How data & analytics is fueling the retail industry?

This post talks about how Data Analytics allows retailers to turn their data into meaningful insights that they can leverage to define new go-to-market strategies with a better approach to winning customers.

Data Guy

3/6/20234 min read

Honestly, Data is not fueling the Retail Industry directly. it’s the Analytics that is doing it. But to get the right analytics, you need data first. So, indirectly, and technically, data plays a vital role as it is the foundation step in the overall process of Analytics.

In Retail, the old saying that the customer is God still applies!

And today, the customer is well-informed and has access to all the details that catalysis his buying decisions. One of the ways to win customers today is to target them with a customized and personalized approach that offers them what they are looking for and only Data analytics can do the trick in this case.

Analytics allows retailers to turn their data into meaningful insights that they can leverage to define new go-to-market strategies with a better approach to winning customers.

Below listed are a few ways that describe how Data & Analytics fuel the Retail Industry:

  • Knowing Customers and their Behavior:

Today, Data not only helps in understanding the customer's behavior but also helps in adapting to the changing behavior of buyers. Data, when managed properly, generate the 360 Degree of customer view that helps us find the buyers who are actively involved in buying behavior and then puts the products and services firmly in their line of sight, so they can easily slip into the next stage of their buying cycle. Data improves the understanding of the customer’s behavior and helps retailers to target them accordingly.

  • Forecasting Demand and Supply:

To run any retail business successfully, Demand forecasting becomes essential as it gives you a possible picture of future demand, which allows you to start planning everything else from production, inventory, and supply avenues to meet the expected needs of the market. The forecast is usually made on different levels of granularity – and can go from quarterly to hourly to support different planning processes, execution strategies, and business decisions. Having said that, no one can deny that higher granular forecasts are always extremely valuable and that becomes possible only with Data Analytics implications.

To effectively execute the store capacity planning for a retail outlet or doing the store replenishment, the retailers need to leverage the demand forecast in all their planning-related initiatives to eventually get more sales with better product availability, reduced spoilage (mostly in the case of perishable goods) with better stock allocation, increased inventory turnover with reduced need for safety stock and this list can go on because there is a lot more discipline that you can bring to the retail operations with having right forecasting of Demand and supply that is powered by data.

  • Assessing Customer Engagement:

Data & Analytics helps you uncover the true information about your customers that you can be optimized to give a better customer experience and can be even monetized easily if used correctly. More than 80% of Customers today are ready to pay more for a better customer experience. And hence, it is crucial to measure customer engagement based on the experience you provide.

The metrics like how much time your customers spend waiting in queues, the time they spend in the stores, their engagement with the loyalty programs, the feedback you receive, and the average net promoter scores provide the information that can be used in improvising the overall engagement of your shoppers. Taking customer experience from Ooh to Aha I am sure you heard this next statement before “Data is only as powerful as what you do with it”. That says, if you use the data to its potential, it will help you to learn from the mistakes and make changes that will help you provide delightful “aha” moments and positive long-lasting experiences to your customers. One of the ways to provide a better experience is by providing personalization and that is possible when you capitalize on the data about the preferences of your customers.

  • Predicting Customer Churn and Retention:

The best way to stay profitable and grow significantly is to take care of your customers and ensure that they stick around. And the first step to take so is having track of your customers’ churn and retention. You can use Analytical customer churn models that are backed by data and uses behaviors such as customer purchase intervals, upgrades, cancellations, follow-ups, and overall engagement throughout the tenure to predict when a customer may stop using your products and offerings. Using analytical models, you can identify a unique score that is attributed to each customer and will help you gauge the chances of them continuing the use of your products or not, so you can make the pivots accordingly.

  • Prize Optimization:

In retail, Prize optimization is a critical aspect as it directly results in Revenue optimization. Retailers use Data & Analytics to determine how customers are responding to different prices for their products and services through different channels. To build an effective model that shows the impact on Sales when prices of the products are changed, you need the combination of historical as well as current pricing along with consumer buying data. The more relevant data, the more accurate the model, and the better equipped the retailers will be to determine the optimal price points for the products.

  • Improvisation and Evaluation of Marketing Mix:

Today, in the digital era, where most shopping is taking a digital route, it becomes significantly essential to re-evaluate the marketing mix and see if your Brand and its products are fitting in the gamut of the futuristic e-shopping world or not. Luckily, that can be evaluated today and further improvised by integrating the marketing mix models with analytical models and techniques to provide multichannel impact analysis that can be used to drive and evaluate the success of the applied marketing mix. Such Analytics also embarks the indicators that can be used to improvise and transform the old marketing mix into something that is more relevant for success today and in the future.


Today, to be successful in retail, you got to rely on advanced retail analytics, metrics, and strong KPIs to support and take critical customer-centric business decisions. And to do so, retailers need data-backed processes that can harness the power of retail data in their analytics journey to deliver a good shopping experience to their customers that can improve their satisfaction, loyalty, repeat purchases, and eventually makes the customer more engaged and delighted. Not just that, it also helps in growing the overall revenue of the business.

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