---
title: "How do you answer every user’s question?"
date: 2013-06-28
description: "$( document ).ready(function() { // Handler for .ready() called. $("
canonical_url: https://idratherbewriting.com/2013/06/28/how-do-you-answer-every-users-question/
---
# How do you answer every user’s question?
I also realized that if there's been a transformation in the user experience of help at all in the past 50 years, one that has had a positive impact on the user experience, it's this: you can type a question into Google and find an answer.

The way Google provides answers to nearly every question imaginable has transformed the user experience of help in profoundly positive ways. The transformation is less about the medium (whether visual, textual, auditory) and more about the findability of answers.

Answering the user's question sounds easy, but it's actually quite difficult. There are a lot of questions, in fact, about answering user questions.

## Anticipated questions or actual questions?

Pre-release, before you have actual users, you can only imagine what their questions will be. You can try to predict questions users will have. Formulating personas, putting yourself in user scenarios, and noting all the questions you have are good ways to predict user questions.

But once you release the product, don't consider your work done. After release, you can start focusing on *real* questions from users. To gather the real questions, you have to listen closely to support channels, forums, social media, and other feedback channels.

Rather than relegating the feedback to support, integrate the new questions and answers directly into your writerly workflow.

## Which questions do you answer?

Do you answer all questions or just the most common ones? What if you have 500 questions to answer and only limited time to respond (and some of them are really hard questions)?

If you have a lot of questions, you can prioritize them. You could prioritize them in a number of ways:

- Easiest questions first

- Questions from most important customers

- Questions that have severe consequences if users have misinformation

- Questions most frequently asked

## How to you find bandwidth to answer all the questions?

This is the golden question. Beyond foregoing sleep and working 80 hour weeks, you might approach questions by grouping them in similar categories. It's easiest to answer all questions about "widgets" and then answer all questions about "gizmos" and then all questions about "wackimos" and so on.

If you answer questions in 15 different directions at once, setting up environments to test, explore, and research the answers may require a lot more time and will be inefficient.

Also, you can chip away at the pile of questions one by one. Rome wasn't built in a day, and elephants aren't eaten in one bite. A journey of a thousand miles begins with a single step. You pick your metaphor/cliche.

## How do you manage the question-answer workflow?

Questions come in through a variety of channels -- probably from your support center, a documentation feedback email, your user forum, and more. You need a system for cataloging the questions and tagging them into controlled ways that allows you to tackle all questions related to a specific topic at one time. It might also make sense to assign items of the same category to a JIRA or other bug tracking ticket.

## How do you integrate short answers into help material?

Many questions may have just one or two sentence or paragraph answers -- hardly enough to constitute a substantial topic. Do you just write tiny little topics that function more like knowledge base articles? Doing so would at least allow you to optimize keywords in the title of the topic.

I've written before about topic length, and I argued for [longer topics](https://idratherbewriting.com/2013/05/06/why-long-topics-are-better-for-the-user/). The chances of someone landing on the topic and finding an answer are greater if the topic is more substantial, since the topic will have more keywords and therefore have a greater chance of connecting in some way with keywords in the user's search. However, longer topics require you to synthesize more material and go deeper with the content.