5 Must-haves in E-Commerce Product Discovery
15 April, 2022

5 Must-haves in E-Commerce Product Discovery

15 April, 2022 • 1015 Words

In the online competition for traffic and conversion, companies must implement sustainable strategies in order to survive in the market. An essential part of this strategy is the search function in the online shop, and the way products are presented to the customer. In this article, I describe what makes the difference in successful Search & Merchandising in e-commerce. During recent years, I have supported companies throughout Europe in the implementation of numerous e-commerce projects, with the focus to add value by enabling a mature Search & Merchandising function. Now I also offer that expertise to companies in Australia.

In practice, mastering certain Search & Merchandising functionalities and processes have shown to make online retailers successful. An important component is the search function in the online shop, and the way in which products are presented to the customer. In the following, we will take the example of Anna, a persona who is actively involved in the purchase of a coffee machine, and will take a closer look at four important cornerstones of successful Search & Merchandising.

Autocomplete and suggest:

As soon as Anna clicks into the search box, she expects to see search suggestions based on trending keywords in a flyout menu. Then when she starts typing, she expects suggestions which are relevant to her input only. She likes to be inspired by a variety of suggestion types such as search suggestions, products, categories and content. Suggestions for misspelled words offer Anna added value and supports a seamless search experience.

An example of the Suggest variety can be seen on Buttinette.de:

Buttinette's approach for a good baseline Product Discovery via Search Suggestions

Buttinette's approach for a good baseline Product Discovery via Search Suggestions

Intelligent contextual search results

When Anna searches for a product in a supplier’s online shop – using the existing product number – or by keyword such as “coffee machine”, she should only see the products that match exactly. In addition, companies should also be able to make incorrect inquiries possible by displaying the same hits when searching for “cofe machine” as when searching for a correct spelling. Anna also expects an online retailer to provide a relevant product selection when searching for more specific descriptions such as “suitable for all cups and glasses”. If she searches for independent terms, for example “coffee machine, tea machine”, she would also like to get matching results for the individual terms. This way, she can decide for herself which product list to use to continue her evaluation process.

SportScheck.com efficiently implements this by displaying two product lists in such a search:

Sportscheck's multi-faceted Ways of showing Results for non-specific Search Terms

Sportscheck's multi-faceted Ways of showing Results for non-specific Search Terms

Sophisticated product lists and navigation options

Product lists should contain the most important information for Anna’s further search, but should not be overloaded. My experience has shown that potential customers primarily expect information about availability, price, promotional badges, product titles and appealing product images in their search process. In our example, Anna expects the most relevant products in the upper product slots. These expectations can be met via ranking rules based on a combination of marketing, commercial, behavioural and logistical information. For example, commercial data can include the number of product views, clicks, add-to-baskets, sales and click-through rates per product. Furthermore, when Anna uses appropriate filtering options, she wants to see useful, understandable and visually appealing results to intuitively navigate further. Accordingly, companies can make the search journey more visually appealing for customers like Anna with sliders or colour icons in the colour filter.

One example is Otto.de, where they display a balanced mix of product details on the product list, as well as filters relevant to the products for a search for „washing machines“. With their wide product range they have managed to make the product list as specific as possible for the user context:

Otto shows Search Result Lists differently based on the Type of Search Term

Otto shows Search Result Lists differently based on the Type of Search Term

Relevant product recommendations

Campaigns can provide Anna with further helpful ways to gain access to products. These can be displayed in the form of product sliders on pages such as the homepage, product lists, detail pages and shopping cart, for example. Depending on the page type, companies should adequately configure the algorithms for displaying products. Anna may also be inspired by bestsellers or sales articles on the homepage. Practical tests have also shown that potential buyers like Anna often find product alternatives offered on detailed pages of out-of-stock products very helpful.

An example for good product recommendations is Zalando.de, displaying alternatives as well as matching products as outfits on its product detail pages:

Zalando shows various Product Recommendations for its Product Detail Page

Zalando shows various Product Recommendations for its Product Detail Page

Efficient organisation and processes

In order to be able to offer the above functionalities, a continuous optimisation process within a company is required. Companies should track when users like Anna search for a product in their online shop and get zero results. It is also important to get an overview of Anna’s favourite search terms. Companies should regularly check their analytical reports and use these insights for optimisation. Quick wins can be achieved by configuring result modifications, synonyms and redirects. Furthermore, a close cooperation between the search owner and other teams is necessary. For example, by collaborating with the online product management team, the product catalog can be optimised based on Anna’s feedback. Moreover, regular monitoring of relevant search KPIs supports these processes. An implementation is often successful if capable cloud solutions such as Attraqt Fredhopper are used in the search area, as this simplifies the creation of business rules via a clear interface.

Conclusion

From my experience in e-commerce I can conclude: Only when these cornerstones have been implemented, companies have reached a baseline for successful Search & Merchandising and can ultimately win potential customers like Anna as customers.

Next steps

In further upcoming posts, I’ll be addressing the question: What could inspire Anna in the field of product discovery in the future – in times of ever faster digitalisation and ever shorter technological development cycles? Innovative technologies open up additional possibilities for addressing potential customers in existing channels or offering new channels. Feel free to share your opinion about these topics below.







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