How Advanced Analytics Can Improve Operations In The Retail Sector
The retail industry has evolved over the years, becoming increasingly complex and competitive. The volume of decisions to be made in the day-to-day of a retailer is enormous. More and more variables influence it without considering the sector’s difficulties, such as seasonality, variability of demand, stock management, hourly staff, etc.
The traditional tools used until now are no longer enough. They cannot extract the valuable knowledge that hides the large volume of data available today to optimize processes and tasks. This directly influences employees’ day-to-day work and, above all, customer satisfaction.
Advanced Analytics as a Lifeline For The Retail Sector
In the current retail industry, offering the best experience to customers has become the key objective to improve sales and a challenge for retailers. So much so that the success of their businesses depends directly on achieving this goal. This is where the role of data becomes relevant. Data hides valuable knowledge, which can help us make better decisions that directly impact business results. But what data is necessary, and how to extract value from it?
Thanks to advanced analytics and historical data, it is possible to accurately predict the volume of visits that the store will have, forecast sales volume, or optimize operations such as replenishment or customer service. The application of advanced analytics can help us improve the customer experience in all its dimensions, working on each of the main pillars of the retail sector: the store, the product, the employees, and the customer.
The store is one of the most valuable assets of physical retailers since, together with the employees facing the public, they are the point of differentiation from online retail. Attractiveness to customers seems like an obvious requirement for retailers, but sometimes this is not enough for consumers. They want to find what they are looking for quickly, although they are not close to acquiring other items of interest to them. And how can retailers take advantage of this?
Thanks to data such as the history of visits and customers’ movements within the store, heat maps can be generated that indicate the most visible areas of the establishment. With this information, advanced analytics can create an optimal configuration of the products in the store. For example, on which shelf to place each product and in what way, which products to put next to others to improve cross-selling or their distance or proximity concerning the boxes; always looking to maximize the conversion of each visit.
On the way to achieving the best “customer experience,” as we have already explained in other articles, the most valuable asset that the retailer has is the employee. And the employees, together with “the store,” are the other key point of differentiation with e-commerce.
The employee is the visible face of the company in front of the consumer and is the one who, thanks to customer service, can offer a memorable experience to customers. Not to mention that they are the only ones who can convince them to purchase at the key moment of consumer decision. That is why it is essential that store employees’ management and their training are focused on achieving high customer satisfaction.
Emphasize the importance of having an optimal sizing of store personnel. Customers do not like having to wait longer than necessary or not being served due to the lack of employees in the establishment. Properly sizing the store at all times is not easy. Still, if we do it correctly, we can have the indicated number of workers both during peak hours and when there is less influx of customers, optimizing resources and maximizing sales.
But it is not only essential to have the correct number of workers overtime and to plan for the right employees at all times. For example, suppose you want to maximize the number of visits that end in conversion and thus maximize your results. In that case, it is crucial to plan the employees with the highest performance in the peak hours of visits, leaving the rest in less productive hours in sales.
Personnel management solutions that only automate the process of scheduling workers do not consider a prediction of visits by type of client or employee profile, among other variables. In addition to not generating shifts looking to improve the conversion rate and customer satisfaction.
Only those that use advanced analytics and artificial intelligence achieve the main objective: having the right employee in the right place at the right time. Well, they are capable of predicting the volume of visits to each store to adjust the schedules and tasks of each employee with the real needs of the store and its potential and seeking to improve the conversion rate without neglecting employee satisfaction and salary cost.
Ensuring a good supply of products so as not to lose sales and avoid having surpluses is crucial for saving costs and optimizing results. Often the tools used by retailers do not achieve the main objective, which is to ensure that the right product is present in the right store at the right time. The negative result is excess stock in some stores, stock out in others, and large amounts of surplus at the end of the season. This translates into costs, lost sales opportunities, low profitability, and dissatisfied customers for not finding what they wanted.
To correctly manage inventories and product replenishment, a solution is needed that applies advanced analytics and artificial intelligence to the replenishment process, such as NEXTEL, optimally distributing items between stores to avoid stockouts and maximizing sales and the ratio Of conversation. In addition, these tools automatically review and update the actual stock levels at the point of sale and in the warehouse in real-time, which allows, in the event of low stock of a product in the warehouse, to prioritize its deployment in stores with a greater probability of sale.
Who better than customers to give us the key to their satisfaction? Knowing what customers want and how they want it will allow retailers to offer it to them in the most optimal and individualized way. Personalization has become one of the main ways to attract customers and offer them the best possible experience. To achieve this goal, it is necessary to know their tastes and preferences through the data they generate during the multiple iterations in the different channels, including the social networks themselves.
Having a repository in which customer interactions and experiences are consolidated in the various channels allows us to have a 360-degree vision that will make it possible to provide exemplary service or products to the customer when they reach us through any point of contact. Thanks to advanced analytics, it is possible to discover trends, consumption patterns, and other insights related to our clients, which encourages the creation of new products and services and guides us towards more effective and efficient operations.