Geospatial Analytics

Domains Involved
  • Continuous Delivery
  • Geospatial Analytics
  • Lean UX
  • Retail
  • Saas Software

Presence Insights is an analytics SaaS tool using GPS, WiFi, and Bluetooth technology to track and analyze customer behavior across physical locations.

Defining a New Market

The potential applications for location tracking were incredible. So much so that they were likely the single greatest issue the team grappled with.

Companies had a strong understanding of what their customers did in their digital channels. Embeddable analytics meant they could track behavior down to the click and respond to it with context. However, within their physical locations, they were almost blind to when and where customers went during visits. Our research determined the opportunity space was in providing better customer service. With better context on a user’s current location, situation or past behavior, our clients could better accommodate their customers’ needs. Retail, healthcare, hospitality, travel — all lacked the information they needed to best help their customers.

Getting Resourceful with User Research

The roles involved didn’t exist within IBM’s client base or varied so widely between clients that identifying the right people to talk to became its own intensive work stream. The team’s response to the challenge was crafty. To get attention from and meaningful time with IBM’s largest customers who were always very busy, the team built a level of domain expertise that allowed us to approach conversations with a “give to get” model. In return for their time and insights, the team could help our clients understand the potential the technology had and how to use it effectively in their own business.

We also turned to LinkedIn, MeetUps, and online forums to better understand potential users as well as hiring a Research Agency to recruit professionals who met our screening criteria. The outcomes were incredible and allowed us to set a sprint cadence that included generative research, concepting & prototyping, and user testing to rapidly evolve our understanding of who would use our tool and how.

Creative User Research

Without an existing user base within IBM, the team resourcefully scoured MeetUps and LinkedIn to develop a profile for our Design Targets and start talking with potential users.

A Lean & Iterative Approach

My teams always take an MVP approach to releasing and learning early. However, it was clear that for a service with such broad potential we would have to narrow focus even more. If we didn’t pick an industry to get on our feet with, we risked being swallowed up by the volume of requirements to needed understand and satisfy every industry while at the same time learning how to work with these new technologies.

We chose to focus on Retail where our strongest client interests lay for our first iterations. From the retail use cases, we would then come to understand how easily concepts from the technology would be consumed. We built new metrics and Retail-specific models like Customer Loyalty and Customer Journey. Armed with the expertise gained from Retail, we could then begin to find both common and unique use cases across our other target industries — Healthcare, Hospitality, etc.

As we got a high-functioning Agile process running, we were able to get iterations in front of our target users often enough to say we were almost co-designing with the ideas they were spitballing from call to call. As we tested, our designs inspired use cases born from their experience in their industry that we couldn’t have otherwise thought of. The pact between design and development to build and scrap designs and code with new insights gave the team the ability to be responsive to a market that was itself still struggling to understand its potential.

Presenting a single “solution” from an iterative team wouldn’t make sense. Instead, the designs evolved with the team’s insights sprint after sprint.

Simplifying Difficult & New Concepts

As we better understood our users, we better understood how their fields thought of customer behavior, used analytics to communicate results, or used data analysis to predict trends. This also brought us an understanding of how we should present the charts in each industry’s language. As a result, the designs began to take on a more “conversational” tone, as if they were an extremely well versed co-worker explaining what happened in stores over a period of time.

With this new engagement model, user comprehension jumped. Free of the frustrations of trying to map technological or literal verbiage to their own field, customers could now focus solely on how to effectively apply the insights provided by the service.

Early designs took a very clinical tone to labeling — visits, devices, dwell. User testing showed that those concepts were hard to grasp. We began describing charts with more conversational language and users immediately responded positively and better understood the service’s potential.

Hands on Hips

My designers have heard me say that I value a team that enjoys looking back at what they’ve built each day with their hands on their hips and an “oily rag” in their hand proudly stating, “Look at this incredible thing I built.”

This tool is just that — something I and the team are incredibly proud to have built, and built with care in craft. We fought hard for the insights that fueled the designs. We worked through teaming issues to build a healthy and nimble collaboration model. Most importantly, we built a tool that would bring value into other people’s lives. Retailers would be able to better understand their customers and provide better service, and customers could receive that service in completely new ways from way finding, to personalized digital assistance aware of their current situation and able to respond accordingly.

I can’t go into further detail about this project publicly, but we can still talk about it.

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