How to Increase Customer Dwell Time?

Customer dwell time is an analysis that should be closely monitored to capitalize on the full potential of each point of sale, indicating greater customer satisfaction.

Estimating and improving the average customer dwell time inside physical stores is possible thanks to technological tools such as Big Datalocation intelligence analysis and mobility data, which improve strategic decision making by helping to increase the time consumers spend inside stores, and increasing the sales conversion rate as well.

You may be interested in: “How to Increase Foot Traffic in stores?.”

Today it is no longer necessary to have staff collecting manual information or watching a camera for hours; the analysis of the consumer path allows to offer a truly personalized experience, helping to improve and increase the customer journey, optimize the consumer buying processes, innovate in the internal signage of the stores, integrate products, services and implement advertising more suitable for each season and type of customer, among others.



How can the consumer “path” be measured and what are the benefits?

Consumer path analysis is a very useful method for understanding customer flow at any internal store location, as it helps to understand the differences between normal or expected customer behavior and atypical customer behavior, identifying how and why people search for a specific product or service, tracking the customer path segmented by departments, aisles and products, making it possible to estimate the average time of the consumer’s shopping journey from the time they enter the store until they leave the store.

Some of the benefits of these analyses are:

The identification of the point of purchase (P.O.P), finding the areas of the store where visitors become buyers, obtaining more clarity on why certain products or services are purchased.

“Image showing the potential sell points of a retail chain in California”

By making use of location intelligence and Big Data techniques, it is possible to extract all the observations recorded within an area of interest, the quality and resolution of the data allows to identify in which specific areas inside a store, the movement of consumers is concentrated. This is very useful when conceptualizing the design of the interior space and the distribution of the sections that make up an establishment.

“Image representing the distribution of consumers within a supermarket.”

Knowing how many times a customer was and how long a customer spends in a particular area (foot traffic), quantifying the number of shoppers with occupancy and increasing product demand, measuring customer service to improve service quality and staff productivity.

“Image representing an analysis of the foot traffic of a street.”

Establishing from the site selection of a new point of sale, choosing in which areas to place the entry and exit points of the stores to optimize the consumer journey times and not create drop-outs, bottlenecks that create obstacles in the buying process and customer experience, choosing the correct positioning of shelves, advertising, employees and products within the stores, among others.

“Image showing an analysis of site selection segmented by business revenue.”

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