This is a series of posts on the way that teams try to derive a list of features that they need for basing their features sets for the current and future versions of the product. The better a list of features that you have available with you, the better will be the options available with you for generating a list of great selling features. However, even before you can get started with the process of defining which feature to use in the current release vs. features that should be done in future releases, you still need to generate such a list of features; and your attempt should be that such a list is as comprehensive as possible. In the previous post (Developing a list of features for the application - Part 3), I talked about getting features from the posts that users make in online forums. There is an increased tendency for people to use forums to present their problems and a lower percentage of people point out features that they would like. However, since these represent features suggested by actual users, such features should be considered seriously. This also ensures that users appreciate that their suggestions are also being incorporated and increases their involvement in the product.
Another way for you to determine which features are being used the most as well as which features are causing users problems is through the statistics on help items. If you are into providing more information to your customers, one easy way is to have all your application help online along with other areas that would be helpful to users such as How to help videos, Tutorials, Solutions for major bugs, and so on. Now, such items on your company's servers are typically indexed easily enough and will show up when users search for such items. Along with such help pages, it would be easy enough to provide a small section where users can put in their suggestions.
Once these pages are up, monitoring the suggestions provided by users along with the statistics on which of these pages are accessed by users can provide invaluable help to a team that is trying to make sense of this data. So, for example, if you have provided a video on how to use a particular feature, and this is being accessed the most by your users, and they also provide feedback, then a team tasked with trying to evaluating this data will be able to determine which part of the feature works well, which part does not, and also about suggestions for improvement. There are many teams and organizations that try to make sense out of such data, and they have managed to determine which features are the ones where users are reporting problems, and once they even managed to determine that a feature that was a technical masterpiece did not seem to have much user attention (atleast not to the level that was required by the team).
Continuing on this line will enable a team to make improvements to their existing features or even do major modifications, which can actually almost seem like new features if the change is big enough.
Read more about this feature collection and analysis in the next post (Developing a list of features for the application - Part 5)
Another way for you to determine which features are being used the most as well as which features are causing users problems is through the statistics on help items. If you are into providing more information to your customers, one easy way is to have all your application help online along with other areas that would be helpful to users such as How to help videos, Tutorials, Solutions for major bugs, and so on. Now, such items on your company's servers are typically indexed easily enough and will show up when users search for such items. Along with such help pages, it would be easy enough to provide a small section where users can put in their suggestions.
Once these pages are up, monitoring the suggestions provided by users along with the statistics on which of these pages are accessed by users can provide invaluable help to a team that is trying to make sense of this data. So, for example, if you have provided a video on how to use a particular feature, and this is being accessed the most by your users, and they also provide feedback, then a team tasked with trying to evaluating this data will be able to determine which part of the feature works well, which part does not, and also about suggestions for improvement. There are many teams and organizations that try to make sense out of such data, and they have managed to determine which features are the ones where users are reporting problems, and once they even managed to determine that a feature that was a technical masterpiece did not seem to have much user attention (atleast not to the level that was required by the team).
Continuing on this line will enable a team to make improvements to their existing features or even do major modifications, which can actually almost seem like new features if the change is big enough.
Read more about this feature collection and analysis in the next post (Developing a list of features for the application - Part 5)
No comments:
Post a Comment