Dimension Labs

Industry

Member experience analytics for fitness, golf and recreation

Read every member review, survey and cancellation reason. Find which issue at which club actually drives churn.

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Ask Which club issue actually drives member churn?

We work with enterprises such as NBA, Travelers, Mars and Concentrix.

[01] The problem

Members tell you why they're leaving months before they cancel.

Cancellation reasons are a dropdown. The real reasons, broken equipment, crowding, a cancellation process that feels like a trap, are written in reviews and surveys nobody joins to churn.

Right now

01Cancellation reasons come from a dropdown
02Equipment and cleanliness complaints are read club by club
03Churn models flag members but never explain them
04Course and club comparisons stall on inconsistent feedback
05Retention offers go out without evidence

Churn is a lagging number. What members said last month is the leading one.

[02] EnrichOne record, structured

Language in. Structured data out.

Every record is read in full and written back with dozens of typed Dimensions, the same way every run. Here is what that looks like for fitness, golf and recreation.

enrichment · one record

Raw text

Half the treadmills have had out-of-order signs for a month. Tried to cancel at the front desk and was told it has to be done by certified mail. Moving to the gym down the road.

Google review · member · club joined

Dimensions written to the record

Facility & Cleanlinessequipment broken · 1 month
Reliability & Defect Typeequipment
Churn & Cancellation Riskcancelling
Effort Levelhigh · mail-only cancel
Trust & Honesty Signallow
Competitor Mentionednearby gym

Each colour links a phrase in the raw text to the Dimensions extracted from it. Hover either side.

[03] The product

3.1 · Read everything

Every record, enriched.

Start with one export of member reviews, NPS surveys and cancellation notes, or connect every channel. Every record comes back with typed Dimensions like facility and cleanliness, churn and cancellation risk, effort level, staff interaction quality and loyalty signal, written the same way every run, then joined to club, membership tier, visit frequency and tenure.

Read every record, not a sample
Join each record to club, membership tier, visit frequency and tenure
Add your own Dimensions in plain English
Backfill years of history in the same run

dimension labs · blend

3.2 · Prove the cause

Ask why. Get proof.

Ask in plain English. The agent writes the queries, controls for what would confound the answer, and ranks each issue by its measured effect on cancellation and visit frequency, with an effect size and a confidence interval. Findings that fail the robustness checks are never reported as causal.

Which club issue actually drives member churn
Find the members at risk, and the reason
Compare every club or course on the same Dimensions
Test whether a retention offer changed anything

dimension labs · ask

Example finding

Which club issue actually drives member churn?

See the Planet Fitness member churn monitor: 28 Dimensions across public Google Maps reviews, tracked as a live causal monitor.

Published artifact · public reviews

3.3 · Deliver

Ask for the report. Get the report.

Ask for the readout your club and regional leaders needs and the agent builds it: summary, ranked findings, charts and recommendations, each figure checked. Schedule it weekly or monthly on fresh data, or publish it as a live monitor.

Produce the monthly readout without building it
Publish a live monitor leadership can open and question
Track whether the fix you shipped moved the number
Export to PDF, slides or your BI tool

dimension labs · report

[04] How the platform worksRuns daily

From raw conversations to a proven answer.

Language from every channel and your business data flow into one pipeline that enriches, governs and tests every record, then delivers wherever your team works.

Language · 37 sources

ZendeskIntercomSalesforceLiveChatDriftSlackQualtricsMedalliaSurveyMonkeyQuestionProGenesysAmazon ConnectAvaya Cloud8x8TwilioSMSAdaKore.aiYellow.aiCognigyRasaMicrosoft Bot FrameworkAmazon LexAmazon AlexaOracle Digital AssistantBotcopyCapacityFacebook MessengerKikX (Twitter)OpenAIEmailCall recordingsApp store reviewsGoogle reviewsOpen-ended surveysCommunity forums

Business + world data

SnowflakeDatabricksBigQueryAmazon S3Salesforce CRMCSV + ExcelREST APIRevenueOrdersRenewalsUsage eventsLoyaltyStore + location dataWeatherSeasonalityMarket events

Dimension Labs pipeline · Runs daily

Ingest + normalizeEvery channel and language into one schema

EnrichDozens of Dimensions written onto every record

Map + governValidated for drift, versioned, the same fields every run

Analyze + proveJoined to outcomes and tested for cause

Where it goes

Dimension Labs agentAsk, report, schedule

Your warehouseSnowflake, Databricks, BigQuery

BI toolsTableau, Power BI, Hex

Claude and ChatGPTvia MCP · coming soon

[05] ArtifactsBuilt by the agent