Last week I joined a panel of intent data experts and marketing technologists for Inverta’s webinar, “The ‘Work from Home’ impact on intent data: What you need to know about intent data and the shift to remote work.” What ensued was a lively and informative discussion—among and between both the panelists and the audience.
Below are my responses to the questions that provoked the most spirited discussions, which have been lightly edited slightly for clarity and flow.
Many in the community are concerned that intent data is going to be less accurate or effective now that people are working from home. Can you describe how the move to remote work has affected the intent information coming in?
I’d argue intent data is more effective and valuable now since more companies are going to the web for their research to make up for the in-person events they’re missing. Of course, we won’t know for sure for another couple months. We have seen a general uptick in overall web research activity, but what companies are researching and the way they’re researching is changing. And this has resulted in a drop in actual intent signals.
Obviously, topics around healthcare, news and mobility are all way up, and this trend isn’t necessarily indicative of intent to purchase. Further, the cancellation of events has pushed buyers to get their information from different sources (often online). This, in turn, impacts the buyer-journey baseline against which intent signals are often measured. So, it’s requiring users of intent data to adjust the ways we analyze the data we’re seeing.
For example, when looking at the intent signals, we should be thinking in terms of relative differences between targeted accounts when prioritizing them—that is, identifying which company’s intent signals have increased the most against their own historical baseline—rather than simply adhering to pre-set thresholds to trigger engagement.
Further, when prioritizing accounts for various use cases, it’s a good idea to start analyzing various types of intent data to identify which companies are simply still “in play.” This requires layering in intent feeds that can track whether your target accounts are still actively marketing, hiring and launching products. Intent signals from public web sources can be important in this regard. As Tukan Das, CEO at LeadSift, recently told me,
The most important thing marketers need to consider is ensuring their ideal customer profile (ICP) and target accounts are not severely affected by the current crisis and still doing business as usual. To be effective with their targeting strategies—on top of looking at behavioral intent signals—marketers need to incorporate additional signals to see if companies are still growing their team, actively running paid media campaigns, executing marketing strategies, actively deploying product features etc.
Overall, the data isn’t any less accurate, but rather the work-from-home circumstances we’re in requires us all to tweak the way we understand intent signals and the conclusions we draw from them.
Are you seeing any changes with different types of intent data (e.g., co-op, exchange, public) or upticks in one type or another since the WFH phenomenon? Any other interesting trends?
There are numerous types of intent data, and they can work quite differently from one another. My firm, Intentsify, is in a good position to compare and contrast what we’re seeing in all the various feeds, since we work with a lot of various intent data providers to synthesize multiple signals into a more precise, holistic few of the market. As mentioned before, we’re seeing more research across the board, but with important nuances.
In the exchange data, we’re seeing an increase in overall research, but fewer intent signals attached to specific companies in North America and EMEA due to those who can’t log in via VPNs. Keep in mind, this mostly affects smaller businesses—typically those with fewer than 500 employees—that don’t have VPNs (IP matching is down about 25% for small businesses and around 10% for mid-market businesses).
As far as content consumption around specific topics is concerned, we’re seeing dramatic increases in the expectedly impacted categories, such as virtual environments and mobility (+192%), while B2B categories like data storage are only slightly up, relatively speaking (+36%).
Public web intent data, such as that from LeadSift, hasn’t been affected from a tracking standpoint since it doesn’t rely on IP matching. Here we’re seeing the same topic trends we see in the exchange feed—typical business-related categories like data management platforms and business intelligence are relatively flat or slightly down (+12% and -5%, respectively), while there have been huge jumps in activity around categories such as tele-medicine (+413%) and unified communication (+628%).
Technology review-site portals like G2 are showing the same topical research trends. All tech around communications (audio-conferencing, video-conferencing, webinar, virtual whiteboard) and healthcare (tele-medicine, HIPAA-compliant messaging) are way up. But, it’s not just these health and communication topics that have increased. G2 recently stated the occurrence of “massive traffic surges of 50%-500%” due to event cancellations causing buyers to do more research online.
With regard to co-op data, Bombora is seeing the same increase in content consumption around the categories of healthcare and a relatively stable consumption of content around technology- and business-related topics.
Generally speaking, it’s a good idea to look at various intent data feeds, which allows you to corroborate the signals coming out of any one individual feed.
Have you seen any interesting, new, or encouraging trends since the move to remote work began?
Beyond the fact that research is actually up overall (though intent signals have been dampened), what I find most interesting is the strong rebound of intent signals coming out of APAC. Between January and early April, intent signals in APAC jumped more than 200%. This could, optimistically, be seen as a harbinger of a quick economic rebound in North America and Europe. But, I’m hesitant to draw that conclusion without further evidence.
Are you seeing more research but less traffic to company websites?
We haven’t seen any sweeping changes here. Of course, it really depends on what marketing teams are doing. Those teams reinvesting event- and field-marketing budgets to digital channels (which is a good idea) are obviously going to see greater increases in first-party web activity.
When you think about intent data and what’s possible with integrating it into some of the more standard types of marketing programs out there—where do you think the biggest opportunities are?
I strongly believe the biggest opportunity for marketers lies in first solving two common intent data challenges:
These issues are, in my opinion, largely owing to a dearth of thought leadership content and education geared toward B2B marketers. The prevailing sentiment about intent data is that it’s simply a tool for identifying targets for account-based programmatic campaigns. It’s certainly valuable here, but there are many more use cases.
Leveraging intent data for account-based lead generation often results in a significant, quick win for demand gen teams—especially now that in-person events are out, and teams need to find new sources of demand.
Lesser known, but always important, is leveraging intent signals to inform your message selection. For example:
These all help to create meaningful experiences that increase performance throughout the demand funnel.
And don’t forget the customer success use cases. Though not necessarily a marketing focus, intent data can be used to effectively prevent churn and identify opportunities to upsell or cross-sell current customers.
The problem is most B2B marketing teams don’t know where to start when they invest in intent data. There’s so much you can do with it. That’s why it’s important to lay out a strategy in advance, and one that doesn’t try to boil the ocean. Rather, the key is to take an incremental approach to leveraging the data for differing use cases throughout the funnel.