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Power delivers effective product recommendations in different phases of the customer journey

Power International AS is the leading electronics retailer in the Nordics since 2015. Their strategy of relying heavily on the omnichannel business has always been successful with a considerable market position and a turnover of 1.1B Eur. 

For a retailer like Power with 20,000 different items to sell, it’s crucial to have personalized and relevant product recommendations for every step in the customer journey. 

Creating an optimal customer journey with so many products is not an easy job. Customer journeys are far from linear but rather a maze of repeated visits, a variety of consumed content, and other actions. The final conversion is seldom gotten during the first website visit. Every customer comes from different circumstances and has different ways to discover products and make purchase decisions.  

All these mean that the whole customer journey needs to be personalized, not just the page where we think the conversion will happen. For example, it doesn’t make sense to show a static front page for the visitor who has previously engaged with the website and is likely to complete the purchase. With this complexity, Power wanted to have the best personalization software in the market. 

The Frosmo personalization software brings product recommendations to a whole new level by using different data points about the customer to select the perfect AI-based recommendation strategies to support the customer journey in the best possible way. These data points include the customer’s location on the site, the phase in the customer journey, segment information based on historical behavior, and customer affinity. Taking the whole customer journey into account makes Frosmo the most versatile personalization software in the market.

The cooperation with Frosmo and Power started when Frosmo got a chance to prove our product recommendation capabilities against a leading competitor, increasing the overall conversion which is their most important KPI to follow.

To support the whole customer journey, we implemented Frosmo’s AI-driven product recommendations strategies for the following pages in their online store: frontpage, category page, product detail page, add to cart pop-up, and search page results.

 

Great results in conversion rates and average order value

With product recommendation strategies implemented on the pages, the results have been proven strong and effective. Purchase conversion rates have gone up by 170% compared to the group who didn’t see recommendations. The average order value got up by 41% compared to the group who didn’t see the recommendations.

“We’re very satisfied with the increase in conversions and average order values that Frosmo brings us with AI-driven product recommendations. The overall experience of implementing the recommendation strategies and the cooperation with Frosmo has been straightforward and was surprisingly deployed as a turnkey project. I would highly recommend using Frosmo against other competitive solutions.”

Jarkko Lehtismäki, CTO, Power International AS

 

Different recommendations strategies for friction-free customer journey orchestration

Personalized and AI-driven product recommendations aim to perfect the customer experience by helping the visitors go through the customer journey as friction-free as possible. Here are the strategies implemented for different Power sites.

  1. The first strategy is to advance the customer journey towards better product discovery and conversion on the front page. Recommendations show the most popular products at the moment, based on most converted and most-visited products by all users. The second set of recommendations shows recently viewed products by the customer.
    Power recommendations- popular products
    Power recommendations- popular products

     

    Power recommendations- recently viewed products
    Power recommendations- recently viewed products

     

  2. In the category pages, the aim is to find the most relevant product to purchase. Two strategies were implemented to make the product discoverability easier. The first set of category page recommendations shows the trending products based on highly-converted and most popular products. To enforce product relevancy and increase average order value, behavioral data is also used to show recommendations based on particular user interests in a specific category and combine it with products viewed or bought together.
    Power recommendations- trending products
    Power recommendations- trending products

     

  3. The product page is all about making sure the conversion happens and that the average order value increases. Traditionally, customers put a lot of effort to choose the product that best suits their needs. To make the choice easier, Frosmo creates recommendation strategies based on relevant products viewed or bought by others and uses historical data of the visitor to recommend other related products.

    Power recommendation strategies based on relevant related products viewed
    Power recommendation strategies based on relevant related products viewed

     

  4. Basket pop-ups are being developed to include physical store data for recommendations used to raise the level of relevancy and effective cross-selling.
    Power basket pop-up recommendations
    Power basket pop-up recommendations

     

“We’ve skimmed the surface of Frosmo and have seen a great potential for our business in the near future. Some of the most interesting future aspirations include increasing AOV by tweaking the AI-recommendation strategies and gaining higher organic traffic by combining recommendations with content-crunching NLP”,  Jarkko Lehtismäki concludes.

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