Articles
August 20, 2024

Our Methodology: Optimizing Game Features and Ads through Behavioral Research

At Sensemitter, we use advanced AI tools grounded in behavioral and emotional psychology to analyze audience behavior. This article will outline our methods for playtesting and ad creative evaluation.

Our approach is grounded in the principles of behavioral and emotional psychology. By leveraging proven methods for analyzing target audience responses in marketing, we have developed a research process specifically designed to enhance player engagement in the gaming industry.

At Sensemitter, we utilize advanced AI tools that incorporate two neurobiological methods to study audience behavior: facial coding and eye tracking. Eye tracking generates heatmaps that trace where players focus their attention, while facial coding monitors changes in their emotional responses.

In developing this methodology, we placed significant emphasis on ensuring the validity and reproducibility of the data collected and its correlation with the performance of game features and creative ads. This blend of techniques allows us to meet the unique demands of the gaming industry.

In this article, we'll walk you through our process for conducting playtests and analyzing ad creatives.

Analyzing Ad Creatives

Ad creatives reach a broad audience, and gaming companies invest heavily in promoting them. In just 15-30 seconds, a video must capture the user’s interest and compel them to download the game. Every detail matters, from the storyline’s pace to the button’s placement.

To identify the most engaging segments of a video, it's crucial to obtain consistent, repeatable data validated by a large audience sample. Therefore, we employ a quantitative approach.

Using heatmaps, we determine where users focus their attention throughout the video: where they look and, more importantly, where they don’t. This helps answer critical questions such as:

  1. Which elements on the screen attract the most attention, and does this align with the creators’ intentions?
  2. Are there elements that viewers overlook, even though they are meant to be noticed?
  3. Is there a conflict in the audience’s focus points? Is there an element that distracts from another, or does the scene's composition cause a lack of focus, making it hard for viewers to process the information adequately?
  4. Do players read the text on the screen, or are they more captivated by the visuals?
  5. Do they notice the packshot (final product shot)? If not, what distracts them?

Next, using facial coding, we analyze the user’s emotional response throughout their interaction with the video. This emotional analysis helps us track the player’s engagement on a second-by-second basis, assessing whether we can evoke contrasting emotions. It also checks whether players understand the intended humor in the video or if they find the fast-paced action irritating.

AI processes these emotional responses, helping to create emotional heatmaps. A mathematical algorithm segments players based on their perception patterns. Our researchers then step in, comparing the data with what’s happening in the video frame by frame, highlighting well-executed elements and pinpointing problem areas.

We collect not only the players’ subconscious reactions but also their rational assessments—after watching the video, players are asked to complete a short survey.

Conducting Playtests

A game’s enjoyment is built on many elements. While the primary concern in ad creatives is whether they convert viewers into users, games have more variables to consider: Is the meta engaging? Is the progression curve well-balanced? Are offers not too intrusive? Did we successfully lead the player to make their first in-game purchase? Does the player understand what actions they can take, and so on?

Given the numerous variables, it's vital to analyze how players interact with every element in detail, whether it's a bundle, battle pass, or new mechanic. We conduct tests on a small group of players, focusing deeply on each detail to uncover key interaction triggers and barriers.

We select participants based on specific client criteria. The playtest session is conducted as follows: We monitor the player's actions, recording both their screen activity and facial expressions. The player interacts with the game independently, progressing through levels, studying hints, and reading dialogues while our moderators remain silent observers. This setup allows players to immerse themselves fully in the game and us to understand their genuine behavior.

In the next phase, we gather the players' feedback—what they liked, disliked, and their thoughts on specific aspects.

We then thoroughly examine each screen of interest, from character control to shop navigation, to identify what players understood during their experience and where they encountered difficulties. Did we explain the mechanics sufficiently, or were the hints lacking? Did the player grasp the victory conditions? Can they choose and purchase the item they want?

After collecting the necessary data, we proceed to a detailed analysis phase. Using face scanning results, our researchers analyze the player engagement curve, identifying patterns and trends.

Finally, we analyze the issues encountered in detail, uncover their causes, and provide recommendations for improvement.

The applications for such research are vast. During pre-production, this methodology can be used to test settings and styles, choose the most appealing characters, and refine the storyline and narrative.

In operational games, the scope of possibilities is extensive, including:

  • First Session Analysis: Our first-session analysis method and overall first-time user experience (FTUE) optimization help reduce churn and increase playtime.
  • Analysis of First to Nth Day: This helps identify and refine hooks for player retention and re-engagement, ultimately improving retention rates.
  • Testing New Mechanics and Tutorials: This provides insights into what engages players and what confuses or demotivates them, identifying where difficulties arise.
  • Testing Monetization Mechanics and Offers: This helps increase conversion rates into paying players, thus boosting ARPU/ARPPU (Average Revenue Per User/Payer).
  • Interface Interaction Analysis: This helps understand where problems with readability and interface usability arise.

The results we obtain differ significantly from those of a typical playtest or creative analysis. We provide concrete data that allows for a detailed analysis of player responses to any aspect of a game or advertisement—most importantly, identifying what needs improvement to enhance the user experience.

Want to learn more about how our insights can optimize your game or ad campaigns? Leave your contact information, and one of our experts will reach out to discuss how we can help you achieve your goals.

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