Your users are already telling you what they think. The trouble is that it is stored in three places that never meet.
In brief
- Users speak through public reviews and social posts, support contacts and what they do in the product. Most platforms hold all three and read none of them together.
- Each source is biased on its own. Together they cross-check each other.
- You can start without new tools: pick one question and join the three sources around it.
- The hard part is matching and definitions, not technology.
Many platform teams pay for outside research to learn what users think, while sitting on three sources that say it every day.
App store reviews and social channels hold opinions. The support desk holds problems. Product and transaction logs hold what people actually did. Each team looks at its own and reports on it. Nobody puts them side by side.
The real issue is that each source tells a different half of the story
| What it tells you | What it misses | |
|---|---|---|
| Reviews and social | What people say publicly and why | Who they are, whether they are active users |
| Support | What went wrong, in detail | Satisfied users who never contact you |
| In-product behaviour | What people did, repeated or abandoned | Why they did it |
A spike of one-star reviews may come from a few loud users after one release. A rise in tickets may reflect one device or one region. A drop in repeat use may have nothing to do with either. Looking at one source invites the wrong conclusion. Looking at all three shows where they agree.
A practical way to combine them
1. Start with one question
For example: “Why do new users complete sign-up but never place a second order?” A single question limits the work and shows quickly whether the combination is worth it.
2. List what you hold for that question
Reviews and posts mentioning the feature, support tickets and chat transcripts about it, and product events such as sign-ups, orders and cancellations. Note where each is stored and who owns it.
3. Agree on shared labels
Pick a small set of topics (for example payment, delivery, login, price, driver or merchant behaviour) and use them across all three sources. Without shared labels, a “payment failed” ticket and a “can’t pay” review look like different issues.
4. Connect what can be connected
Some links are direct: a ticket and the account behind it. Others are only by topic and time: a spike of reviews about one issue after a release. Be clear about which is which, and respect privacy and consent rules when linking records.
5. Read together, then act
Look for agreement (“reviews, tickets and cancellations all rose for the same cause”) and for disagreement (“people praise it online but stop using it”). Both are useful. Then decide on an action and a way to check it worked.
Five mistakes we see repeatedly
- Waiting for a perfect platform. Start with one question and spreadsheets if needed.
- No shared vocabulary. Product, support and marketing name the same issue differently.
- Treating public reviews as the whole user base. They show the vocal minority.
- Linking personal records carelessly. Joining data about individuals raises privacy duties. Use aggregate topics where possible.
- Insight with no owner. Decide beforehand who acts on the findings.
Our experience
Much of our work is joining information that sits in separate systems: matching identifiers, agreeing what fields mean, and building one place where the numbers can be compared. Customer and user data is no different.
We can explore connecting two of your three sources around a single question.
Which question would you start with?
Use what you already have
You probably don’t need another survey to learn what users think. You need to read your own three sources together, around one question. Start small, and widen only when the first answer has changed a decision.
Talk to Balerion about connecting your user data into one useful picture. Email us at talk@balerion.co.th.
