In the automotive industry, it is expensive to win a new customer. Therefore, it is crucial to identify customers with switching intentions at an early stage and retain them through appropriate measures. Our client, a leading car manufacturer, was faced with the challenge of identifying customers with a high risk of switching and understanding the reasons for their churn behaviour.

To predict customer switching intentions, we used a generalised linear model (GLM). The GLM uses various data sources, including customer, vehicle and social media data, to create a holistic customer history. Using this data, we performed modelling to determine the likelihood of customer churn and identify the drivers of it.

Thanks to our method, we were able to identify exactly those customers who had the highest risk of switching. By targeting these customers and developing appropriate customer retention measures, our client was able to significantly reduce churn rates. Resource allocation in the company became more effective and the company was able to both save costs and increase customer loyalty. The method has a hit rate of 90%, which means that our model was able to correctly predict churn in most cases.

Our project shows how Big Data Predictive Analytics can help companies better understand their customers and develop effective marketing strategies. The use of machine learning methods such as GLM and the use of social media data enables companies to develop a deep understanding of their customers and better understand their needs and wants. This can help businesses not only retain customers, but also attract new ones and increase their sales.

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Our company had the pleasure of developing a customised solution for an automotive company to conduct competitive analysis for the US market. The company was struggling to collect and visualise the data needed for a thorough analysis. The data sets were large and complex, and the company did not have the necessary tools and technology to process them effectively.

Our team of experienced data analysts and AI experts worked closely with the company to implement an interactive and flexible application to perform competitive analysis. The application included different maps with two different views to provide users with a wide range of visualisation options.

By using the latest technologies and tools, we were able to ensure that the application was easy to use and user-friendly. Users had the possibility to filter and visualise the data in different ways to find relevant information quickly and easily.

The result was a powerful competitive analysis software that enabled the company to identify, analyse and visualise relevant markets. The retailer or the respective sales department now had the possibility to compare the direct competition with their own product and visualise the relevant data. With our solution, users could quickly and easily access extensive data that was previously difficult to access. The visualisation of the data enabled the company to gain important insights into the market and make better decisions.

Thanks to our solution, the company was able to improve its competitive analysis and gain valuable insights that enabled it to improve its marketing strategy and strengthen its position in the US market. Our clients value our expertise in data analytics and AI technologies as we always strive to develop innovative solutions that help them grow their business.

If you too are looking for powerful competitive analysis software to help you identify relevant markets and improve your marketing strategy, don't hesitate to contact us. We pride ourselves on providing you with customised solutions that are tailored to your individual business needs.

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A successful aftersales sector is crucial for car manufacturers to retain customers in the long term and increase sales. One important metric for this is the retention rate. However, a leading car manufacturer was faced with the challenge of calculating and analysing the retention rate in different markets and at different levels of aggregation.

In order to increase customer loyalty and the turnover of the car manufacturer, the company relied on the support of data scientists from Alexander Thamm GmbH. They developed an analysis tool that not only allows the retention rate to be broken down according to vehicle attributes, but also allows the vehicles to be divided into dynamically definable age segments and the rate to be calculated on different reference dates. In addition, information on service packages and special equipment was linked to the tool.

Thanks to the implementation of the tool, the individual markets of the car manufacturer can independently carry out success measurements of customer campaigns. The big advantage here is that automating the calculations not only saves a lot of effort, but also improves the quality assurance of the results. In addition, the tool opens up the possibility of increasing customer loyalty and customer turnover through active upselling of service packages and special equipment.

In addition to providing the analysis tool, Alexander Thamm GmbH also helped the car manufacturer to improve its overall data strategy. This included, among other things, the definition of data standards and processes as well as the introduction of data quality management methods.

For companies that also want to calculate and analyse their customer retention rate, Alexander Thamm GmbH offers a customised solution. By using modern technologies such as data science and artificial intelligence, we support our customers in optimising their business processes and achieving business management goals. If you too would like to increase your customer loyalty and boost sales, please feel free to contact us and let us develop a suitable solution together. And who knows, maybe we will soon be able to count your company among our satisfied customers who have been able to successfully calculate and increase their customer retention rate.

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