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Understanding intent in the era of work-at-home B2B purchase research

Posted August 25, 2020

Understanding intent in the era of work-at-home B2B purchase research

Posted August 25, 2020

Ray Estevez, Chief Data Officer, Anteriad

Regardless of how the COVID-19 pandemic plays out in the coming months, it’s clear that business is not going back to usual any time soon. Employees who once did all their purchase research from a business campus now work remotely, and B2B marketers need to identify and activate these new sources of purchase intent signals – no matter where they originate.

As I often say here on our blog, the essence of intent intelligence is sorting through billions of intent signal data points and finding meaningful patterns that map not only to businesses, but also to individuals within the buying groups that make major purchase decisions. That’s the idea behind our category-defining Relevance Engine™ Big Data analytics, and we constantly refine it to more precisely identify the context, weight and specific source of B2B purchase research activity.

And today, that means correlating business domains, device IDs, referring IP addresses and a host of other clues that identify exactly who is conducting the research, often from numerous locations.

In this post, I’ll look at the growing evidence that B2B decision-makers are going to work from home for a long time to come, and also discuss how Relevance Engine and its advanced Identity Graph use machine learning and Artificial Intelligence (AI) to map billions of intent signals to specific locations and contacts. I’ll also discuss some potential trends in intent signal monitoring that we’re watching as work-from-home becomes the “new normal.”

B2B purchase research comes home, for good

If you’ve been following the trade press, you’ve undoubtedly seen reports about how professionals have adapted, and even flourished while working remotely – even when local regulators have opened the door for them to return to a conventional office setting.

The data, while still preliminary, is pretty convincing:

And remember, these surveys are being conducted exclusively among people whose jobs can be done from home, which now constitute about a third of the U.S workforce, according to the U.S. Census Bureau.

I do need to note here: Not everyone has fully embraced the transition to work-at-home. Barclays recently made headlines when it said that, eventually, it does want its team members to return to the traditional workplace. C-level and executive managers have always gravitated to the higher visibility and almost immediate access to team members that comes with gathering all your employees in the same place.

And some traditionally conservative voices, such as The Wall Street Journal, note that many companies will need to invest heavily in cloud and other infrastructure tech if they are going to fully commit to remote network access.

But, all in all, work-at-home is a trend that’s here to stay, and B2B marketers need to adapt their tactics and technologies in this new reality

What work-at-home means to B2B demand gen

Obviously, building relationships over video conferencing is a new reality for many B2B marketing teams, but they seem to be adapting well. A quick online search will provide a wealth of tips on how to market when folks aren’t at their desks.

I particularly like this one at adExchanger that provides examples of how B2B marketing teams have modified their campaigns to generate interest at the top of the funnel in a time when you’re not likely to get your foot in the door at a more advanced funnel stage. Many marketers have switched resources to focus on video and other media that create a more immediate personal connection.

I’ll also note that adExchnager piece touts  the benefits of focusing on personalization within B2B buying groups to increase efficiency in B2B demand gen. That’s one of our core beliefs here at Anteriad, as well, and our Anteriad Marketing Cloud™ solutions are built around buying group modeling and contact discovery.

You can also find any number of advice posts on how to conduct B2B sales from a home office, when an in-person call is simply out of the question. (Again, our own CEO offers some great pointers here.)

The bottom line is that sellers are still selling, and B2B decision-makers are continuing to research purchases from home. And B2B marketers need technologies that gather and distill that research, across all digital channels, into actionable intent signal intelligence.

The power of Relevance Engine’s Identity Graph

Our proprietary Relevance Engine analytics filters through billions of intent signals generated from multiple channels – display, email, webinars, downloads, page reads and more – to identify and categorize online research activity. Its Identity Graph then uses advanced AI and other Big Data tools to map that activity to IP blocks and addresses, and eventually assign multiple intent from multiple locations to a distinct individual.

For example, we can look at an IP address that’s exhibiting a lot of research activity and know pretty quickly that it’s based out of, say, Long Island, NY. But we also can pretty quickly tell that it’s not originating from a known business address or domain. So, we make the assumption that this is someone’s home, or that it is a mobile IP.

Then, Identity Graph begins its detective work.

If it is a home IP, we may have seen it before, and hopefully the user has opted-in somewhere within our data network for access to a webinar or document. In that process, there’s a good chance that they’d indicated the company where they work, since that’s a vital piece of information for B2B marketers. We may simply see that the same IP has a repeated pattern of visiting a site or collection of sites, and we begin to search for more connective tissue to let us know who this person is.

Or, we may be able to match hashed emails to similar markers in the data stream. (At Anteriad, we adhere to all privacy standards, and that includes accepting obfuscated PII from our partners.) We might find a name, say Ray Estevez, that we can associate with the hashed record, and then find via LinkedIn that Ray Estevez works at Anteriad. Then we begin searching for a work email or business domain.

It’s all a function of the data we have, and we collect billions of intent signals. The more touchpoints we have with an IP address, the more confident we are the inferences and conclusions we draw. Ultimately, Identify Graph can determine a relevant business for the activity (we’re talking like 95 percent confidence), and in many cases it can map purchase intent all the way down to a B2B persona – even if the signals are generated from multiple locations, including a home office.

The future of finding

As more and more B2B decision makers work from home, the way marketing intelligence technologies like Relevance Engine identify and weigh their purchase research activity will also continue to evolve.

To date, our primary weighting factors have been the recency and frequency of the content consumption. How many times in the last four weeks have we seen you researching cybersecurity, for example. Our Anteriad Marketing Cloud maps individuals who exhibit intent activity to buying group roles we identify via our massive B2B contact database. This matrix of information – who is exhibiting intent and what role do they play in the purchase decision – is the ultimate payoff of intent-driven integrated marketing.

But with the emerging realities of remote work, new layers of relevance and intent weighting may become meaningful. For example, if we see a lot of activity from a home IP address between the hours of 9 a.m. to 5 p.m., we’d likely be able to infer that this person is working. If the signals are being generated later in the day, we may have just found someone who’s extremely enthusiastic about cybersecurity, or perhaps doing very early background research around an issue that really hasn’t yet evolved into a purchase journey.

Of course, this is just a hypothetical. Data-driven marketing is all about collecting information and adapting to market conditions, and that’s what will guide the future development of Relevance Engine and Identify Graph.


Business decision makers will continue working from home, even after the current pandemic is over. So identifying and understanding the purchase intent signal data they create from their home and mobile devices will become even more essential to successful intent-driven B2B marketing.

Visit our Intent Data Center for a look at trends that could impact your business and B2B marketing.