Contact scoring: how to rank the people in an account and measure buying group coverage
Account scoring tells you which company to work. Contact scoring tells you which person to call, and buying group coverage tells you whether you have reached enough of the right people.
Contact scoring ranks the individual people inside an account by how much each one matters to a purchase and how active they are right now. Account scoring tells you which company to work. Contact scoring tells you which person to call first, and buying group coverage tells you whether you have reached enough of the right roles to win the deal.
A company does not sign a contract. A group of people does. Forrester found that 95% of B2B purchases involve three or more people. An account score cannot tell those people apart, and a single lead score cannot tell you who is missing.
Contact score vs. lead score vs. account score vs. buying group coverage
These four share inputs and rank different things.
| Lead score | Contact score | Account score | Buying group coverage | |
|---|---|---|---|---|
| What it ranks | New people, often before they are tied to an account | Known people inside an account | Companies | Nothing. It measures one account’s readiness |
| The question it answers | Should sales talk to this person at all? | Who at this account do we call first? | Which companies deserve our time? | Have we reached enough of the right roles? |
| Typical inputs | Person and company fit, first activity, disqualifiers | Role in the purchase, seniority, function, account fit, recent replies and meetings | Company size, industry, systems, plus rolled-up activity | Roles needed for the sale, and which have an engaged contact |
Contact fit factors: who this person is in the purchase
Contact fit is about the person’s part in a buying decision. Four factors do most of the work: role in the purchase, seniority, function, and tenure in role.
Role in the purchase is the factor most teams skip, and the most useful. A typical B2B sale has five roles:
- Economic buyer: owns the budget and gives the final yes.
- Champion: wants the change and sells it internally when you are not in the room.
- User: will work in the product every day and can sink a rollout.
- Technical evaluator: checks that it works with the systems already in place.
- Procurement or security: runs the contract, the vendor review, or both.
One person can hold two roles, and smaller companies often fold several into one. Seniority (the level that signs for a deal of your size) and function (the department that owns the problem) are easier to get, but they are proxies for role. On tenure, many teams rate a person who is new in role above one who is five years in seat, because new leaders review what they inherited. Test that against your own wins before you weight it.
Contact engagement signals, with recency
Engagement is what the person has done lately. Keep it as a second score next to fit, because a blended number hides which half is doing the work.
| Signal | How much it should count | Recency window to start with |
|---|---|---|
| Replied to a rep | Strongly | 30 days |
| Meeting held | Strongly | 30 to 60 days |
| Pricing or comparison page views | Strongly | 14 to 30 days |
| Event or webinar attended | Moderately | 30 to 60 days |
| Content read or downloaded | Lightly | 30 days |
Let activity fade, so a meeting from last spring does not outrank a reply from Tuesday, and cap repeat signals, so twelve blog visits cannot outscore one pricing view. Leave email opens out: Litmus reports that over 50% of email opens come from devices with Apple Mail Privacy Protection turned on, which loads tracking pixels whether or not anyone reads the email.
Use the account’s fit as an input to the contact score
A VP of operations at a company you will never sell to is not a good contact. A contact score that only reads the person’s own fields will rank that VP above a director at your best-fit account.
The fix is cross-object scoring: bring the account’s fit score into the contact’s fit model as a weighted factor. Then the contact score means “the right person at the right company.” Give it roughly 25% to 35% of the weight. Much more, and every contact at a strong account scores about the same. Take the number from your ICP scoring model so the company is scored once and fit has one definition.
Buying group coverage: have you reached enough of the right people?
Buying group scoring, or buying committee scoring, looks at the shape of the group you have engaged. Coverage is the simplest honest measure of it.
Step 1: define the roles for your sale. Pull your last 20 to 30 closed-won deals and list who was involved by the time the contract was signed. The roles that show up in most wins are your required roles, usually three to five.
Step 2: measure coverage. Coverage is roles engaged out of roles needed. A role counts as engaged when at least one contact in that role has a meaningful signal inside your recency window, such as a reply, a meeting, or a pricing view in the last 60 days. A contact who only exists in your CRM is “known,” a lower bar.
Step 3: count roles, not activity. This is why one very active contact is weaker than three moderately active ones in different roles. A single champion with fifteen page views is one opinion inside the account, and if that person changes jobs the deal has no second path. Three engaged people in three roles mean the group that decides is talking.
