How to Boost Sales with Artificial Intelligence

New data management methodologies now allow retailers to take advantage of even the smallest piece of information to generate valuable insights that help optimize their marketing and customer loyalty strategies.

Tuesday, August 24, 2021

  • What promotions do we do to get more customers to the point of sale?
  • How do we make them stay longer in the store? 
  • How do we improve the customer experience so that they buy more at each visit?

These questions are frequently asked by the sales teams of all retail companies, regardless of their industry. Increasing turnover, increasing the number of customers in physical stores, building customer loyalty so that they come back and also buy online, are part of the challenges that companies face today.

New techniques for mining and analyzing hundreds of thousands of pieces of data, coupled with the ability to use technology to model customer behavior at the point of sale to predict specific actions, is part of what retail companies can do today to better understand their customers and optimize their marketing and sales strategies at the point of sale.

How to increase conversion at the point of sale?

Before increasing the conversion rate of potential shoppers, it is necessary to measure foot traffic; to know how many people are in the store, in which areas and their potential interests.

Also read "Foot traffic analysis: Home Depot vs. ACE Hardware in California, USA".

With mobility data, for example, it is possible to identify what the people who enter the store are like, what interests they have, their behavior, their socioeconomic level, among other data. With this information it is possible to profile the consumers who enter the stores and use this information to develop promotional strategies adapted to these groups or clusters of customers.

Foot traffic analysis is derived from location intelligence, helping retailers better understand how people move around a physical location and providing new visibility into consumer behavior patterns by presenting an aggregated picture of the movement of people within a physical area, even segmented by the types of consumers passing near a store.
 
See "Big Data to Understand Consumer Mobility."

Through analysis of consumer behavior patterns, store design is improved and marketing strategies are created to attract more consumers at the right time and place.
 
Predictive models and AI (artificial intelligence) also help to renew aspects of stores, products and services, based on future trends, in order to stay one step ahead of competitors and keep customers interested and engaged.

Do you want to know how to apply these models in your business? Contact us!









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More on this topic

How to Improve Performance in Brick-and-Mortar Stores?

October 2021

Consumers are shifting their spending from physical stores to e-commerce, physical stores will only survive in this new environment if they reinvent their business, taking advantage of new technologies and modern analytical capabilities.

Today, there is access to significant amounts of data on consumer behavior, information on the economy of different areas, competitors' sales, and market trends. However, only a handful of forward-thinking retailers are leading the way in advanced analytics as they use location intelligence, foot traffic analytics, and predictive modeling to make smarter business decisions.

How to Increase Foot Traffic in stores?

August 2021

In the digital age, location intelligence and foot traffic analytics based on mobility data are changing the retail business, giving many retailers an edge over their competitors.

Location intelligence is defined as a methodology for understanding and visualizing mobility data to help solve a wide variety of retail problems.

Location analytics can drive retailers to success

August 2021

Retail companies are already implementing Big Data and geolocation analytics tools to understand consumer mobility patterns, measure foot traffic in each store, understand the performance at their points of sale and estimate competitors’ turnover.

Big Data techniques allow the recollection of large volumes of geospatial and anonymous data from various mobile devices such as cell phones, computers, tablets, etc., making possible to generate different detailed and general analysis that help to solve any kind of business problems in any specific sector.

Traditional Channel: How to Increase Profitability?

April 2021

Determining if the highest possible profitability is being obtained at each point of sale and if the establishments with the greatest billing potential are being reached, is part of what can be solved with geomarketing solutions.

Through Big Data management techniques, it is possible to collect, validate and analyze large volumes of information for all types of points of sale, such as convenience stores or grocery stores that operate in Central American countries.

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