Heat Map Analysis
Heat Map Analysis is a method of graphical representation of the user’s mouse or eye movement when using a product or service. Heat Maps are helpful indicators of what grabs a user’s attention, where the users are spending their time and how much time is being spent on which areas. Additionally, Heat Maps can help determine which aspects of digital or non-digital products need to be improved. The data collected is represented using different colors where warmer colors indicate where the users spent the most time and cooler colors indicate a reduced level of attention or interest for the users. Heat Maps can also be segregated into different types such as scroll and confetti, making the map easy to interpret. Scroll maps represent data in the form on a spectrum of colors showing how far to the bottom of a page do users navigate whereas confetti Heat Maps give an indication of mouse clicks represented as spots of different colors. Depending on the kind of data that needs to be gathered to improve on user experience; one, the other or both can be employed. For example, if a submit button located at the foot of a long form doesn’t get clicked, then how far the user scrolls down on the form can be figured using a scroll type Heat Map whereas when there are multiple buttons on the page and we need to find out which button is optimally placed, is made of the appropriate colors, the terminologies used accurately capture the function the buttons will perform on click.
Heat Maps can be used to test different prototypes and models in terms of how engaging they are for the users, whether they are addressing the needs of the users and whether the user is taking intended actions intuitively. Similarly, Heat Maps can help to determine the optimum layout and user experience of websites. Various elements that make up a good user experience can be gauged for optimization. The aspects to analyze include navigation, user goals achieved with a fewer number of clicks, page layout, the kind of images used, the color combinations employed, the shape and size of buttons, the terminologies used to state the functionality of the buttons, the length, and language used for content. If coupled with other methods such as usage analytics and usability testing, Heat Maps can give comprehensive and valuable insights to optimize the models under inquiry.
Heat Maps are not necessarily restricted to mouse tracking, there are devices that can track eye movement and represent that data graphically in the form of Heat Maps.
|Mouse Tracking||To track and record mouse movement of users|
|Eye tracking||To track and record eye movement of users|
Advantages of Heat Map Analysis
01 Rich Insights
Heat Map Analysis gives quite rich insights in terms of usability if used correctly and can determine not only user behavior but also why they behave the way they do.
02 Optimization direction
Heat Map Analysis can help figure the user experience of prototypes or models and indicate the possible design directions that the designs must take.
03 Easy to interpret
Heat Maps are easy to interpret so it can be easily read and fairly understood by most people.
Disadvantages of Heat Map Analysis
01 Incorrect use of Heat Maps
Depending on whether an eye tracking or mouse tracking device is used or whether a scroll or confetti type Heat Map is used to represent the data gathered, the findings that a researcher can draw from the Heat Maps will vary.
02 Use of additional methods
Standalone Heat Maps as not as effective as using it in conjunction with usage analytics and testing methodologies.
03 Data interpretation
For a researcher who doesn’t have any background knowledge in analytics, Heat Map data analysis may not be as in-depth as required.
Think Design recommendation
Use Heat Map analysis to indicate a trend, especially something that has characters of density and movement. In other circumstances, Heat Maps may not make much sense. Few of the questions where Heat Map may be able to answer:
- Number of users over time (density: number of users, movement: time)
- Users’ mouse movement on a website/ portal (density: number of recorder cursors, movement: mouse position, time)
- Pedestrian movement pattern (density: number of pedestrians, movement: time, footprints)
- Medicine purchase pattern (density: number of units sold, movement: time trend)
- Goal accomplishment over time (density: transaction completed, added to cart, movement: time)
- Support call volume by geography (density: number of support calls, movement: geographic location)