Data enrichment for targeted decisions and personalized customer communication

Enabling omnichannel commerce

If users shop both in a brand's physical store and online shop, both channels can be connected. This is because relevant events also take place outside your shop that can serve as a supplementary data source. With the help of customer loyalty programs such as a bonus program or a customer card , you can collect information in brick-and-mortar stores and use it profitably in your online shop thanks to data enrichment.

In-store purchases are an example of relevant events outside the shop and offer you the chance to complete the most valuable type of event – namely the buy event. It is valuable in the sense that it provides AI with the most relevant information for personalized recommendations, enabling you to deliver tailored recommendations. For example, you can provide your customer with online styling suggestions that match the shirts she last purchased offline. This link optimizes the shopping experience, strengthens brand awareness, and ultimately brand loyalty.

Preventing abandoned purchases

In e-commerce, it's all about preventing abandoned purchases. Imagine if you could remove obstacles from the checkout process step by step. For example, by presetting the default address or preferred payment method based on previous purchase behavior data. This significantly reduces the risk of abandoned purchases.

Minimize returns

Returns are the weak point of every online retailer. Enriched data helps you avoid them and minimize your return rate. The return rate is an important KPI because sales are directly dependent on it. Return data is an important part of purchasing behavior and can provide you, as an e-commerce manager, with information about frequently returned products and reasons for returns, for example.

The product recommendation system can benefit from these new sources of information, as products that are frequently returned should certainly be recommended less often. This means you can exclude goods that are frequently returned from campaigns and exclude items with high return rates from your recommendations. For new customers , you can also feature top sellers with low return rates in your recommendations. In addition, data enrichment allows you to flexibly display information on product detail pages that can help prevent returns, such as details about the fit of a pair of pants. You can enrich this additional information based on the reasons for returns.

NKD aims to prevent returns by providing information on fit, a size chart, and a size finder directly on the product detail page.
(Source: Screenshot from nkd.com)

If you generally notice a high return rate in certain categories of your shop, you can counteract this by using a product advisor. This also requires data enrichment, or more precisely, an enrichment of product data so that shop customers can select the features they want. In the case of a luggage advisor, as offered on worldshop.eu, the required features would be, for example, what type of wheels a suitcase has, what compartments or what fastenings the luggage has. Especially when the product range is somewhat more specialized, expanding the product features in the sense of data enrichment makes a lot of sense.

Each of the three aspects of data enrichment can significantly improve the quality of such an online product advisor. For example, cleaned data prevents items from being displayed even though they do not match the current feature selection. With the help of completion, you prevent the opposite from happening, namely that suitable items are not displayed. Finally, expanding the data brings the product advisor to life. This gives the customer enough options to choose from, and the features really help them.

The Worldshop luggage advisor offers shop customers many features that make product selection easier.
(Source: Screenshot from worldshop.eu)

You can find out more about how personalization can help you avoid returns in our blog article on this topic.

Avoid out-of-stock situations and inventory backlogs

Data enrichment also helps you avoid out-of-stock situations by determining stock range based on factors such as current stock levels and historical order and return behavior. This allows you to hide certain products in your shop that may not be delivered on time.

You can also use data enrichment to identify slow-moving items. This allows you to boost sales of these products and avoid stockpiling.

Maximize high-margin sales

Data enrichment also enables you to identify high-margin products and thus maximize your sales. To do this, your data must be enriched with information such as the product's contribution margin, marketing costs, or transactional costs.

Use 1:1 personalization

Also consider the interests of your shop visitors and address each individual customer with 1:1 personalization. Based on previous transactions and interests, customers can be segmented or addressed individually. Use the enriched data in email marketing, for example, to personalize newsletters more effectively. Instead of just using a personal greeting with their first name, you can even customize the entire content of the email, for example with recommendations for their favorite brand, preferred colors, or styles. Information about your customers' interests can also be used for recommendations in your online shop. This will increase the average order value and your sales.

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If you would like to learn more about how to tailor product data in your online shop to the needs and pain points of your customers, as well as how to prepare and enrich your product data feed in order to optimize search results or display relevant recommendations in your shop, we recommend reading our blog articles on these topics.

Thanks to an optimized search function, customers in the PICARD online shop can also obtain relevant results for search term combinations they enter.
(Source: Screenshot from picard-fashion.com)

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