Account Scoring Step-By-Step - How to Make First-Party Intent Data Work for You

Posted by Alex Chan on September 5, 2019

Historically, account scoring has been tied directly to a company's perceived "fit" to an Ideal Company Profile (ICP). However, this is just one piece of the puzzle, and on its own, this model has a hard time accounting for potentially unknown markets. So in this post, instead of looking at traditional account scoring models, we're going to talk about account scoring based on first-party data. We will look at the perceived interest an account has in your solutions and how to determine exactly when to engage with them. 

Just a quick recap: First-party intent data is information collected from your website that indicates different levels of your prospective buyers' intentions based on their behavior on your site. While the benefits you get by utilizing this data depend on your ability to track your target account's activity on your website, the benefits far outweigh the costs of doing so as this data is paramount to effective account scoring.

How Do You Use This Data?

The process of account scoring can be broken down into three major steps. (Although each one of these requires multiple steps on their own (so it's more like three plus a few smaller steps).

Define all first-party intent signals 

Sales and marketing teams should collaborate to create a list of possible signals or events that indicate an in-market account (a company that is showing signs they are looking to purchase a solution like yours). These could include downloading a PDF, signing up for a free trial, or reaching out via a contact form or email. These are just some examples to give you an idea of what you should be looking for. 

Assign a value to all intent signals

Think of this as a point system that will determine which accounts are showing sufficient interest to engage with them. Unfortunately, I can't tell you exactly how to value each intent signal as your company has its own unique goals and strategies. However, we can look at multi-touch attribution for inspiration about weighting each intent signal.

Multi-touch attribution models look at historical sales and marketing data and weight each touchpoint based on which ones a prospect engaged with in the buying process. Did they fill out a form? Attend a webinar? We can extend this principle to our scoring process by placing a higher value on touchpoints that generally indicate increased interest. 

For example, downloading a guide or other gated content might be worth 10 points while looking at a single web page might only be worth 5 points. 

Set a "green light" threshold 

Set a total number of intent signals or "points" an account must accumulate to become a Marketing Qualified Lead (MQL) or a Sales Qualified Lead (SQL). This will prevent you from spending valuable time and resources marketing to accounts that may have stumbled on your page by accident and instead, focusing on those that are actually interested. 

One word of caution is that MQLs and SQLs are different, and just because an account has shown interest doesn't mean they're necessarily ready to hop on the phone with a sales rep. The threshold for placing an account into the sales process should be much higher than putting them into a marketing campaign. 

For example, the threshold for a website visitor to enter a marketing campaign might be 45 points, while the threshold to warrant a sales action might be 70 points. 

Let's Look at Account Scoring in Action

Ok, so now you've got the general idea of what account scoring looks like; let's see how it works in practice.

For this example, let's assume a page view = 5 points, a content download = 10 points, and a contact form = 70 points (you'll see why soon). 

We'll say the "green light" threshold for a marketing campaign is 45 points, and the threshold for a sales action is 70 points. This is why a contact us form fill is 70 points – if a visitor has reached out, they should automatically receive a call or an email from a sales rep.

Let's compare three different companies that visit your website:

 

Company X: Looks at 5 pages. Account Scoring-1

5 page views = 25 points

 

Company Y: Looks at 5 pages, downloads 3 (gated) guide.

5 page views + 3 content downloads = 55 points 

 

Company Z: Looks at 2 pages and fills out a contact form.

2 page views + contact form fill = 80 points

 

In this scenario, Company X has not shown enough interest to warrant any actions. Company Y has shown enough intent to at least be placed in a marketing campaign. Finally, even though Company Z has looked at fewer pages overall than either of the other two companies, they have reached out directly and thus should bypass the entire marketing process and be placed directly into the sales process. 

Quick side note: Filling out a contact form in order to receive a piece of gated content is NOT the same, and should not be given the same weight. While engaging with gated content might be a good signal of intent, filling out a contact form should warrant a touch from a salesperson directly as they basically stood up and said, "I'm interested, tell me more." 

Unfortunately, we cannot rely solely on our target accounts to reach out directly. But by now, it should be clear that leveraging buyer intent data is one of the most effective ways to leverage your website traffic to find new leads. Furthermore, understanding where companies are in the buying process will allow you to create personalized messaging that reaches them at the right time.

If you want to see what first-party data looks like and learn more about how to uncover the companies visiting your website, check out our guide to IP address intelligence.