AI-Driven Success: Electrolux's Strategy for Enhanced Customer Experience

Electrolux is a great example of a retailer using first-party data and a CDP to boost sales and customer engagement in innovative ways. They began by identifying and grouping customers based on their product interests. Then, they used AI to match these interests with products that had price reductions. When prices dropped, an API call notified their CDP, which then sent targeted emails to interested customers.

Unlike traditional one-time email blasts, this method involved an always-on campaign that ran continuously with minimal intervention. The initial setup required IT support, but after that, the marketing team managed the process on their own.

This price drop strategy significantly paid off, generating five-figures in e-commerce revenue within the first 30 days. Additionally, web engagement and e-commerce conversion rates saw a marked improvement, with an 80% increase in e-commerce rates and a 20% decrease in e-commerce bounce rates. A big part of this success was the enhanced customer experience from matching products with customers' historical interests.

Nicky Peterse

Manager, Strategic Customer Success, BlueConic

07/14/2024 20:58:06

Navigating the eGrocery Landscape: Lessons from Walmart’s MAU Growth

The most interesting data point we’ve seen in recent months is the increase in MAUs for Delivery.

If you look a little bit deeper into these numbers, you can connect the increase to a discount perk (50% off) being offered by Walmart to members who commit to its loyalty program for an entire year. This, alongside other recent initiatives from the big retailer, suggests that Walmart is shifting focus slightly to further retain the customers they initially attracted with lower prices.

To this point, Walmart has done an excellent job of not only leveraging its inherent pricing advantage but also communicating value and convenience to customers as part of a broader retention strategy.

This should raise some alarm bells for grocers that need to include these two consumer drivers in their service offering.

Yes, that could mean fees based on delivery speed and highlighting savings at checkout. But to really make a difference, they have to focus on personalizing the overall customer experience.

Every month, in our analysis of eGrocery sales data, we emphasize the importance of providing customers with an engaging experience. There is nothing more engaging and relevant than communicating and providing targeted savings on products that a customer regularly buys timed to when they buy it.

That level of predictive personalization, of contextualized commerce, is the best means for grocers to compete with the value offerings of larger retailers and win back their market share.

Mark Fairhurst

Chief Growth Officer
Mercatus

07/14/2024 20:58:06

A Holistic AI Strategy: The Key to Retail Success

Retailers can significantly boost efficiency by leveraging AI-powered solutions like predictive inventory management and personalized recommendations. These technologies enhance customer experiences, optimize product availability, and improve recommendation accuracy, ultimately minimizing waste from overstocking or shortages.

The first step in your AI strategy shouldn't be on selecting the solutions to implement, but rather on establishing a robust data foundation. This entails addressing fragmented data silos and aligning AI deployments with comprehensive use cases, supported by an integrated underlying data infrastructure. Without this cohesive data foundation, efforts to enhance efficiency and unify customer experiences may result in disjointed outcomes. In addition to a suitable data foundation, it's vital to embrace a holistic approach to your AI strategy, acknowledging AI as more than merely a tool but as an orchestrator that synchronizes data, insights, and actions to greatly improve operational efficiency.

Whether it's optimizing store locations, streamlining the store opening process, modernizing stores, or effectively managing underperforming locations, each aspect requires careful consideration and integration within a comprehensive data model during the evaluation of your AI strategy.

Sushant Warikoo

SVP, Business Unit Head Retail, Cognizant