Yesterday, Blis introduced Smart Trends, an analytics tool that offers robust in-store comparison of multiple location types and brands. The tool allows users to conduct demographic, contextual, time and weekday, and device type analysis from a single platform in order to compare behavior of user groups side by side.
While Smart Trends is certainly a hugely valuable tool for media buyers and campaign planners, this alone perhaps doesn’t do justice to the potential of mobile movement data. A range of industries and roles therein could benefit by its use, be it financial analysts, general managers, heads of operations, brand managers and so on. It could even be useful for city planners (more on that later).
What sets Smart Trends apart is its use of mobile movement data. This is a complex data set that overlays device ID, longitude and latitude, and timestamp data. It builds on traditional location data in that it represents a consumer’s location movement over time as opposed to just a snapshot.
There are other characteristics of the data that make it a valuable complement to existing sources: it’s raw – meaning it isn’t subject to how a survey question is worded – indeed it isn’t self-reported at all. It simply says this consumer, using this (fully anonymized) device, visited this location, viewed this content. Smart Trends has the ability to collect at scale, making it the ultimate dataset for people who want to know where their consumers are, and what they’re doing.
The true power of mobile movement data lies in how it could be blended with other data sources, particularly an organization’s first-party data, as well traditional market research. In other words, once you know where your consumers are and what they’re doing, you could combine it with myriad other sources to understand why they behave the way they do. This combination could yield game-changing competitive advantages.
For instance, most marketers know a great deal about their customers’ behaviors and how they interact with their brands. What marketers don’t know is how those behaviors relate to their competitors, or even their more general day-to-day behaviours. The ability to glean those insights via unbiased mobile movement data could allow organizations to apply that intelligence to a wide variety of business challenges, and make decisions with confidence.
Case in point: we used Trends to conduct a Global Retail Study comparing shopper behavior across seven countries which looked at foot traffic at H&M, Victoria’s Secret, Topshop and Zara locations across the globe. A key business decision for global retailers is selecting where to open new outlets, with common sense suggesting that it makes sense to open new stores away from their competitors. However, our foot traffic analysis in this study revealed that brands may actually benefit from shopper crossover. For example, H&M appears to benefit when located in areas where foot traffic is naturally high, as shoppers may be less inclined to go out of their way to visit them than they might a Topshop.
Though scale is possible with mobile movement data, it’s not always necessary, especially when used outside of media and advertising use cases. Often, the goal is nuanced. Were a retailer looking to determine where to open a new downtown outlet in a city, it goes without saying that they wouldn’t necessarily need to know shopper behaviors on a global, or even national, scale. Instead, they’d focus on how shoppers behave when they’re downtown. The point is that that datasets can be both broad or narrow depending upon your goal.
Smart Trends lets you look at foot traffic volume by brand, by store, or by very tight local areas, and allows you to quantify the relative importance of different factors, such as competitor proximity, store size, or number of stores around the country.
Analysis based on mobile movement data could also be useful to professionals in other fields, who perhaps need to gain an understanding of how people move to, from and around locations. City planners could use it to determine where to deploy traffic taming devices to protect pedestrians, expand cycle paths, and widen roads. They could also use it to determine where additional stop lights are needed.
To be sure, these are early days for mobile movement data, but we’re confident Smart Trends provides the foundation of what can be a transformative tool. As we begin to see how it’s blended with other data sources, we will see it enrich everything we thought we knew about our target markets and constituents.
If you haven’t seen the power of Smart Trends, I recommend downloading Mastering Consumer Trends: a Global Retail Study, a custom in-store and inter-store brand analysis of four global retailers using audience, contextual and location data.
