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RelevanceTV: Book People


For more information on how Book People work with RichRelevance, read their case study here.  Find out more about RichRelevance personalization solutions here or request a demo.

Blue Tomato Case Study

  • RETAIL SEGMENT: Sporting Goods
  • PRODUCT: Personalized Recommendations
  • CHALLENGE: Wide range of products. 60% Webshop in 14
    languages and nine currencies
  • RESULTS: 3x revenue from orders containing product recommendations. 20% increase in
    average shopping basket. Average of one more product per purchase. Improved revenues on mobile devices

Blue Tomato was founded in 1988 as a snowboard school by the former European Snowboard Champion Gerfried Schuller. Since then it has transformed into a successful international boardsport and fashion shop. Blue Tomato now owns more than 30 shops in Austria, Germany and Switzerland and their webshop offers more than 450,000 products from more than 500 brands and delivers to more than 40 countries. Having launched its webshop in 1997, Blue Tomato was an eCommerce pioneer. It now aims to become the leading omnichannel retailer for boardsports and freeski in Europe.

Product variety proved too challenging for existing recommendation engine

By 2016 the growing breadth of Blue Tomato’s product range became a challenge for the company’s existing recommendation engine.

“Our traditional tools weren’t working for us anymore,” explained Andreas Augustin, Head of Webshop Development at Blue Tomato. “Our existing tool had reached its capacity to make automatic recommendations. We spent a lot of time and resources trying to manually improve results and ingest products, with limited results.”

Blue Tomato therefore sought a more sophisticated recommendation engine to handle its growing complexity. “We knew of several diverse eCommerce tools that included an element of machine learning within its platform to make recommendations”, said Andreas. “We decided we did not want this type of solution, but one whose core competency was recommendations.”
During an exploratory stage Blue Tomato evaluated solutions from six different vendors and finally chose Recommend™ by RichRelevance for its advanced machine learning algorithms, ease of use and merchandising functions.

Machine learning algorithms that challenge each other

“We particularly liked RichRelevance’s ‘King of the Hill’ approach, with its different machine learning algorithms that continually challenge one another to get the best results,” said Andreas Augustin. “We also valued the extended merchandising functions that enable us to maintain specialist product areas inhouse. Finally, the personalization developed specifically for mobile devices was very important for our omnichannel strategy.”

Experienced RichRelevance consultants supported Blue Tomato through the implementation process, which ran smoothly and fast despite the webshop’s complexity. “Thanks to RichRelevance’s great support – often on short notice – we were not only able to optimize the system but could also be assured that our personalization project would be successful in real-time mode,” explained Andreas Augustin.

Personalization that customers and staff can equally identify with

Blue Tomato’s revenue created by product recommendations has grown significantly since going live with RichRelevance in Autumn 2016. Crucially for Blue Tomato, revenue resulting from product recommendations has tripled, proving the value of the investment in RichRelevance. That the personalized recommendations resonate with Blue Tomato’s customers is also rejected by the fact that they spend more. “Thanks to RichRelevance, the value of the shopping baskets resulting from the product recommendation has increased by an average of 20 percent, with an average of one more product purchased by each customer”, summarized Andreas Augustin. ”The numbers apply as well for the recommendations shown on the mobile devices, where significantly less products can be listed but thanks to RichRelevance these are the most relevant.”

Blue Tomato’s product management and marketing teams are also impressed by the the quality of the recommendations. One type of recommendation problem that has been historically difficult to manage is when customers buy separate matching products – for example bikini tops and bottoms in different sizes or from different collections. When this happens, appropriate recommendations should still appear as if the customer had chosen a matching set. “Before using RichRelevance, this common scenario had been difficult to maintain and manage,” explained Andreas Augustin. “We were able to configure Recommend™ to ensure matching parts were listed together. However, this wasn’t even necessary as the algorithms figured it out pretty fast themselves.”

More personalization, also for content

Looking to the future Blue Tomato plans to extend personalized recommendations to its various online theme parks such as “beach life,” and also for the Blue Tomato “rider crew” sites that feature snowboard, freeski, surf and skate athletes who are sponsored by 30-40 different brands. The company plans to use RichRelevance to personalize the content that visitors see, along with more interactive sites to further improve the customer experience.


Clarisonic Case Study

  • RETAIL SEGMENT: Wellness & Beauty
  • PRODUCT: Engage™
  • CHALLENGE: Clarisonic wanted to maximize revenue per session by optimizing home page content tiles for different customer segments.
  • RESULTS: Using RichRelevance Engage, Clarisonic achieved the following performance on its home page content tiles:*
    • 20% increase in clickthrough rate (CTR)
    • 24% increase in revenue per session
    • 35% increase in overall clicks

* Comparing performance from October 2014 against October 2015.

“The fact that I can keep testing content and justify why I’m showing it is amazing! I’m confident that these data-driven decisions are helping to move visitors efficiently through the purchase funnel.” Casey Davidson Director of Ecommerce and Digital Marketing , Clarisonic.

