{"id":44042,"date":"2023-08-03T11:06:24","date_gmt":"2023-08-03T09:06:24","guid":{"rendered":"https:\/\/www.altares.be\/?p=44042"},"modified":"2023-09-12T15:54:27","modified_gmt":"2023-09-12T13:54:27","slug":"data-done-right-3-tips-for-optimal-use-of-your-external-data","status":"publish","type":"post","link":"https:\/\/www.altares.be\/en\/blog\/master-data-management\/data-done-right-3-tips-om-optimaal-gebruik-te-maken-van-je-externe-data\/","title":{"rendered":"Data done right: 3 tips for optimal use of your (external) data."},"content":{"rendered":"

Everyone in the office uses and processes data throughout the day. In many cases, however, we are not aware of it, and we mainly associate data with IT specialists doing 'special' things with ones and zeros. But if you see through the smoke screen of IT jargon and understand how data truly works, there is more than enough that 'ordinary' company personnel can do to make optimal use of their data. Here are the top tips: <\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

1. Data engineering for dummies (create your own data)<\/h2>\n\n\n\n

One plus one equals three. Not really accurate in the real world, but it holds true within data. Take one piece of data, combine it with another piece of data, and you'll end up with three pieces of data - the two originals, plus the new one you created with them. This may sound more complicated than it actually is. Let me give you an example: <\/p>\n\n\n\n

Imagine you have, on one side, the names of all your customers. On the other side, you have a field with the annual revenue of each customer. You can use this data together to create a new data field, for example, with four categories of companies. One category for all small businesses (up to revenue X), and then further categories for progressively larger customers (from revenue X).  <\/p>\n\n\n\n

The significant advantage of this is that, based solely on the revenue amount, it can be challenging to classify companies into groups. By linking them automatically to a category, this task becomes much easier. This kind of simple data engineering enables you to work with data that you may not have directly available, but can still shape indirectly.<\/p>\n\n\n\n

2. Segmentation can be learned<\/h2>\n\n\n\n

The main goal of this type of data is often segmentation: the ability to divide your customers or contacts into specific groups. This is essential for everyone, whether you work in marketing, sales, finance, or service. Even more useful is to implement such business-wide categorization. Often, this is already done with all the different types of products or services a company provides, which can be seen as the vertical columns in a grid. However, segmentation becomes truly powerful when you can add other segmentations alongside them - the horizontal rows. <\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

With only the vertical categories, you have four segments. But with the addition of the four others, you suddenly have sixteen at your disposal. <\/p>\n\n\n\n

3. Use external data<\/h2>\n\n\n\n

By cleverly merging data and creating segments, you can already extract much more value from your data. At the same time, you may wonder how to retrieve the annual revenue of your customers. The easiest way, of course, is to simply ask for it. Add a field to your website's form, and voil\u00e0!  <\/p>\n\n\n\n

Indeed, there are only a few companies that follow this approach. The reason is that the fewer fields you use in a form, the higher the chances that someone will fill it out. Companies prefer to omit anything that is not strictly necessary. Asking for sensitive information such as credit status or whether their company is on a sanctions list is generally avoided, as it may deter potential customers from completing the form.<\/p>\n\n\n\n

To still gather this information, you can utilize external parties to enrich your data. By using an API from the form or database, you can compare your customer data with the information an external party holds about those customers. This way, you can obtain fairly comprehensive data with limited information and then leverage it to your advantage. If you want to learn more about this, read more here<\/a> or contact us below.<\/p>","protected":false},"excerpt":{"rendered":"

Using data has long since gone beyond IT professionals. Everyone in your organization uses data for work, but how do you make optimal use of it? 3 tips on how to make optimal use of your (external) data.<\/p>","protected":false},"author":8,"featured_media":44043,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[19],"tags":[],"class_list":["post-44042","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-master-data-management"],"acf":[],"yoast_head":"\nData done right: 3 tips om optimaal gebruik te maken van je (externe) data - Altares<\/title>\n<meta name=\"description\" content=\"Data wordt door je hele organisatie ingezet tijdens het werk, maar vaak niet optimaal met verloren inzichten als gevolg. 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