Cross-channel marketing across many channels is now standard in e-commerce. However, the evaluation of important touchpoints with users is often missing. Which channel contributes to my marketing success? Which campaigns are the biggest drivers and where can budgets be shifted?
Blinkist uses different channels with dedicated content. These include platforms such as Google Ads, YouTube, Instagram, Microsoft News and other content marketing offerings. As a result, Blinkist has extremely extensive marketing data at its disposal, which needs to be consolidated and processed in order to be able to carry out valid analyses of its impact. Data management was increasingly becoming too technically demanding for previous solutions, which was mainly due to an outdated tech stack. Together with taod, blinkist succeeded in modernizing the tech stack in connection with the development of a customer data analytics platform.
How can data from different touchpoints be merged in a meaningful way?
What is necessary to be able to interpret the behavior of customers?
Which technical components are essential for customer journey analytics?
In a data use case workshop, taod develops a proof of concept together with Blinkist's finance team. More than half of the budget is invested in marketing or represents a necessary investment for effective marketing. Ultimately, therefore, a clear allocation of investments must be made so that it is clear where exactly what money is being spent. Existing discrepancies between self-generated reporting and actual accounting must be eliminated. This use case should form the basis for further optimization of the analysis activities.
During the workshop, it quickly becomes clear that Blinkist's data stack needs to be fundamentally overhauled. A high susceptibility to errors was identified in the existing data pipelines, which had to be completely rebuilt. Changing the connector tool from Data Virtuality to Fivetran via Airbyte on a trial basis, primarily to relieve the burden on internal resources, and the transformation tool from Matillion to dbt will ensure enormous flexibility in future and allow any adjustments to be made quickly and easily.
As a transformation tool, dbt reduces the effort required for thorough testing by up to 80 percent. In addition to the complete overhaul of the data transformation and the change of connector tool, taod designs new logics to meet the dedicated analysis requirements. The data vault method is used. It ensures the fast and correct integration of data into a data warehouse. It can react flexibly to major changes in content.
The existing Amazon Redshift data warehouse will be replaced by the Snowflake cloud data warehouse, which will ensure high scalability as required in future. The development of the data stack will initially be managed and subsequently supported by taod, thus ensuring a high level of enablement for Blinkist. Data Vault also represents a new modeling technique for Blinkist's data team, which will be trained through 1:1 coaching sessions over the course of the project. Technology and enablement also reduce the time needed for bug fixing.
After four months, the Blinkist team manages the new Modern Data Stack independently. taod takes on an advisory role from this point on and supports the project at regular intervals with an FAQ format. The optimized tech stack ensures smooth and error-free processing of the complex data. Thanks to modern modeling technologies and efficient ETL processes, potential sources of error are significantly reduced and data quality is sustainably improved.
The focus of the project is the modernization of Blinkist's technical infrastructure. While Blinkist initially had access to a small database that was managed in-house and with solid BI knowledge, the company recorded a rapidly growing volume of data. Due to a lack of optimization in data management, considerable errors crept into the data evaluation, which were mainly due to technical reasons. The existing modules are being reviewed and scrutinized accordingly in order to ensure efficient and reliable data analysis. Broken data pipelines and unnoticed errors in data processing are to be fixed. This is done in close cooperation with the Blinkist data team, which is also enabled by taod to be able to work consistently with the tech stack. With a modernized tech stack, Blinkist is able to process and analyze extremely complex, heterogeneous data from marketing, CRM and sales.
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What components does a professional tech stack for analytics consist of?