Step 4: use coverage in the account score, in the right place. Coverage is a readiness signal. It says how far a buying process has progressed, not whether the company matches your ideal customer. Keep it out of the fit model. Put it in the account’s engagement or readiness score as a factor, or run it as its own score next to fit. An account with an 8.8 on fit and one role engaged is a great target that needs multi-threading. Mixed into fit, it would look mediocre.
A worked example
A demo account scores 8.4 on fit. Here is one contact there, a VP of revenue operations who owns the budget, scored on contact fit out of 10. The first factor comes from the company record. One factor subtracts: her title was last confirmed more than a year ago, so the role may be out of date.
- Account fit (from the company record) 30% 8.4
- Role in the purchase (economic buyer) 30% 9.2
- Seniority (VP) 20% 7.8
- Function (revenue operations) 15% 6.6
- Title not confirmed in over a year 5% -3.4
The math: 8.4 at 30% is 2.52, 9.2 at 30% is 2.76, 7.8 at 20% is 1.56, and 6.6 at 15% is 0.99, which adds to 7.83. The stale title subtracts 3.4 at 5%, or 0.17, for a contact fit score of 7.7.
Now the account’s buying group. This team needs five roles, and counts a role as engaged if a contact in it replied, met, or viewed pricing in the last 60 days.
| Role needed | Contact known? | Contact fit | Last meaningful activity | Engaged? |
|---|---|---|---|---|
| Economic buyer | Yes, VP of revenue operations | 7.7 | Meeting held 9 days ago | Yes |
| Champion | Yes, marketing operations manager | 7.1 | Replied 4 days ago, pricing viewed twice | Yes |
| User | Yes, SDR team lead | 5.8 | Webinar attended 21 days ago, replied to follow-up | Yes |
| Technical evaluator | Yes, CRM administrator | 6.4 | One blog visit, 5 months ago | No |
| Procurement or security | No | None | None | No |
Coverage is 3 of 5, or 6 out of 10 as a factor value. The deal has a buyer, a champion, and a user, with no technical evaluator in the conversation and nobody from procurement or security. The next two actions are clear, and neither is “call the VP again.”
Plays by score: who to call first and who to multi-thread to
Contact scores order the people. Coverage decides whether to go deeper or wider. The cutoffs are a starting point.
| Contact fit | Contact engagement | Play |
|---|---|---|
| 7 and up | 6 and up | Call first. Reference what they did, and ask who else is involved |
| 7 and up | Under 6 | Multi-thread target. Ask your engaged contact for an introduction, with a reason tied to this person’s role |
| 4 to 6.9 | 6 and up | Likely a user or influencer. Help them, and ask who owns the budget and the technical review |
| 4 to 6.9 | Under 6 | Nurture. No rep time until engagement rises |
| Under 4 | Any | No rep time. Answer direct questions only |
Then apply coverage on top:
- Coverage of 1 or 2 roles: go wide before you go deep. The next call is to the highest-fit contact in an empty role.
- Coverage of 3 or more, with the economic buyer missing: ask the champion for the introduction this week.
The job-title data problem
All of this depends on knowing each contact’s role, and job titles are messy. “Head of Growth,” “VP, Revenue,” and “Director of GTM Systems” can describe three roles or one, and titles go stale when people move. Validity found that 76% of CRM users say less than half of their data is accurate and complete.
Normalize each title into three short fields, then score the fields.
| Raw title | Seniority | Function | Likely role in the purchase |
|---|---|---|---|
| VP, Revenue Operations | VP | Revenue operations | Economic buyer |
| Head of Demand Gen | Director or VP | Marketing | Champion |
| HubSpot Admin | Individual contributor | Operations | Technical evaluator |
| SDR Team Lead | Manager | Sales | User |
A workable process:
- Write keyword rules for seniority and function. “Chief,” “VP,” “head of,” “director,” and department words cover most records.
- Map seniority plus function to a default role, using who filled each role in your won deals.
- Use AI to classify the titles your rules miss, with a person reviewing the mapping before anything is scored.
- Let reps override the role on the record. A title suggests the champion. A rep who was on the call knows.
Contact scoring in HubSpot
HubSpot’s default contact properties include Buying role, the role the contact plays during the sales process. A contact can have more than one role and you can add your own. It is tied to HubSpot’s account-based marketing features, so check that your subscription includes it.
