The Account Scoring Playbook

Here's what too many public sector sellers think about account scoring: it's made up by a higher-up that doesn’t have any sense of what things look like on the ground.

Bad account scoring results in a lack of trust between sellers and leadership  AEs waste hours chasing accounts that are in 5 year locked contracts. 

Why does this seem to happen to most companies, even some of the most established? 

When I was at Coursedog where we sold to higher ed, the greatest challenge was real-time comprehensive data that we could use for our account scoring model.

We had to rely on two-three year old stale IPEDs data and AEs filling in the blank on competitive insights or current ERP provider. 

If I could go back in time, here’s how I would build an account scoring model:

1. Imagine your ideal  ICP

Before you can score accurately, you need current information. Publicly aggregated data like IPEDS, NCES and FPDS are not going to be adequate. 

Don’t constrain yourself to what’s currently available. Use your creativity to imagine what an ideal customer profile looks like.

If any piece of data was accessible to you, what would be the strongest signs of a high-fit account? Maybe it's competitive intelligence. Maybe it's a new CIO being appointed. Create a list and start to work backwards. 

This is critical because you want your reps operating with real intelligence, not outdated estimates.‍

2. Build a Dynamic Scoring Rubric

This is probably the hardest part, but it's where the magic happens.

Start by identifying each piece of data that aligns to your ideal customer profile. Don't just list attributes—think about how they interact.

A school with a legacy SIS and an expiring competitor contract is fundamentally different from one with the same legacy SIS but a 4-year renewal they just signed.

The key is building a rubric that captures nuance, not just checkboxes. For each data point, define what "Full," "Partial," and "Low" readiness looks like. Be specific. "Modern tech stack" is useless. "Canvas LMS with API integrations to their SIS" is impactful.‍

3. Generate A Weighted Score

Not all signals are created equal.

Maybe the current ERP vendor is a lot stronger of a signal than a recent job change. Your weighting should reflect that reality.

This is where you need to get empirical. Look at your closed-won deals from the past 12-18 months. What attributes did they share? Which ones consistently showed up in fast sales cycles versus the deals that dragged on for 18 months?

Weight your scoring model based on what actually predicts outcomes in your business, not what sounds important in a vacuum. 

4. Make it actionable in the tools reps already use: 

Your scoring should live in your CRM. Whether it’s Salesforce or  Hubspot, and whatever the framework is, Tier 1, Tier 2, Tier 3 - reps should be able to filter accounts from top to bottom and see both the score and the summary explaining why this account is prioritized.

Anyone can score a list of accounts. The trick is scoring accounts with deep specificity, imagination, and against the most reliable and up-to-date data. When you score accounts like that, time wasted goes down drastically and time invested in meaningful outbound skyrockets. 

P.S. Guess who can help with accomplishing all of this…?

Check out the use case videos below to see how Starbridge can help you put account scoring on auto-pilot.

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