MoodPanda.com HEART/GSM Model
This article presents a HEART/GSM model for the MoodPanda.com website. MoodPanda is a website and mobile application that helps users track their mood changes over time while connecting with others to receive anonymous peer support. Users can log their moods using numerical scores (0–10) and add a brief description of their mood updates.
To develop the HEART/GSM model, I created a hypothetical situation to understand the goals, signals, and metrics better:
MoodPanda is planning to enhance its website. Before that, they want to understand how they can create the website's user experience more interactive and gain more users and retain the existing users over the next six months. The team has decided to create a HEART/GSM model to understand better how users use the website.
By looking at the hypothetical situation, I listed five business goals for MoodPanda:
Goal 1: Make mood tracking fun and enjoyable.
Goal 2: Users interact with others on MoodPanda Community.
Goal 3: Gain 100 new user accounts over six months.
Goal 4: User return every week to log their mood posts.
Goal 5: Minimize the time for the users to log their mood.
For signals, I analyzed the website to identify the areas that a user would typically visit on MoodPanda. One of the key areas is the user dashboard, where users can see their previously logged moods, the badges they have received, and log moods using the slide indicator. Another key area is “World Feed,” which connects users to other people for mood tracking purposes and to support each other. When developing the HEART framework, I focused on setting metrics for key areas of the website as this will enable MoodPanda to understand which areas they need to improve.
After understanding, Goals-Signals-Metrics, I mapped out HEART categories as follow:
Happiness
Users must find the process of mood tracking fun and enjoyable. The signal for this category is the badge they receive when they log their moods for seven days. Metrics applied here is the user satisfaction with the website (via a survey).
Engagement
For engagement, the feature of giving “Hugs” and making comments would increase user involvement. The key signal here is the time user spends on the “World Feed” page to interact with others. The metric here is tracking the number of hugs and comments by the user.
Adoption
For Adoption, MoodPanda wants new accounts to be created over six months. The signal is the increase in the account creation rate. The metric is the number of new user accounts in six months.
Retention
For Retention, MoodPanda wants existing users to log their moods regularly. The signal is the time user stays active in their account and revisits the log mood section. The metric is capturing the number of users who return daily or weekly to log their moods as this shows that the users are interested in using MoodPanda to log their moods.
Task Success
Make the process of logging moods less time-consuming for users. The signal is the time taken to log mood. The metric includes average time spent to complete logging mood, and this will enable MoodPanda to simplify the process and understand what areas could be improved.
HEART/GSM Model
Using the above reasoning, I created the HEART/GSM model for MoodPanda:
References
https://www.interaction-design.org/literature/article/google-s-heart-framework-for-measuring-ux
