Hit or miss – Will my new feature make the difference?

All people working on the production side know this feeling. You’re deciding on moving forward with implementing new features to your game. Even how you look at it using your internal tools, you have that eery feeling haunting you that will that feature impact the KPI in the way you’re expecting? There would be nothing more demoralizing than developing a major feature that might take multiple sprints and weeks of your team’s precious time just to it ending up being a dud.  

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We have all been there, and so have I. 

Thanks to historical performance data of multiple updates, GameRefinery can show you in advance how your competitors have been performing before and since implementing the same feature so you can make the right decision and get a good night’s sleep!

It all boils down to feature filtering with our Game Update Impacts!

In our imaginary scenario, we are once again product owners of a puzzle genre game, and we’re thinking about implementing recurring live events. Not only will the feature be development heavy, but so will all the tools around it. 

To make our final decision on whether to pull the trigger, we’ll check out all the Puzzle-genre games and what kind of results they’ve gotten. This post has hyperlinks so you can check out the results yourself! 

 This article covers three sections:

 1. Filtering data

 2. Selecting the specific feature

 3. Seeing the results!

Note: To follow these steps on your own, you’ll need to have access to GameRefinery’s Update Impacts feature. If you don’t have access, drop us an email or chat message! 

Filtering data

Not all updates and games are equal. Hence for that reason, we want to focus on the most crucial games and updates out there!

As a first pick, we’ll narrow our focus down to the Puzzle genre as that is where our game lands in GameRefinery’s genre-taxonomy. Why should we care in our initial research what kind of results, for example, FPS games have had? It’s best to be as precise as possible.

The 2nd filter for us to work on is time. We can filter on three variables: 6 months, 12 months, or all time. As we’re interested in comparing the highs & lows of this feature, we’ll select the all time filter.

The 3rd filter is the content of the update. Naturally, not all updates are equal, and because we’re looking into features added after the soft launch of the game, we’ll filter updates only for those with feature updates.

Game update analysis in Update Impact Analyzer

That’s more like it! Now we have all the puzzle genre updates that included new features.

You can click here to access our search results with all search filters in place. Time to move to the 2nd part!

Selecting the specific feature

We now realize that there are hundreds of updates in GameRefinery. Very neat, and this will surely be helpful when analyzing competitor products to see what’s worked and what’s not, let’s focus on recurring live events specifically.

See that little button right next to the feature changes tab? Click it to open our 2nd cornerstone, feature groups. 

Filter for updates that implemented features that you are interested in

Now we can begin filtering for updates that implemented features that we’re interested in!

Since we’re looking for Live Events – Recurring, let’s use the search bar to find and select our feature. Next, we click Done.  

Select features in Game Update Impact

Seeing the results!

After narrowing things down to the puzzle genre, selecting all time, filtering in only feature updates, and finally selecting our desired feature, we see the updates where this specific feature was introduced. 

 Click the link to access our search results!

How much the feature changed impacted revenue when comparing one month before and one month after the update

From here we can rank all updates by how much the feature changed impacted revenue when comparing one month before and one month after the update. (Note: Not considering UA or how the feature was implemented!)

From this we learn two things:

1. A good majority of updates that implemented our feature had a positive impact on revenue, which is great news!

 2. Only in two updates were recurring live events the only introduced feature. In most updates, it was part of a bigger update, so going solo has been rare. 

Conclusions:

Not only did using GameRefinery’s Update Impacts help us see that implementing this feature has brought positive results to other games, but it also helped us understand that games have added more than one feature when doing so. This data gives us breathing room knowing that we are on the right path. By clicking the” Show Update”-button, we’d naturally learn more about the specific update. When was it introduced, what were the developer’s update notes etc. that can provide us more insight!

The next step would naturally be going to Implementation Examples and finding how other Puzzle games have implemented this feature into the games using GameRefinery’s massive feature screenshot archive. But that is another story for another time. 

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