How AI Helps Retailers Stay Relevant And Improve Sales

  • Written by  Kishore Rajgopal, NextOrbit

0aaaKishore Rajgopal NextOrbitAccording to 2018 statistics, an estimated 1.8 billion people worldwide purchased online goods. 2018 also saw global e-retail sales amounting to $2.8 trillion U.S. dollars, and project growth of up to $4.8 trillion by 2021.

Three insights can be drawn immediately for retailers on analyzing these statistics:

  • There is a certain willingness among customers to purchase products online;
  • Tough competition exists in this segment because there are too many retailers offering the same product or service; and
  • The customer dynamics are changing, and so is the customer. Their consumption habits, as well as their growing needs, need to be considered.

As a retailer in a tech-driven customer-centric environment, you are not only supposed to gather insights from the data available, but also couple them with the latest trends in the segment for the best results. 

Here are a few trends that are raising the bar for customers in the retail industry. 

  • There is an increasing demand for experiential retail. You need to combine your traditional and online stores to offer a 360-degree seamless experience. IKEA offered an AR platform for 3D at-home furniture preview. It lets users check if the furniture they are eyeing will look good in that particular space at home. Charlotte Tilbury introduced Magic Mirrors by bringing the AR technology to the mirrors installed in their stores. The shoppers could check out their makeup looks without wearing them, and know which one would suit them.
  • Immediacy combined with convenience is the need of the hour. To serve these customers, retailers need to plan their inventory as well as the distribution channels to avoid stockouts and overstocking. People prefer shopping on Amazon for products, as the platform offers good discounts as well as same-day delivery, catering to the need for immediacy. 
  • Mobile wallets and other payment modes need to be integrated into your e-Commerce channels for secure payments and faster checkout. 
  • Keep an eye on the demand. If the product is in demand, you need to have it stocked in your store. The customer is bound to go elsewhere if the product is unavailable.
  • Global markets are providing opportunities in newer and emerging markets to retailers. With the rising usage of technology, it has become easier for the retailers to reach the international market and tap into some of the unexplored territories

How Can AI Help Enhance Business Opportunities For Retailers?

To tap into these opportunities and fully explore them, retailers need higher levels of understanding their customers. It is important for them to personalize the experiences and individualize the purchases within the store and outside.

#1: Better Targeting

Let’s say you are new to baby products. You need to acquire customers, which becomes difficult if you start targeting just about everyone. People with no babies or those who have older children may not be interested in you, and targeting them would result in lowered reputation and acquisition. 

Now look at another situation. You know your target market, their behavior, the purchase history, the browsing history and even their preferences. Based on the data you have, you need to identify people who are likely to splurge on baby products.

Artificial intelligence will take into consideration all the factors responsible for identifying this segment and offer you insights that will improve your targeting abilities. 

#2: Improved Forecasting

When you know the demand for a product is going low, then you will stock the product accordingly. 

For instance, based on the season and the demand for the product in the past, AI models can predict whether the product you are launching will work with audiences or not. If you are a leather boot seller, then AI will tell you the store where there is higher demand and the stores where there is no demand for the product. Accordingly, you can allocate the products to different stores and manage the inventory. This will help you make sure there is no inventory lockdown, stockout or overstocking. 

#3: Taking A Personalized Approach 

Today’s retailers need to take a personalized approach with their customers. Sephora is an excellent example of using AI for personalization. Sephora has directed experiential retail by incorporating virtual artists and tap-and-try tools, which allow customers to understand what products will suit them. This has led to an increase in sales. 

AI dives into the historical data of the customer along with the demographic, behavioral and other data available to deliver a personalized solution. 

#4: Preferential Assortment

The customer fancies assortments, and if your store does not cater to their needs, then you might lose out on a potential conversion.

AI will help identify the preferences for products based on past purchases, current browsing history and other such data available from the customer’s store activities. Apart from that, a check into the demographics and other external factors will help explain the preferences. This will help the store keep up with the essential stock.

Summing Up

Retailers need to adapt to the digital era by transforming the way they connect with customers and convert. Retailers need to understand their customers, their growing preferences and their dynamic needs before putting the products in their store.

Artificial intelligence is the way forward. You will not only know the demand for a product but also be able to manage the inventory better, and in a more dynamic manner. You need to incorporate the aspect that you believe will improve your business. This means you need to study your business and its requirements before adopting the new technology.


Kishore Rajgopal is Founder and CEO at NextOrbit. His primary strength is to bridge business and technology/analytics and use it for a useful purpose. His other natural strength is to inspire people and bring out the best in them. NextOrbit is a SaaS offering that uses Artificial Intelligence and machine learning to solve demand-planning and demand-allocation problems in supply chains.

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