Atrápalo seat maps

Atrápalo is a company which sells leisure deals for people who want to spend their spare time in their city or others. It is divided into nine areas: tickets, restaurants, activities, flights, trains, hotels, travels, cruises and cars.
“Tickets” and “activities” areas are basically an online service which allows purchasing tickets to go to the theatre, concerts and sports events in your city or nearby. It is possible to access this service both with a computer or with a mobile device (tablet / smartphone) wherever you are.

In this project, I worked as a UX designer in the design team of the company.

CompanyAtrápalo, best price leisure'sRoleUX designer

The challenge

How may we improve the seat maps experience?

The approach

Creating an inventory


The main goal was to provide a comfortable experience to customers during the purchase of online tickets for their favorite spectacles.
The purchase of an event which has the possibility of choosing a numbered seat takes customers through a seat selection flow. The seat maps are provided by a variety of different providers.

Therefore, it was important to inventory all the map typologies in order to locate pain points which were difficulting users to succeed on their task.

The approach

Creating an inventory


The main goal was to provide a comfortable experience to customers during the purchase of online tickets for their favorite spectacles.
The purchase of an event which has the possibility of choosing a numbered seat takes customers through a seat selection flow. The seat maps are provided by a variety of different providers.

Therefore, it was important to inventory all the map typologies in order to locate pain points which were difficulting users to succeed on their task.

The approach

Creating an inventory


The main goal was to provide a comfortable experience to customers during the purchase of online tickets for their favorite spectacles.
The purchase of an event which has the possibility of choosing a numbered seat takes customers through a seat selection flow. The seat maps are provided by a variety of different providers.

Therefore, it was important to inventory all the map typologies in order to locate pain points which were difficulting users to succeed on their task.

Constraints

It becomes interesting


Iframes difficulties
We could not redesign nor customize external seat maps because they were built inside provider’s platform and shown directly on our website with an iframe, therefore we had no control of the code. It also had no option to activate or deactivate elements inside external seat maps. At this point, the challenge was on improving the way those maps were shown.

Unpredictable designs
Each seat map provider could have different designs for their maps, depending on the theatre and the city. Furthermore, new maps could appear with new designs never seen before.

Constraints

It becomes interesting


Iframes difficulties
We could not redesign nor customize external seat maps because they were built inside provider’s platform and shown directly on our website with an iframe, therefore we had no control of the code. It also had no option to activate or deactivate elements inside external seat maps. At this point, the challenge was on improving the way those maps were shown.

Unpredictable designs
Each seat map provider could have different designs for their maps, depending on the theatre and the city. Furthermore, new maps could appear with new designs never seen before.

Constraints

It becomes interesting


Iframes difficulties
We could not redesign nor customize external seat maps because they were built inside provider’s platform and shown directly on our website with an iframe, therefore we had no control of the code. It also had no option to activate or deactivate elements inside external seat maps. At this point, the challenge was on improving the way those maps were shown.

Unpredictable designs
Each seat map provider could have different designs for their maps, depending on the theatre and the city. Furthermore, new maps could appear with new designs never seen before.

Research

A huge task


We inventoried all the different kinds of seat maps, grouping them by typology and having in that moment two providers + one own seat map created by the company.
Exploring the collected data we realised the old tracking code was not well implemented and the metrics we were collecting were not correct, therefore we decided to remove it and to implement a new one.
A new tracking code was created successfully this time and every seat map type was able to be segmented by providers.

A few examples of different seat maps.
Research

A huge task


We inventoried all the different kinds of seat maps, grouping them by typology and having in that moment two providers + one own seat map created by the company.
Exploring the collected data we realised the old tracking code was not well implemented and the metrics we were collecting were not correct, therefore we decided to remove it and to implement a new one.
A new tracking code was created successfully this time and every seat map type was able to be segmented by providers.

A few examples of different seat maps.
Research

A huge task


We inventoried all the different kinds of seat maps, grouping them by typology and having in that moment two providers + one own seat map created by the company.
Exploring the collected data we realised the old tracking code was not well implemented and the metrics we were collecting were not correct, therefore we decided to remove it and to implement a new one.
A new tracking code was created successfully this time and every seat map type was able to be segmented by providers.

A few examples of different seat maps.

