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📝 As we approach the end of this month’s them, “Idea Validation,” we want to check in with you to see if there’s anything you would like to see in next month’s theme. Just fill out our form here to share your suggestions.

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🤝 In this week’s strategy, we’ll be diving into the most important element of idea validation: analyzing what you learned to make informed decisions. Scroll past the tools section to get the inside scoop on industry secrets.

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Tools + Productivity

Strategy

Collect Feedback
So you’re going through the trial-and-error process of launching a new product or feature for your business.

If you’re doing it with intention, you will probably have lots of channels to collect feedback from your customers.

This could be active feedback, like targeted focus groups or paid surveys.

Or, it could be passive feedback, like feedback forms throughout the users’ customer journey or comments on social media.

If you’ve done that, then you have qualitative feedback, and if you are using a platform that gives you statistics on customer usage (page views, clicks, etc.), then you have quantitative feedback as well.

A great platform for tracking all kinds of feedback is UserPilot (though it’s a bit pricey).

If you have customer feedback data, you are already doing an amazing job - congrats!

But, the question then becomes, how do you use this information to make adjustments?

Finding Insightful Data
The key data points that you should be focusing on when making adjustments are what we call insightful data.

This is data that gives you insights into the things in your app that can be improved (e.g., a bug reported in your app, a block in the user workflow, a knowledge gap in your course, etc.).

When you have insightful data, you can use this information to fix the roadblocks in your product and make it better.

Non-insightful data, on the other hand, only confirms what you already know, so although it can be validating, it is much less useful for making improvements.

Categorizing Data
Once you’ve extracted the insightful data from your customer feedback and stats.

This involves categorizing the feedback into different buckets based on how you can address them. Some common divisions are:

1. Product-related feedback (Do users enjoy the product? Are they engaging with it?)

2. Service-related feedback (Is the product being effectively delivered? Is the user experience enjoyable?)

3. Bugs-related feedback, etc. (Does the product crash? Are there issues with uptime or broken links?)

Analysis
Once you’ve organized your feedback and understand which data points are of actionable use, you can begin your analysis - drawing conclusions from the data and implementing changes. Now, let’s talk about how.

One option is to manually parse through your data by loading it into excel files and creating graphics that show trends from your data.

Although it’s effective and can let you get much more granular with how you engage with your customer feedback, it takes a lot of effort and time.

Instead, I recommend utilizing tools. These can streamline your analysis and often result in better conclusions than you could generate yourself.

Some useful tools include: NPS (net promoter score) tags that let you filter user data by engagement/loyalty; AI trend identifiers (e.g. LoopGenius); for qualitative data, NLP tools can extract conclusions about customer sentiment based on written feedback.

Implementing Change
Once you have strong insights into how your customers use and feel about your product, it should be evident what needs to change, though it can still be tricky figuring out how.

For example, if your customers have demonstrated less engagement over time, perhaps it is time to implement a new product/feature that grabs their attention.

From there, you can monitor how the new feature performs and whether it has successfully boosted engagement. If it fails to do so, it is important to think creatively about what your customers want to see - sometimes they don’t even know until you show them!

Looking Ahead
As we wrap up this month, feel free to check back on some of the previous topics in “Idea Validation” that you may have missed earlier in the month. If you want to offer a suggestion for next month’s theme, let us know right here.

Week 1: Testing an Idea 
Week 2: Market Research and Customer Insight
Week 3: Testing and Validation Techniques
Week 4: Analyzing what you learned to make informed decisions (this week)

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