Retailers of the future use instore analytics | the red queen effect
The Red Queen phenomenon, is when “it takes all the running you can do, just to keep in the same place. You need to run at least twice as fast to get somewhere else”. Evolve at a furious pace would be my advice to retail.
Retailers are nowadays under a similar evolutionary constraint: pandemics, e-commerce dominance, increasing competition, complex shopper journeys, increasing regulation in digital marketing are all stressors requiring continuous innovation or will hold you back.
Instore analytics allows retailers to capture customer behavior and provides actionable insights in improving customer experience and operations. Retailers need intelligence into their shoppers’ interactions with various touch points in order to optimize operations and determine how well different channels generate sales.
Digital storefronts have (had!) a natural advantage in measuring and optimizing shopper behavior, the advances in convenience and personalization of digital stores have only increased shopper expectations in physical channels. Replicating this shopper experience in brick-and-mortar enterprises, like retailers or malls, requires technologies that capture and measure shopper behavior seamlessly.
Metrics such as footfall analytics, dwell time, return visits, conversions, and customer loyalty are important factors to measure. Countless operational, tenanting, security, and marketing decisions depend on this data, however, retailers are forced to make these decisions without the necessary insight.
Instore analytics tools capture and analyze data from many touch points throughout the store, providing retailers with detailed insights into their customer experience. Replicating the same level of insight as digital storefronts in brick-and mortar channels is possible nowadays but does require several considerations. Don’t factor in the limitations imposed by the physical space and therefore requires several considerations.
Unique Buying Reasons
There are many important considerations that need to be considered when choosing to develop these capabilities.
1.Capture shopper data in real time.
The actual process of data capture must be seamless and in real-time to avoid Hawthorne Effect, Observer-expectancy effect or Observer bias.
Understanding shopper behavior requires capturing attributes of shoppers in real-time, requiring multiple sensors. However, this can lead to several disparate technologies that can be intrusive and increase the number of silos.
It is also important to understand the unique and personal attributes of an individual visitor as well as at an aggergated level. Having a unified view of your shopper allows you to understand shopper needs, build segments, and more important engage with them.
Retailers typically have many legacy investments in store hardware and software. A solution that integrates with existing systems is an important consideration to truly drive insight.
5.Seamless shopper experience.
All the above factors are dependent on not interrupting the shopper experience instore with surveys, lengthy sign-up processes, booths, or privacy risks. Measuring shopper behavior should be seamless, non-intrusive and privacy friendly.
At the core of any successful strategy is a data capture platform that is not only scalable but also flexible in terms of deployment of sensors and deployment of analytics. To move forward successfully it’s critical that businesses take time understanding their unique needs, determining which features will help them grow their business while still maintaining a high level of service quality they expect from themselves.