Clarisonic’s mission is to beautifully transform skin through its award-winning devices, which cleanse skin six times better than hands. Hand-assembled at its Redmond, Washington headquarters, the devices are distributed through prestige retailers, dermatologists, cosmetic surgeons, spas and online at Clarisonic is part of the L’Oreal Group.

As Director of Ecommerce and Digital Marketing for Clarisonic, Casey Davidson is in charge of managing customer website experiences to achieve the directto-consumer revenue goals for the business. In addition to optimizing traffic, conversion and revenue, the team manages all content, paid media channels, affiliates, search engine optimization and search engine marketing as well as retargeting, email and loyalty programs.

For Davidson, engaging and educating the new user is a critical objective for the website. When new visitors have their first experience with the brand on the website, she wants the site to represent the “knowledge hub of the brand” so they can learn everything—from which Clarisonic device is right for them to what skin care products and brush heads pair best with their chosen device.

Old way: multiple messages meet multiple needs

Prior to working with RichRelevance, Davidson’s team used a carousel approach for their website homepage. A rotating carousel of three to four content tiles cycled through the home page, switching to one static tile during sale periods.

Davidson considered this method to be standard but outdated. “Promoting multiple messages regardless of behavior, and hoping one sticks, was not ideal. We gained no insight into the segmentation of our customer database—who’s coming, what they’re interested in,” said Davidson.

While the approach satisfied internal stakeholders who wanted frequent home page updates and wanted to ensure that a variety of messages for different products were seen, the issue remained: It was impossible to determine which messages resonated with visitors.

Personally, Davidson felt that it could be hard for visitors to digest any message moving through a carousel, let alone decide where to click. With no analytics or data to back up the message choices being made, she knew it was time for a change.

“We spend a lot of money to drive folks to the website and my job is to make sure they convert with the highest revenue per session,” said Davidson.

New way: content and context motivate visitors through the purchase funnel

Having learned about RichRelevance through existing partnerships with sister brands at L’Oreal, Davidson decided to use the Engage™ solution to segment audiences, and test and optimize content tiles against key metrics—clickthrough rate and revenue per session.

“Everyone will always have an opinion, but our job is to move from opinions to data-based decisions that show what customers are gravitating toward,” said Davidson. “Clickthrough rate may be a function of creative; revenue per session may be function of the right message and content. A lot of times we don’t know, and that’s why it’s critical to always be testing.”

RichRelevance Engage maps individual shopper behavior against advanced targeting and audience segmentation tools so that marketers can deliver highly personalized campaigns with relevant content. Its ability to automatically target each segment, optimize the most effective creative for that segment, then pass the data back to the business to inform creative decisions for the next round of campaigns saves valuable time and eliminates the need to run hundreds of manual A/B tests to get content personalization right.

Clarisonic implemented Engage in June 2015, and has seen significant success in key metrics for users that interact with its home page content tiles, such as a 20 percent increase in clickthrough rate and a 24 percent increase in revenue per session, while also seeing a 35 percent increase in overall clicks.

“Engage gave us information on what messages and creative were resonating with customers. We tested 12-15 pieces of content for each customer segment and found two that resonated very well: ‘Find your Clarisonic’, which linked visitors to an interactive skin quiz recommendation engine, and a tile with the message ‘Great Skin Starts Here,’ which highlighted our key skin care benefits to our users,” said Davidson.

With plans to continue testing current content “winners” against new content, Davidson looks forward to uncovering more learnings and insight from using Engage.

“The fact that I can keep testing content and justify why I’m showing it is amazing! I’m confident that these data-driven decisions are helping to move visitors efficiently through the purchase funnel,” she said.


Shop Direct Case Study

  • RETAIL SEGMENT: Pureplay Department Store
  • PRODUCT: Personalization Consultancy
  • CHALLENGE: Not satisfied with the out of the box improvements, Shop Direct sought the help of the RichRelevance personalization consultants to optimize implementation and maximize results from their personalization initiative.
  • RESULTS: 2.5% lift in revenue per visit (Electrical Category)

Shop Direct is the second largest pureplay retailer in the UK with brands including and Littlewoods.

Shop Direct has been working with RichRelevance since 2014. They selected RichRelevance as a forward thinking technology partner who understood the needs of the customer and was able to provide personalization at all parts of the customer journey.

Over the past two and a half years, RichRelevance has grown to account for just over 6% of Shop Direct’s increasing sales, which are now almost £1.9 billion.

With an experimental test and learn culture, Shop Direct wanted to get more than the out of the box improvements they were seeing from the RichRelevance personalization platform. In August 2016 they commissioned a consulting engagement with the objective to optimize placements and maximize the results from their personalization initiative. In addition they sought technical assistance on implementation methods across the Shop Direct sites and

Measures of success

RichRelevance first undertook an assessment of the site, which included an implementation health check and a review of manually created rules. As a result, enhancement opportunities were identified and outdated rules were cleaned up. Improvements were made to enable Shop Direct to update additional placements more quickly as well as adding more parameters as a default.

