Success Stories

Customer

Our customer, a leading automotive financial services company, is represented in more than 50 countries. With nearly 50 years of history, the company employs more than 1.200 people and offers a variety of financial services.

Challenge

Nowadays, many companies are pressured to utilize their advertising budget efficiently. Marketing actions are ideally designed so that as many (potential) customers as possible are reached with a minimal allocation of resources.

Solution

By means of combining data from the customer database with milieu data, thaltegos helps companies to address the right target group at the right place with maximal likelihood. The customers of a specific product – for example the car model A – often exhibit great similarities with regards to age, lifestyle and family status. Therefore, it is reasonable for companies to additionally consider milieu data (e.g. SIGMA Milieus® and DELTA-Milieus®) in the context of customer segmentation and the respective communication. Once the available customer information is enriched, current customers can be divided into segments based on product and brand affinity. Moreover, customer profiles can be derived and conclusions about potential customers can be drawn. For instance, it is possible to determine which characteristics (age, income, etc.) a typical customer of the car model A has. As a result, a scoring model is derived which assigns potential customers to segments even if only little or poor information is available.

Benefit

This enables companies to adjust their sales and communication activities to be more client-specific. Potential customers of a certain product can be identified and targeted by marketing actions more precisely. Customized scoring, based on product and brand affinity segmentation, makes it easier to target potential customers. Consequently, companies can learn from existing customers about potential customers to then adjust the sales approach to be segment-specific. For an automobile manufacturer this sustainably increased the efficiency of customer communication and sales activities. The conversion rate was increased by 100 % compared to a similar campaign. Furthermore, this information can be used for a customer-oriented product design.

Customer

Our customer, a globally operating German car manufacturer, employs nearly 130.000 people and is one of the largest commercial enterprises in Germany. The traditional company, which looks back on more than 100 years of history, is one of the premium brands in its sector.

Challenge

In the automotive industry, vehicles are usually individually configured by the customer and then specifically produced. However, many markets and the respective customers are located far from the automotive manufacturer. For this reason, pre-configured vehicles are planned and produced. To ensure optimal sales, these vehicles should be aligned as closely to desires of potential customers as possible.

Solution

thaltegos supports a car manufacturer with this optimization through a data mining application. To reflect the wishes of future customers as well as possible through configuration suggestions, historical order data are analyzed. On the one hand, it is determined how often certain options are ordered by different customer segments. On the other hand, correlations between these options are calculated. For this, the data mining application groups the multitude of features into overarching factors by means of a factor analysis. For instance, this results in a factor for sporty options and a factor for comfort-oriented options. Based on these findings, similar orders are aggregated to determine statistically significant configurations for the individual customer clusters. This enables the creation of configuration suggestions which enhance the ordering of new vehicles in the sales process.

Benefit

The utilization of these configuration suggestions makes it possible to verifiably align vehicles with customer and to implement pre-configurations that lead to fast sales. On top of that, the insights gained from the order data analysis can be used for further optimizations. This encompasses the planning of special options as well as the forward-looking allocation to production sites. Moreover, these results enable the deduction of market trends (based on the historical order data) as well as measuring the effects of campaigns and activities in product management.

Customer

Our customer, a globally operating German car manufacturer, employs nearly 130.000 people and is one of the largest commercial enterprises in Germany. The traditional company, which looks back on more than 100 years of history, is one of the premium brands in its sector.

Challenge

The after sales business is highly important in the automotive industry. Apart from the sale of new vehicles, the service, parts, and maintenance business constitutes a significant share of the profits. With increasing competition and decreasing customer loyalty it has become ever more important to retain customers and to submit the right offer at the right time.

Solution

thaltegos supported an automobile manufacturer in the prediction of service intervals to enable a targeted sales approach. For the prediction of the next service event in after-sales it is crucial to define the relevant customer segments as well as influencing factors on the service intervals. For example, the intervals for an oil filter change can differ considerably depending on the vehicle model and age. To include these factors in the prognosis, service history data have been used as a starting point. Based on this information, the “Interpurchase Time (IPT)” – the time between two consecutive service events – as well as factors influencing the IPT have been extracted. Consequently, it was possible to determine the effect of specific factors and to derive a regression model for the prediction of service intervals.

Benefit

By means of this model, future service events can be predicted more precisely than before. Compared to the simple sequence continuation, the share of correctly predicted service intervals is 20 % higher with the regression model. Hence, for instance the next oil filter change of a vehicle can be determined more accurately and the customer can be approached in time. The prediction of service intervals enables the automobile manufacturer to carry out targeted marketing actions in after sales. Depending on the service demand and service time it is possible to individually approach the customer with the right offer at the correct moment. Furthermore, segments at risk of customer churn can be identified to launch measures for customer retention. As a result, dealer and workshop capacities can be planned better and customer loyalty and profitability are positively influenced.

Customer

Our customer is a multinational lighting manufacturer with a history of more than 100 years. Listed on the stock exchanges in Frankfurt am Main and Munich, the company employs more than 25,000 people worldwide and offers lighting products and solutions along the entire lighting value chain.

Challenge and objective

The digital marketing, service and sales activities were considered and optimized separately. This was due on the one hand to the organizational division of responsibilities for different digital contact points (touchpoints) and the touchpoint-specific tracking of different metrics and KPIs. The objective of the customer was to have an integrated view of the relevant digital contact points and thus to have the opportunity to demonstrate the interplay of the individual measures along the digital customer journey with the goal of optimally orchestrating websites, E-Commerce, apps, digital advertising and social media from corporate marketing and the individual business units.

Solution

The solution developed for our customer was an integrated digital performance management approach. For this purpose, a KPI set was defined for all digital touchpoints, which on the one hand measures the performance of all digital marketing and sales activities and also measures the spill-overs and interconnections of of different digital touchpoints. By setting up a reporting tool with integrated cross-touchpoint dashboards based on a business intelligence solution, the individual digital marketing and sales activities were integrated into the context of the customer journey. The comprehensive digital performance dashboards enabled our customer to visualize and understand the marketing and sales funnels and optimizing the entire digital ecosystem of marketing, sales and service. Relevant areas of consideration were the click stream on the websites, SEO performance of the website, the influence of SEA and advertising as well as the role of different social media channels and activities on marketing conversion and sales funnel as well as campaign performance. After creating dashboards at different levels of analysis (operational dashboards, management dashboards), the solution was rolled out both in the central departments and selected countries, and training was provided to ensure the widest and most effective use at all levels of the organization.

Customer Benefit

An integrated digital performance reporting tool generates transparency across all digital channels and the measured KPIs. This overcomes "silo management", puts individual measures in the context of the digital customer journey and optimizes the overall system instead of individual measures. Furthermore, continuous monitoring of digital performance provides control over the course and impact of digital marketing and sales activities, and enables early detection of optimization potentials in marketing and sales. Thus, individual campaigns, measures and contents can be subjected to a precise performance control, which leads to a cost-optimized and benefit / user-oriented control of campaigns. In addition, the allocation of resources and budget can be optimized based on the overall overview of all digital channels.