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.

+122%
OF ORDERS PER PRODUCT FINDER USER VS. PER WEBSITE USER
78%
COMPLETION RATE FOR PRODUCT FINDER
+18%
IN AVERAGE ORDER VALUE
+122%
OF ORDERS PER PRODUCT FINDER USER VS. PER WEBSITE USER
78%
COMPLETION RATE FOR PRODUCT FINDER
+18%
IN AVERAGE ORDER VALUE
emma case study landbot
COMPANY

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.

HEADQUARTERS

Frankfurt am Main, Germany 🇩🇪

EMPLOYEES

1,001-5,000

INDUSTRY

E-commerce

AGENCY PARTNERS
+122%
OF ORDERS PER PRODUCT FINDER USER VS. PER WEBSITE USER
78%
COMPLETION RATE FOR PRODUCT FINDER
+18%
IN AVERAGE ORDER VALUE
emma case study landbot
COMPANY

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.

HEADQUARTERS

Frankfurt am Main, Germany 🇩🇪

EMPLOYEES

1,001-5,000

INDUSTRY

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.

landbot case study challenge
THE CHALLENGE

Creating awareness about animal cruelty and improving engagement with prospective donors to improve leads

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.

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landbot case study solution
THE SOLUTION
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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.

Our goal is basically to help our customers find the best sleep products for them and improve the customer experience on our website. That's what we want. We want customers to feel happy and feel that it's the best decision that they're making.

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.

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Step 4 - Campaign assets submission, review & approval

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Our goal is basically to help our customers find the best sleep products for them and improve the customer experience on our website. That's what we want. We want customers to feel happy and feel that it's the best decision that they're making.

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.

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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.

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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.

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Our goal is basically to help our customers find the best sleep products for them and improve the customer experience on our website. That's what we want. We want customers to feel happy and feel that it's the best decision that they're making.

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.

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.

customer 3rd person
quote pink
My origins are in ecommerce where lead generation can be complex. Thanks to Landbot we achieved improvements of up to 400% in 3 months, with the same advertising expense.
Marco Borsani

customer 2nd person
quote mark blue
Landbot allow us to go beyond the simple concept of chatbot or livechat and to provide to our customer and even to ourselves a complete and immersive conversational experience.
Lara Petraglia

Marketing Manager | Conversational Design

landbot case study results
THE RESULTS

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.

CAMPAIGN TYPE
Conversational Design Bot-Powered eCommerce Campaign for an aluminum planter manufacturer.
Conversational Design Graphic
RESULTS
Close to 5,000 chats with 40%+ conversion to lead and a CPL of 1.71€.
CAMPAIGN TYPE
Own Conversational Design Bot-Powered Facebook Campaign.
Conversational Design Graphic
RESULTS
Over 64% lead conversion with 345 completed chats out of 536, with a CPL of 2.44$.
CAMPAIGN TYPE
Landbot on a full landing page + integration with Active Campaign for the email marketing campaign.
SOAP Graphic
RESULTS
From 6665 emails sent, the open email rate was 73.64%, and 61.97% of clicks.
CAMPAIGN TYPE
Levels of engagement - email marketing campaign
SOAP Graphic
RESULTS
In red, the number of opened emails are the biggest slice of the pie chart.
LEADS GENERATED
Number of leads acquired using a standard landing page VS using Landbot for lead generation.
552
😑 Landing Page
3588
🏆 Landbot
4000
3000
2000
1000
500
0
RESULTS
552 leads acquired with a landing page VS 3,588 leads using Landbot.
COST PER LEAD (CPL)
Cost per lead results when using a landing page instead of using Landbot.
Landing Page 😒
CPL of over
650$
Landbot 🚀
CPL below 400$
RESULTS
CPL of over 650$ when using a landing page VS less than 400$ with Landbot.