How to Score Account Fit for Life Science Sales

A fit score is only useful if two different people scoring the same account would land on the same answer, and if the answer tells someone what to do next. Both of those depend on using a short list of concrete criteria instead of a vague sense of "who we sell to."

1. Define the ICP layers

   Write down two separate definitions before scoring anything: company fit (does this account look like the companies you sell to and win) and buyer fit (is there a person inside it who matches who you sell to). See building an ICP as a CRO or CDMO for the fuller reasoning behind the two-layer split. The mistake to avoid here is writing one blended "ideal customer" paragraph that mixes company and buyer attributes together, since that makes it impossible to tell later which layer a bad-fit account actually failed.

2. Pick scoreable criteria

   For each layer, write down a short list of attributes you can check against a real account in under a minute, not a paragraph of adjectives like "innovative" or "growth-stage." A workable starting set:

   • Company fit: therapeutic area or modality overlap, development stage, company size, and resemblance to your best existing customers.
   • Buyer fit: the function that owns the problem you solve, and the seniority needed to influence or approve a purchase.

   When you write the buyer fit criteria, reason about equivalent titles rather than matching on exact job title text. Life science titles vary widely across company size and structure: a "Chief Scientific Officer," a "Head of Scientific Affairs," and a "VP of R&D" can all represent the same science-leadership buying authority, and "Director of Business Development," "Head of Alliance Management," and "VP External Partnerships" can all represent partnerships and BD authority. A rule that matches on title text alone will miss good contacts and let in irrelevant ones.

3. Score and band

   Score each account against the criteria, then group results into a small number of bands rather than a single long ranked list. Bands absorb the noise in any one criterion and keep the output usable: a workable starting set is strong fit, partial fit (clears company fit but is missing a matching buyer, or is borderline on one company-fit attribute), and weak fit.

   Resist the urge to force a precise 0 to 100 number out of criteria that are mostly judgment calls. A three or four-band system that a rep trusts is more useful than a decimal-precision score no one can explain.

4. Act on the band

   A fit score only earns its keep if it changes what happens next. Map each band to a clear action:

   Strong fit

   Company fit and buyer fit both clear

   Ready for outreach as soon as a readiness signal appears, or ready to monitor if nothing has happened yet.

   Partial fit

   Company fit clears, buyer fit does not

   The account is worth working, but the next step is finding the right person, not sending an email.

   Weak fit

   Company fit does not clear

   Deprioritize regardless of how strong any later signal looks. No amount of buying activity should pull a weak-fit account back onto the working list.

   Once accounts are scored and banded on fit, layer in readiness scoring to decide when inside the strong-fit band to actually act.

Checklist

• Company fit and buyer fit written down as two separate definitions.
• Each layer reduced to four or five criteria you can actually check per account.
• Buyer fit criteria reason about function and seniority, not literal job title text.
• Accounts scored and sorted into a small number of honest bands.
• Each band mapped to a clear next action, not just a label.