Account scoring worksheet: score target accounts and their buying groups
Deals are bought by companies, not single contacts. This worksheet scores the account, uses everyone there as evidence, and shows which roles you still need to reach.
Lead scores rank people. B2B deals are bought by companies, and usually by several people at once. A lead score can tell you that one contact visited your pricing page twice. It cannot tell you that four people from the same company have been active this month, or that none of them is the person who signs.
Account scoring answers a different question: which companies should we work now, and who at each one? This worksheet builds that model in a spreadsheet, so you can test it on your own target list before anything touches the CRM. It comes in six tabs.
What the worksheet does
It scores every account two ways and keeps the scores apart.
- Fit is a score out of 10. It asks whether this is the kind of company you win.
- Engagement is a second score out of 10. It asks whether the account is active right now, using everyone there as evidence, and it fades as activity gets older.
Two cutoffs on each score split accounts into nine bands, from fit 7.0 and up with engagement 6.0 and up, down to fit under 4.0 with engagement under 3.0. The worksheet also checks which roles in the buying group you have reached, lists the ones you are missing, and gives every account a play.
Two rules do most of the work:
- Breadth beats volume. Each contact’s activity is capped, so one very busy person cannot make an account look ready.
- Coverage counts. An account where the economic buyer, the champion, and a technical evaluator are all engaged is worth more than one where only the champion is, however active that champion is.
Tab 1: Account fit
Name your fit factors and weight them. The template uses four: industry, company size, region, and tech stack. The weights must add up to 100%, and the sheet tells you when they do not.
Under each factor, list the values you see in your data and give each one points from 0 to 10. Tech stack often carries the most weight, because it separates two companies that look identical on paper. In the template, a company running a system you integrate with scores 9.7. One that just signed with a competitor scores 1.3.
Unknown values score zero. They add nothing, but they do not count against the account either. Account disqualifiers subtract: competitors, current customers (who belong in your expansion model), regions you do not serve, and existing partners, who should go to your partner team first.
The fit cutoffs start at 7.0 and 4.0. Move them so the first band holds about as many accounts as your team can work one to one.
- Industry 25% 6.3
- Company size 25% 5.8
- Region 20% 9.6
- Tech stack 30% 8.1
This is the third demo account in the worksheet, a healthcare group in your primary market running a system you replace. It clears the 7.0 cutoff with a 7.4. As you will see on tab 5, nobody there is talking to you yet.
Tab 2: Buying group
List the roles that decide your deals and weight them. The template uses four:
| Role | Weight | Why it matters |
|---|---|---|
| Economic buyer | 35% | Nobody signs without them. |
| Champion | 30% | Sells for you when you are not in the room. |
| Technical evaluator | 20% | Can stop a deal late if they are brought in late. |
| End user | 15% | Adoption, and the proof your champion needs. |
A role counts as engaged when someone in it has taken a high-intent action within a window you set, 30 days by default. Buying group coverage is the share of role weight you have reached. An account where only the champion is engaged has 30% coverage.
Tab 3: The engagement model
Account engagement has five parts, weighted to 100%:
| Part | Weight | How it is measured |
|---|---|---|
| Contact activity | 35% | Rolled up from every contact at the account, capped and decayed |
| Buying group coverage | 30% | From tab 2 |
| Meetings or calls held | 20% | Count and days since the most recent, 45-day half-life |
| Third-party intent surge | 10% | Count and days since, 21-day half-life |
| Event or webinar attended | 5% | Count and days since, 60-day half-life |
Contact activity is where the per-contact cap matters. Each contact’s high-intent actions count up to a cap, three by default, and fade with a 30-day half-life, so each contact is worth at most 1. The account gets full credit at the equivalent of three fully active contacts. One person who does everything tops out at a third of the credit.
The engagement score is 10 times the weighted sum of the five parts, and its cutoffs start at 6.0 and 3.0.
Tab 4: Contacts
One row per contact: the account, the contact, their role, the number of high-intent actions, and the days since the most recent one. The sheet works out each contact’s credit and whether they count as engaged. Account names need to match tab 5 exactly, which is the most common reason a roll-up shows zero.
Tab 5: Score your accounts
One row per account. Pick the fit values from the dropdowns, enter the account-level signals, and the rest calculates: contacts listed, contact activity, coverage, missing roles, fit score and band, engagement score and band, and play.
The three demo accounts in the worksheet are fictional. They show why the model is built this way:
| Demo account | Fit | Engagement | Coverage | Missing roles | Play |
|---|---|---|---|---|---|
| 1 | 9.6 | 7.1 | 85% | End user | One to one, outreach this week |
| 2 | 5.8 | 2.4 | 30% | Economic buyer, technical evaluator, end user | One to many nurture |
| 3 | 7.4 | 0.3 | 0% | All four | One to few, alert the owner when engagement climbs |
- Demo account 1 has four active contacts, including the economic buyer, the champion, and a technical evaluator, plus a recent meeting and an intent surge. It lands in the first band on both scores.
- Demo account 2 has one champion who has done six high-intent things this week. A lead score would put that person at the top of the list. The account scores 2.4 on engagement: 30% coverage, and no one else engaged.
- Demo account 3 is a strong fit with nobody engaged in the last 30 days. The missing roles column lists all four, which is the brief for the account team.
The missing roles column is often the most useful output. For a strong-fit account with partial engagement, it is the list of people to go and find.
Tab 6: Plays by band
Every band gets a play, built around the usual account-based tiers: one to one, one to few, and one to many.
| Engagement 6.0 and up | Engagement 3.0 to 5.9 | Engagement under 3.0 | |
|---|---|---|---|
| Fit 7.0 and up | One to one. Named owner and SDR, outreach this week, executive sponsor on the deal | One to one. Multi-thread now, starting with the missing roles | One to few. Targeted ads and content. Alert the owner when engagement climbs |
| Fit 4.0 to 6.9 | One to few. Qualify quickly, and check whether the fit data is incomplete | One to few. Qualify quickly, and check whether the fit data is incomplete | One to many. Programmatic nurture, no rep time yet |
| Fit under 4.0 | Check the fit data, then self-serve or a partner at most | Check the fit data, then self-serve or a partner at most | Leave them alone |
Edit them to match how your team works. The point is that every band has one, so a score always leads to an action.
From spreadsheet to CRM
Once the ranking matches how your best account executive would triage the list, move the model into your CRM. In HubSpot, company scores can combine values from associated contacts by sum, average, minimum, or maximum. That covers contact activity. Coverage by role and the per-contact cap usually need extra workflow logic, so keep the spreadsheet as the reference for how the model is supposed to behave.
Every quarter, compare pipeline created and win rates by band. Accounts with fit 7.0 and up and engagement 3.0 and up should turn into pipeline clearly faster than everything else. If they do not, change one or two weights, write down why, and check again next quarter.