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Sayfitech
Data & analytics

Customer analytics

Segmentation, lifetime value, behaviour and retention modelled end to end.

Engagement
Fixed-scope build
Typical timeline
6–8 weeks
Starts with
Two years of subscription or order history, anonymised if you would rather.
01The situation

Churn gets reported as one monthly percentage, which tells you the building is on fire without saying which floor. Accounts rarely leave suddenly, they go quiet for eleven weeks first, and nobody is watching for quiet.

Why it matters

Spend concentrated on the customers worth having.

One number everyone trusts.

What we build

Concrete artefacts, handed over and documented.

  1. 01

    Cohorts by signup month, plan, channel and first action, so a retention difference has somewhere to point

  2. 02

    Lifetime value computed on margin rather than revenue, with every assumption written beside it

  3. 03

    A churn signal model: the behaviours that precede cancellation, ranked by how far ahead each one warns

  4. 04

    Health scores pushed into the tools your team already works in, so the signal lands in front of someone who can act

  5. 05

    Segment profiles describing who stays, who leaves, and what the difference is worth over a year

What changes

01

At-risk accounts surface weeks before they cancel, not on the day

02

Retention effort points at the segment where it pays rather than at the average

03

Lifetime value stops being a number nobody can reproduce on request

How it runs

  1. Weeks 1–2

    01Cohort baseline

    We rebuild your history into cohorts and establish what normal retention looks like for each one.

  2. Weeks 3–6

    02Signals

    Behaviour modelling to find what precedes cancellation, tested against customers who have already left.

  3. Weeks 7–8

    03Into the workflow

    Scores land in your CRM and support tool with a reason attached. A score without an explanation gets ignored.

06Typical stack

Chosen per project. Named here so you can see the shape of it.

  • BigQuery
  • dbt
  • Python
  • HubSpot
  • Metabase

Questions we get asked

Next step

Tell us the outcome, not the tooling.

Send us the situation you are in. We will tell you which discipline it belongs to, what we would do first and what it costs, including when the answer is to wait.

Start a projectOr email us directlyinfo@sayfi.ai