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Report: How Marketers Are Tracking In-Market Buyers

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Tracking Intent Signals eBook

According to 6sense Research, Forrester, and Gartner, today’s B2B buying teams usually consist of between five to 16 people — or more. And while solutions exist for B2B marketers to quickly identify and engage these buyers as they conduct research, few marketers actually take advantage of this opportunity, 6sense Research recently found.

As buyers search for solutions on the B2B web, they leave behind invisible trails of “virtual breadcrumbs” that, when using the right technologies, can reveal their concerns, interests, and intent. 6sense Research recently conducted a survey to learn how B2B marketers leverage these anonymous buying signals.

The survey results indicate that marketers continue to rely heavily on website form-fills and other legacy lead generators, and largely neglect buying signals that would deliver more impactful results.

Key Findings

  • Most marketers prefer buying signals like form-fills and virtual event registrations, which contain contact info, are offered directly by the lead, and represent a single person.
  • More than half (55%) of marketers don’t think their current buying signal mix is close to ideal.
  • Group-level signals like third-party intent and de-anonymized web traffic lag behind individual-level signals.


Although marketers still favor identified and received signals like form fills, only 3% of web visitors complete forms. Teams should implement tools and processes that capture anonymous signals to reveal a bigger picture of prospect behavior. 

Further, most marketers are using individual buying signals, yet we know that B2B buying happens in groups. More group-level signals should be adopted, like:

  • De-anonymized website traffic
  • Third-party intent 
  • Product review site intent

Read the report, Tracking Intent Signals: How Are Marketers Really Identifying Their In-Market Buyers?, to explore more findings from the survey.

The 6sense Team

6sense helps B2B organizations achieve predictable revenue growth by putting the power of AI, big data, and machine learning behind every member of the revenue team.

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