After launch, how do you know whether a product is working? Opinions differ, and the loudest voice is not always right. Data gives you a shared, honest view. Adverts for product analysts, business analysts and data roles in Ghana ask for data analysis, KPI tracking, dashboards and reporting, and some ask for spreadsheets at an advanced level and SQL. Even product managers who do not run the numbers themselves must read them confidently.
Numbers and stories together
Data tells you what is happening: how many people signed up, how many saved twice, where they dropped off. Interviews and feedback tell you why. Good product people use both. If the numbers say farmers stop after registering, conversations tell you it is because the price field is confusing.
Honest reading
Numbers can mislead if you are not careful:
- Vanity numbers look good but do not show value. Downloads and sign ups can rise while almost nobody uses the product.
- Small numbers jump around. If 4 out of 10 users did something last week and 6 this week, that may be chance.
- Correlation is not cause. Imagine savings rose in December, the same month you launched a feature. Many people earn and spend differently around Christmas, so your feature may not be the reason.
- Missing data hides problems. If only smartphone users are tracked, USSD users disappear from your charts.