What’s Hot: Heat Mapping

August 16 2012 User Experience Design

Trulia.com recently released a responsive, interactive heat-mapping tool that helps visualize “average commute time” — a tool that enables a user to get a quick snapshot of areas that might be out of consideration or expose neighborhoods they haven’t considered yet.

Instead of showing a user the ETA based on a specific location, Trulia’s heat map U/X allows a user to drop a pin on a location and set their mode of transportation. The user can then view the average commute times it will take to get to any surrounding location based on that pinned location. This is a clever and useful feature for the Trulia user who is often searching a new neighborhood or city for the first time to make meaningful decisions from often silo’d data.

Trulia’s map also shows data overlay for violent and non-violent crimes by location, which is also critical information for a potential resident. The crimes map, however, does not display as a heat map, but rather specific, pinned locations.

While this is great information, it lacks the quick decision-making approach of neighborhood history that the heat map so clearly illustrates.

Imagine a crime map that provides high-level visualization of the most crime-stricken (and violent areas — perhaps even by times of day and/or even by lengths of time), with the ability to zoom in on specific criminal activity.

Trulia’s step into heat-map U/X for data visualization is on-trend and useful as users expect digital to not only present information but enhance decision making.

Nike has begun integrating heat maps to allow Nike+ users to see most routes that runners use or haven’t used, and is a great tool for discovering popular running areas or little-known routes.

From a U/X perspective, heat maps are a perfect starting point to presenting patterns of data, whether aggregated from users or from a single source. With the ability to provide the bird’s eye view and bigger picture, users are quickly provided visual information and then afforded the opportunity to zoom in.

One specific area Trulia fails in is segmenting their heat map into a “discovery” funnel that doesn’t tie to a “conversion” funnel. Assuming Trulia’s business goal is to drive property views and contact lead generation, it would seem natural that the two funnels should be better integrated.

The heat map stops at discovery — but imagine if a user could zoom into an area and be given layers of additional information including suggested properties within zoomed in areas. The U/X experience would then be a deeper, more engaged experience and would hold to reason that a user would be more likely to spend more time on site and be a qualified lead as they’ve zoomed past layers of data.

Here are a few insights I think will help companies leverage heat mapping in the most optimal way:

  • Make your maps responsive. Digital experiences should be accessible on the go and from mobile devices.
  • Present meaningful data. For example, common sense would make you think that Trulia’s average commute time data might not be the most useful. Obviously, the further you live from a destination the further it will take to get there. What if Trulia were able to take commute time further and calculate traffic time? That would paint a more realistic and accurate picture of a commute than simply “average time.”
  • Allow users to create views that matter to them. As the web becomes ever more a curated experience, allow users to turn on, turn off filters and explore data that matters to them. Trulia’s map could benefit from cross-visualization of multiple filters to get a good comparison view of multiple important points. For example, seeing an overlay of crime over commute times might allow a person to weigh the importance of their filters and find the most optimal area.
  • Capture the spirit of personal exploration. Allowing a user to connect social graphs could allow users to see where their networks have been, what’s popular or trending — on a personal level. This next step allows a user to not only discover data but personally relate to it.
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