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How to Answer Can You Describe a Project That Demonstrated Your Analytical Skills

Posted by Tarik | Jan 26, 2021

Analytical skills help you evaluate problems – both simple and complex. It sets you apart from the rest with your capability to focus on the details, critical thinking, and researching skills.

Today, analytical skills are the single most crucial aspect that makes you a better-suited prospect for a job. Recruiters love candidates with analytical skills.

Interviewers often will ask you to discuss an example where you used your analytical skills. They are looking for you to demonstrate analytical skills in your answer to get a better insight into your capabilities.

Employers are looking for leaders for their workplace, and leaders essentially possess a great analytical skillset.

Critical thinking and decision making are essential parts of analytical skills that allow you to demonstrate your capabilities in evaluating a problem and making the right decision expecting the best outcome.

When the interviewer quizzes you asking for an example where you used your analytical thinking, you need to be particular in what you relate.

The example needs to be on point, bringing out your critical thinking capabilities and showcase that you can evaluate situations based on research and data.

Using the STAR method will help you bring out an effective response to the question and make a great impression with the interviewer.

Divide your answer into sub-sections using the STAR method - Situation Task, Action, and Results to provide a wholesome view.

Here is an example STAR answer.


One particular shopping app that we developed was seeing more than 65% dropouts from the landing screen.

I was tasked to analyze the problem behind this and come up with a solution. I successfully figured out the problem and converted 80% of the dropout users to add items to their carts.


Our shopping app was seeing a massive dropout rate extending over 65%. I was tasked to reducing the dropout rate to 20% and increase users proceeding to checkout.


I took to the data that we gathered over the last few interactions to get an idea of what was going wrong.

I then processed the raw data and converted them to see where precisely the problem was.

While analyzing the data, I found out that the app did not render correctly on selected Android devices after the update, and nearly 60% of the users who downloaded the app were using Android smartphones.

I then reported the findings and communicated this to our UI/UX team to take immediate action to rectify the issues.

I also made a note to the project managers to consider all the use cases before rolling out an update to continue to be compatible and not lure away users.


I was delighted with the outcome of the findings. The UI/UX team made amends immediately, and the 65% drop out rate came down to 18% in two weeks.

The Android user dropout rate, which was 80%, also came down to 21%, a remarkable achievement. Thanks to the data mining that I conducted, I analyzed the issue and got the remedial measures exactly.

I got appreciation from the client as well as my manager, who acknowledged my analytical skills.

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