When building your account list and running your ABM campaigns, you'll want to track which accounts are engaging to measure the likelihood of conversion. If you can tell a cold MQL from a hot one, you'll understand which accounts need more time to warm up and which are ready to be passed to sales.
To do that, you must create a scoring model to help clarify which accounts are cold, warm, or hot. But how can you tell which account is likelier to convert, where they are in the buyer's journey, and if the lead is ready for sales outreach? The secret: scoring your accounts. To do that, you'll need to understand what your intent data is telling you.
If you're new to ABM and want to understand account scoring and how to score effectively, you've come to the right place! This article will take you through the different types of intent data, what they reveal, and how to score with relative accuracy. In just a few short minutes, you can begin scoring your own account list for increased ABM campaign success.
What is Intent Data?
Intent data is formed around the research a company does. When a company researches different topics or articles, it signals an intent or interest in that topic or area. When you begin to monitor for specific intent signals, you'll uncover which companies are interested in the topics most relevant to your offering.
Why is Intent Data Scoring Important?
When building your account list, you want to make sure it’s comprised of companies that are in-market (a relevant potential client) and showing signs of interest in your product or service. Intent data will reveal if a potential account is showing interest in purchasing a product or service related to your offering and, therefore, is more likely to be open to/ready for conversion. You don't want to target accounts that lack interest in your company's offering. So, to divide those most interested from those least interested, you want to develop a scoring scheme that can help you organize your list effectively.
Basically, using intent data is an important first step in finding the ICPs (Ideal Customer Profiles) with the highest intent signals. That way, you can better prioritize leads and find more effective messaging strategies when running your ABM campaigns.
First vs. Third-Party Intent Data
There are first-party and third-party intent signals to consider when scoring your accounts.
First-party intent signals reflect data collected directly from your digital properties and brand interactions. For example, website visits, content downloads, webinar attendance, form submissions, email interactions, and other engagements on your owned channels. First-party intent signals provide direct insights into the behavior and interests of your audience. And, since they are based on interactions with your brand, they give you a clear view of engagement levels and areas of interest.
Third-party intent signals are collected from external sources, typically through data vendors or specialized platforms that aggregate data from various online activities. You can compile third-party intent insights via information from publisher networks, content syndication platforms, industry forums, and other external sources that track online behavior and interactions even when users are not directly engaging with your brand. Third-party intent signals provide a broader view of the market landscape and potential opportunities. They can help identify accounts that may not interact directly with your brand but exhibit relevant behavior elsewhere.
How to Score Your Accounts Using Intent to Find Your Ideal Customers
You can effectively score your account list using first and third-party intent data. Here, we break down some strategies to ensure you score correctly - and accurately.
Start With the Right Firmographic Data
Not all accounts will fit your ICP, so start by narrowing the list of target accounts via firmographic data. Firmographic data can include company industry, size, revenue, and location. Once you've decided on your firmographic data, you can move on to intent data to score your accounts with a certain amount of accuracy.
Make Enterprise vs. Mid-Market Scoring Distinctions
Are you targeting mid-market accounts…or enterprises? This distinction, when it comes to account scoring, is essential. Why? While a mid-market company may have just one location, an enterprise will have offices nationwide. You need to understand where the intent is coming from to target the right buying circles, so when it comes to enterprise targeting, the bigger the accounts are, the more critical it is to score the individual engagement over the account engagement.
Consider this rule of thumb: enterprises should have a contact-centric score emphasizing the contact itself and their engagement with your website, marketing materials, and omnichannel campaigns. A mid-market lead should be account-centric to help you identify the contacts you should be following up with.
Scoring Effectively Using Third-Party Intent Data
The main thing to consider when scoring accounts based on their third-party intent is the recency and frequency of the signals they're trending on. Accounts showing a higher frequency and recency around intent signals should be scored higher. When scoring an account based on its third-party intent, you're looking for the most recent signals trending for the longest time. These get the highest scores as they suggest that accounts are researching those topics more regularly with more recency.
Gauge How Far an Account Is in the Buyer's Journey via Third-Party Intent Data
To determine where an account is in its buyer's journey, look at both frequency and recency. These help gauge their likelihood to buy and reveal a company's position in the decision-making process.
To reveal where an account is in the buyer's journey, look at when they started trending on a particular signal. If an account's intent signal is highly recent (for example, within the last two or three weeks), you can presume they're beginning their research. But, if an account had more frequency in research eight to 12 weeks ago, and the frequency was strong at that time, then you can assume they're at the later stages or already at a purchasing decision. How early or late an account is in its buyer’s journey will affect its score, as accounts earlier in the buyer's journey offer a better opportunity for building brand recognition and engagement.
Your Website Traffic is Your Secret Weapon
Because we have so many channels available to us to be able to target individual accounts, one of the most important things to do is to capture the website traffic as a catch-all for engagement.
All the accounts visiting your website should be known and de-anonymized. That way, you're capturing those website visits, and you can score their visit history based on whether or not they're in your ICP. If they're part of your ICP, you want to flag those accounts visiting your website and give them an increased score. And, if they're visiting your website with a lot of recency and frequency, you want to score those accounts even higher.
Check What Web Pages Accounts Are Visiting
If an account has visits that reflect a lot of frequency and recency and is visiting a high-value page, it stands to reason that their score should be much higher in terms of the first-party intent score.
Separate Existing from Potential Customers
Be sure to check whether an account visiting your website is an existing customer. You shouldn't be folding existing customers into ABM campaigns targeting new accounts. But that doesn't mean they don't have value. Depending on which part of the website they're frequenting, they may be signaling an upsell or cross-sell opportunity, and they should be handed off to sales with that context in mind.
Don't Forget to Factor in Second-Party Data
We've talked a lot about first and third-party data, but there's second-party data, too. Second-party data is reflected in engagement across different channels, including actions like email and ad clicks. Think of it as a hybrid type of intent data. It's not visiting your website directly - it's engaging indirectly via your ads and marketing touchpoints. The score should be determined by the level of engagement on the different channels and tracked alongside web visits and ad impressions. For example, the more they visit your website and click on email links or ads, the higher their engagement and, therefore, the higher their score.
Score and Weigh Accounts Across All Channels to Maximize Accuracy
Your second-party engagement score must consider all the channels you use in your ABM campaign. If you have a collection of scoring across all the different channels you are using, you tend to have a much higher degree of accuracy. It all comes together to give you a fuller picture of the individual accounts that you can then turn into an overall score that can help sales prioritize outreach.
Remember: each channel should have its unique way of scoring - those scores should be weighed against other scores. Programmatic ad impressions should be scored differently than LinkedIn or Facebook ad clicks, which should be scored differently than email link clicks. Also, a website visit to a pricing page likely has more value than an email open, so the score should reflect that. The cumulative score of all models reflects the actual engagement across all channels to help your team fully understand which accounts are cold, warm, or hot.
Once you've decided on your scoring model, you can develop an overall score that works for your business while giving rich context to sales for more effective (and personalized) outreach.
Conclusion
There are various ways to uncover details about your accounts that can reveal their level of interest or intent. However, to get the most out of the insights you're collecting, you need to create a scoring model for each part of your omnichannel outreach. By taking each touchpoint, giving it weight, applying a score to it, and cumulating your findings, you can effectively score each account on your list for a clearer picture of which leads are ready to be passed to sales and which require more time to warm up.