AI-Driven Grocery Data Analytics

The grocery business is among the various retail categories that handle large volumes and require an efficient way to manage and track items across different categories. With Predictive Analytics that forecast trends based on looking at past and present-day data, grocery stores are getting an upper hand over the competition.

However, with many non-grocery players such as Amazon entering the grocery sector, it has become inevitable for the retail sector to adopt data-driven innovations such as AI-driven grocery store marketing tactics and grocery store analytics to stay on top of the competition. They can do so by leveraging their hard-earned data and gather insights from shopping preferences and consumer behavior.

What is the Artificial Intelligence (AI) Driven Approach?

With the AI-driven approach, all the available data will be processed and evaluated, and a decision will be made based on the connections between every single product that sheds light on aspects such as promotional and price elasticities.

For many, AI solutions will make the difference by discovering the best solutions to complex situations that need analyzing huge data sets. With the cost of AI technologies coming down and with rising computing capacity, grocers can make the most of the latest best practices when it comes to pricing, forecasting, and promotion.

Here is a list of business segments where AI-based analytics and predictive analytics can be used to help grocery store chains increase profitability:

Shopper Targeting

Customers are central to shopping and over time they form a pattern with granular data such as customer demographics. This can subsequently be utilised to the grocer’s advantage, for instance, to produce customized offers targeted explicitly at specific shoppers.

Pricing

Pricing has often been used as a tool to pull in customers. Predictive analytics can help retailers get answers to critical questions such as:

·         What is the right price point to enhance sales?

·         How would the sales increase with competitive pricing?

·         How frequently to introduce price-based promotional deals?

Many experts are certain that the use of Predictive Analytics starts showing results in just six months thus helping grocers make revenue gains.

AI analytics on the other hand can be used to sense buyer intent. Here is a list of sources of intent:

·         A favourite source of the intent signal is from knowing what a customer has searched for online. For instance, if a person has searched for gym shoes, there’s a good chance he/she is going to buy.

·         Other sources of buyer intent include what a customer is currently reading. For example, when someone starts reading about specific food brands, he/she is almost ready to purchase.

·         Lastly, the type of ads that individuals are clicking on can tell you what they are looking for.

The insights that AI offers, support substantial sales growth without amplified advertising cost. In the high-volume, low-margin grocery industry, it can prove to be very impactful. Manthan, offers newer ways to seamlessly align technology and customer to create opportunities for customer-obsessed businesses.