AND Digital worked in partnership with Zapmap to provide a more seamless experience for app users through a 400% reduction in loading speeds. This was achieved by utilising bounding boxes supported a more rigorous logic to underpin their API calls.
Zapmap is the UK’s leading app and digital platform for electric vehicle drivers, enabling them to search for available charge points, plan longer electric journeys, pay for charging and share updates with other EV drivers.
With nearly 10 years experience in the EV sector, Zapmap's database covers c. 95% of all publicly available UK charging points - so unlike their competitors, they are not beholden to third-party agreements - this means that Zapmap customers can find the best charging option for their vehicle and journey, regardless of the provider.
A purpose-led company, Zapmap’s mission is to accelerate the shift to electric vehicles and help the drive towards zero carbon mobility.
Zapmap’s existing API implementation meant that users were experiencing 100s of points of interest loading simultaneously, leading to a cluttered map and a confusing and frustrating experience when they were trying to locate a nearby charging point or plan their journey. This occurred because Zapmap was using a region bound API for the entirety of the UK which loaded all UK data points at the same time.
With international expansion on the horizon, Zapmap recognised that this was problematic not only for current users but for new markets as well. With that in mind, they approached AND Digital to develop and implement a new bounding box prototype that was scalable and would prioritise different data points to create better user experiences, wherever their users were located or travelling to.
Prior to delivering the prototype, AND worked with Zapmap to undertake initial analysis and experimentation at pace. This allowed us to produce a set of recommendations for scaling and developing the solution beyond the initial brief.
Due to the impending international roll-out and a number of ongoing projects in the Zapmap backlog, pace of delivery was deemed mission critical. With that in mind, the process kicked off with a two week technical discovery combining AND’s experts as well as the Zapmap team. A series of workshops were conducted in a time-boxed environment in order to:
Zapmap selected AND Digital for this project because of our depth and breadth of expertise in developing and delivering innovative mobile apps at pace, as well as our extensive work in the electric vehicles (EV) industry with other clients. In addition, our strong cultural alignment meant that integrating our teams was a smooth and efficient process.
We experimented with the API to implement logic that determined what data points should be loaded per region. This ensured consistent, even data density on the map at each zoom level as only the most important POIs are loaded per region. By limiting the app to a maximum of 120 data points at any one time we improved user experience by reducing overwhelm. This also reduces the number of API calls per zoom level as regional requests are made once, then cached. Usability was also improved through the implementation of a toggleable grid overlay that helps to visualise regional subdivisions.
Our solution enables the Zapmap app to:
This has set Zapmap up for success when scaling to new international markets.
The prototype app was designed for a larger viewport, making it easier to visualise the regional subdivisions, and allowing space for a text pane. The text pane displays live measurements on the number of regions in view, giving a clearer depiction of how the system is working at different scales.
Through this prototype, we were able to deliver clear results for Zapmap:
c. 250 POIs loaded at any one time*
Logical loading based on user location and proximity
*Averaged over 8, 12 and 16 regions in view on map
<5 seconds per API request
API calls were sluggish due to the high data volume
Average duration of 1.2 seconds per API request
On average, load speed improved by over 400% and caused a significant improvement to usability
>5 seconds to load all POIs
Slow load speed and cluttered maps meant users were unable to effectively view data points
Average time of 190 milliseconds to load 200 POIs
Significant improvement to speed and efficiency
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