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Leverage Intent Data for More Effective Marketing & Sales Teams

Intent monitoring combines internal data (data that comes from your customer-facing applications) with external data (data that comes from a third party) to give you a more expanded view of buying intent in your target market.  Intent monitoring is a foundation piece to predictive analytics, but because it tends to be more ‘historic’, it doesn’t deliver true “predictive” data.

What is Intent Data?

  • Internal data:  This is the data that comes from customer-facing platforms, including marketing automation platforms, CRM systems, and websites.  In the past, companies put that information into a data warehouse, where they asked questions and drew inferences about buying intent based on past behavior.  Nowadays, this information may go into a CRM system, but it only provides a limited view of buyer intent.
  • External data: The real breakthrough in intent data came with third party, or external data sources.  There are two primary sources of third party data:  publishers and ad exchanges.
    • Publisher data:  Like a newspaper publisher, electronic publishers have a network of subscribers that comes to them for relevant content.  The publisher has a number of websites that cover very specific niches in the market, and anytime people visit the website for information, their IP addresses are captured.  The publishers are then able to aggregate IP addresses, and determine the domains and the accounts of the website visitors.  Publisher data is very good, but it’s somewhat limited.
    • Ad exchange data:  Ad exchanges cover 93% of the entire web, which gives them access to a lot of advertising real estate across the Internet.  The way in which ad exchanges extrapolate IP addresses, domains, and accounts works in much the same way as publisher networks. The big difference is the amount of data available from ad exchanges – their coverage is much broader than publishing networks.

The large amounts of data available from the ad exchanges require much more computing power to sift through all the digital exhaust to help get a clearer picture of the intention of your target market.

Ways to Leverage Intent Data to Drive Sales

While intent monitoring should not be classified as predictive, it is operationally easy and can be a valuable resource for sales activities.  Here are a few examples:

  • Identifying net new accounts that fit your customer profile: Sales can use intent data to identify net new accounts that are in an active buying cycle, but aren’t currently in their database.  This type of modeling is called “look-alike” modeling, and looks at company characteristics and answers the question, “How similar is this company to those we’ve sold to before?” You can make the assumption that the tactics and messaging that worked for your current customers will resonate with the “look-alikes”.
  • Prioritizing accounts that are showing interest in your solutions:  Another way to use intent data is to prioritize the actively buying accounts that are already in your database.  The most active accounts get the most attention.  You can also run targeted nurture campaigns that feature the content and solutions that are generating the most interest from your prospects.
  • Accelerating the sales cycle: Sales can use intent data to progress opportunities by matching their messaging to the specific needs of the active buyers.  Why is this important? Because according to a recent study from Unsplash, 62% of B2B buyers say they develop their vendor shortlist based solely on digital content.  The more targeted the content, the faster the engagement.

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