Personalization in Retail

Advantages for retailers und customers: From the retailer’s perspective, personalization aims to maximize customer value. You, the retailer, use personalization to optimize sales, turnover and earnings throughout the entire customer life cycle. But personalization also provides customers with significant advantages. Customized content increases customer-specific relevance. This relevance leads to awareness which in turn results in higher click and purchase rates. If customers feel good when they are with you, they will also look forward to coming back. Goal achieved: stronger customer loyalty, greater purchase frequency, bigger shopping baskets!

In other words: Personalization in retail means offering every customer the perfect deal at the perfect time and via the right channel.

Scenario 1 illustrates nicely that recommendations made on the basis of purchase history are often irrelevant. It is highly unlikely that Max is going to buy another fridge in such a short period of time. In Scenario 2, artificial intelligence (AI) identifies Max’s current needs.

Real-time personalization solutions analyze the search and buying behavior of customers starting at the first click, adjusting immediately to the new situation. Similar to a chess computer, AI calculates all of the possible “moves” of the visitor and generates the best suited recommendations.

Actual and expected buying behavior: If a female customer, for example, purchases a gift for her partner, the actual buying behavior deviates from the expected behavior. Real-time solutions respond immediately to each change in buying behavior with relevant recommendations. They also recognize that the female customer found the gift and has now turned to the next shopping goal.

• Increased awareness leads to higher click and purchase rates: Appropriate deals that reach your customers at the right time and via the right channel are effective because of their relevance. It could be a product recommendation in the online shop or editorial content in the newsletter. Or, you can send a push notification with a personalized coupon to your customers’ cell phone. The range of applications is huge and there is no limit to your imagination.
• Automated personalized content results in lower costs: It goes without saying that with a good team you could manually create 100 relevant newsletters a week and send them to handpicked customers. The same goes for generating banners on the website or for digital signage solutions in the branch. However, automation saves enormously when it comes to both time and cost – and increases customer-specific relevance in the process. For example, AI automatically creates the right newsletter for each customer and sends it out at the time best suited to that customer.

• Consultant-tablets at the point of sale (POS)
• Call centers
• Digital signage (e.g. smart fitting rooms or in-store TV)
• E-readers (e.g. Tolino)
• Receipts (e.g. through coupons)
• Newsletters
• Online shops
• Package inserts (e.g. catalogs)
• Shopping apps
• Smart TVs

• Rebates & coupons: Generate strategic rebates for customers to whom those rebates are currently relevant. This increases the probability of purchase and avoids scattering losses.
• Content: Generate editorial content such as guidebooks, checklists or videos that match each customer’s behavior perfectly. Your customers will consider suitable information, especially online, to be a service. It could be styling tips for a specific outfit or a tip about washing instructions – use relevance to score big here too.
• Brands: When it comes to customers who are particularly loyal to brands, show them products from their favorite brands first or invite them to discover similar products from other brands. Some shops use so-called product feeds to do this. Customers themselves control the content of such feeds by marking their favorite brands and excluding unwanted brands.
• Products: Recommend the right product to each customer at the perfect time and via the right channel.

The prudsys RDE algorithms recognize not only the customer behavior and respond to it (e.g. with individual recommendations), but they also measure the acceptance of the generated content at the same time (= reinforcement learning). When a customer accepts (i.e. clicks on) a generated recommendation, the system rewards itself. If the recommendation is not accepted, there is no reward. This way, the prudsys RDE gets to know its customers better with each move and can tap into the individual preferences of each customer in a more strategic way.

There’s more: The prudsys RDE can deviate from learned patterns by way of so-called exploit and explore mechanisms, e.g. to recommend products or content that has never been recommended or has not been recommended for a very long time. The AI ensures that its scope of learning and action remains flexible by trying out alternatives or new variants. For your customers, that means that they will always see new content and products. They are not stuck in a filter bubble. This is a great advantage, especially for quickly changing product ranges: Products from new collections or brands flow automatically and immediately into the recommendations.

An intelligent personalization solution evaluates large volumes of data in real time, recognizes patterns and performs the “right” action in order to reach the corporate goals of the retailer.