Raising the Data Treasure – Specialist Article by Christian Ebernickel in the Handelszeitung By Christian Ebernickel | November 16, 2019 (updated December 7, 2019) | Analytics The use of data permeates our everyday lives and yet only a minority of companies actually use the data consistently to analyse, control and monitor their marketing. This could be fatal; a study by Forbes Insights has made it clear that the efficient use of data will be a decisive factor in the future as to whether a company continues to develop successfully in the market. In the marketing supplement of Handelszeitung No. 44/2019, I was able to point out six building blocks for a data-driven culture. ContentsIntroduction: How Data Can Improve the Customer Experience1. Objective2. Data3. Analyses and Optimizations4. Business Intelligence Manager5. Data-Driven Culture6. External Specialists Introduction: How Data Can Improve the Customer Experience Streaming services know our preferences and guide us to series and songs that suit us. Leading online retailers not only provide us with a highly personalized shopping experience, they also deliver consumer goods to us on time before they are used up. Based on weather data, drug manufacturers and online pharmacies can anticipate the first wave of colds in the fall and play out timely advertising campaigns for nasal sprays, throat pills, and so on. But what do companies have to do that want to establish data-centered marketing? First of all, data-centric marketing is not just a question of the right use of technology. It is equally important to understand data-centric marketing as a process that will change the way companies and external partners work. If you don’t involve the people in this process, you run the risk that your investments won’t pay off. Six building blocks have proven to be particularly important when companies want to establish data-centric marketing: 1. Objective If data is to be used, this cannot be done without a clear objective. If a company does not know which goal it wants to achieve, it is not even possible to identify the required data. Therefore some basic questions should always be clarified at the beginning: What is the goal of data analysis and optimization? Which key figures are relevant for assessing target achievement? Which data segmentations would allow deeper insights? 2. Data The better the objective is described, the more clearly the required data and data sources can be derived from it. In addition to internal data sources such as website usage data, store visit information and customer service data, this can also include data from external systems (e.g. weather data). Of particular importance is the consolidation of data from different sources in a shared data warehouse. Only then are they available for comprehensive analyses and make it possible to uncover connections that would otherwise remain hidden. The better the resolution of data silos, the higher the potential that can generally be exploited. 3. Analyses and Optimizations Unfortunately, analyses are of little value in themselves. It is crucial for a company that concrete steps are taken from the analyses. Only then can the investments made generate added value for the company. Therefore, from the outset, special emphasis should be placed on a process of continuous analysis, optimization and follow-up. This ensures that analyses and optimisations are aligned with the objectives and that the results are regularly reviewed. 4. Business Intelligence Manager In addition to the Marketing Director, the Business Intelligence (BI) Manager is the central person for anchoring data-centered marketing in the company. However, hiring the right person is more difficult for most companies than it initially seems. In addition to the fact that the personnel market in the BI area is tense, there is another challenge: How can you identify suitable candidates if the company only has rudimentary knowledge about the tasks of a BIManager? The risk of misplaced candidates is high. This makes it all the more important to concretize the requirements for the skills of a BI manager in advance and to at least build up basic knowledge about the work of a BIManager in order to make a good decision. 5. Data-Driven Culture Data-driven work should not end at the boundaries of the BI department. If a company wants to get the most out of the analyses and insights of BI specialists, it is important to make them available throughout the organization. The more employees can incorporate the BI department’s insights into their decisions, the greater the impact the use of data will have. The consistent use of data also makes wrong decisions in marketing more transparent. The establishment of an error culture is therefore of particular importance if data-driven work is to be successful. 6. External Specialists Their support can be valuable in order to avoid mistakes and to build up data-centered marketing in a targeted manner. Nevertheless, it should be examined for which tasks their use makes sense. If the tasks involved are irregular or even one-off, and may require special know-how that is difficult to build up, then external consultants are the right choice. On the other hand, operational tasks should rather be covered by your own employees. PS: You don’t have enough e-mails yet? Then subscribe to our newsletter. Wortspiel Launches Friendly Analytics, the Privacy-Friendly Swiss Google Analytics Alternative About Christian Ebernickel Christian Ebernickel is a Senior Consultant at Wortspiel. He focuses on the conception and implementation of extensive tracking setups with Google Analytics and the Google Tag Manager. The winner of the Google-supported “Analytics Award” is a sought-after speaker at conferences such as the “Data Driven Business” in Berlin, the “SMX” in Munich and the “Analytics Summit” in Hamburg as well as a lecturer at 121WATT. Christian's motto is: “The right data in the right place at the right time”.