Once the new tracking code was implemented, we measured a two weeks period and we segmented the data by device and type.
Meanwhile, we did a heuristic evaluation by typology just analyzing the way the seat maps were shown inside the iframe and how customers were able to interact with them.
With the data collected and compared with the heuristic evaluation, we were able to discover the points where customers either failed to complete their purchase or succeeded with difficulty.

Once the new tracking code was implemented, we measured a two weeks period and we segmented the data by device and type.
Meanwhile, we did a heuristic evaluation by typology just analyzing the way the seat maps were shown inside the iframe and how customers were able to interact with them.
With the data collected and compared with the heuristic evaluation, we were able to discover the points where customers either failed to complete their purchase or succeeded with difficulty.

Once the new tracking code was implemented, we measured a two weeks period and we segmented the data by device and type.
Meanwhile, we did a heuristic evaluation by typology just analyzing the way the seat maps were shown inside the iframe and how customers were able to interact with them.
With the data collected and compared with the heuristic evaluation, we were able to discover the points where customers either failed to complete their purchase or succeeded with difficulty.

General data segmentation by device and seat map provider.
User experience

Proposed improvements


Based on the obtained data, we proposed a variety of usability improvements for those pages, keeping in mind it was not possible to change anything on the provider's seat maps.
The improvements, segmented by typology and device, were:

  • Expanding iframe area on desktop in order not to lose vital information.
  • Removing extra information such as explanations about how the map should be used (implemented due to the difficulty on using it).
  • Making an automatic seat allocation on mobile devices (because the difficulty on tapping the tiny seating areas).
Recommendations to improve user experience.
User experience

Proposed improvements


Based on the obtained data, we proposed a variety of usability improvements for those pages, keeping in mind it was not possible to change anything on the provider's seat maps.
The improvements, segmented by typology and device, were:

  • Expanding iframe area on desktop in order not to lose vital information.
  • Removing extra information such as explanations about how the map should be used (implemented due to the difficulty on using it).
  • Making an automatic seat allocation on mobile devices (because the difficulty on tapping the tiny seating areas).
Recommendations to improve user experience.
User experience

Proposed improvements


Based on the obtained data, we proposed a variety of usability improvements for those pages, keeping in mind it was not possible to change anything on the provider's seat maps.
The improvements, segmented by typology and device, were:

  • Expanding iframe area on desktop in order not to lose vital information.
  • Removing extra information such as explanations about how the map should be used (implemented due to the difficulty on using it).
  • Making an automatic seat allocation on mobile devices (because the difficulty on tapping the tiny seating areas).
Recommendations to improve user experience.
Remarks

Interesting surprises


During data collection, it was interesting to discover many customers who had purchased tickets on their smartphones without going through a seat selection flow and without raising any complaints about that. Those customers purchased their tickets and they didn’t need to select anything else because the website automatically assigned the seat randomly for them among the best places available.
This showed that customers didn’t perceive this automatic seat assignation as a stopper on their way to purchase a ticket. In other words, the data showed that the fewer options customers have, the more focused they are on their task.

Remarks

Interesting surprises


During data collection, it was interesting to discover many customers who had purchased tickets on their smartphones without going through a seat selection flow and without raising any complaints about that. Those customers purchased their tickets and they didn’t need to select anything else because the website automatically assigned the seat randomly for them among the best places available.
This showed that customers didn’t perceive this automatic seat assignation as a stopper on their way to purchase a ticket. In other words, the data showed that the fewer options customers have, the more focused they are on their task.

Remarks

Interesting surprises


During data collection, it was interesting to discover many customers who had purchased tickets on their smartphones without going through a seat selection flow and without raising any complaints about that. Those customers purchased their tickets and they didn’t need to select anything else because the website automatically assigned the seat randomly for them among the best places available.
This showed that customers didn’t perceive this automatic seat assignation as a stopper on their way to purchase a ticket. In other words, the data showed that the fewer options customers have, the more focused they are on their task.

Future

Next steps


Next step would be A/B test the proposed improvement vs. the current one and then measure the collected data, to validate hypotheses. Once validated, it would be fully implemented.

Future

Next steps


Next step would be A/B test the proposed improvement vs. the current one and then measure the collected data, to validate hypotheses. Once validated, it would be fully implemented.

Future

Next steps


Next step would be A/B test the proposed improvement vs. the current one and then measure the collected data, to validate hypotheses. Once validated, it would be fully implemented.