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April 17, 2024

Magda Beckner

Comprehensive Services

How to Use Data, Not Intuition, to Predict User Behavior

Introduction

As a designer, you need to be able to make decisions about your product. But how do you know if these decisions are the right ones? That’s where data comes in. Data is one of the most powerful tools we have as designers, but it can also be confusing and overwhelming when we first start using it. In this article, I’ll explore some ways to use data in your decision-making process without relying solely on intuition or experience.

Find the right balance between data to drive your decision making.

You can’t use data to replace your intuition, but you can use it to support your decision-making. The key is finding the right balance between data and intuition.

When you have a gut feeling about something, ask yourself: “Does this feel right?” If the answer is yes, then go with it–but only after making sure that all other factors are covered (e.g., cost or resources available). If not, then try looking at some specific metrics related to what you’re trying to achieve before making any moves; this will help confirm whether or not there’s any merit behind what’s going on in your head!

You should always be wary of relying too heavily on either one alone because both approaches have their drawbacks: Intuition doesn’t always account for all possible outcomes; meanwhile any amount of analysis won’t tell us exactly how users behave unless we know exactly what questions we need answered beforehand.”

Data is not an end, it’s a means.

Data is a means to an end, not an end in itself. And that’s a good thing! It means that you can use data to make better decisions and understand how users behave, but also understand how your company is performing.

If you’re looking for answers about why something happened or what users want next, then looking at the numbers isn’t going to help much–you need qualitative feedback from real people (and their data). But if all you want is evidence that something works or doesn’t work? Then the answer lies in our trusty friend: cold hard facts from testing sessions and surveys!

Use real world examples and stories.

One of the best ways to get people to understand a concept is through an example. The same goes for data science, which can be a difficult subject to grasp if you’re not familiar with it.

A good way to explain how you should use your data is by using real world examples of companies who have used it effectively and how it helped them achieve their goals.

For example, let’s say that you have an eCommerce store that sells shoes online but wants more customers who are willing to buy shoes outside of their comfort zone (i.e., they usually only buy running shoes). You could use this article as inspiration: https://www2.deloitteconsulting-us1/en-us/insights/blogs/2019-marketing-forecast?id=a5d567b8f81e4ef0c9dcabac0d9b7ba3

Use data at the right time.

Data should be used to make decisions, not to justify them. This is an important distinction in the way you approach data analysis. Data can tell you what’s happening and help validate gut feelings, but it shouldn’t be used just because it’s there or because someone else says so.

It’s tempting to use data as a crutch when making decisions–if something doesn’t feel right intuitively, then look at some numbers! But this isn’t always helpful; in fact, sometimes it can lead us astray from what we really need: gut instinct and experience (which comes from making mistakes). Of course there are times when we need more than just our gut feeling or intuition–and those times are when analysis tools come into play!

Data can help you make better decisions, but you must be cautious with how you use it.

Data is a means, not an end. It can help you make better decisions, but it’s up to you to use the data correctly and apply it in ways that are useful for your users.

There are two things you must remember when using data: 1) don’t just use the data because it’s there; 2) always ask yourself how this information will affect the user experience of your product or service.

This means asking yourself questions like: “Why am I collecting this information?” or “What questions does this answer?” If there’s no clear reason behind why you’re collecting something, then maybe collecting it isn’t worth your time right now–or ever!

Conclusion

Data is a powerful tool, but it can also be dangerous if used incorrectly. If you’re not careful, your data-driven decisions could lead to a product that no one wants or needs. The key is finding the right balance between intuition and data so that you can make smarter decisions about your product roadmap.