There are a number of ways you can write and format your articles to work best with Answer Bot. You may find that you can't or don't want to use all of the suggestions in this article, but applying just one or two can greatly improve your Answer Bot Article Recommendations.
This article contains the following topics:
Structuring and organizing your information
One area where you can make a difference is in the structure and organization of your articles. The suggestions in this section include both customer-facing and behind-the-scenes decisions.
Creating titles for your articles
When determining whether an article is a good candidate for a customer's problem, Answer Bot looks at (among other things) an article's title. If an article's title closely matches the text of a support request, it's more likely to come up as an Answer Bot suggestion.
To take advantage of this, you should give your articles titles that are similar to how your customer might phrase their support request.
Try formatting your article titles in one of the following ways:
- As a question: "How do I reset my password?"
- As a simple, active phrase: "Resetting a password"
Narrowing an article's focus
Wherever possible, an article should cover a single, specific topic. How this impacts your articles depends on how you present information to your customers:
- Issue/resolution articles: If you prefer to write your articles around issues and resolutions, try to focus each on a very specific issue with a single resolution. For instance, rather than having a single article covering multiple, related billing issues – payment options, requesting a refund, and challenging a charge – write three articles, one for each issue. If possible, offer a single resolution for each issue as well. This way, you can guide your customers to the resolution you prefer, and if necessary, link to other articles that may offer alternative resolutions.
- Process articles: The same general principle applies to articles built around processes and procedures. Say, for example, you need an article walking a customer through an account set-up process, which involves two main tasks: Creating an account and selecting account options. You could have a single article covering both tasks, since they are both part of the account set-up process. However, breaking it up into two articles, one for each task, will help Answer Bot choose the article that best matches your customer's needs, and help your customer locate the applicable information without having to wade through unnecessary text.
Writing article introductions
Answer Bot weighs the first 75 words in an article more heavily than the subsequent text. By including as many related keywords and context as possible in an article's introduction, you will boost Answer Bot's accuracy.
For example, if you're writing an article about your company's return policies, don't include a preamble about how you understand that sometimes a shirt is the wrong size or that everyone makes mistakes. As charming as that might be, it gets in the way of Answer Bot's functioning. Start your articles cleanly and precisely: "We accept returns for a full refund within 30 days of purchase. After 30 days, you can request a store credit," then get into the details.
Using alternative text
What you write behind the scenes can impact Answer Bot Article Recommendations as well. Use alternative text on your embedded images and videos to add descriptive keywords.
Using segmentation and labels
The power of article labels really comes through when you have a situation where you can segment your customers when tickets are created. A good example of this is a game developer supporting iOS and Android platforms. The developer has two channels for incoming tickets: one for iOS issues and one for Android. Using the trigger conditions, you can create 2 Answer Bot triggers (one for each channel) and then use article labels to serve up only iOS or Android articles where they make sense. So, stop for a second and really think about how you could best segment your customers and create useful conditions around them - and then serve them the best articles possible! This is described in more detail in the best practices for using labels with Answer Bot guide. For information on working with triggers for Answer Bot, see Creating new triggers for Answer Bot.
Even if you are not using customer segmentation, labels have a huge impact on Answer Bot results. Use them thoughtfully. For example, if an article is about a topic that does not tend to generate customer questions, you might omit the label you've configured for Answer Bot. This helps Answer Bot consider a smaller, more curated pool of articles when making suggestions.