Churn research service cover

Churn research service

Combines customer explanations with account chronology without assuming causation.

See the demo site Get this built for you

For
Customer success leaders at B2B subscription firms
Solves
Exit reasons are too shallow to inform product decisions.
Delivers
Churn evidence report and research backlog
Built in
about 3 weeks of creation time, MVP in 3 days
Investment
$6,500 for the MVP, $22,500 for the full product
Run it
Inside your business, or as part of your offer to clients
01

What it does

For customer success leaders at B2B subscription firms, turn authorized exit interviews and account history into churn evidence report and research backlog.

  1. Plan exit interviews.
  2. Preserve customer context.
  3. Compare stated reasons.
  4. Examine timeline evidence.
  5. Flag alternative explanations.
  6. Propose product questions.

What goes in, what comes out

What the customer puts in
  • Authorized exit interviews
  • Account history

AI drafts, people review. Research evidence workspace with reviewed deliverables.

What the customer gets
  • Churn evidence report
  • Research backlog
02

How it works

The workflow

  1. In
    Start with

    Authorized exit interviews and account history

  2. 1

    Agree the decision and research questions

  3. 2

    Define permitted sources or participants

  4. 3

    Collect evidence

  5. 4

    Code findings

  6. 5

    Compare supporting and contradictory material

  7. 6

    Review interpretations

  8. 7

    Deliver a cited brief with next questions

  9. Out
    Finish with

    Churn evidence report and research backlog

AI does the heavy lifting, people stay in charge

Assist with retrieval, transcription, structured extraction and thematic synthesis. Preserve source passages and methodological context. Human researchers validate inclusion, quotations and conclusions. Use real participants when customer research is required.

What your team sees

Key screens: Exit study, evidence themes, product questions. Organize work by research question. Show a source library, an evidence matrix and a draft findings panel with linked quotations. Keep contradictory findings and unanswered questions visible. Allow reviewers to inspect the original context before accepting an interpretation. In this product, the first view is exit study, followed by evidence themes and product questions.

Accounts and administration

Source provenance, participant consent where applicable, research questions, coding definitions, reviewer disagreements, citations and versioned conclusions.

Integrations and data access

Product feedback, authorized interviews, usage exports and requirement records. Permitted research libraries, interview recording imports, citation exports and document editors. Preserve original source metadata throughout the workflow. These are candidate integration categories, not verified supported connectors.

03

How we build it

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

  1. 1

    Scoping call

    Day 1

    Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

  2. 2

    MVP

    3 days

    One buyer segment, one recurring use case; first modules: plan exit interviews; preserve customer context. Manual review in the loop. Built by our AI software factory.

  3. 3

    Paid pilot

    4 days

    Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

  4. 4

    Full product

    7 days

    Remaining modules: examine timeline evidence; flag alternative explanations; propose product questions. Self-serve onboarding, billing, monitoring and the wider integration set.

  5. 5

    Run and improve

    Monthly

    We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

  1. Pick the riskiest assumption. Here: will customer success leaders at B2B subscription firms use it to solve "exit reasons are too shallow to inform product decisions"?
  2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
  3. Run a paid pilot. Answer one practical question using a bounded evidence set.
  4. Measure, then decide. Track interview insight quality and tested improvements. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Begin with customer success leaders at B2B subscription firms and one recurring use case. Build the first two modules: plan exit interviews; preserve customer context. Provide operator assistance for the third module: compare stated reasons. Deliver churn evidence report and research backlog through a manual review queue. Perform other necessary full-scope functions manually during the pilot. Include all applicable access, accuracy and professional-review controls from the start.

After the MVP. After paid pilots establish value, automate the remaining modules: examine timeline evidence; flag alternative explanations; propose product questions. Add one validated source integration, reusable customer configuration and recurring delivery. Expand to additional teams, document formats or languages only after testing the new scope.

What the build depends on. A clear research protocol, source access, citation tracking and qualified interpretation. Interview work also needs relevant participants and consent management.

04

Investment

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

  1. Phase 1

    MVP

    One buyer segment, one recurring use case; first modules: plan exit interviews; preserve customer context. Manual review in the loop.

