Thalia cultivates an appetite for reading with personalized book recommendations

Realtime personalization in the online shop, newsletter, app and tolino eReader increase customer retention and sales

Produktempfehlungen im Newsletter, Thalia Newsletter mit Recommendation Engine prudsys RDE
Thalia Bücher GmbH leads the market in the German language bookselling trade, operating more than 280 bookstores in Austria, Germany and Switzerland. The collection features more than 11 million products, including a wide variety of books, audio books, CDs, DVDs, games and toys, gifts, stationery and eBooks such as the tolino eReader. Thalia is an omnichannel retailer, at home in both the real and virtual world of books. The company is constantly discovering innovative ways to retain customers. Thalia has been using the prudsys Realtime Decisioning Engine (prudsys RDE for short) since 2011 to develop a high-quality personalized sales approach across different channels. That makes Thalia a pioneer when it comes to personalization.
Personalisierte Produktempfehlungen im Thalia Newsletter mit Recommendation Engine prudsys RDE

The objective

Customer service is the top priority for Thalia Bücher GmbH. In order to offer its customers real added value through personalized offers, the company tested the prudsys RDE against its own software solution in 2011. The objective was to improve both sales from recommendations and customer retention. During the test, Thalia generated additional sales in the two-digit range by using the prudsys RDE. The following steps were the result: The prudsys RDE was integrated into all Thalia online shops and personalization was expanded to include other customer channels such as newsletters and subsequently also the tolino eReader.

The solution

The prudsys RDE was implemented into the German Thalia online shop in 2011. There are many different types of recommendations in the form of personalized product recommendations in use in all five Thalia Bücher GmbH online shops. The prudsys RDE personalizes all of the important pages on Thalia.de, Thalia.at, Buch.de, bol.de and orellfuessli. ch. That includes, among other things, the home page, product detail pages, interim shopping cart pages, the wish list and “no match” pages. In the “My shop” area, customers also receive personalized recommendations with their logins in real time based on user behavior. In 2015, the prudsys RDE was integrated into the Thalia newsletter in its various formats, including the new customer greeting, shopping cart interruption campaigns and weekly eBook mailings. Readers even benefit from realtime product recommendations by the prudsys RDE on Thalia’s own eReader, the tolino brand, which Thalia launched in conjunction with bookstore partners in 2013. These recommendations appear on the start screen, for example, or after the “continue reading” message upon finishing a book.

The result

Thalia successfully creates a personalized customer approach in the online shop, newsletter, tolino eReader and on app for mobile end devices. Sales from recommendations saw an above average increase in the two-digit range in all online shops thanks to the constant development of personalized areas and consistent testing. Customer response in the form of clicks on recommended products also increased continuously. Thalia continues to constantly test and optimize the latest personalization scenarios. In the future, the company would like to link the online and offline worlds more closely.

Sven Klenner, Director of Sales eCommerce and Marketing:

„We have been working with prudsys for many years and are impressed with the pruddsys RDE. The realtime algorithms used in the personalization solution ensure a high customer response. For us, an integrated, personalized customer approach across all channels is the key to successful customer retention.“

At a glance

Objective

  • Personalized shopping experience in Thalia online shops, newsletters, tolino eReader and app
  • Increase in customer response and sales from recommendations
  • Various personalization scenarios, especially in the online shop and newsletter

Solution

  • Automated generation of product recommendations in real time through various channels
  • Analysis of user behavior in real time and inclusion of historical data for appropriate recommendation calculation
  • Diverse use of personalization, e.g. in numerous different newsletter formats

Result

  • Two-digit increase in sales from recommendations
  • Increase in click rates
  • Use of different personalization scenarios automated in different channels

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