Gap Inc has a single bag and checkout experience for all four of its brands. Design decisions constrained by legacy systems, different technology stacks and organizational cautiousness due to business sensitivity resulted in a sub-optimal customer experience. Two different teams were initiated to solve “low risk, high impact” issues with an overarching “do no harm” philosophy.
Collaborators: Product management, visual design, marketing, customer insights, content writer, brand leaders, engineering
Gap’s shopping bag featured a breakdown of the costs of the items in the bag and a selection of shipping methods. A threshold amount of $50 was required to enable the free shipping selection.
Free shipping is a very standard customer expectation. And it was a well-documented customer behavior to add items to bag just to meet the free shipping threshold.
However, customers could apply promo codes they receive only one step before placing their order in checkout.
If valid promo codes brought their final total below $50, they were automatically switched over to the basic $7 shipping fee option.
Inevitably customers would try to apply their promos at this last step in checkout bringing their total to less than the $50 threshold and thus losing the free shipping.
Loss of free shipping led to checkout abandonment.
Looking at over 30 other retail experiences, a landscape of threshold shipping and promo code relationship emerged
The restrictive sequence in which Gap was offering application of its promo codes and qualification for free shipping was not what customer’s were experiencing at other retailers.
A typical beginning is a team brainstorming session where we whiteboard all known facts/data points and assumptions the team has around the perceived problem.
In this case, we had factual data about- checkout abandonment in promo module, how competitors were offering “qualified for free shipping” and promo, reported problems around promo use (through numerous surveys and call logs over the years) etc.
Some assumptions we made included:
The first hypothesis to be tested in this case was IF we remove shipping method selection from bag, customers would continue to checkout in order to make a selection which we can measure by comparing bag conversion rate.
This was the smallest possible experiment to learn whether pushing all shipping related selections to checkout have any effect on bag conversion.
Following a similar brainstorming process on the project objective the next hypothesis was around moving the promo module out of checkout and into the bag.
IF customers are allowed to see all of their possible savings in bag including qualification of free shipping then they are likely to checkout during the same visit to back as measured by increased bag conversion
This required considerable technical development to create an A/B experiment.I decided to go with a more traditional approach, first creating divergent concepts of how all savings could be shown in bag.
While these concepts were focused on the larger picture of how all possible savings could be shown in bag, the experience had to be mindful of a few unique features of how Gap businesses show savings and promos
The concepts were reviewed by UX leaders and the three best ones were selected for rapid interviews with customers.
This is something I typically always set up to orient researchers, product managers and other designers on the team. Some questions here included
The final designs went through reviews with UX leaders, product partners, business experts and leaders. Over several months of developer pairing, the product was launched on Gap sites.
Overall savings on shipping calculations were reported. There were also lower call volumes with regards to promo redemptions