← BUILD LOGTAM + PRIORITIZATION
BUILD LOG · SCORE THE WHOLE MARKET

The funnel was full of accounts a rep could not tell apart. So we scored the whole market.

A rep opens the pipeline and sees a thousand accounts that all look the same. An account scoring model that runs across the whole TAM, fit plus product plus intent, turns the market into a ranked list where every account carries a tier and a next move before anyone touches it. Scored right, the ranked list is what reps work top-down instead of guessing.

Steal this build ↓See the stackThe people part →
~4x
more revenue-bearing opps than the prior run rate
~4.5x
more new pipeline created than the prior run rate
~90%
of that pipeline came from strong-fit accounts
100%
of outbound landed on-strike-zone
THE STORY, FROM THE SEAT

Here is one I actually shipped. What happened, what I did, and the stack if you want to run it yourself.

The pipeline was full and useless. Every account looked like every other account, so reps worked whoever was on top, not whoever was ready.

Scoring one deal at a time does not fix that. You have to score the whole market on the same rubric, so a rep can look at any account and know its tier and its next move without a research project.

The Sales Operator
Keep Building,
Heath
FOUNDER, THE SALES OPERATOR
THE BUILD IN FIVE MOVES · THE GIANT METHOD
  1. GThe pipeline was full and useless: reps worked whoever was on top, not whoever was ready.
  2. IOne rubric for the whole market: Deepline scores ICP fit, Amplitude adds product engagement, Common Room adds capped buying signals, weekly.
  3. AThe operator sets the rubric, AI scores the whole market, and the rep works a tier and a move, not a list.
  4. NReps saw why an account ranked, so they trusted the order and worked the top, not their personal favorites.
  5. TRevenue-bearing opps ran about four times the prior rate, and 74% of opps scored strong-fit.
RUN THE PLAY YOURSELFThis exact build is a playbook. Run it on your own data.
→
01 / HOW WE APPROACHED THE PROBLEM

Ran the loop.

The pipeline was full of accounts a rep could not tell apart, and scoring one deal at a time was never going to fix that. The call was to put the entire market through one rubric: fit for the base, product for the lift, intent capped so it can only help. Every account came out the other side with a tier and a first action, so a rep could work the list top-down without a research project.

  1. 1
    One rubric for the whole market

    ICP fit earns the base, 40 to 70. Product engagement adds up to 30, the loudest and most honest signal. Buying signals add up to 20, bounded so they can only ever help, never carry a bad-fit account.

  2. 2
    Three stages, one engine

    Fit, product, and intent are scored separately and stacked, so the number always shows its work and no single signal can hide behind another.

  3. 3
    Every account gets a tier and a move

    The output is not a score in a vacuum. It is a tier, Strike or Hot and down, and a specific first action per account, by role, so a rep never has to ask what to do next.

02 / WHAT IT TOOK CROSS-FUNCTIONALLY

Nobody ships this alone. Here is who had to move.

One rubric for the whole market only holds if the functions feeding it agree on what the market is.

MARKETING
ICP alignment.

The fit base of the score is a shared definition. Sales and marketing scoring the same market on the same ICP is what kept the ranked list from being two lists.

REVOPS
Score into routing.

A rank that lives in a warehouse is trivia. The tier and next move landed in the CRM, routed, so the top of the list was what a rep saw first.

03 / HOW WE TURNED IT INTO A SALES MOTION · THE PEOPLE PART

Scoring the whole market ranked the list. Teaching reps to read it is what made it move.

A ranked TAM is only useful if a rep knows why an account is near the top and what to say to it. The leadership half was turning the score into a prospecting motion the team could actually run.

THE FRAMEWORK BEHIND IT
SMART Prospecting off the ranked list

The score tells the rep where to spend the hour; SMART tells them what to open with. Show you understand why this account scored, map the problem the signals point to, acknowledge the cracks, reveal the impact, take action.

  1. 01
    Made the score legible to the rep

    Reps saw why an account ranked, so they trusted the order and worked the top, not their personal favorites.

  2. 02
    Paired the tier with a motion

    A top-tier account got a different play than a mid-tier one, and I coached the difference instead of one blanket cadence.

  3. 03
    Fed conversions back into the rank

    What actually closed re-weighted the score, so the list got smarter every quarter.

Work the ranked list →
04 / WHAT I LEARNED

Not proof. Just what the build taught me.

  1. 01
    Score the market, not the deal

    Scoring one deal at a time does not fix a full, useless pipeline. One rubric across the whole TAM is what lets any account show its tier and its next move.

  2. 02
    Cap intent so it can only help

    Product engagement is the loudest and most honest signal, so it earns up to 30. Buying signals are bounded so they can never carry a bad-fit account.

  3. 03
    The number has to show its work

    Fit, product, and intent are scored separately and stacked, so no single signal can hide behind another. That visibility is why reps trusted the order.

05 / THE WORKFLOW

The runnable version. Copy it into your stack.

DeeplineAmplitudeCommon RoomSalesforce
[ SALES OPERATOR ]

Scoring the TAM

Heath Barnett · Sales Operator
G / Groundthe problem that started all of it, with the receipt and the cost
Prioritization

The pipeline was full and useless.

