Saturday, July 13, 2024

How smart retailers are creating frictionless shopping experiences

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When brands are initially transparent with customers, they build trust-based relationships. Loyalty programs are an ideal bridge to communicate data principles clearly with consumers.

Bloomberg has reported U.S. shoppers are finally feeling frisky with their wallets again, spending in March 2024 double what it was back in September 2023.

Nevertheless, the 40-year inflationary high in June 2022 is still stinging a bit. This means that even though people are spending more, they’re also being careful, looking around for deals, and trying out new stores.

Three in four consumers tested new brands and stores on the hunt for competitive pricing, reliable inventory, or enjoyable customer journeys. To steady inflation-induced ripples and keep customers loyal, retailers turn to data — and AI-powered analytics. These days, brands have access to tons of information on customers, some of it pretty personal. The trick is using it to create fantastic experiences shoppers actually want without creeping anyone out.

According to Deloitte’s research, trust in a brand drops by 144% for customers who know a brand is using AI — but when retailers build trust into the change process, market value can grow four times.

So, let’s look at how retailers can collect that necessary first-party data with customers’ consent and provide seamless, trusted shopping experiences.

Loyalty platforms bring quality data

Retail executives’ biggest priority for 2024 was strengthening loyalty programs. Why? The opportunity to gather first-party data, customize experiences seamlessly, and build revenue. The more accurate the data, the more personalized retailers can be at scale. However, consumers need to trust the brand to share birthdays and product interests.

Loyalty programs provide a channel to communicate directly with consumers. When retailers are transparent about data usage in loyalty program sign-ups, they strengthen confidence. Retailers should move away from long lists of terms and conditions and break critical points into digestible parts. Informing shoppers of the benefits of receiving their data fosters a positive and rewarding experience for all the parties involved.

There are five things customers should definitely understand:

  1. Earning rewards: Explain clearly how shoppers rack up points or rewards. How much do they spend (or data do they provide) to get something cool?
  2. What counts (and what doesn’t): This clarifies what purchases earn points, and what behavior (such as browsing without logging in) won’t.
  3. Keeping their membership: Make cancellation options simple — reducing exit barriers boosts sign-up acceptance.
  4. Settling disagreements: Customers have many queries; how do you settle things if something goes wrong? Ensuring this process is easy for members is a huge plus.
  5. What happens to their data: Do you sell anonymized first-party data? Tell them. And reassure them that how you remove their personally identifiable information (PII) is safe. Do you enter customer data into AI tools? Let them know why.

The retail industry is shifting from mass production and marketing to microservices and tailored interactions. Thanks to loyalty programs, retailers can collect high-quality data, allowing them to refine experiences based on each shopper.

Predictive analytics get personal

Loyalty program sign-up data, selected interests, purchase history, and app navigation are just some of the customer touch points that tell retailers what shoppers want. From gathering warehouse data with drones to interactive customer engagement tools capturing behavior and preferences, retailers can understand their shoppers better than ever.

The Retail analytics market is projected to grow from $8.5 billion in 2024 to $25 billion by 2029, at a compound annual growth rate of 24%. By deciphering diverse sets of high-quality current and historical data with advanced analytics tools, retailers gain precise insights into consumer preferences and trends, allowing them to start personalizing customer experiences.

Customers benefit from an elevated shopping experience, receiving product recommendations based on previous selections, page durations, and purchase history. When retailers use self-learning algorithms or continuously update predictive analytics tools with each new customer interaction, models better understand customers’ preferences, leading to enhanced personalization and satisfaction.

Optimizing existing tools with generative AI

Why do all the repetitive work when you can train a machine to do it for you?

One way to get to know your customers better (and make loyalty programs more engaging) is to incorporate AI generated content in the design process. Designers can present shoppers with multiple new looks and produce those with the highest interest. Here’s how:

1. Train AI with trends

Feeding predictive analytics tools with customers’ top picks or current trends over time — as little as two months but two years or more is preferred — allows the tools to analyze trends and frequency of consumers’ behavioral changes to predict upcoming desires.

2. Generate content

Designers, empowered with the latest trends analytics, can prompt generative AI tools to produce new content in seconds. The idea is to leave designers in the driver’s seat to select looks that meet the brief and tweaking prompts to refine outcomes accordingly.

3. Engage consumers

Let shoppers pick which designs to bring to life! Enabling them to influence fashion and see their selections in the flesh builds a stronger connection with items before they’ve even reached the shop floor. Retailers can keep shoppers in the loop, updating them if their designs receive enough votes to produce, when they’re in the studio (for physical prototyping), and again once available for purchase — building suspense and interest throughout the process.

Creating unique loyalty services like these entices consumers to join and engage with programs and provides retailers with new avenues to reward customers for sharing their ideas and preferences (erhm, data).

When brands are initially transparent with customers, they build trust-based relationships. Loyalty programs are an ideal bridge to communicate data principles clearly with consumers. Those demonstrating how they use consumer data, what data usage gains them additional loyalty points, and how their data stays safe, help retailers gather the first-party information. Consumers can feel confident sharing the relevant data retailers need to provide seamless, personalized experiences, a win-win for all.

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