E-commerce Product Recommendation: How Emma Increased Average Order Value by 18% with a Website Chatbot
Emma launched a Landbot-powered Product Finder to guide customers through their online product catalogue, match them with the best products based on their preferences, and drive more sales.
Emma is an e-commerce business that started as an innovative mattress-in-a-box company, and has expanded to a comprehensive sleep company offering mattresses, pillows, beds, and accessories aimed at enhancing customers’ sleep quality.
Frankfurt am Main, Germany 🇩🇪
1,001-5,000
E-commerce
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Meet Miguel Almeida, CRM Marketing Manager at Emma.
Emma is an e-commerce sleep business based in Frankfurt am Main, Germany, that operates in over 30 markets across Europe, North and South America, and Asia Pacific.
It started as an innovative mattress-in-a-box company, and has expanded to a comprehensive sleep experience company, offering mattresses, pillows, beds, and accessories aimed at enhancing customers’ sleep quality and improving their daily lives.
Improving the online shopping experience
As it expanded its product range and global presence, Emma faced several challenges. As an e-commerce business, the company needed to enhance the online shopping experience for customers. Since Emma has limited physical stores, many customers can’t test Emma’s products before buying them, leaving them feeling uncertain about which sleeping products best suited their needs.
The solution, at the time, was to contact Emma’s call center of Sleep Experts, who would assist customers in finding the right product. However, this wasn’t ideal, as it was taking time away from the call center team to focus on customers with more urgent issues related to purchases they had already made. Plus, while on a call with a Sleep Expert, not all customers felt comfortable sharing personal information about their sleeping habits over the phone.
There was a clear opportunity to minimize the costs of contact centres and improve the customer experience on the website.
In an effort to find out how to solve this, Emma sent out a survey which revealed:
- Customers were looking for more information on products;
- Customers were missing detailed information on products;
- Customers didn’t understand the product differentiation.
So, Emma needed a tool that was able to offer personalized product recommendations on their website, helping customers feel confident about their decision to buy.
Additionally, the team also wanted this tool to help them leverage customer data more effectively and better understand individuals’ preferences and improve product recommendations even further.
Product Finder website chatbot powered by Landbot
To address these challenges, Emma implemented a dynamic Product Finder on its website powered by a Landbot chatbot.
Product Finder is an interactive quiz that asks customers about their sleep habits, preferences, and budget such as:
- The type of product their looking for;
- What their preferred sleeping position is;
- If they struggle with room temperature at night;
- If they’re looking for a budget or premium product;
- Etc.
Based on their responses, Product Finder uses decision trees and criteria to recommend the most suitable products, removing the need for customers to contact the customer support team.
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Step 4 - Campaign assets submission, review & approval
Miguel Almeida | CRM Marketing Manager at Emma
Product Finder was initially launched only in the Italian market in May 2023. However, soon after, the Emma team realized Product Finder was outperforming the product comparison tables that were available on their website. Given the results, Emma expanded Product Finder to all its main markets in 15 countries.
On the backend, Emma’s team uses the website chatbot to collect customer feedback and make data-driven improvements to Product Finder.
Step 5 - Campaign publishing and submission of post links for tracking
In the last three months, Product Finder handled an average of 3,000 chats per day, which amounts to a total of 200 thousand chats across all markets in 3 months, providing Emma with significant data to continuously improve its product recommendations.
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In the last three months, Product Finder handled an average of 3,000 chats per day, which amounts to a total of 200 thousand chats across all markets in 3 months, providing Emma with significant data to continuously improve its product recommendations.
Co-founder of Conversational Design
Marketing Manager at Conversational Design
Landbot’s website chatbot improved the buying experience and boosted conversion rates
The implementation of the Landbot-powered Product Finder has improved the buying experience for Emma customers and increased conversion rates.
The improvement in the buying experience is evident with an average of 78% completion rate from customers who initiate the process and receive a product recommendation. However, it’s not just about receiving a recommendation; it's also about making a purchase. Emma saw significant increases in conversion rates from recommended products to actual purchases. In Spain, the conversion rate saw an impressive +122% uplift of visitors to Product Finder versus the website average.
Finally, the average order value for customers who use Product Finder increased by +18% compared to those who don’t use it. This demonstrates how secure customers feel about the recommendations, leading them to buy more or choose more expensive products.
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The Landbot-powered Product Finder chatbot has enabled Emma to significantly enhance its online shopping experience. This aligns perfectly with Emma’s mission to improve sleep quality while also driving business growth and operational efficiency, all while enhancing the customer experience.
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650$
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SOC2
Compliant
GDPR
Compliant