Great products address a clear need, where the audience and their goals are easy to understand and articulate. If you can’t identify your user’s goals and motivations, you can’t design an effective product.
Quri offers a retail intelligence platform that audits retail execution using crowdsourced consumer data from our mobile app EasyShift. There are two audiences served - the task force collecting the data, and the customers who use it. The customer’s goal is easy to define - to gain insight into their retail execution. The task force’s motivation is equally clear - to get paid for completing simple tasks.
Because our customers lack the manpower to audit their product execution themselves, there is clear value in a service which can quickly aggregate this information. The dashboard started with basic job-based data (what was collected for a specific set of stores for a specific date range). As we collect more data the possibilities for new features which make use of that data increase - like the ability to see trends in data over time or to gauge the efficiency of corrective action. More features require a better understanding about how those features are used, how they work in relation to each other, and how the UI should be optimized to support them.
The problem is that the consumer package goods industry has never seen an offering like this, so until we acquire a larger customer base, finding users to give feedback on the dashboard design can be a challenge. Without direct access to users we have to find alternative ways to evaluate the designs.
We have analytics on the dashboard to identify patterns of behavior and preferred features of heavy users, but this only provides insight into the usage of our limited customer base. We always have access to proxy users - either in the form of internal users or third party recruits. But one of the best vehicles for gathering customer feedback is our sales channel. We include proposed feature designs in sales presentations and gauge customer interest. Some sales presentations include rich interactive demos of potential features, and this helps us gather feedback on how these designs meet or fail to support customer needs.
Fortunately the audience for the EasyShift consumer app is more accessible. We have analytics to monitor app usage, direct access to users for exploratory conversations, and a community forum in which users regularly volunteer information about their behavior, motivations, and problems. We have also used testing service usertesting.com for evaluating new features and better understanding user behaviors.
For example, heavy users tend to reserve several shifts at once, and have a tendency to travel from location to location completing shifts in a single trip. The interaction therefore needs to be optimized to support this behavior. Users have expressed secondary motivations for using the app beyond just the payment incentive, like the feeling that they have contributed to correcting systemic problems in retail execution. This kind of sentiment helps inform the way we communicate the messaging in the app.
Having a clear understanding of the audience of both sides of our product helps us to iterate our product designs to make the experience for both audiences even better.