on the uplift in response. For example, one of the publishers in our cooperative is Forbes, and they use a partner of ours called MOAT for campaign analytics.

Forbes was running a cloud computing-related campaign for a B2B marketer, and through MOAT we found out that when Forbes showed the ads to users Bombora classified to have intent on cloud computing, the campaign drove 1300% more engagement than average.

Sometimes it sounds like hyperbole, but when you consider that historically we’ve only been leveraging our own first party behavior and now we can harness all of the content consumption from the B2B web, it’s easy to see that we’re really onto something.

Infer: Can you explain your taxonomy? What is the process that goes into taking billions of activities and bucketing them into different topics?

For every interaction we monitor, we’re listening for 2,300 granular B2B topics. We will assign up to 10 of the 2,300 topics to every interaction, and we score the prevalence of each topic to each interaction.

So, for example, we might monitor a user reading an article, and resolve that the article is mostly about firewall and intrusion detection, but also tangentially related to security management, internet security, and malware. We update the taxonomy every quarter almost exclusively through customer requests. Over time we expect to track closer to 6,000 topics, as we scale coverage across more information sources.

Infer: In Infer’s eBook, we referenced the big three intent data providers, including Bombora. How would you tease apart the players in this space?

Bombora is a data aggregator, and IDG and TechTarget are publishers, so it’s difficult to compare. One way to think of it is that all of the individual publishers are like the banks, and we are like FICO. We’ve created a co-op of 50+ premium B2B media companies, including 2,500+ B2B sites, across which we monitor over five billion behavioral events and associate those with 1.4 million companies and over 400 million global users (cookies). We organize behavior across all of the sources, and then we activate it for B2B sales and marketing teams.

Infer: Over time, third-party Intent data is going to get better and better. What breakthroughs will we see over the next two years?

It’s a boring answer, but it’s all about coverage and scale. With that comes innovation challenges around language processing, tag deployment automation, etc., but from a macro level our role is to consolidate as much of B2B’s behavior as we can. It is the application providers and the marketers themselves that will drive innovation around what to do with the data, and that process is really just starting.

This article first appeared on the Infer blog.