What Matters With Intent Data
Revenue teams need to be equipped with actionable information in order to move buyers through an account-based buying journey and close sales. But much of the information they need lives in the “dark funnel,” an ocean of anonymized buyer data. Gathering intent data can give revenue teams the advantages they need to successfully guide prospects in the buying journey.
Account Match Rates
Today’s B2B buyers don’t want to fill out forms or contact sales when they’re searching for a new product. According to Forrester, 62% of B2B buyers say they can now develop selection criteria or finalize a vendor list based solely on digital content — by the time you reach out to prospects, they might already have their minds made up.
Essentially, match rates provide the ability to match known and anonymous activity to an account to get a full picture of the buying team and journey. The higher your match rate, the better you are at finding hyper-relevant buyers who want your product just as much as you want them to buy it.
There are account tools that can provide a long list of prospects to hungry revenue teams. But chasing bad leads will get you nowhere — you need highly-qualified accounts from the outset to actually accomplish your revenue targets. What’s more, each account is creating intent data signaling where the buying team is in the pipeline. If your tools aren’t matching those intent signals to the right accounts, then you’ll spend your time and resources pursuing the wrong accounts altogether, even if they were “highly-qualified” by your account tool.
Your revenue teams need access to those intent signals in order to deliver compelling content at the right time to move prospects through the pipeline. With the right tools in place and the correct matching of intent data to accounts, your team can accomplish a high-performing match rate.
Multiple Data Sources
Successful match rates are tied to the data sources you use to build your matched account profiles. Some companies offering account matching rely on a single source like IP addresses to tell when buyers are sending their intent signals. While buyers do still search for product information from the computers in their offices, the changing nature of work has muddied the waters around IP addresses. Buyers are using their laptops, tablets and mobile devices to research from their homes or coffee shops — all of which use different IP addresses. Using one data source ends up leaving a lot of data in the “dark funnel.”
A healthy account match rate depends on gathering data from multiple sources and the ability to marry that to the right kinds of prospects. To do that, you should consider how data sources merge to tell the full story. Data from not only IP addresses but also advertisement IDs and cookies, providing information across multiple devices and channels, capture intent signals from wherever your buyers are looking. This information can then qualify matched accounts to create a fuller picture of your prospects, giving your revenue teams the information they need to make that critical personalized outreach at the right time.
A large dataset of matched accounts might look impressive, but if those accounts are not qualified with the right intent signals and tied to your IICP, then your revenue teams can’t deliver effectively. While buyers are abandoning forms and rejecting spam and cold calls, they are providing plenty of intent signals and data companies can use this insight to guide their prospecting efforts.
A high-performing match rate comes from the “dark funnel” data you use to assess the actual buying intent behind matched accounts. This assessment then tells your revenue team how they can effectively deploy their resources toward highly qualified prospects at the appropriate time to move them through the pipeline and ultimately close more deals.
In-market Ideal Customer Profile (IICP)
Successfully matching anonymized buyer data to accounts your teams want to pursue also hinges on your team developing a strong ideal customer profile. Account-based engagement relies on you really understanding your buyers and then providing them with engaging content personalized to their needs. So not only do you need to know who your ideal customer is but when they are in-market, and what they are looking for.
Revenue teams used to be limited to gut instincts, lists, and form-fills when targeting prospects. Marketing and Sales teams would try to assess which accounts seemed the most receptive and pursue them without accurate data to support their claims. Even with more data-driven account matching, pursuing accounts who are not in-market can easily waste dollars as much as gut instinct does.
Matched account selection should originate from real buyer intent and activity data coming from the “dark funnel,” which then informs the buyer journey your company crafts to move prospects through the pipeline. It’s not only matching accounts that want to buy but knowing when they’re ready to buy that matters. With an accurate picture of buyer intent and a well-defined IICP, you can direct personalized and compelling content to prospects when they want it in order to achieve success in your ABM program.