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How to Discover User Issues: A Beginners' Guideby@rifco
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How to Discover User Issues: A Beginners' Guide

by anton rifcoJanuary 24th, 2020
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The Product Development process should always be about discovering your users’ pain points. The next thing that may arise would be “How do we find the actual User Problems?” In trying to find the problems that your users have, don’t start with your assumptions. Chances are you are probably wrong. You should always depend on data to discover user issues. You can get them by analyzing lots of supporting data, such as: Internal data / Analytics / Surveys / Testing.

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First Things First: 

The Product Development process should always be about discovering your users’ (or potential users') pain points.

Simply put, discussion about an Idea should never start at Product Development efforts. It should always start with finding the problem of the users.

The next thing that may arise would be “How do we find the actual User Problems?”

In trying to find the problems that your users have, don’t start with your assumptions. Chances are you are probably wrong.

You should always depend on data to discover user issues.

Finding users’ Pain Points is not easy. However, you can get them by analyzing lots of supporting data, such as:

> Internal data / Analytics
> User Feedback / Surveys
> Internal Feedback / Testing
> Market Situation / Market Research
> Industry Trends / Desktop Research

2 Steps Towards Users’ Problem Discovery

Step 1: Analyse Available Data

As a data-driven Product Manager , you need to regularly analyze any qualitative and quantitative data about your users’ activities / behavior in your product.

Quantitative data sources:

> Product High level metrics (e.g: #Transactions, #User-registration)
> Product User behavior metrics (e.g: Transaction Conversion funnel)
> Traffic Report (Visitors, Attribution)
> Market Research Data

Qualitative data sources:

> User interview (Ad-hoc / Staged interview)
> Focus Group Discussion
> User Activity Observation (Direct observe / Recorded )
> User feedback (internal and external users)

Step 2: Find Patterns in Data

From above data, try to find patterns that can be improved. Example:

> Data Decline based on Historical graph
> Data is Poor (too low) relative to Industry standard
> Occurrence of unnecessary steps to achieve products’ goal
> Absence of Feature to achieve products’ goal

Now that you’ve got idea what keeps your customers awake at night. If you’re still unsure about it,

talk to more customers.

And only after you’re confident with your findings, then you can start prioritizing the building of solutions as remedies to your users' problems.