Matched subscriber data
Store, subscription app, and payment gateway records joined per subscriber, with test orders and duplicates removed.
The Problem
One Blended Number Hides Three Different Problems
Your store, subscription app, and gateway each hold part of the answer. Until they're combined, one cancel rate can't show you what to fix first.
01 · Mixed signals
Your app, gateway, and inbox each tell a different story.
Orders, renewals, payment failures, and cancel reasons get matched to each subscriber.
02 · Declined cards
A spike in declined renewals hides inside your cancel count.
Failed payments get split from real cancellations, so each gets the right fix.
03 · Guesswork
The team guesses with a discount here and an email there.
Cancel reasons get broken down by product and signup month.
04 · Flat numbers
Months later, the number hasn't moved, and nobody knows why.
A report or dashboard keeps answering what to fix first.
Your subscription app says cancellations went up last month. Your payment gateway shows a spike in declined renewals. Your inbox fills with people saying the product arrives too often. Each tool tells a different story, and nobody can say which one matters most. So the team guesses: a discount here, a new email there. Three months later, the number hasn't moved, and you still don't know why.
We start by putting the data in one place. Store orders, subscription events, payment failures, and cancel reasons get matched to each subscriber. Then we split failed payments from real cancellations and break the rest down by reason, product, and signup month. You get a clear answer on what to fix first, and a report or dashboard that keeps answering it.
One subscriber, one record
Orders, renewals, payment failures, and cancel reasons matched to the same customer across tools.
Failed payments split out
Declined renewals separated from real cancellations, so each problem gets the right fix.
Cohorts instead of averages
Signup months, products, and channels compared side by side over time, not blended.
Our Analysis Process
From Raw Exports to Answers You Can Act On in Five Steps
You see which data we use and how each metric is defined before any chart gets built. Nothing hides in a spreadsheet only we can read.
We look at what your store, subscription app, and payment gateway can export. You get a short list of the questions your data can answer today, and what's missing or messy.
What's Included
What You Get Beyond a Churn Rate Analysis
Clean, matched data, chosen and failed cancellations split apart, and breakdowns your team can act on, as a report, a dashboard, or both.
Compare Options
DeveloperLook vs App Analytics vs a Spreadsheet
Your subscription app's analytics are free, and a spreadsheet costs only time. Both suit some stores. Here's where each stops answering why subscribers leave.
| Feature | DeveloperLookBest fit | App analytics | Spreadsheet |
|---|---|---|---|
| Upfront cost | Fixed, from $600 | Included in your app | Your team's hours |
| Time to answers | 1 to 6 weeks | Already there | Days per report |
| Data joined | Store, app, and gateway | App data only | Manual copy and paste |
| Failed vs chosen | Split in every view | Often blended | Only if you split it |
| Cohort views | By month, product, channel | Basic cohorts | Hard to maintain |
| Reason breakdowns | Grouped into clear themes | Raw reason list | Manual tagging |
| Data refresh | Daily, automatic | Real time, app only | When someone updates it |
| Feeds your fixes | Segments sent to tools | Limited exports | Not connected |
DeveloperLook
App analytics
- Upfront cost
- DeveloperLook: Fixed, from $600App analytics: Included in your app
- Time to answers
- DeveloperLook: 1 to 6 weeksApp analytics: Already there
- Data joined
- DeveloperLook: Store, app, and gatewayApp analytics: App data only
- Failed vs chosen
- DeveloperLook: Split in every viewApp analytics: Often blended
- Cohort views
- DeveloperLook: By month, product, channelApp analytics: Basic cohorts
- Reason breakdowns
- DeveloperLook: Grouped into clear themesApp analytics: Raw reason list
- Data refresh
- DeveloperLook: Daily, automaticApp analytics: Real time, app only
- Feeds your fixes
- DeveloperLook: Segments sent to toolsApp analytics: Limited exports
Projects We've Built
Ecommerce Projects We Have Built
Online stores and shopping apps we've built. Retention reports and dashboards plug into stores like yours.
Sefinix Furniture Ecommerce Store and Dashboard
- Furniture
- Dashboard
- E-commerce
Unicom Fashion Ecommerce App and Admin Dashboard
- Fashion
- Dashboard
- E-commerce
Havenly Furniture Ecommerce Website
- Furniture
- E-commerce
- Dashboard
Modeverse Ecommerce Web Design & Development
- Fashion
- Retail
- E-commerce
What Our Clients Say
What Clients Say After Launch
Feedback from store teams we have built for.
We had a different kind of problem. People were visiting the store, adding products to their carts, and then disappearing before they finished the order. We had tried a few apps and made changes here and there, but nothing really seemed to solve the bigger issue. The team went through the shopping experience with us and pointed out things we hadn't really noticed ourselves. They cleaned up the cart and checkout flow, made the mobile experience much smoother, and helped us make the store feel easier to shop. I’m not going to pretend we fixed everything overnight, but it finally feels like the store is helping the sale instead of getting in the way of it.
