With a recommendation engine you provide inspiration in the online shop and increase the shopping cart value

epoq Inspire

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Did you know that…

13,9%

of online shoppers say they were encouraged to buy by recommendations in online advertising? (Source: ECC)

64%

of shop visitors find it important that companies address them with relevant information? (Source: Monetate)

56%

of customers more likely to revisit a page that recommends products? (Source: e-tailment)

6.

more than every 6th online purchase is an impulse buy? (Source: ECC)

A recommendation engine inspires
your customers in the purchase readiness phase

A recommendation engine is a software service that displays relevant recommendations in an online shop and thus provides inspiration in the phase of readiness to buy. For this purpose, the click and purchase behaviour of each shop visitor is recorded in a knowledge base and processed into a history. Through a self-learning technology, product or content recommendations are played out to the shop visitor that match their interest. This creates buying impulses that fill the shopping cart. This is exactly what epoq Inspire offers.

Connect

Connect with your customers and build customer trust. Your customers visit your online shop regularly, so let them hear from you too. Send personalised emails on different occasions, such as birthday, lifecycle, transactions, etc. Learn more

Stream

Also provide entertainment and thus ensure constant customer loyalty. Customers like to browse through their own product and brand world to discover new things. Start here with a personalised shopping area and keep your customers coming back to your online shop every day. Learn more

Inspire

Inspire your customers as soon as they show a willingness to buy. They are now open to further buying impulses that complement or supplement their selected product. Relevant recommendations are particularly suitable for this.

Advise

Provide your customers with advice on product selection. Your customers have a need, but need help choosing the right item from the product range. An intuitive product advisor can help. Learn more

Search

Offer your customers orientation in their product research. This way, they can quickly and easily get to the desired product detail page and find out more about a product. If you want to personalise this customer touchpoint, check out our intelligent search. Learn more

Personalisation is the key
for relevant recommendations on
every shop page

The Recommendation Engine is part of our personalisation platform, which is powered by our AI engine. It uses artificial intelligence techniques to calculate relevant recommendations for each individual customer. This enables it to inspire your shop customers in the customer journey phase of purchase readiness on various shop pages via relevant recommendations and to set purchase impulses. This is because each recommendation widget displays exactly those products that correspond to the personal preferences of your shop customer at that moment. If, for example, a customer has searched for “Tom Tailer” trousers using the search function, the recommendations will also display suitable “Tom Tailer” trousers, as the brand has been recorded as a preference. If, for example, the customer has already placed a pair of “Tom Tailer” trousers in the shopping cart, he or she will be shown matching T-shirts of his or her preferred brands that match the selected “Tom Tailor” trousers.

7.6% increase in turnover through the use of a recommendation engine

“We are pleased to have had a competent partner in terms of recommendations at our side for years, who has provided us with advice beyond the standard business. The powerful recommendation engine from epoq brings us closer to our goal of offering our customers “the best shopping experience”.”

André Vollmer, Director UX | Internetstores.

Personalisation via the
Recommendation Engine can
take place in stages

Before you start personalising, you must first make sure that your recommendations are displayed correctly, such as the additional items on the product detail page. Only then you can start with the personalisation. In the first stage, for example, you can already prioritise certain brands. In the second stage, you have the possibility to play out the recommendations appropriately for certain customer segments and in the third stage, you can implement a complete 1:1 personalisation. You can define a personalisation strategy for your entire online shop or carry out customer targeting as part of campaigns. Our AI technology makes it possible.

The most popular use cases
of a recommendation engine

Show additional products in the shopping cart layer

Inspire your customers by clicking on the shopping cart button

Offer product sets on the product detail page

Enable your customers to buy a complete package

Include category recommendations on the homepage

Meet the individual tastes of your shop customers right from the start

Set up a checkout zone in the shopping cart

Let your shop customers access spontaneously

Display bundles on product detail pages

Offer your customers products that belong together
Show additional products in the shopping cart layer

Once an online shopper has decided on a product, you can inspire them with additional products when they click on the shopping cart button. The relevant recommendations are calculated and displayed in milliseconds. This increases your shopping cart value and sales. Ankerkraut was able to increase the shopping cart value by 6%.

