How Data Analytics Can Help To Transform Retail

How Data Analytics Can Help To Transform Retail

August 20, 2020

Data Can Help RetailersLast updated December 19 2022 by Matt Felix


The retail industry is evolving at a tremendous speed. Consumers are shopping differently. The difference between online and offline is more blurred, and more retailers are looking for an edge in their retail strategies, as well as help understanding consumer behavior. Big data in retail is becoming more and more prominent.

Retail data analytics is taking over. The brands that are focused on accessible retail data are delivering increased value to their customers.

Let’s look at how retailers can use big data to gain a unique competitive advantage in a highly competitive space.


Comprehensive understanding of customers through Big Data in Retail

Big data is helping retailers to get a full understanding of customer trends. Combined with behavioral analytics, retailers can now predict what the next big trend will be. Crucially, these insights are allowing retailers to look forward rather than back.

In this way, brands can be more reactive. They can understand when preferences are changing before their competition. It means that the cost to acquire customers is kept low.

Instantly available retail analytics can help retailers to plan for the next must-have item. They can understand the type of user that visits their stores, with detailed insights into demographics and other key indicators of the kind of consumer.

Tools like Almanac help retailers see trends such as millennial customers’ growth, or regional patterns such as more young families in a specific area.

Moreover, being able to digest this in real-time before your competitors allow you to adapt to changes quickly and plan effectively.

Find out more about consumers here


Store customization and tailored promotions

Retail is so competitive that matching consumers to products is a must. Data enables this at an unprecedented scale, allowing retailers to target the right consumers for each product.

Understanding consumer behavior is at the core of this process. It allows you to map your customer profiles with more accuracy, which, in turn, helps inform more precise marketing strategies.

In-feed targeting can effectively reach the ideal customer with the best message when the right data sets are used. What’s more, data that can explain how customers are interacting with your brand providers retailers with a means to provide more personalized and effective marketing campaigns.

Find out more about retail marketing here

Using Big Data in Retail store planning

Personalization extends to in-store experiences. Big data can help retailers understand high-level insights around how consumers move in their retail stores and other areas.

Truly understanding a region can help to inform planning and franchising. Big data is at the forefront of this effort. Real-world consumer data fuel this revolution, but it’s not always easy to get the insights in a digestible way.

Almanac is helping insights and planning teams to achieve this at scale. By taking control of the processing of over a billion daily data points, it allows brands to focus on using the insights to achieve their goals.


Extending physical trends to e-commerce

E-commerce is a sizeable chunk of the modern retailer’s revenue stream. It’s essential that brands can use retail data analytics to help make the experience between online and offline seamless.

Customers want an online shopping experience that naturally works with their visits to real-world stores. Retail analytics can then help by providing detailed information on how industries and brands are performing.

Services such as click and collect and abandoned baskets messages are seen as something most consumers now expect.

Big data can answer questions that allow retailers to join the Ecommerce world to the physical retail store.

Read more about Physical trends here


Demand and order management

Behind the scenes, insights around consumer behavior help to inform the supply chain and optimize production.

Retail brands on the pulse of trends and changes in demand can plan to support this demand in the supply chain.

Using big data generated insights is useful in predicting trends, and assuring stock are in the best place. For example, when significant retail events happen, such as Black Friday, instant and accessible retail trends are useful to monitor regions where there is heightened demand to enable retailers to respond to changing demand and trends.

Big data in retail help brands answer questions that are vital to growing a modern retail business. Almanac helps to answer the questions that matter, such as:

  • Who are your customers?
  • What motivates them to visit?
  • What engages them?
  • How do they behave outside of your store?
  • How can you target them?


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