The mobile experience is probably my favourite part of the new site. We had spent a lot of time making sure the desktop version looked right, and the team kept pushing us to think about how everything would actually feel on a phone too. They were right. The navigation is clean, the interactions feel natural, and everything we’ve tested so far works exactly as it should. They also went through the links, forms, integrations, and other details more than once before launch, which I really appreciated. And even after going live, we could still reach out when something came up. The whole process felt friendly, organised, and surprisingly straightforward.
We had a pretty specific idea of what we wanted our website to become, but I wasn’t sure how easily we could explain all of it to a development team. There were quite a few moving parts, and we were working toward a deadline, so I expected a few things to get lost along the way. That never really happened. They understood what we were trying to achieve, kept us updated throughout the process, and got everything ready within the agreed timeline. The final site feels much easier to navigate, works beautifully on mobile, and is noticeably smoother for our customers. It was a huge relief seeing the original idea actually turn into the website we had in mind.
1,250+
Projects shipped
10+
Years of experience
Top 3%
Upwork Top Rated Plus
5 stars
Average review score
Want results like these?
Tell us what you are building. You get a reply within 24 hours on business days, then a written estimate.
Work Culture
Why Subscription Brands Trust Us With Their Data
Retention numbers only help when everyone trusts them. These habits keep your data clean, your definitions clear, and your findings honest.
Definitions agreed first
We define cancellation, failed payment, and active subscriber with you before any chart. Every number on the page then means the same thing to everyone.
Test orders removed
We strip test orders, staff purchases, and duplicate accounts before counting anything. Otherwise the numbers you see aren't the numbers you have.
Findings ranked by impact
We rank what we find by how many subscribers it affects and how easy it is to fix. You get a short list, not a pile of charts.
Data that feeds your fixes
Findings don't stay in a slide deck. We push segments to Klaviyo and your subscription app, so offers and retries use what we learned.
Honest about your data
If your data can't answer a question yet, we'll tell you before we quote. We'd rather fix the tracking than sell you a guess.
You own the dashboards
Dashboards, queries, and exports live in your own accounts. Your team can change a chart or add a metric without asking us.
Overview
What is churn analysis for a subscription or ecommerce store?
DeveloperLook runs churn analysis and builds retention reporting for subscription and ecommerce stores. We join store, subscription app, and payment data, separate cancellations from failed payments, and break losses down by reason, product, and cohort in a report or live dashboard. Projects start at $600 and take 1 to 6 weeks.
DEVELOPERLOOK
Project facts · Churn Analysis and Reporting
- Service
- Churn analysis and reporting (reasons, products, cohorts, dashboards)
- Typical timeline
- 1 to 2 weeks for a report, up to 6 for systems
- Platforms
- Shopify, WooCommerce, BigCommerce, and Stripe-billed subscriptions
- Built with
- Looker Studio, Power BI, Google Sheets, PostgreSQL, Python
- Experience
- 10+ years of development experience and 1,250+ shipped projects
- Post-launch support
- 30 to 90 days of post-launch support
- Communication
- Calls in US, UK, and AU business hours
- Starting price
- From $600 USD, fixed scope after a free data review
Reviewed 28 Sep 2026 by Saimul Islam
Good fit
Stores with one blended cancel rate
You know your overall cancel rate, but you can't tell whether price, product fit, or failed cards drive it.
Brands planning retention fixes
You're about to spend on save offers or a new app, and you want data showing which problem is biggest.
Teams with data spread across tools
Your store, subscription app, gateway, helpdesk, and email tool each show part of the picture, and nothing ties them together.
Founders who want plain answers
You want a churn rate analysis that explains the why in plain language, not another dashboard nobody opens.
Agencies reporting to clients
Your agency runs client churn analysis for several subscription brands and needs matched data and reports under your brand.
Not a fit
Reasons already known
You already know why subscribers leave and need the fix built. Subscription Churn Reduction builds the cancel flow and offers.
Whole-store reporting
You need reporting across your whole store, not just subscriptions. Ecommerce Reporting Software covers sales, margin, and channels.
Program only weeks old
Your subscription program is weeks old with little history. Ecommerce Subscription Platform Development comes first, and analysis can wait.
Under a hundred subscribers
You have fewer than a hundred subscribers. Your app's analytics show the same patterns, so a $600 report is more than you need.
Not sure we're the right fit?
Book a free call or message us. We'll tell you honestly whether we're the right team.
Pricing
Transparent Starting Prices for Churn Analysis and Reporting
These are starting points in USD. Your price depends on your data sources, history, and dashboard needs, and you get a fixed proposal after a free data review.
For stores that want clear answers from existing data, delivered in 1 to 2 weeks.
