How does data enhancement work?
The data that a company has access to is usually unstructured. In order to turn that into useful information and maximize its value, you can use data enhancement. This means that every piece of data is examined and given meaning. For example: Customer data such as addresses can be checked to ensure that they are complete and up-to-date, product information can be classified to make filtering options in an online shop easier, or images can be segmented and analyzed to help train AI.
Data enhancement and enrichment services for direct marketing
When it comes to marketing, data quality plays an important role. Address lists, for example, are often full of errors or no longer up-to-date. Address validation can help with that. Every address is checked to make sure that it is correct and useful to your direct marketing and sales campaigns. In addition, data enrichment services for companies improve your database’s value. This includes filling out existing data sets to ensure that you have all relevant information in your customer files.
Classifying product data for online shops
In online shops, good product data management is important to make it easier for users to find the products they are looking for. Whether they are searching for products in their favorite color, with specific dimensions, or with special attributes – a good filter can only function properly if the data is suitably structured and classified. Data enhancement services ensure that all relevant product information is included and that customers can filter according to what they need. This increases customer satisfaction and leads to a higher conversion rate.
Helping machines learn through data enhancement
Another area of application for data enhancement is machine learning. When training AI to understand data and be able to identify it, it is necessary to have good training data. Image annotation services or tagging, for example, allow you to achieve a high data quality, which can be used to train computer vision models. With improvements in this area, machines can learn to identify objects in an image, pick out groups of objects – such as vehicles and street signs – or recognize facial features, expressions, and emotions. This, however, requires large amounts of data which has to be expertly classified. Data enhancement or data enrichment services are the ideal way of achieving this goal and guaranteeing progress in AI learning.
Data enhancement and data enrichment are vital to make sure that you have high-quality product data that you can use to improve your business or advance machine learning. The rule of thumb here is: the better your data, the better your results.