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Pipeline & Deals
AI Customer Scoring
Scores every account and lead on fit and intent, trained on your own historical wins.
Reps who work leads in the order they arrived spend their best hours on the wrong people. This build scores every account and lead on fit and intent, trained on your own wins and losses rather than a generic model. Each record gets one ranked score with the reasons behind it, refreshed on your schedule, inside the CRM your team already uses every day.
- One ranked fit and intent score on every account and lead
- Trained on your own historical wins and losses
- Clear reasons shown with every score change
$2,900
20–30 working days
Optional maintenance $249/mo
What it is
AI Customer Scoring is an agent that scores accounts and leads on fit and intent, trained on your historical wins and losses rather than a generic industry model. Reps see one ranked score per record, refreshed on your schedule, inside the CRM they already use. Fit and intent signals come from your CRM and deal history.
Why businesses buy it
Generic lead scores are easy to ignore because they do not match how your customers actually buy. Reps fall back on instinct, and good accounts wait while weak ones get calls. This build learns from your own closed deals which signals matter, then ranks every account and lead so reps start each day with the right list. Because every score shows its reasons, reps trust it and managers can challenge it. The scoring criteria, data sources and refresh schedule are written into the scope before you order.
Problems this solves
Reps chase whoever shouted last, not whoever is likeliest to buy
Each account and lead gets one ranked score for fit and intent, shown inside the CRM your reps already use. They can plan their day by likelihood instead of inbox order.
Generic lead scores ignore what your own wins look like
Scoring is trained on your historical wins and losses rather than a generic industry model. Fit and intent signals come from your own CRM and deal history.
Lead scores go stale because nobody updates them
Scores refresh on the schedule you set, so a lead that becomes active rises up the list. Results are checked against three months of your history before launch.
A good fit if
You close deals often enough to have a real pattern of wins and losses, and want the score to reflect that pattern instead of a generic firmographic guess.
Your reps currently chase leads in whatever order they arrived, and you want a ranked list based on fit and intent instead.
You keep deal outcomes, firmographic data and activity history in a CRM such as HubSpot, Salesforce, Zoho CRM or Pipedrive.
You want the score refreshed automatically and delivered to one dashboard, report or alert channel, not recalculated by hand each week.
Not the right fit if
You want the system to act on a high score by drafting outreach itself. See AI Upsell Agent or AI Cross-Sell Agent, which turn scores into offers.
You need insight from call recordings, not CRM records. See AI Sales Call Analysis.
You want scoring bundled with pipeline mapping, forecasting and call analysis in one connected system. See AI Revenue Intelligence.
Your CRM records are too inconsistent to score reliably yet. AI Revenue Operations Assistant fixes stage rules and data quality first.
How it works
- We connect read-only to your CRM and pull closed-won and closed-lost history, firmographic fields and activity data from up to three sources.
- The scoring model learns which combinations of fields actually preceded a win in your business, not a published industry benchmark.
- Every open account and lead gets a fit score and an intent score, ranked so your reps see who to call first.
- Scores refresh on the schedule you set and appear in the one dashboard, report or alert channel you chose at intake.
- We test the model against three months of your own closed deals before handoff, so the ranking reflects real outcomes, not assumptions.
- You get a written explanation of what drives each score, so reps can see why an account ranked high, not just the number.
What you provide within 72 hours
Your portal lists these the moment you order. Delivery starts the working day after everything is in and your access is checked.
- Read-only access to each CRM or data source the score is built from.
- Your definitions of a qualified account, so fit means the same thing to the model as it does to your team.
- At least three months of closed-won and closed-lost history for training and testing.
- The report recipients and the channel you want scores delivered to, whether that is email, Slack or a dashboard.
- Admin access and API keys for every connected system, shared by adding our team as a user or creating a key you control, never by email.
- Your business information (company basics, hours and brand voice), shared during intake.
- One decision-maker who can approve the scoring criteria before it goes live.
- An API key for your own AI model account (for example OpenAI or Google Gemini), created for this build with a spending limit.
The 72-hour rule. Send everything on your checklist, including access, within 72 hours of ordering so your build starts on time.
Timeline
Start
Intake verified and scoring criteria agreed.
Weeks 1–2
Data connected and the scoring model built.
Week 3
Fit and intent logic tuned against your history.
Weeks 3–4
Score checked against three months of closed deals.
Week 4
Your review and two rounds of changes.
Go-live
Live, recorded handoff session, support starts.
| Option | Delivery time | Price |
|---|---|---|
| Standard | 20–30 working days | $2,900 |
| Express | 15–25 working days | $3,400 |
| Rush | 10–20 working days | $3,900 |
What you receive at handover
- AI Customer Scoring configured, showing one fit-and-intent score per record in your CRM
- Read-only connections to up to three data sources, with scoring guardrails
- One dashboard or recurring report with up to five alerts
- A test report comparing scores with three months of your won and lost deals
- An admin guide, a recorded handoff session and 30 days of post-launch support
Expected benefits and how to measure them
- Helps reps spend more time on accounts that resemble past wins
- Can make the lead handoff from marketing to sales less contested
- Makes prioritization consistent across the team
- Conversion by score band
- Each month, compare win rates for high-scored and low-scored records using a CRM report.
