4 Steps of Mobile App Conversion Research

Introduction

Objective

The purpose of Conversion Research is to provide valuable insights on gathered data about user behavior and suggest related improvements. We start with data gathering and suggestions on the related tools setup. Once we have the data we need, we will dig deep into them focusing on:

  • Functionality — testing the App from the functional standpoint accordingly to the set business goals.

  • Usability — answering to questions if App is intuitive and optimized for the target audience from the UX perspective.

  • Information architecture — identifying the optimal navigation and wayfinding path, testing the organization of labeling and hierarchy of the App to support usability.

  • Design best practices — explore if best modern design practices are used for the App, accordingly to the target audience behavior.

The deliverables of Conversion Research are:

  • Presentation on findings (pdf document)

  • Prioritized list of improvements and clear actions to be taken to improve mobile users experience

  • Detailed issues log for each section based on data sources (google analytics, heatmaps, users testing etc)

Detailed issues log for each section based on data sources (google analytics, heatmaps, users testing etc)

Contents of Conversion Research for Mobile Apps

Step 1: Heuristic Analysis and App walkthroughs

When starting to optimize for conversions, it’s best to begin by understanding the user’s experience on the App. To begin the conversion research process, we start with App walkthroughs and heuristic analysis. This step helps to familiarize with the App and map out the “problem areas” which are afterward validated or invalidated using data. The heuristic analysis serves as an input for creating the hypothesis.

We start by conducting App walkthroughs with all the top-used mobile Operating Systems, Operating System versions, and device categories (tablet and mobile). Walkthrough is done on the devices used by the most of App users if such data is available. We pay attention to the app structure and the conversion processes. In addition, we look for technical issues (bugs, broken screens/buttons etc.) that are considered low-hanging fruits towards conversion optimization, since smooth app technical functionality is the foundation for enabling users to convert.

When evaluating an App, we will:

  • Assess each screen for clarity — is it perfectly clear and understandable what’s being offered and how it works? This is not just about the value proposition — it applies to all screens (pricing, featured, product pages etc).

  • Understand context and evaluate screen relevancy for visitors: does App screen relate to what the visitor thought they were going to see? Do pre-tap and post-tap messages and visuals align?

  • Assess incentives to take action: Is it clear what people are getting for their money? Is there some sort of believable urgency? What kind of motivators are used? Is there enough product information? Is the sales copy persuasive?

  • Evaluate all the sources of friction on the key screens. This includes difficult and long processes, insufficient information, poor readability and UX, bad error validation, fears about privacy & security, any uncertainties and doubts, unanswered questions.

  • Pay attention to distracting elements on every high priority screen. Are there any blinking banners or automatic sliders stealing attention? Too much information unrelated to the main call to action? Any elements that are not directly contributing to visitors taking the desired action?

  • Understand conversion phases and see if visitors are rushed into too big of a commitment too soon. Are there paths in place for visitors in different stages (research, evaluation etc)?

During the App walkthroughs and heuristic analysis, we write down all observations and areas of interest, which are afterward analyzed using Google Mobile Analytics and other sources of data to confirm or disprove the findings. If not enough data is available to confirm or disprove a hypothesis, we proceed with additional data gathering (screen recordings, touch points, gestures, surveys).

Step 2: Digital Analytics (quantitative data) analysis

After Heuristic Analysis and thorough App walkthroughs, we have identified potential User Experience “problem areas” for certain OS and/or Device categories. In addition to that, we have gathered observations of the clarity, relevancy, incentives, frictions and distractions on all the major screens of the App. We proceed to investigate and evaluate the potential “problem areas” and the heuristic observations using quantitative data analysis from Google Mobile Analytics (or the preferred Digital Analytics tool that is being used for visitor tracking and data gathering).

Afterward, we proceed to a general Digital Analytics data analysis and evaluation with the main purpose of identifying where the app is leaking conversions.

In the Digital Analytics data analysis and evaluation, we will:

  • Analyse user Funnels and identify main drop-off points

  • Analyse App goal flows using different user and behavior segments

  • Key audience analysis (Country, region, city, visitor type, demographics)

  • High traffic, low-performance screen analysis

  • User screen navigation analysis

  • App top exit screen analysis

  • Advanced user segment building and analysis

Note: Before any full-scale digital analytics data analysis, we have to make sure that everything that needs to be measured is being measured (goals, funnels & event tracking set up), the data in the property is not corrupted, and that the account has correct configurations and set-up. Having genuine and full data is extremely important for any data analysis and conversion research. In case technical adjustments are needed, we will prepare clear tasks for the development team to setup needed tool. Note that technical setup is not a part of this research.

Step 3: UX research and analysis

In the beginning of any conversion research project, we make sure that User Experience data collection and tracking tools are configured correctly in order to gather the necessary amount of data (sample size) to be able to draw statistically significant and valid conclusions (since data collection takes time). When enough data on actual user behavior on the App is collected, we proceed with user behavior and user experience analysis.

In the process of actual user behavior analysis, the main goal is to identify conversion path problems and aspects of app screens which are impairing user navigation towards converting. In addition, we look for aspects of the app which are confusing users (e.g. elements which seem like buttons, but are not).

For actual user experience and behavior evaluation, we will analyze:

  • Individual user screen recordings — evaluate user interaction with the App and different screens (how users fill in forms, navigate screens, how they search for specific screens/actions). Gather insights on the user experience on the app.

  • Tap Heatmaps — evaluate and understand user tap distribution on the App (do user tap on the most important buttons (call to action) on different screens, do users tap on elements in screens that are not buttons, understand user behavior and attention attracting elements on screens, potential CTAs improvements)

  • Segmented user flow analysis — evaluating particular segments of user screen recordings and identifying user experience problems towards the goal conversion path (drop-off screen problem and potential improvement identification, user form-filling behavior and problem identification)

Step 4: All data analysis, research findings report, and improvement list and actions report

In the last step of the Conversion Research for Mobile Apps, we put together all the gathered insights of the research and prepare:

  • Executive summary of the research findings and condition of the App

  • Key insights about the App customers and the app itself

  • Data-driven prioritized App conversion drawbacks and problems list

  • Detailed App conversion rate optimization step-by-step guide with identified and prioritized problem solution hypothesis and A/B testing suggestions