Expanding Customer Base through AI-Led Pricing and Promotions

By CIOReview | Thursday, June 6, 2019

FREMONT, CA: The retail industry has undergone a drastic transformation in recent years. From the shopper’s empowerment to the sudden entry of online players, everything has affected the retail industry in various ways. With relevant data just a click away, consumers are increasingly trusting data statistics and technology to filter the plethora of offers and promotions.

For a majority of customers, price is the single factor that dictates their shopping behavior. Thus maintaining correct pricing is one-way retailers can stay relevant to their customers. Incorporating artificial intelligence (AI) based pricing gives shoppers the prices they expect for their favorite products. 78 percent of shoppers accept the price variations using data science.

AI plays a critical role in promotional strategies. According to a study, 52 percent of retailer's promotional efforts are confined to the customers who would have paid the full price. The loss of margin due to wrong audience targeting is just one aspect. Repeated promotion to the already loyal customers can create a feeling of distrust among them. Thus, there is also a risk of losing customers from the established customer base.

Shoppers are relying on AI technologies for fair pricing and accepting the promotional offers on their favorite products. Even the retailers agree that AI-led pricing systems have a positive impact on their businesses. An AI-led prescriptive and predictive analysis enables the retailer to design relevant promotional offers that can be channelized to the correct audience.

Some retailers are distrustful over AI capabilities that they prefer to rely on the traditional approach for their respective businesses, while other retailers are leveraging AI with proven success across the verticals. With a better return on investment (ROI) and optimization of promotional strategies, AI also provides further invaluable market insights.

AI capabilities can help retailers to provide targeted and segmented prices that impact shopper’s sensitivity and competitive elasticity. As the technologies are gaining experience over time, their efficiency and success rate are also getting better. Moreover, with machine learning (ML), self-learning algorithms continue to grow, thereby enhancing their capabilities to offer a broad overall market picture.

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