  • Additional products appear with a click on the shopping cart button.
  • Relevant recommendations are calculated and displayed in milliseconds.
  • Shopping cart value and turnover are increased
Offer product sets on the product detail page

Offer your online shoppers the opportunity to quickly click together complete product sets. For example, you can create a stylish outfit or compatible snowboarding equipment. The set can be shopped directly or saved first. This way, the online shopper gets inspiration for a compatible product set directly on the product detail page and also saves time. Shopping cart value and turnover are increased as a result.

  • Customers can quickly click together product sets
  • The set can be shopped or saved directly
  • Time saving for the online shopper
Include category recommendations on the homepage

Online shoppers want to be inspired already on the homepage – it is important to meet the individual taste of the visitors already when they enter the online shop in order to inspire them. The visitor is not always known – in this case, top sellers or auto-generated recommendations based on the behaviour of all visitors are helpful.

  • Online shoppers are already inspired on the homepage
  • If the visitor is unknown, top sellers can be used
Set up a checkout zone in the shopping cart

What works in stationary retail can also be used online. The checkout zone and spontaneous access to additional items can be mapped via relevant recommendations in the shopping cart. This fills the shopping cart and increases sales.

  • Spontaneous access can be shown in the shopping cart
  • Products that are cheaper should be displayed
Display bundles on product detail pages

“Often bought together” – combine what belongs together. Identify thematically matching products in the range and actively offer them. This creates needs and inspires the visitor.  A Harry Potter fan, for example, not only buys a book, but also a second one or a Blu-ray, etc… Based on visitor behaviour and customer history, targeted recommendations can be made on the product detail page.

  • Thematically matching products are offered together

The AI engine of our
personalisation platform
makes it possible

Before the recommendation engine is used, we first generate a knowledge base for your online shop with our AI engine. To do this, our AI engine uses your product catalogue, the click and purchase behaviour of your shop customers and our and your expert knowledge. It links the data to knowledge and thus calculates the relevant recommendations for your shop customers and plays them out. Since the Recommendation Engine is located on our personalisation platform, which is designed for the personalisation of the entire customer journey of your shop customers, you have the option of activating further touchpoints in your online shop and using the knowledge already generated by the Recommendation Engine for this (modular structure) and further enriching the knowledge base for your online shop. Would you like to learn more about the AI engine? Then go to e-commerce technology.

Check out the latest insights
on the Recommendation Engine

Press

epoq Presents Control Desk Release 6.0

06. Apr 2022

With Control Desk Release 6.0, epoq improves the user experience of its monitoring and control tool.

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epoq Personalises the Customer Journey and Inspires the Shop Customers of the Traditional Company Görtz

15. Dec 2021

Görtz relies on a personalised customer journey in the online shop and inspires shop customers on the path to checkout.

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epoq Identifies Shop Customer Needs and Supports Digital Development at Fackelmann

03. Jun 2020

In addition to its needs-based products, Fackelmann’s online shop is also to be geared to meet individual customer requirements.

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6% higher shopping cart value via product recommendations in the shopping cart layer

“It is very important to us not to disturb the customer in his decision-making and purchasing process or to push him in a certain direction. The cart layer from epoq offers a very good option here. It fits seamlessly into the design of our online shop and provides the customer with relevant recommendations that add value to their user experience. This was already reflected in increasing shopping cart values during the test period. The enormous flexibility, competence and reliability of the epoq team round off this positive experience.”

Robin Haas, Online-Marketing | Ankerkraut

Tailoring is a must-have
of the Recommendation Engine

Data models

Depending on which customer journey phase a customer is in and on which shop page, a different data model can be used. A hybrid model would be possible, for example, on the product detail page, such as this pair of trousers is bought with this T-shirt. Here, the customer’s clicking and buying behaviour plays a role, as well as human insights.

