As cities around the world began to lockdown, and the reality of what a pandemic meant settled in, the insecurity that the public was feeling led to panic shopping. Hand sanitizer, shelf-stable food, and toilet paper became rare commodities. We saw unprecedented scenes of empty shelves and overzealous hoarders. The grocery stores were a complete mess with frontline grocery workers overworked and overwhelmed. Months later, grocery chains have had to adapt quickly with new guidelines to increase efficiencies of both the merchant and customer experiences, limit store capacity, and sanitize everything. And while the supply of toilet paper has been restored, we’re still seeing outbreaks occur in these highly-trafficked and essential indoor spaces.
With a team composition of two engineers and one product designer, we set out a one-month project plan to research, ideate, define and develop a prototype that would allow us to validate and assess our concepts.
Depending on our desired outcomes for our internal research projects and given the lower risk that internal projects present we can sometimes take a leaner approach to immersion research to get into the making quicker. With a time-box of four weeks we took this leaner approach to get to the making quickly, while still ensuring we had a grounding in our users’ needs; an understanding of what products exist for them today and a good level of technical knowledge that would allow us to assess our concepts for feasibility.
User research
We started with identifying who our customer segments are when it comes to the grocery store space, and who are we trying to create value for. We realized that we have three groups to consider who have very different and sometimes conflicting experiences of the grocery store.
Standard Shopper Familiar with the store but looking for the location of a one-off item.
Professional Shopper Gig-economy shopper or store employed ‘pickers’ trying to fill orders fast.
Store Employee Tired frontline workers trying to be efficient as possible.
To help us understand the needs of different customers within the grocery store we held a small number of 1:1 interviews, conducted observational research, and also did digital ethnographic scans of various online forums. We synthesized our research into 3 customer profiles for store shoppers, gig-economy shoppers and store clerks.
A method we like to include in many of our short exploratory lab projects that helps us helps us rapidly build empathy with customers through digital ethnography, for this project we leaned on it almost entirely Digital ethnography refers to carrying out ethnographic research in an online space. Some benefits of this research methodology include:
- Extremely fast to begin and cheap when you don't have a budget or time.
- Access the customers in their natural context and environment.
- Online observations are less intrusive and immediately apparent.
- People’s behaviours are not as likely to alter as much as they would, should a researcher be physically present.
User insights
By conducting a scan of forums, subreddits, and Facebook groups we were able to record over 120 unique and connect them with specific insights into our user segments. Here’s a look at just a few of the anecdotes of shopping perspectives that we found:
Grocery store shopper
- Familiar to the store but looking for a one-off item for a new recipe
- Travelling and shopping at a store they are unfamiliar with
Gig economy Shopper
- Visiting multiple unfamiliar stores
- Shopping for unfamiliar items for their customers
- Short time limits set by Instacart
- Pay level equates to efficiency/speed
- Store Clerks are becoming hostile
Store clerk
- Frontline workers who are concerned for the health and safety
- Tired from months of high demand shift work
- Bothered by professional shoppers who ask too much of them
Research synthesis
While all our user segments experience the store differently we can find a more viable product-market fit if we can address pains that overlap between these different groups.
Identified opportunity
The pandemic has caused significant additional strain to grocery store clerks with panic buying, strict health mandates, and accelerated adoption of gig-economy shopping. We see an opportunity in automating a routine part of customer service within grocery stores to help alleviate the pressure and encourage less wandering and more efficient shopping. With rapid changes to the needs of both the customer and the merchant there presents an opportunity to innovate and help support these critical frontline workers. Our team saw store wayfinding as an underserved, unmet need, and one that is being exacerbated by both the needs of a new customer — gig-economy shoppers, as well as the new need of store clerks to physically distance from shoppers. We gave ourselves the following ideation prompt:
Concepts
Prototype Development
When deciding on what type of prototypes we needed to validate our concept for usability and desirability we aren’t simply considering high or low fidelity. We actively considered all of the following metrics in crafting our scope and approach:
To better understand the usability and desirability of our concept we wanted to test it in the store context with real customers. To do this requires a functional prototype with dynamic flows and real data. We want to assess it’s utility and desirability so we are aiming to have a relatively high experiential fidelity, but since this is just a prototype we feel that our rendering fidelity can be lower fidelity than we would otherwise aim for in an MVP.
Functional Prototype
In order to validate our concept's desirability, we wanted to create a functional prototype that could be tested with real users that would have a high degree of experiential fidelity. As a test environment, a medium-sized No-Frills grocery store was selected.
Mapping
The store was mapped for its layout, landmarks and product merchandising. The mapping process needed to be thorough in order to create a functional prototype that would deliver on our value proposition.
Each zone of the store was associated with a row in a database that contained the items found in that area and directions to that area of the store that would be agnostic of the position of the shopper
"Alright, Oatmeal can be found in Aisle 6 near the back of the store"
Position agnostic directions are important for our first concept because we don't have exact positioning of our users head position and longitude, latitude to accurately give turn-by-turn directions.
With our second multimodal example, however, we do know the position of the station and can give more referential directions, along with a visual routing to the queried product.
Actions Builder and Dialog Flow were used to map user queries to actions that would be rendered on the interactive canvas.
Onscreen Map & Pathing
Interactive Canvas is a framework built on Google Assistant that allows developers to add visual, immersive experiences to Conversational Actions. This visual experience is an interactive web app that the Assistant sends as a response to the user in conversation. Unlike rich responses that exist in-line in an Assistant conversation, the Interactive Canvas web app renders as a full-screen web view that users can control with either voice or touch interactions.
To help visualize our store map and our routing we used the API for Mapwize which is an indoor mapping tool that allowed us to:
- Overlay our store map onto a physical address
- Set product locations
- Create aisles on the store map
- Create and render directions between product locations
In three weeks we designed, developed and deployed a functional Google Action in a beta release that worked with navigating a local No Frills grocery store. Our prototype could work on a smartphone as an Action on Google Assistant, this interaction also works with hearables like the Pixel Buds. We've also developed the multimodal experience, as seen in the below demo video of it running on a Smart Display. The advantage here is that we can also see the store map and the pathing, as well as the dialogue.
Demo
Update
Just a few months after our work on this project it was amazing to see Amazon come out with the same concept for their chain of Fresh stores. Alexa-powered kiosks are now available to give directions to shoppers.
