![]() Key steps in this context include anchoring the system’s continuous improvement, but also data use by the organization’s departments from the outset.Ī distinction is made between three levels of complexity when modeling CLV and CAC: Aside from linking different data sources and formats, the customer data platform also enables the integration of suitable external systems as well as customer segmentation according to behavior and demographic data. Then, returning visitors (including to different channels) are identified by matching them against the full array of profiles compiled. For this purpose, profiles comprising as many attributes as possible are created for visitors to the various channels (based on browser data, among other things). ![]() Successful providers solve this problem with an integrated customer database (customer data platform) that can recognize customers even when they do not sign in. This is partly due to purchases made across different channels, for instance, in the company’s own online and offline stores or perhaps through third-party suppliers such as retail partners, which often do not require registration (with an e-mail address, etc.) for identification. Marketing data such as search behavior, response to campaigns, and external online data help to flesh out the respective customer profile and, in turn, deepen customer knowledge, including as regards preferences or purchasing behavior.ĭespite ample data, it is often difficult to clearly identify customers throughout the entire customer journey.Demographic data such as gender, age, occupation, and place of residence are condensed into customer profiles in order to better predict future shopping behavior and personalize marketing actions.Transaction data such as shopping timeline, product information, prices, method of payment, delivery, or returns are supplied by the e-commerce platform and the connected financial systems.The greater the volume of data available, the more meaningful and accurate the analyses. ![]() This is because the corresponding analytical models are dependent on the availability of sufficient amounts of information to identify relevant patterns. To estimate the current and future value of customers and keeping privacy regulations in mind, companies need to collect relevant data points on as many customers and their behavior as possible over multiple years. Collect data throughout the customer journey To make the most of the CLV approach and use it to manage their e-commerce business, they should adopt a long-term strategy and proceed systematically in three steps: collect data, determine true customer value, and target investments to the most valuable customers. Many traditional manufacturers and retailers, on the other hand, still have some catching up to do. That’s something we are working on, aside from further refining our analytics and increasing their granularity to the level of geographical micro-cells.ĭigitally aligned companies and start-ups have long been successfully applying and refining this approach (see sidebar, “‘CLV is our core steering metric,’ Four questions for Emmanuel Thomassin, Chief Financial Officer of Delivery Hero”). Do you still see untapped potential in the way you use CLV?Ī major challenge is responding directly to improvements in the KPIs with measures designed for pinpoint accuracy, especially in marketing, and then evaluating these with precision. This shows that our marketing measures, among them personalization, have a direct impact on the KPIs and thus on Delivery Hero’s success. Today, they are many times higher than the investments in customer acquisition and retention. Over the years, we have seen CLVs rising steadily across all our cohorts, even before Covid. Perhaps the most important KPI-based analysis is breaking down customers into cohorts to fine-tune the targeting of marketing drives. ![]() Over time, we have learned an enormous amount, especially through monitoring in new markets and with the introduction of new business models. Initially, for example, we only calculated the cost of customer acquisition meanwhile, we also know what it costs us to retain customers. It is crucial to continuously adapt and improve the calculation of CLV and the corresponding operationalization in marketing. CLV monitoring is directly linked to our operational marketing systems and thus directly influences our investments. We have a standardized approach for all our markets. We use CLV to support our strategic and operational decisions, such as whether to enter a new market or whether to continue or end a marketing campaign. It’s a topic we’re driving intensively at all levels of the organization and we have set clear goals from which we can only deviate in exceptional cases. Just how important is CLV for Delivery Hero?Ĭustomer lifetime value is one of our core metrics.
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