HubSpot’s scoring tool needs Marketing Hub Professional or Enterprise for contact scores. Company scores can use associated records, rolled up as a sum, average, minimum, or maximum. Know what each roll-up says before you use it for coverage: a sum rewards volume, so one busy contact can look like a group, and a maximum reports only your best contact. Neither counts distinct roles engaged.
Common mistakes
- Scoring titles as raw text. Normalize to seniority, function, and role first.
- Treating the most active contact as the most important. Activity without role is noise from one person.
- Putting coverage in the fit score. It measures readiness. Mixed into fit, it punishes good accounts you have not worked yet.
- Counting known contacts as engaged contacts. A bought list fills every role and tells you nothing.
Our guide to where teams get ICP scoring wrong covers the fit-side versions.
How to validate it: win rate by coverage level
Take closed deals from the last 12 to 24 months, record how many required roles were engaged at a fixed point, such as 30 days after the opportunity opened, and compare win rate at each level.
| What you see | What it usually means | What to do |
|---|---|---|
| Win rate rises with each added role | Coverage works as a readiness factor | Use it in the account score and in deal reviews |
| Win rate is flat across coverage levels | Wrong roles, or “engaged” is defined too loosely | Redefine roles from won deals; tighten the window |
| Most deals show coverage of 1 | Contacts are missing from the CRM, not from the deal | Fix contact capture before trusting the number |
Check the contact score the same way: contacts scoring 7 and up should appear on won deals more often than the rest. If they do not, revisit the weights, starting with role. Our five-step framework for building an ICP scoring model covers weighting.
Where BoostIdeal fits
BoostIdeal is a scoring engine for HubSpot teams. It works with HubSpot, or a CSV you upload. For contact and buying group scoring:
- It scores contacts using their account. A contact model can take the account’s fit as one weighted factor next to the contact’s own properties.
- It scores accounts using their contacts. An account model can use how many known contacts the account has, or their job titles and buyer types, as a factor. That is how coverage becomes a number.
- It keeps coverage separate from fit. Several models run side by side, so fit stays about the company and coverage sits in its own readiness model or factor.
You build each model and set the weights, with AI helping to analyze data and draft a starting point. Scores are out of 10, a missing value contributes 0, and each score writes back to HubSpot properties with its reasons, so your own workflows, lists, and agents can act on them. Scores recalculate hourly by default, and in near real time with webhook sync.
When it is not the right fit. It is not the right fit if your data is not in HubSpot and you do not want to work from CSV uploads, or if you want a vendor to hand over a number you never question. In those cases, another approach will suit you better.
Frequently asked questions
What is the difference between a contact score and a lead score?
A lead score rates a new person mostly on their own, to decide whether sales should talk to them. A contact score rates a known person as one member of an account, using the account’s fit and that person’s role in the buying group.
What is buying group scoring?
Buying group scoring, also called buying committee scoring, measures how well you have engaged the set of people who decide a purchase. The most practical version is coverage: the number of required roles with an engaged contact, out of the number of roles the sale needs.
How do you measure buying group coverage?
Define the roles your sale requires from your won deals, then count how many have at least one contact with a meaningful recent signal, such as a reply, a meeting, or a pricing view. Three engaged roles out of five is 3 of 5.
Who should a rep call first at an account?
Call the contact with the highest fit and recent engagement, usually an engaged champion or economic buyer. Then use coverage to pick the second call: the highest-fit contact in a required role that nobody has engaged yet.
Should buying group coverage be part of the fit score?
No. Fit describes whether the company matches your ideal customer, and it changes slowly. Coverage describes how far a buying process has progressed. Keep coverage in an engagement or readiness score, or as its own score next to fit.
Can HubSpot score contacts and buying roles?
HubSpot’s scoring tool scores contacts with Marketing Hub Professional or Enterprise, and company scores can roll up associated records as a sum, average, minimum, or maximum. HubSpot also has a Buying role contact property. Test any coverage setup on a few accounts first.
The takeaway
An account score picks the company, a contact score picks the person, and coverage tells you whether the group that decides is in the conversation. Score contacts on their role in the purchase and the fit of their account, keep engagement separate and recent, and count roles engaged out of roles needed. Then check that deals with broader coverage win more often. When that holds, a rep opening any account knows who to call first and who is still missing.