IMPROVING SHOP TOOLS
IMPROVING SHOP TOOLS
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THE PROBLEM
THE PROBLEM
John Lewis in-store staff use a special Partner Device containing a set of appropriate software, including Partner App, with which they can help customers make online purchases from within the shop.
Not all product information was available to Partner App, meaning Partners had to use multiple tools to find it, generally with a customer present: a time-consuming and frustrating experience. So the team was asked to look at possible ways of letting Partners access content from an additional in-house source.
DISCOVERY AND SUPPORTING HYPOTHESES
DISCOVERY AND SUPPORTING HYPOTHESES
An interview with a key stakeholder (with in-store experience) yielded an initial set of additional data points that might be useful to Partners.
Interviews with some in-store Partnes led to insights around the ways in which they currently access the additional data points
The current Partner journey was full of pain points, including time taken and the requirement to physically move around the store with the customer
Outline journey: information request from customer > information not found on Partner Device > move with customer to in-store till > log in > search for additional data
We used test cards and Value Proposition Canvases to tease out pains, gains and possible routes forward.
From this we created a small set of prototypes which explored a number of ways of integrating the data into Partner App and then tested it in-store with Partners
A sample Value Proposition Canvas exploring how Search would benefit from the additional data
TESTING & RESULTS
TESTING & RESULTS
In-store testing and contextual research with Partners focussed around three main areas
Confirming (or not) the typical Partner journey when trying to find the data
Talking to Partners confirmed that this was a major pain point, taking a long time, requiring multiple logins and potentially causing friction with customers
Ascertaining how useful and intuitive the proposed integrations were (at a fairly high level)
The prototypes were aligned with existing search functionality in Partner App and as such were easy for Partners to pick up. The majority of Partners felt the proposed integrations would be a benefit to them
Confirming (or not) that our initial discovery had identifed the correct data points
Here the contextual research only partly backed up intitial discovery e.g. certain hypotheses around future stock levels were found to be not important to Partners, and from his work we created a new, revised set of data points.
Sample screens for testing
FURTHER WORK
FURTHER WORK
From this point the work split into three main areas
Helping the team with data point definition and liaising with in-house technical staff to ensure the data could be retrieved
Creating a value matrix, looking at
value to the business
implementation cost
value to Partners
The matrix was completed by a cross-discipline team of POs, BAs and Devs. This gave us a rounded view where the costs, opportuniies and value lay
Finding a way to put a commercial value on the work, as it wasn't directly tied to sales.
FINDING VALUE
FINDING VALUE
The key metric for Partner (and hence business) value was the time saved by integrating the new data into Partner app, as opposed to leaving it in external systems.
To measure this I created a series of working prototypes, taking the test subject through the process of scanning a product and finding the additional data within Partner App. I added some special timing features, the results of which were then saved to an anonymous Google Form.
We had over 500 responses and found that the new approach would save on average 90 seconds for search. When multiplied out across all shops and relevant staff, it represented a substantial time saving, which the team were able to use as justification for the ongoing development work.
Prototype with tooltips and 'I'm done' button to record the time taken
SO HOW DID DESIGN THINKING HELP?
SO HOW DID DESIGN THINKING HELP?
The discovery process brought us into contact with end-users (in this case Partners) giving us insights and empathy with the issues
Tools like the Value Proposition Canvas helped us to organise and prioritise the results, and the next steps we wanted to take
Brainstorming with the team, which included BAs and Devs, gave us a wider range of perspectives on what was possible
Discovery-driven Prototyping gave our test subjects more context for our ongoing questions and led to more robust answers from them
Using a value matrix helped define the most appropriate and high-value approaches, focussing the work even further
Large scale quantitative testing gave us the justification to push the project further
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