Next-best-action on autopilot:
what to do with this lead, not just its score
A lead score tells a manager who to call first, but not what to actually say or offer once they pick up. We build a model that suggests the specific next action for each lead or account, call now, send this content, offer this upsell, wait, trained on what actually worked for similar cases in your own CRM history.
The process today
Most CRMs tell a manager where a lead sits, what stage, how old, how big, but stop short of suggesting what to actually do next. That gap gets filled by instinct and habit: a manager calls the leads they feel like calling, sends the follow-up email they always send, offers the discount they always offer, regardless of whether that specific action is what actually worked for similar leads in the past.
The pattern that would answer “what should I do with this one” usually exists in the CRM’s own history, deals with this profile that responded well to an early call versus deals that responded better to a content piece first, accounts that upsold successfully after a specific trigger versus ones where an upsell attempt too early backfired, but nobody has connected that history to the lead or account sitting in front of a manager right now.
The result is a sales or success team operating on personal habit rather than on what their own collective experience, recorded in the CRM but never analysed, actually says works.
What the agent does
The model trains on your CRM’s own outcome history, what actions were taken at each stage and what happened next, and learns which actions tend to precede a good outcome for which kind of lead or account. For each live lead or account, it suggests a specific next action, call now, send this content piece, offer this upsell, or wait because the data suggests this one is not ready, with the pattern behind the suggestion shown in plain language.
The suggestion shows up inside the CRM itself, as a field or a note on the record, so a manager sees it exactly where they are already working instead of needing to check a separate tool. When a manager follows a suggestion or deliberately ignores it, that choice and its eventual outcome feed back into the model, so it learns over time not just from what worked historically but from where its own suggestions proved useful in practice.
Before go-live, the model’s suggestions are checked against your past won and lost deals, so you can see what it would have recommended for cases you already know the outcome of, and whether that recommendation would have been the right call.
What stays with humans
The actual conversation, the specific words used, and the final judgment call on any lead or account stay entirely with the manager. The model suggests an action and explains the pattern behind it; it does not take the action itself, send a message, or commit to an offer without a person deciding to do so.
Guards
Every suggestion is logged with the reasoning behind it, and whether it was followed, along with the eventual outcome, so the model’s usefulness is tracked over time rather than assumed. A backtest against past deals runs before go-live, and a kill switch removes the suggestion feature from the CRM in one message if it ever looks unhelpful or wrong.
Price and timeline
| Option | Price | What it covers | Timeline |
|---|---|---|---|
| Single automation | from $900 | CRM outcome model, in-CRM suggestions, feedback loop | 7 to 14 days |
| Department package | from $2,800 | Next-best-action across sales and customer success teams | 3 to 5 weeks |
Running cost is usually $25 to $90 a month in model usage depending on CRM record volume.
Related
Pair this with lead scoring so prioritisation and action suggestion work together, and with sales pipeline hygiene alerts so a stuck deal’s next-best-action gets surfaced before it goes cold. The full package breakdown is on the AI agents service page and the automation-everything overview; for real CRM-driven sales results, see the seven-channel AI sales agent case study and the real estate lead routing case study.
Ready to see what your own CRM history says actually works? Get in touch and we will look at your deal history in the first call.
Tired of doing this by hand? We can take the whole routine off your team, not just this step: Routine takeover, from $400 →
FAQ
How much does next-best-action automation cost?
From $900 for a model trained on your CRM's outcome history, live in 7 to 14 days. A department package adding it across sales and customer success usually starts at $2,800.
How is this different from lead scoring?
Scoring ranks who to prioritise; this suggests what to actually do with them once prioritised, call, send a specific piece of content, offer a specific upsell, or wait because the data suggests now is not the moment.
Does it tell managers exactly what to say?
It suggests the type of action and often the specific offer or content piece that historically worked for similar leads or accounts; the actual conversation and wording stay with the manager.
What if a manager disagrees with a suggestion?
They can ignore it, and that choice feeds back into the model as a data point, so over time the model learns not just from outcomes but from where its own suggestions were and were not trusted.
What CRM data does it need?
Deal or account history including what actions were taken at each stage and what the outcome was, won, lost, upsold, churned. More labelled outcomes produce sharper suggestions.