Hypotheses

Hypotheses are made about the buying behaviour of customers and tested using suitable test procedures, e.g. A/B tests. The findings are incorporated into the recommendations.

Rules

With use case-oriented and highly customised rules, recommendations from the system are narrowed down according to the needs and industry knowledge of the shop operators.

This is how the integration
of the Recommendation Engine works

01

Generation of a knowledge base

To generate the knowledge base, we need your product catalogue in XML or CSV format and the click and purchase behaviour of your shop customers. The latter is recorded via a tracking code in your online shop.

 02

Setup in the test system

We discuss your visual ideas together and send you the div element as a placeholder for the frontend of the relevant recommendations. You integrate this into your test system. Now we fine-tune the search algorithm and the required configuration.

 03

Activation in the live system

After the setup in the test system and the successful function test, the Recommendation Engine is activated in your live system and is ready to display relevant recommendations to your shop customers. If necessary, we will carry out a fine-tuning in live operation.

 04

Introduction to our backend

We will introduce you to our backend, the Control Desk, and train you in the various analysis and configuration options as well as the use of features. This will enable you to monitor and control the recommendation engine.

 05

Display of relevant recommendations

Your shop customers receive relevant recommendations on various shop pages that lead to buying impulses. In this way, you provide inspiration in the purchase readiness phase and increase the shopping cart value, which has a positive effect on your conversion rate and your turnover.

epoq Control Desk

Monitoring and controlling the Recommendation Engine

The epoq Control Desk provides you with extensive options for monitoring and controlling the Recommendation Engine.

  • Configuration

    The “Configuration” tab shows you immediately how many recommendation widgets are integrated in your online shop and where they are placed.  In addition, you can see the various rules on which they are based. Click on the ‘Edit’ button to access the Rule Editor, where you can create, edit, prioritise or delete rules.

  • Key figures

    The “Key figures” tab provides you with information on various KPIs of your recommendations, such as click performance, conversion rate and conversion funnel.

  • Analysis

    The “Analysis” tab allows you to view the most popular recommendations and the various recommendation strategies. Screenshots also show you how your recommendations look live.

  • Features

    Within the framework of “Features”, various options are available to you, such as whitelisting, blacklisting, combi creator and theme worlds.

More info on the control desk

When the use of a
Recommendation Engine is worthwhile for you

Basic functionality

You already run an online shop or similar and have ticked off all the basic functionalities and now want to set incentives to buy on various shop pages.

Orders

You have more than 1000 orders per month

Product range

You have more than 1000 products in your range

Want to inspire online shoppers to buy with relevant product recommendations?

Our Reco Engine fills the shopping cart along the customer journey.

Request offer now

The latest blog articles
on the Recommendation Engine

Blog Post

Cross Selling Strategy : How Easy It Is to Increase the Value of Your Shopping Cart

Discounts and promotions are real boosters that significantly increase the value of your customers’ shopping carts. However, they only work in the short term. Other techniques, such as cross selling, are time-consuming but cause long-term benefits and lead to a significant increase in sales. This article is your guide to cross selling strategies, from the definition of cross selling to increasing cart value through the targeted sale of complementary products.

Sarah Birk: 22. Feb 2022

Learn More
Blog Post

Inspiration Made Easy: How to Use Product Recommendations Effectively in E-Commerce

We often encounter product recommendations when browsing online stores. These suggestions highlight alternative or complementary items, newly added products, or top sellers. While product recommendations in e-commerce provide customers with inspiration to continue shopping, they also offer you, as a store owner, the opportunity to increase the average order value. Product recommendations can guide users throughout their entire journey — from the homepage to category and product detail pages, all the way to the shopping cart and even follow-up emails. In this article, we’ll show you where product recommendations are most effective in e-commerce and what specific factors to consider depending on where they appear in your store.

Sarah Birk: 30. Apr 2020

Learn More
All articles