To make all data sources available for reporting, all data in the customer domain were collected and transformed into a centralized environment on the Google Cloud Platform. This way, BOTS could get valuable insights from the data in their reporting tools. Crystalloids built a data warehouse to get all the data to a central place. The main view could then be created from the customer-related data, which includes payments, deposits, withdrawals, subscriptions, trading, registrations, the first installation of bots, and wallet balances.
For BI reporting and modeling, the Looker Data Platform was selected. With Looker, BOTS can build their views to get valuable insights. An advantage of Looker is that the data can be managed and defined in Looker. With Looker ML, users can do more customized data manipulation.
The solution architecture is as follows:
Crystalloids and BOTS started with multiple sessions to define a detailed and prioritized backlog. As a result, a precise estimation of work, tasks, dependencies, and deliverables, such as a solution architecture and definitions of done, was delivered.
One of the results that Crystalloids achieved is that BOTS has better insights now into their customer journey because of the comprehensive views. Next to that, all data sources now lead to one customer identity. Also, new data was fetched, which contributed to new insights. In Looker, they can build customized views to get precisely the information they need. The data warehouse was equipped, and the data was prepared for use in Looker. BOTS has a better understanding now of the customer domain metrics and dimensions. One of the bottlenecks was the onboarding process of new customers. They can now see where a customer drops out. Based on this, they can improve the customer journey and decrease the number of dropouts.
- Google Cloud dataflow
- Google Cloud storage
- Google Cloud BigQuery
- Google Cloud Functions
- Google Data Studio
- Looker data platform