Why can’t offline retail analytics be as smart as online?

Juha Mattsson

why can't offline be as smart as online

With the adoption of sophisticated web analytics, traditional retail analytics has gradually proven to be insufficient in understanding customers’ buying behaviour. As discussed in our blog post From retail analytics to Walkbase analytics, traditional data sources, such as point-of-sale data, do not provide information on customers’ whole buying path in physical stores. This holds true especially for the part between entering a store and going to the cash register – and understanding also those people who leave the store without going to the register. Arguably, we are talking about the most important phase in terms of converting intentions to purchases here.

Conversely, understanding customers’ shopping behaviour in detail is crucial to retailers for optimising store operations, increasing marketing ROI, and driving conversion and sales. Yet such customer insights and optimisation have become everyday practice for online retailers but not for offline.

Why can’t offline be as smart as online?

Well, with the help of modern in-store analytics, offline totally can.

In-store analytics technologies are currently revolutionising retail analytics. Walkbase is able to use a store’s existing Wi-Fi to capture precisely & real-time how we all behave in stores, from (i) passing by to (ii) where we go and how long we stay, (iii) up to the register and beyond.

The increase in the use of mobile devices enables the use of new and advanced technologies for this level of data collection. With the Walkbase retail analytics solution, retailers can capture precise data of customers’ in-store behaviour by for example counting the average length of a store visit, the frequency of repeat visits, or how many passersby the store is able to attract.

This data is vital in evaluating marketing campaign impacts, validating layout changes, window marketing and other in-store marketing, benchmarking the customer engagement and conversion ”capability” of multiple stores against each other, and drilling down to detailed analytics of customer behavior. When used rightly, such data can also form a new basis for behavioural customer segmentation.

The most applicable technology in most situations is Wi-Fi. In essence, Wi-Fi enabled devices, e.g. smartphones, can be anonymously and accurately tracked within a given indoor space. Compared to other passive people counting technologies, Wi-Fi tracking enables a cost-efficient and an effortless way to gather data, as the majority of customers are already equipped with a traceable device when they enter stores. Furthermore, a majority of stores are already equipped with existing Wi-Fi infrastructure, which can be readily utilised.

Wi-Fi based people counting is just like camera surveillance – it doesn’t require any actions from the customer, as long as the Wi-Fi functionality is enabled on the smartphone. All Wi-Fi enabled devices within the range of the store can be detected, as the device pings the Wi-Fi network. Even if no connection is established, the unique ID of the device can be collected. Following strict privacy standards, this ID is then scrambled before analysis, which ensures the appropriate consumer privacy – in many cases better than with cameras.

By combining traditional and new data sources, retailers can gain a more thorough understanding of their customers’ paths to purchase. This analytics information helps retailers to truly understand customers’ in-store behaviour and improve the whole shopping experience. In-store analytics technologies allow as effective data collection in the physical channel as e-commerce sites have had for years. When decision-making is based on precise real-time data, retailers are better equipped to adjust their actions according to their customers’ needs.

Walkbase Analytics enables data-driven decision-making to optimise store operations, grow marketing ROI, and improve shopping experiences. Learn more about Walkbase Analytics.

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