    $6,500 · about 3 days of creation time

  2. Phase 2

    Paid pilot

    Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

    $6,500 · about 4 days of creation time

  3. Phase 3

    Full product

    Remaining modules: examine timeline evidence; flag alternative explanations; propose product questions. Self-serve onboarding, billing, monitoring and the wider integration set.

    $9,500 · about 7 days of creation time

Indicative total, MVP to full product$22,500about 3 weeks of creation time · start with the MVP from $6,500

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

StageHosting and infrastructureAI usageTotal per month
MVP and paid pilotabout 3 customers$30–$60$80–$160$110–$220
Full productabout 50 customers$110–$210$880–$1,750$990–$1,960
05

Run it or resell it

Internally

For your own team

Customer success leaders at B2B subscription firms run it inside the business: authorized exit interviews and account history in, churn evidence report and research backlog out, reviewed by your people.

For your clients

As part of your offer

Agencies, consultancies and software companies can offer it to their own clients under their brand. We build and maintain it; you sell and deliver it.

Your brand, or this one

Run it under your own brand, or start from this concept style.

  • primary#712791
  • accent#66c954
  • surface#ede4f1
  • ink#22201e
Headings
Fraunces
Text
Inter
Voice
Curious, rigorous, user-led
Selling it to your own clients: the go-to-market playbook

Pricing to test

Test USD 750-3,000 for one tightly bounded research question and evidence pack. Participant recruitment, specialist review and licensed data are separately scoped. Repeat tracking can become a retainer. Prices are hypotheses.

Message to test

Churn research service for customer success leaders at B2B subscription firms. Combines customer explanations with account chronology without assuming causation. Demonstrate the claim through an anonymized churn research brief.

Where to find buyers

Customer success consultants

Lead magnet

An anonymized churn research brief

The first 30 days

  1. Week 1: interview five prospective buyers in this segment: customer success leaders at B2B subscription firms. Ask to see a recent example of the problem and their current process.
  2. Week 2: prepare this demonstration using authorized or synthetic material: an anonymized churn research brief.
  3. Week 3: present it through customer success consultants and seek one narrowly scoped paid pilot.
  4. Week 4: review interview insight quality, tested improvements, total delivery effort and a concrete renewal decision before increasing scope.

Paid pilot

Answer one practical question using a bounded evidence set. Ask a domain expert to review citations and reasoning, identify contrary evidence and assess whether the deliverable supports the intended decision. For this solution, use authorized exit interviews and account history and evaluate churn evidence report and research backlog. Agree success thresholds with the buyer before starting; collect a baseline for interview insight quality, tested improvements. A positive signal is payment and repeat use with acceptable quality and delivery cost, not a favorable demo reaction alone.

Success metrics

Interview insight quality, tested improvements

Retention and expansion

Maintain the research question and evidence archive, offer follow-up studies and refresh important sources. Build repeat work around the buyer’s decision cycle.

Why clients would pick it

Niche research protocols, credible researcher relationships and a rights-cleared evidence archive with consistent interpretation methods. For this solution, build around combines customer explanations with account chronology without assuming causation. This advantage requires execution and accumulated customer trust; the base model alone is not a defensible asset.

Alternatives and positioning

Research consultants, internal analysts, literature databases and general search or summarization tools. Differentiate on this specific proposed advantage: combines customer explanations with account chronology without assuming causation. Test it against the buyer's current method on the same task. Competitor coverage and uniqueness have not been established.

Main delivery costs

Researcher time, source access, participant recruitment, transcription, evidence coding, expert review and report revisions.

06

Safeguards

Use consented research and preserve contradictory evidence. Separate observed user behavior, proposed explanations and untested product assumptions. Validate source access and reviewer availability during the pilot. Maintain customer-level access, data deletion controls and a record of final approvals.

Get this solution built

Built for you by our AI software factory, MVP in about 3 days. Tell us about your business and how you want to run it: inside your company, or as part of what you offer your clients. We reply within one working day.

More in Product Development

Bring one process you are sick of. In thirty minutes we will tell you whether it can run itself. Book a call.

© 2026 Nexibeo LimitedFounded 2017contact@nexibeo.com