How retail businesses can use data in the most beneficial way
Nowadays, retail businesses are opting for big data analytics and AI in their operations. The research from McKinsey shows that retailers who can use data to their full potential may increase their operating margin by 60 percent.
It is said that if retailers haven't started to consider implementing data, they are at risk of falling behind. This is surely not overstated because data is the knowledge of behaviors, activities, and operations circulating in businesses. Disregarding data means we are not learning about our customers' behaviors, not inspecting purchasing activities, and not understanding our operational performances. Therefore, we won't be able to accelerate business growth and generate profits as much as those who optimize their data.
The main question from retailers who aren't ready to participate in the data world is that "How could we start implementing data in our business?".
Sertis wrote this article as an answer that will guide you through the areas where we can implement data and how we can utilize its potential to the fullest. The answer is we can use data to answer the 3 main questions in businesses - What should sell? Who is our customer? And how can we manage our inventory?
Having data in your hand, finding decisive strategies, products and services that serve demand, and a profitable inventory management approach is no longer difficult.
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What should we sell?
Selecting and assorting products and planning the campaign such as promotions and discounts are essential parts of both online and offline retail. Among plenty of product choices out there, choosing the right products leads to success, while mistakes may cost you a lot of money.
Data help answer the question of which products you should select for your stores and your individual customers, as well as design the effective promotion to reduce cost and maximize profits with these solutions:
Product Recommendation: The solution helps recommend the right product to the right customer by analyzing the data of the best-selling products, more specific data of each target customer's preference, and the records of the potent products and bundles that customers buying these specific products might consider buying as well. AI analyzes these data and provides a recommendation to a similar group of customers or suggests more products that each customer might be interested in.
Assortment Optimization: The solution uses purchasing records in each branch to recommend types, brands, and quantities of products that have potential in each store branch. AI will also help create a product assortment that is different for each branch based on factors. For example, this branch should sell the detergent from brand A instead of brand B because it is more preferred among the customers in the area. Data is utilized to create the product mix that suits the needs of customers in specific branches.
Promotion effectiveness: The solution collects the data of each promotion to evaluate their effectiveness and see which works and which doesn't in order to improve or change the promotion strategies.
Who is our customer?
Targeting the right customers and truly knowing them by understanding each customer's preference and how their relationship with us is like, as well as knowing before they stop buying from us - this all knowledge may sound challenging to gain within the limits of our capability, but data make it all possible and easier with these solutions:
Customer Segmentation: We can sort and study the complex groups of customers by using business data, characteristics data, and customer demographic data, including ages and sexes and specific behavioral data. Target customers will be divided into groups based on their behaviors and needs, so that we can offer products and services that serve rights to their needs, and attract the right groups and individual customers that are looking for what we offer.
Customer Lifetime Value: We forecast each customer's lifetime value based on their purchasing history to see how much they purchase from us over the whole period of our relationship. We also forecast changes over time and the worth of future purchases to design the strategy to maintain the relationship.
Churn Prediction: We analyze customers' purchasing records to know whether they have the probability of leaving the service and provide a timely alert. We also inspect their behavior to find the cause of churns and provide a signal when the signs indicating that they might leave are found. This insight is for us to take action by designing strategies to attract them back and maintain the relationship.
How can we manage our inventory?
Inventory management is another essential factor to decide whether retailers can survive. Stockouts mean missed opportunities and overstocks mean more costs you have to bear. Data fits the bill because it offers these solutions:
Demand Forecasting: Purchasing records, trending products, or even weather data, the number of tourists, and other related factors are used to forecast the demand for each month for accurate inventory planning, not too much or too little.
Store Replenishment: Data can tell the optimized amount and frequency of the replenishment, telling us which products should be restored, when, and how many. This will eliminate the missed opportunity from the stockouts and reduce the costs of overstock.
Data is beneficial for all necessary parts of retail business operations. It can be analyzed to find answers to most business problems, whether it is to find the cause of problems, improve the processes, increase profits, or reduce costs. Data can be turned into profits and make business more profitable.
Don't know where to start? Start here with Sertis. We are ready to collaborate with you to customize the most beneficial data solutions that serve right to your needs to steadily and sustainably maximize your profits.
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