Reserved seating was my first design project at Songkick, allowing the business to sell tickets for seated venues for the first time. We had 3 weeks to deliver a solution from scratch in order to sell tickets for an event at the O2 Arena, Greenwich for So Solid Crew.
Venue & competitor research
We began by analysing different venue layouts across the London and the UK in order to understand the complexities of venue layouts. Competitor analysis was carried out on some of the best experiences at the time (SeatGeek, StubHub). The main problems we were trying to solve, was how to best seat customers automatically without them being able to select their own seats (this was deemed too challenging in the time constraints).
User research survey
A survey was run on songkick.com to understand what users perceived to be the most important criteria in choosing seats:
These results indicated that 60% of users say they would not be disappointed if they could not choose their seats. This gave us more confidence that we could design an experience which may not give them explicit control over choosing there seats, could clearly show where their seats were.
Exploring designs
Multiple concepts and approaches were considered before narrowing down the best ideas with the team.
Face-to-face prototype validation
As the Design Lead, I led the recruit and user research of the prototype with Songkick users testing across mobile and desktop web. The users were recruited by emailing Songkick Users and were screened.
The sessions were designed to be 1 hour covering the following:
- Introduction (10 mins)
- Exercise 1: Basic end-to-end tasks on desktop and mobile web (15 mins)
- Exercise 2: Purchase of 6 seated tickets which are not together (15 mins)
- Exercise 3: Seat Allocation Exercise: (5 mins) This would be dropped if we overrun.
- Summary: Thanks for coming, reiteration of what we’ll do with the info and signing of the NDA (5mins)
Seat Allocation Exercise
Another objective of the research, was to get an insight into which seating arrangements users preferred. This insight would be extremely valuable if we pursued the approach of automatically choosing seats for users.
This was run by showing users different seating arrangements and they would choose their favourite in each case describing why.
