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Guest Blog: How to Boost Retail Customer Experience Through AI-powered Price Optimization

This week we feature an article by Alexandr Galkin who writes about how retail management should focus on direct communication and/or a balanced pricing strategy and allow AI to manage price optimization. Customer experience comes first. Give buyers what they want, at the right price and time — and you’ll make them buy more and […]

This week we feature an article by Alexandr Galkin who writes about how retail management should focus on direct communication and/or a balanced pricing strategy and allow AI to manage price optimization.

Customer experience comes first. Give buyers what they want, at the right price and time — and you’ll make them buy more and stay loyal to you. The pricing process is a crucial element in building a successful shopping journey. As PWC recent study reveals, the price is what makes consumers shop at a particular retailer; the desired item being in stock, trust to the brand and a good location come next. Artificial intelligence can help to maintain your prices right.

Using dating terms, the price of a product can be compared to the first glance at a person you like. The price should trigger further interest in the item and seem fair even long after the purchase is made. It is something the buyer looks back at to understand if the whole relationship, or customer experience, was worth it.

Customers choose retailers with optimal prices. Does an optimal price necessarily mean the lowest one? Definitely, no. The art of crafting an optimal price entails persuading customers that your prices are the best bargain in the market (Amazon is brilliant when it comes to building the right price perception) and considering hundreds of variables (customer behavior, business goals, weather, and market data, to name a few) to base your prices on.

Very often, retail managers lack time and capacity to process and take into account all the necessary data to set attractive prices. “If your product managers say they would rather use their experience to set the prices, do not believe them. Human managers cannot work better than a machine,” says Bogdan Nesterenko, Head of Cross-border Projects at Northern European omnichannel electronics retailer RD Electronics.

Maybe, they simply shouldn’t. Advanced retailers have come to a realization that their managers, or agents, should rather focus on direct communication with customers and/or a balanced pricing strategy. Technology augments their expertise by handling routine tasks, analyzing enormous amounts of data, and providing market and customer insights. Powered by machines, managers can switch to making high-level decisions and ensuring that the customer comes first in any of the retailer’s undertakings.

Businesses are embracing AI-powered price optimization. For example, Amazon generates more than 35% of its revenue via AI price recommendations. Considering, that the US giant accounted for almost half of the US e-commerce market, or $258.22 billion, in 2018, its AI-driven earnings are impressive.

What makes such price optimization efficient?

When calculating prices, AI takes into account any amount of data with any number of pricing and non-pricing parameters (which is already unyielding for managers) to forecast demand and recommend the right prices in real time. It can suggest how to build the right price perception for a particular product or group of products and persuade customers that your prices are the most optimal in the market.

Also, artificial intelligence allows retailers to test if their pricing strategies are truly customer-oriented by predicting demand. As a result, you entice more customers, and the first stage of ensuring a rewarding customer journey is complete.

All-in-all, customer experience is becoming the key business priority for many retail companies. As the price of a product remains a crucial element of a rewarding customer journey, retailers adopt innovative technologies to ensure that their prices entice customers. Many businesses turn to AI-powered price optimization as a way to factor in any number of variables when calculating prices and allow managers to focus on interactions with customers and crafting customer-oriented pricing strategies.

Alexandr Galkin, CEO & Co-founder of Competera, price optimization software for enterprise retailers looking to increase revenue and stay competitive. Forbes contributor, speaker at IRX, eCommerce, RBTE conferences.

For more articles from Shep Hyken and his guest contributors go to customerserviceblog.com.

Read Shep’s latest Forbes article: The Thinking Behind Customer Relationship Management (CRM)

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