Fill the shopping cart with a recommendation engine

EPOQ™ Inspire for Inspiration in the web shop

Did you know that…

  • 56%

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

  • 13,9%

    of online shoppers say that they were encouraged to make a purchase through online advertising (Source: ECC).

  • 64%

    of shop visitors consider it important that businesses address them with relevant recommendations (Source: Monetate).

  • 6

    More than 1 in 6 online purchases are impulsive (Source: ECC)?

Relevant recommendations - the sourceof inspiration to browse

A Recommendation Engine inspires online shoppers with relevant recommendations along the digital customer journey. For this, the click and purchase behavior of each shop visitor is recorded in a knowledge base and processed to a history. With a self-learning technology, each online shopper will be presented with customized products. The Recommendation Engine thereby stimulates the imagination of the online shoppers and enables them to recognize the product’s advantages. The transported emotions, lead to purchase impulses, which fill the shopping cart. That’s what epoq™ Inspire offers you.

That’s how it works:

    Shop visitors want to be inspired from the very first page – this is particularly important for fashion shops. It is important to meet the individual taste of the visitors and to inspire them when they enter the shop. The visitor is not always known to the site – in this case, the top sellers can help, or auto-generated recommendations based on general behavior across all visitors.

     

    If the visitor has already been to the shop, their clicking and purchasing history is used to make relevant recommendations.

    “Other customers also purchased” and “recommended with this product” – find the right product and then buy everything at once. This is of particular importance in the area of fashion.

     

    Like men’s fashion – a luxury male outfitter offers his customers alternatives and knows which ties go best with which shirt.

     

    Generate personalized buying impulses, and offer good advice on matching outfits at the same time.

    “Often purchased together” – unite what belongs together. Recognize and actively offer thematically-linked products from your range: This creates a requirement and inspires the visitor.

     

    Linke books, films and music – Harry Potter fans don’t just buy one book, but a second one too or maybe a Blu-ray, etc.

     

    Such targeted recommendations can be made right on the product detail page to encourage browsing. These are based on visitor behavior and customer history.

    Category or industry-specific requirements can be implemented through intelligent rules, so that the most relevant products can be recommended to a customer in the current context.

     

    Like the drugstore area – if a user is interested in a shampoo for greasy hair, they are very probably a good candidate for other products in the range for their particular hair type.

     

    Najoba.de is able to offer personally-tailored recommendations to its customers according to hair and skin types, using individually programmed rules.

    sister surprise Logo für Referenz der Welt Inspirieren durch personalisierte Empfehlungen

    SISTER SURPRISE EXCITES WITH INSPIRING LINGERIE AND SWIMWEAR:

    „The innovative Recommendation Service from epoq enables us to give our customers even more individualized and targeted product recommendations in our online shop and our newsletters.“

    Thorben Siewert | Head of Operations | vStores Commerce GmbH

    Leave customers and visitors with a lasting impression

    It is about matching visitors’ and customers’ taste with relevant recommendations and thereby creating need. This is achieved by:

    • the right data models such as these pants fit to this shirt can be played out. Therefore the algorithm makes use of the collected data in the epoq ™ platform (knowledge base) and the specialist and industry knowledge of the shop owner.
    • new hypotheses about A / B tests are tested and gained insights into the Recommendation Engine. Our algorithms learn independently, but can be controlled by our Data Scientist.
    • individual rules can be applied via the epoq ™ Control Desk.

    We take on all the requirements as well as the specialist and industry knowledge of a shopkeeper and provide a tailor-made recommendation engine.

    Top-quality recommendations contain:

    DATA MODELS

    The models which provide the connection between data (e.g. these trousers are bought with this t-shirt) are controlled by the clicking and buying behavior of customers and visitors to the shop, as well as by human insight (hybrid approach).

    HYPOTHESES

    Hypotheses about the purchasing behavior of customers are first proposed and then tested with an appropriate method, such as an A/B test. The knowledge gained is then used in the recommendations.

    RULES

    Use-case oriented and highly-customized rules narrow the system’s recommendations down to the customer’s needs and the shop owner’s specialist knowledge of the industry.

    Integration?There's nothing easier than that!

    Product catalog

    In order to set up the Recommendation Engine, we first need your product catalog in XML or CSV format. We give you the tracking code for the connection to our platform, which you integrate into the shop.

    Tracking Code & Code snippet

    You add our tracking code to your online shop to connect to our platform as well as a code snippet as placeholder for the frontend.

    Configuration

    The relevant recommendations are configured in your test system until the optimal result is achieved.

    Go-live

    After a short learning phase, the relevant recommendations are displayed in the shop.

    Quality assurance

    We test the recommendations, adjust the rules to the desired strategy and provide training for the login.

    You may also be interested in this case study

    Fully automated personalization in the online store results to more sales. This increased at Sister Surprise the desired KPIs. Case Study download now.

    Download Case Study Sister Surprise starten

    A / B testing shows differences between personalized and manual recommendations.

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