Results: An App Store Experiment Based on Keyword Research

As I mentioned in a previous post, the initial release of ReminderBin resulted in almost no downloads; consequently App Analytics data was not available.

On the 19th March I made the app free; as free it started to get some downloads, enough to draw some conclusions for this experiment…

Reminder of experiment goals

From the original post about this experiment – this is what I was trying to find out:

  1. Can the keyword research be trusted? Will ranking in the identified search phrases generate App Store views (traffic)?
  2. Is it possible for a new app that matches the search terms more closely than existing, ranking apps, to rank highly for those terms?
  3. For a particularly narrow niche, can you rely on search terms as the only input when judging market need and conceiving a product to fulfil that need?


App Store views and downloads over the last 4 weeks:

  • 28 days: 26 Mar 2016 – 22 Apr 2016
  • 168 App Store views
  • 6 views per day
  • 1.5 downloads per day
  • 25% view to download conversion rate

Experiment findings

Despite the extremely low downloads, the experiment wasn’t a complete failure.

1. Can the keyword research be trusted? Above, I noted the number of downloads and conversion rate, but it was App Store views that was the primary focus of this experiment.

The app does get views.

SensorTower suggested traffic and I got traffic; to an extent, the keyword research can be trusted.

That said, if I were to repeat this process I’d want to start calibrating on the information being shown in SensorTower (or similar tool) so that it could be used with greater confidence. E.g.

  • Would a different app with similar numbers produce similar results?
  • Are the traffic values in SensorTower linear?
  • Is the traffic contribution from closely related terms like “delete my reminder” and “delete my reminders” completely separate?
  • Etc.

2. Can a new app rank highly? This will differ from app to app and crucially, the amount of competition for the keywords in question. In this case, with low competition, the results show that a new app can rank highly. Take a look at some data from SensorTower for some of the primary keywords for ReminderBin:

3. Can you rely on search term data only to judge market need and conceive a product? Generally, the answer is clearly “no”. Market research and product development are way too complex to be replaced by some keyword numbers in SensorTower.

However, scaling that down a little, I think the numbers above show that keyword research can reveal aspects of market demand. Such research may serve as the input for further investigation, interviews with users, trial features, maybe even a small MVP, etc.

Whilst it’s difficult to conclude much with such small numbers, the (only) two reviews that the app does have – support search term / keyword research being on avenue to judge market need…