Every account looked like every other, so reps worked whoever was on top, not whoever was ready.

Drag

Scoring one deal at a time does not fix it.

You have to score the whole market on one rubric so any account shows its tier and its next move.

A / Assignthe build, block by block, and who owns each one. Open a step to see it run.
HUMAN + AI, IN THE LOOP
The operator sets the rubric; AI scores the whole market on it; the rep works a tier and a move, not a list.
Set the rubric
The operator01
Define one rubric for the whole market
Details
ICP fit earns the base 40-70; product adds up to 30; intent up to 20, bounded so it can only help.
Human
Score the market
Deepline02
Score ICP fit
Details
The base of the score, run weekly across the whole TAM.
AI
Amplitude03
Add product engagement
Details
The loudest and most honest signal, up to +30.
AI
Common Room04
Add buying signals, capped
Details
Bounded so intent can only help, never carry a bad-fit account.
Powers up with
AI
Route the move
Deepline05
Stack the score and assign a tier
Details
Strike or Hot and down. The number always shows its work.
AI
Salesforce06
Work the top of the list
Details
Any account, its tier and its first action, no research project.
Human
N / Normalizethe motion that made it stick
A workflow without a motion is dead. This is how it became the way the team works.
1

Made the score legible to the rep

Reps saw why an account ranked, so they trusted the order and worked the top, not their personal favorites.

2

Paired the tier with a motion

A top-tier account got a different play than a mid-tier one, and the difference got coached instead of one blanket cadence.

3

Fed conversions back into the rank

What actually closed re-weighted the score, so the list got smarter every quarter.

T / Tie backthe result it drove, and how they know
RESULT · 01

74% of opps strong-fit

scored on one rubric.

RESULT · 02

100% of outbound

inside the strike zone.

RESULT · 03

14 of 19 opps

from strong-fit accounts, not look-alikes.

OUTPUT · 01

One scoring rubric

Fit, product, and intent, stacked.

OUTPUT · 02

A tiered TAM

Every account, Strike to cold.

OUTPUT · 03

A next move per account

By role, ready to work.

The Sales Operator
06 / HOW YOU DO IT TOO

Here is what I built. Here is how you build it.

The whole thing installs as one plugin. Or grab the skills a la carte. Everything on this page, runnable, on what you paste today.

✓ EVAL PASS · 4/4
THE PLAYBOOK · ONE INSTALL
Score the whole market, then work the top

4 skills chained into one runnable play. Installs as a single plugin, no copy-pasting each skill. It runs on what you paste; connect your stack to go live.

SEE THE FULL PLAYBOOK →
SEE IT RUN IN CLAUDE
EXAMPLE CHATMorgan, a RevOps lead, running the loop in one sitting
M
Leadership keeps saying our ICP is 'mid-market SaaS' but that's not a real definition. Can you tighten it?
S
Step 1· Icp Analyst
Rolled firmographics, product usage, hiring intent, and tech stack into one 0-100 fit read and broke it down by source so we see what's driving fit. Also flagged where our current scoring tool is calling fit wrong.
Receipt
ICP fit model built, per-source breakdown showing tech-stack and headcount as the two strongest signals.
M
Now run our whole account universe through that and rank them.
S
Step 2· Icp Scoring
Scored every account into a stack rank with a reason on every row, kept it fair across inbound and outbound, and never scored a blank field as a zero. Applied the gates and escalators so a single strong signal can lift an account.
scored2,400
strike310
Receipt
2,400 accounts stack-ranked with a why each, 310 landing in the strike zone.
M
Take that strike-zone group and turn it into an actual target list for the reps.
S
Step 3· Outbound List Builder
Ran the strike-zone accounts through fit gates, tiered them, and tagged the personas to hit inside each one, keeping the reason each account earns its spot. Reps get a list they can work, not a spreadsheet dump.
tier A90
tier B140
Receipt
310 strike-zone accounts turned into a tiered list, top 90 flagged tier A with personas attached.
M
Of that list, which do we work this week and what's the next move on each?
S
Step 4· Prospecting Analyst
Sorted every lead into hot, engaged, cold, or never-touched, computed how many days each has gone dark, and named the next move per lead so nobody guesses. The hot and engaged ones float to the top of the queue.
hot22
engaged48
Receipt
Full list turned into a ranked work plan, 22 hot leads with a named next move, ready for the team Monday.
THE SKILLS IT USES
Find where the funnel leaks and what to fix.
strike-zone-analyst
Find what your wins, losses, and churn share.
pattern-analyst
Get a ranked slate of customers to interview.
icp-interview-finder
THE OTHER HALF · LEAD THE TEAM
Work the ranked list→
I write up one of these a week. Free, receipts only.
RELATED BUILDS
The ICP Playbook
A real ICP is a person and a problem, not a headcount band
The Win/Loss Backtest
The #1 predictor of a win was not in the model
THE MARKET ON THIS
The craft behind it: SMART Prospecting (PLAN Selling)Account prioritization: a practical guide to signal-based targeting (Common Room)The account prioritization GTM playbook (Koen Stam)Doing B2B account scoring the right way: models and examples (Demandbase)