- Time to first contact on top-scored leads
- Compare created date with first activity date for high-scoring leads, before and after launch.
- Pipeline from top-scored accounts
- Track the value of opportunities opened on top-band accounts each quarter in your CRM.
Before you start: Record your current lead-to-opportunity rate and average time to first contact. Write down how leads are prioritized today.
These are things to track, not promised results. Outcomes depend on your data, your team and your market.
Running costs
The build price is one-time. Running the score costs roughly $20 to $150 a month, covering AI model usage and the hosting or scheduler that refreshes it.
AI usage during the build and testing is billed to your own accounts, so every provider relationship stays yours. Nothing runs through us.
Ask about running costsCustom requirements
Add a note at checkout if you need something specific. If it fits within the Scope Card it is simply included. If it goes beyond it, you get a written Change Quote within two working days, and that work starts only once you accept it, with its time added to your delivery date.
Request a custom versionKeep it running
After launch, monthly maintenance keeps scores accurate as your market shifts. It covers monitoring, fixes, updates, a health report and change hours to retune the model after a new product line or a change in your ideal customer. Maintenance starts after the 30 days of support and can be cancelled any month.
$249/mo (the minimum fee, includes 2 change hours)
Optional. Starts after the post-launch support period. Cancel any month.
How maintenance worksHow this compares
| Do it yourself with a SaaS tool | Hire a custom agency | Upmark Labs | |
|---|---|---|---|
| Price | A lead-scoring tool charges a monthly fee per seat or per record | A data agency quotes after a discovery phase | Ours is one fixed price, shown before you buy |
| Scope | A lead-scoring tool ships a generic model you must retune yourself | An agency agrees scope during the project | Ours is written on the Scope Card before purchase |
| Delivery | A lead-scoring tool is quick to install but slow to trust | An agency usually takes several weeks, set per project | Ours has a fixed delivery time shown before you buy, with faster options |
| What drives the score | A lead-scoring tool often hides its own logic | An agency build depends on what was agreed | Ours explains what drove each score in plain language |
| Training data | A lead-scoring tool uses industry benchmarks by default | An agency build depends on what was agreed | Ours trains on your own closed-won and closed-lost history |
Questions about this product
What data does the score actually use?
Closed-won and closed-lost history, firmographic fields and activity data from up to three read-only sources you connect, most often your CRM. The model looks for the combinations that preceded a real win in your business, not a published industry pattern, so the fields that matter depend on what you sell.
Can reps see why an account scored high?
Yes. Each score comes with a short explanation of the fields that drove it, delivered alongside the ranked list in your dashboard, report or alert channel. Reps see the reasoning, not just a number, which is what makes them trust it enough to act on.
How much history do you need to train it?
At least three months of closed-won and closed-lost records, though more history gives the model a stronger pattern to learn from. If your sales cycle typically runs longer than three months, tell us during intake and we adjust the testing window before the build starts, at no extra cost.
What does it cost to keep the customer scoring model running?
Roughly $20 to $150 a month for AI model usage and the hosting or scheduler that refreshes the score, paid directly in your own accounts. Monthly maintenance is optional if you want ongoing tuning. Its change hours cover retuning the model after a new product line or a change in your ideal customer, and you can cancel any month.
How soon can it go live?
The build follows a fixed schedule that starts once your CRM access and historical data are confirmed. The exact date is shown on this page before you buy, along with express and rush options if you need it sooner. Your CRM access, ideal customer profile and closed-deal history are due within 72 hours of ordering, and each day late moves delivery by 3 working days.
Can I change what counts as a qualified account later?
Yes, within the two rounds of changes included in the build, and afterwards through monthly maintenance if you keep it. Redefining your ideal customer profile after a new product launch or a shift in strategy is exactly the kind of change the monthly change hours are meant to cover.
Does it replace our CRM's own lead score?
It can run alongside your CRM's native score or replace it entirely, whichever you prefer. Many teams keep both scores visible during the first month, then retire the older one once this model proves it ranks accounts closer to what actually closes deals in practice.
What if two accounts score the same?
The dashboard shows both accounts, ranked by the secondary signals you agreed at intake, such as recent activity, deal size or last contact date, so reps still get a clear working order instead of a tie they would otherwise have to break themselves by guesswork.
Stop working leads in the order they arrived.
Order AI Customer Scoring and get a ranked, explainable score trained on your own history, on a delivery date you see before you pay.
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