Data quality is crucial
Many E-Commerce platforms can now filter products based on price, popularity or latest added. But by making product specifications easy to search on and filter within specific categories, you give the customer a much stronger tool for finding the product they are looking for. For example, can the customer search for a ball based on its diameter, or do they have to locate the ball several levels into the menu or scroll through the entire catalogue to find the right one?You can also prioritise your product data so that a search on 'iPhone' will rank the core product, i.e. the actual phone, higher than an iPhone cover.
Equally, when a customer does a Google search for a product that is in your product catalogue, they get your particular product or product page in their search results if you have given Google direct access to searching in your catalogue. This happens based on the data connected to individual products, and how this data is structured, and quality assured.Search engine optimisation is an important e-commerce discipline, where smaller companies can overtake larger brands when it comes to online visibility.
The data quality is essential to how usable your data is for other functions on your e-commerce platform, and with automatic data enrichment, you ensure consistent data quality. For example, describing your product using free text carries a significant risk of spelling mistakes and inconsistent use of language between different employees. If you define the product in a cohesive context, it's hard to filter and search in your product catalogue, because the data has not been individually categorised.
For the customer, highly consistent data quality means a better search function and more filtering options on your e-commerce platform. And for many online users, the search and filtering are essential to whether they bother to use your web shop. Alternatively, your search and filtering options will never be better than your data.
Read more about how to automate the data enrichment of your product catalogue to ensure consistent and good data quality.How to automate data maintenance
The first step in this process is to identify the relevant user journeys that you want to support with search or filtering options in the product catalogue. You can do this by examining what the users on your existing E-Commerce platform are searching under, or by using Google Analytics to analyse the user journey that ends with a purchase of the most sold products. You can also compare the converted user journeys with user journeys that end with the customer leaving your site. Perhaps you'll find that some products are better described than others, or that data is not indexed correctly so that search and filtering are not possible for the product's metadata. The basic aim of metadata should be to create value by improving searches and filtering and increasing conversion on the site.
The next step is to identify what data you have access to, the format the data is saved in and where the data lives in your internal systems. If you discover gaps in your user analysis, which your internal data can't support, you can find out whether there are external sources that can deliver the data you want.To reach the next step you need to be able to correlate data either in a good old-fashioned excel spreadsheet or with integration between your ERP or PIM solutions, from where the data can be imported into your E-Commerce platform and indexed against the parameters the customer has to be able to filter on.
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