From data audit to individual architecture sketch
Challenge
- Our client wants to shift the focus to a customer-focused business model and increase their own brand effectiveness
- The achievement of these goals should be supported by data — the However, resources are limited
- Orientation at Prioritize and implement possible data projects/initiatives is Difficult due to lack of know-how
Situation
- Our customer owns large market shares in Europe in its segment
- The store is transactional driven and end customers are very price-sensitive
- The market is in a phase of consolidation
- The high value of data is established in the company and a variety of initiatives are in the planning/idea phase
Solution
- Outlining the “status quo data” in a “Spotlight Audit”
- Identification of short and medium-term recommendations for action and priorities by targeted in-depth discussions
- Two key recommendations were:
(1) The more accurate Review of the current tracking setup
(2) the Development of use cases and one derived from this Architecture for a modern data infrastructure - Both recommendations were accepted by the customer and successfully implemented in follow-up projects, also together with TDI
Added value
- Laying the foundation for the introduction of a modern data infrastructure
- Identification of profit-oriented use cases to achieve brand effectiveness and customer focus
The implementation
Together with the Babymarkt team, we have structured and successfully completed this first phase of cooperation.
Step 1: Spotlight audit
At the start of the collaboration, we carried out a spotlight audit with selected stakeholders. This had the goal of recording the situation at Babymarkt and identifying potential quick wins right from the start.
Implementation of the Spotlight Audit
We conducted interviews with key data stakeholders, technical employees and management. As a result, recommendations for action could be derived, which we divided into short and medium term.
One of the most important findings was the development of the business goals formulated by management: The development away from a transactional business model towards a customer-oriented and platform-oriented model and thus the establishment of a stronger brand.
However, the technical requirements were not sufficient to support this goal with data.
Our established use case approach showed that, however, a wild implementation should not be the next step. Instead, it was worked out together where the company wanted to go, why it would like to take the next steps and what this means for Babymarkt's use of data.
Results of the Spotlight audit
In addition to illustrating recommendations for action and developing business goals, we also found that the current tracking setup can be challenged, as it is not state-of-the-art. This resulted in a follow-up project with a partner agency, which followed our initial recommendations and adjusted tracking accordingly.
Step 2: Design phase 0
Implementation design phase 0
In design phase 0, we developed various use cases in workshops with people who work with data in the company. Among other things, we focused on pain points and initiatives that required a specific technology in the short and long term.
Of course, this workshop resulted in many use cases, and we prioritized 3 for initial implementation:
- What does the data model look like?
- Where is the data?
- Who is the owner of the data?
The plethora of use cases also made it possible to derive a large architecture for the next 3-5 years and a short-term architecture that the babymarkt can now address.
The results of design phase 0
The short-term as well as the large architecture can now be implemented. With this establishment, our focus is on creating a modular infrastructure so that the costs for tools remain low for as long as possible. The technologies then grow in line with the company's business requirements and capabilities. This also applies to the data model and use cases, which can evolve in an agile way.
A glimpse into the data future of babymarkt
Babymarkt's next steps are to implement an MVPs and thus a modern and scalable data infrastructure based on AWS and Snowflake. Adverity is used for data integration.
This means that all data will soon be in one place and there will be an expandable Star Schema. Real-time tracking and machine learning are also in sight.
Verantwortlich für das Projekt
Thomas Borlik and Mike Kamysz are the right contacts for this project.
Der Referenzkontakt kann auf Wunsch vermittelt werden.
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