Another element to the project was supporting the implementation of advanced merchandising. RichRelevance data analysts built specific reports to show the value of the advanced merchandising rules. Additionally, the personalization consultant provided advice on best practice implementation.

Having an implementation free from technical issues as well as using RichRelevance best practice was the optimal foundation for moving to the next step: the optimization.

Optimization Work

The first step in the optimization plan was to test the RichRelevance best practice strategies verses the current Shop Direct strategies. Four tests were carried out on the cart and item pages. The results indicated comparable or small lifts for the best practice strategies. While it showed that the current strategies were working well, it offered alternative strategies for Shop Direct to utilize if they wanted to.

After completing the site-wide strategy tests, the next step was to narrow the scope to category level. The first test ran on the Electrical category. When certain strategies were preferred, Shop Direct saw a 2.5% lift in revenue per visit. Other category tests are still ongoing.

“We very much see the consulting engagement as a long term optimization partnership for continual improvements across the Shop Direct ecommerce sites”, commented Kathryn Jones, Findability Manager at Shop Direct. “It’s as important to Shop Direct to find out what doesn’t work as well as what does, but to do so quickly and efficiently. By utilizing the skills of the RichRelevance personalization team we were able to tap into their expertise of both personalization and the RichRelevance platform which meant we progressed quicker.”

“We work with our RichRelevance consultant on a weekly basis as a sounding board for both ideas and advice on how to best set up rules and strategies to support our business objectives. This has been very helpful and worked really well for us”, added Isobel Gerrard, Product Recommendations Analyst, Shop Direct.

The optimization efforts continue and Shop Direct is now looking at new on site placements, email implementation and ‘build your own’ strategies.


UK Creepy or Cool

The survey, which includes responses from over 3,500 consumers in the UK, US, France and Germany, gauges consumer opinion on the impact of technology to the in-store shopping experience.


NOTHS Case Study

  • SECTOR: Marketplace
  • SOLUTION: Personalized Product Recommendations
  • CHALLENGE: With a wide array of partners and product offerings needed a personalization tool to help improve the customer experience by connecting shoppers with the most relevant products.
  • RESULTS: 25% order value (from those interacting with Recommend™) is an online marketplace with 5,000 partners and a wide array of product offerings. Since they were founded over 10 years ago, demand for their unique, personalized products has continued to rise, with their customer base seeking bespoke and unique products compared to the mass produced offerings on the high street.

For personalization is a particularly important part of improving the customer experience. As a marketplace with such a broad product range and partner base, notonthehighstreet. com customers have very different shopping missions that range from top ticket items like large furniture pieces to Alpaca walking experiences in Derbyshire. With a mission to make every customer interaction as unique and enjoyable as possible, notonthehighstreet. com was looking for a personalization tool to help them connect the most relevant and appropriate product to each shopper.

After looking at whether they could develop a tool internally, turned to RichRelevance’s personalization platform to automate connecting customers with the right products.

“We chose the RichRelevance solution due to the flexibility and depth of personalization it gave us, dovetailing into our own product curation needs. We also liked the unobtrusive nature of the RichRelevance offering and the way it integrated seamlessly, complimenting the customer journey”, explained Michael Roberts, Senior Merchandiser at

“The RichRelevance system is an AI based self learning tool, so the personalization takes care of itself automatically. A dashboard is provided which is easy to use and has powerful reporting and merchandising features built in. This means I can set high level guidelines to refine the recommendations when I need to – for instance when I want special promotions for Mother’s Day or Valentines Day.”

Since implementing Recommend™, found the personalization tool has provided them with insight into their customers’ behavior leading to the ability to highlight interesting new products within their offerings that the shopper might not have found otherwise. This capability is particularly important on mobile.

“With the advance of mobile shoppers whose browse times are much shorter on, the value of tools such as RichRelevance has increased dramatically, as they allow us to promote relevant product visuals to customers quickly and easily”, said Michael Roberts.

RichRelevance personalized product recommendations have high exposure across the website, with placements on the homepage, department pages, the bottom of listing pages and across checkout and add to basket pages. They help the shopper at every stage of their shopping journey.

Since deployed RichRelevance Recommend in 2015 they have seen steady improvements and many benefits both on conversion rates and incremental gain in sales. The AOV of orders interacting with personalized recommendations are 25% higher than those who don’t, showing the value and relevance of the suggestions being made. A total of 11% of orders on notonthehighstreet. com now interact with RichRelevance recommendations. has also been able to utilize RichRelevance personalization software to overcome specific challenges, for example a high bounce rate from search engine traffic, as Michael explained:

“We were struggling to immediately engage with traffic arriving from search engines, where we had a high bounce rate compared to the overall site. We utilized the RichRelevance technology to show very relevant product alternatives at the right time specifically for this source of traffic and as a result reduced our bounce rate by an impressive 13%.”

In terms of the future, sees personalization of the shopping journey as continuing to play an integral role in the way they deliver the right products to the right customers, alongside promoting new products and supporting their valued partners.

“RichRelevance has the features right now that we need to deliver our vision to focus on the needs of our individual customers and deliver them a great shopping experience.” Michael concluded.

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