$600one-time, USD
- Free data review
- Up to 12 months of data cleaned
- Failed payments split from cancels
- Reason, product, and cohort views
- Written findings and a walkthrough
- 30 days of post-launch support
Recommended
For teams that want a live view refreshed daily, delivered in 2 to 4 weeks.
$1,900one-time, USD
- Everything in Findings Report
- Store, app, and gateway data joined
- Dashboard with a daily refresh
- Retention curves by cohort
- Alerts when cancellations jump
- 60 days of post-launch support
For several stores or apps, with findings fed back to your tools, in 4 to 6 weeks.
$3,900one-time, USD
- Everything in Live Dashboard
- Data warehouse for every source
- Helpdesk and email data included
- Segments sent to Klaviyo and your app
- Monthly findings during support
- 90 days of post-launch support
For Agencies
White-Label Retention Reporting for Agencies
You own the client relationship. We supply the data work: matched data, cohort breakdowns, and dashboards, delivered under your brand. Your client sees one team, and you get a reusable report template.
How the partnership works
White label: your client only ever sees your brand
- Your client
- You, the agency
- DeveloperLook
Share exports or access
Send store, app, and gateway access, plus the questions your client asks.
- Client needs
- You share the details
- Details received
We define and price
You get metric definitions, a timeline, and a fixed price per client.
- Scope and plan
- Proposal to resell
- Your quoteYOUR LOGO
Build and hand off
We build under your brand and hand over reports you can present.
- Done by our team
- Your brand on it
- Handed to your clientDone
Partner with DeveloperLookDelivered under your brand
Stay client-facing
We work under your brand, so you keep the relationship and the credit.
Reusable templates
One dashboard template, adapted to each client's apps and plans.
Clean data first
Test orders and duplicates removed before any client sees a number.
Flexible capacity
Bring us in for one client report or a quarterly rhythm.
The Right Technology for Your Project
Technology Stack
We join your store, subscription app, and payment data, then report in the tools your team already opens.
Shopify
WooCommerce
Stripe
PayPal
Power BI
Google Sheets
Google Analytics 4
Slack
PostgreSQL
Python
Google Cloud
Node.js
Gorgias
Zendesk
HubSpot
Intercom
FAQ
Frequently Asked Questions
Straight answers on what the analysis covers, the data you need, costs, and dashboards.
Saimul IslamFounder & CEO, DeveloperLookStill have questions?
Send a message or book a call with the team.
Churn reporting starts at $600 for a one-time findings report on up to 12 months of data. A live dashboard with a daily refresh costs $1,900, and a full reporting system across several stores or apps starts at $3,900. Tool fees are separate, and your quote is fixed.
A findings report takes 1 to 2 weeks, most of it spent cleaning and matching data. A live dashboard takes 2 to 4 weeks, and a reporting system across several sources takes 4 to 6 weeks. Messy exports can add a few days, and we flag that early.
Customer churn analysis shows which customers leave, when, and why, so you fix the biggest cause first. Stores use it to choose between save offers, better retries, product changes, or pricing, and to check whether a fix worked. Without it, retention work turns into guessing.
Start by exporting 12 months of orders, subscription events, payment failures, and cancel reasons. Match them to each subscriber, remove test orders, and split failed payments from real cancellations. Then compare cancellations by reason, product, and signup month, and rank findings by how many subscribers each affects.
You need subscription events, orders, payment failures, and cancel reasons, ideally for 12 months. Most of it comes from exports in Recharge, Skio, WooCommerce Subscriptions, or Stripe, plus your store and gateway. Helpdesk tags and email data add context, and the free review shows what your data can answer.
Tag every lost subscriber by how the subscription ended: a cancel request is voluntary, while a subscription ended by failed payments is involuntary. Your gateway and app logs show which is which. We keep both as separate lines in every chart, because they need different fixes.
Group every cancellation by its stated reason, the product or plan it held, and the month the subscriber joined. Then compare each group's cancel rate side by side. We group free-text reasons into themes and chart retention curves by signup month, so patterns show at a glance.
Yes, in Looker Studio, Power BI, or Google Sheets, refreshed daily from your store, subscription app, and payment gateway. It shows the voluntary and involuntary split, reasons, products, and cohort curves. We add alerts when cancellations jump, and your team can edit every chart without us.
We turn findings into segments your tools can act on. Overstocked subscribers get tagged for skip offers, price-sensitive ones for a downgrade, and cards about to expire for early reminders. Those segments flow to Klaviyo or your subscription app, so offers and retries follow the data.
Yes. Dashboards, queries, and data connections live in your own accounts, documented so your team can edit them. You also get 30 to 90 days of post-launch support by plan, and we answer questions about the numbers during that time. Nothing is locked inside our tools.
Saimul IslamFounder & CEO, DeveloperLookStill have questions?
Send a message or book a call with the team.
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