Evaluate every accountfor what comes next.
Define what good looks like for each motion. Trailspark brings product activity, marketing engagement, CRM history, warehouse data, and web behavior into one account story. Then it evaluates the evidence, explains why, and sends the result back to the tools your team already uses.
“A trial worth pursuing: a technical evaluator wiring up the product while a champion keeps returning to pricing, with extra weight when several people share one work domain.”
Account evidence changes, the account is re-evaluated under the lens that applies, the reason changes, and the downstream action follows.
Built for RevOps, Marketing Ops, and Growth.
Teams at B2B PLG companies that need every account scored, explained, and sent back to the tools they already use.
The core insight
Same signal. Different meaning.
Every prioritization model has to answer one question: what is a unit of activity worth? An API call, a workflow run, a credit consumed. Most models answer once, in general. The honest answer depends on the account it came from and the question you are asking about that account.
Same measurement, different account
100 events
At a 150-person company
That volume could mean real adoption taking hold.
At a 15,000-person company
The same count may be one team kicking the tires.
Same signal. Different meaning.
Same behavior, different question
Several pricing-page visits
For a new trial
That may support an acquisition evaluation.
For an existing customer
The relevant question may be expansion.
Same behavior. Different question.
Same negative signal, different evidence
Low throughput
On its own
Low throughput is real negative evidence.
In a young trial
Early in a trial, though, it may not outweigh rapid setup across multiple apps, logs, deploy tracking, alerting, and monitoring.
The signal still matters. Its meaning changes with the rest of the account and the timing.
Signals are evidence. Their meaning depends on the account, the question, what else is happening, and when it happens.
One account, several questions
The question changes the answer.
The same account is worth a different judgment at different points in its life. Each evaluation lens carries its own eligibility rule and its own definition of good, so Trailspark evaluates the account story under the lens that actually applies to it.
Is this account behaving like one we should pursue?
- What the people in the workspace set up, and how quickly
- Whether the interest has spread past the person who signed up
eligible: free_trial = true
Is there credible evidence of broader demand or adoption?
- Usage reaching teams, workspaces, or environments outside the original deal
- The product milestones that tend to precede a bigger plan
eligible: customer = true
Does this account match the behavior we consider healthy?
- Usage health across the account rather than one power user
- Whether active people are dropping off ahead of the decision
eligible: renewal < 90 days
Motion is only one way to cut a lens. Segment, user type, and vertical work the same way. Enterprise accounts can be held to a different definition of good than SMB accounts on exactly the same evidence.
The same account can deserve a different evaluation depending on the question. Trailspark evaluates it against the definition of good that applies.
From signal to action.
Connect the tools you already run and describe what good looks like in plain language. Trailspark evaluates the whole account story under the lens that applies and writes the result where your team already works.
Ingest
Every format, every source
Resolve
Match people, accounts & context
Evaluate
The whole account against your lens
Activate
Back to where your team works
Reasoned evaluation
The reason is part of the evaluation.
A factor list shows what moved a score. Trailspark explains why the evidence supports this result for this account right now.
Counter-evidence
- One recorded user on the workspace
- APM event volume near the bottom of the trial cohort
- Zero log throughput
Supporting evidence
- Four apps created in the first three days
- Log sources connected
- Deploy tracking wired up
- Alerting and monitoring configured
Throughput is genuinely low and only one user is recorded, which counts against this account. On day 6 of a trial it reads as a setup still in progress rather than a stalled one: four apps, log ingestion, deploy tracking, and alerting were all configured inside the first three days. That breadth and speed of activation outweigh the volume gap at this point in the trial. If throughput is still flat past the second week, the same evidence supports a different call.
The evidence on both sides, weighed against when it happened, and a sentence a rep can open a conversation with.
Governed re-evaluation
Know when to look again.
New events arrive constantly, and most of them do not change the answer. Trailspark decides when an account has moved enough to deserve a fresh judgment.
Change, not cadence
A fresh look is triggered when the evidence a lens cares about has actually changed. A timer would be arbitrary, and re-reading every event would be noise.
Frequency and cost stay governed
Cooldowns hold an account steady through a busy week, and important events can pull the next evaluation earlier. Your evaluated-account count stays predictable either way.
One current answer per account
Each re-evaluation replaces the call and the reason, so the account record carries the current judgment and what moved it rather than a stack of stale scores.
The model sees a prepared account story. Trailspark handles when to evaluate it again and keeps the process consistent.
Identity, account shaping, lens assignment, cadence, and delivery are the parts a team would otherwise build and maintain around the model call.
Activation
Put every evaluation to work.
Trailspark evaluates. Your existing systems execute.
Every call lands as structured fields and alerts in the tools your team is already working in, so nobody has to live in another workspace to act on it.
Written on the account
CRM
HubSpot · Salesforce
Propensity, reason, evaluated lens, roles, and coverage as fields on the account. Your existing workflows trigger on them.
Alerts
Slack
Propensity changes, newly eligible accounts, and buying-group progress, routed per lens to the channel that owns it.
CDP
Segment
Propensity and stage as account traits, so downstream tools read the same judgment.
Marketing automation and journey tools read those CRM and CDP fields to trigger nurture, ABM entry, and lifecycle changes.
Sales
- High acquisition propensity routes or sequences the account.
- A missing buying role becomes a prospecting task instead of a silent gap.
- A new reason gives the rep something specific to open with.
Customer success
- Renewal risk surfaces the intervention while there is still time to run it.
- Expansion propensity triggers the expansion workflow the team already uses.
Marketing
- A propensity change moves the account into different nurture, lifecycle, or ABM treatment.
- A newly eligible account routes into the program built for it.
RevOps
- Trailspark fields become governed decision inputs across the stack.
- The reason, the evaluated lens, the identity mapping, and the downstream write are all inspectable.
See the people behind the account.
An account evaluation gets sharper when you can see who is creating the evidence. Trailspark infers the buying roles behind the behavior, using what people actually do alongside firmographic detail, and shows which roles are engaged, which are only identified in your CRM, and which are missing entirely. That coverage becomes part of the account context and lands as fields your team can run a play on.
Explore Buying Group IntelligenceHow Trailspark evaluates accounts · Product qualified lead scoring · Integrations
Start free. Scale with the accounts you evaluate.
Each unique account counts once per month, no matter how many times Trailspark re-evaluates it.
Reasoning is included
The written reason comes with the evaluation. No AI credits, no token meter.
The Free plan is the whole platform
Up to 25 evaluated accounts a month, with everything paid plans get.
AI lead scoring with Trailspark: common questions
Everything you need to know about AI lead scoring, PQLs, and how Trailspark works with your existing stack.
Evaluate every account for what comes next.
The evidence is already in your stack. Tell Trailspark what good looks like. It evaluates the account and sends the result where your teams already work.