According to the data from ABN Amro (2018), companies in the Netherlands in various sectors have started working more intensively with customer data in the past six years. This applies not only to the analysis of this data but also to its storage. The increase in data storage in particular is striking. According to the ABN Amro in 2012 28% of the companies said they were saving customer data. In 2017 this was 46% of the companies, an increase of 18%. The ABN Amro also indicates that big data is important for the growth of the Dutch economy. The productivity of companies that work with big data is no less than 6% higher than those that do not. Statistics from the CBS also show that sectors that focus on big data are generally more innovative. In the future we will thus no longer be able to go without big data according to ABN Amro. But what is the value of big data?
The enormous mountain of data collected by, for example, social media and webshops, is completely worthless in itself. Big data has no intrinsic value of its own. The data must first give us information. Only then can an organization get value from the big data. This is done on the basis of various phases that the data must go through before it provides information according to ABN Amro. There are roughly four distinct phases: data organization, data management, data analysis, and taking action. In this article we explain how tritonX supports retailers in creating value with big data through these steps.
Creating value with big data in four steps
- The first phase, data organization, is about digitization, storage, and creating access to the data source. In this phase the conversion of raw data into usable data often takes place. In tritonX all big data is categorized so that it is transformed into smart data. This makes the data readable again so that it can be used. The next step then is to create segments within tritonX, whereby the customer profiles are further categorized.
- The second phase, data management, is about updating and cleaning up all data that is stored. In addition, the data managers are responsible for the quality and security of the data. In this phase it is therefore important to ask who owns the data and how privacy can be guaranteed. The customer data in tritonX must therefore be stored in a secure manner. At the same time, the data must be available in many different places in your company, where possible in real time. tritonX therefore follows the GDPR regulations in Europe, in order to be a smart data hub with secure web services.
- The data analysis takes place in the third phase. These analyses are often largely automated, but human knowledge also plays a role in the meaning of big data. There are roughly three different forms of data analysis. The first form is the explanatory analysis where the data is analyzed to understand what is happening. This could be the analysis of a retailer’s sales data in relation to click behavior on the web shop, for example, to determine why the profit increased in the past quarter and which branches are doing well. A more intelligent form of data analysis is the predictive analysis. In this form of data analysis, we do not only look at the past, but also the future. The data is used here, for example, to be able to predict whether more or less will be sold in a summer month. Lastly, the most intelligent method of data analysis is prescriptive analysis. A specific action is also proposed here based on the prediction.
- In the final phase, an action will be taken based on the information that emerged from the data. This action then creates new information and the cycle starts again. With this information a more targeted newsletter with these brands can be sent to them via tritonX. This can ultimately result in more visits to the web shop or in store and potentially an increased turnover due to the heightened relevance for the customer.
Curious about how you can get more value from data with tritonX? Then contact us!
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