CTO, JavaScipt developer, technical creative, knowledge manager.
Case:
EU-based ecommerce jewellery business BigQuey integration and machine learning.
Context:
Our customer is an e-commerce website with headquarters in Rotterdam (Netherlands) is a pioneer on a jewelry market that allows its customers to create the jewel of their dream in minutes thanks to the multitude of customization options and powerful 3D design techniques. There’s also an option to order a 3D model of the jewel before it goes to production.
Tools/approaches used:
Main complexities of the project:
Project requirements:
Project implementation:
Once we started implementation it became obvious that we won’t be able to receive product details (e.g. stones, metals, sizes, models) from the SaaS provider on frontend/backend. Which was a major blocker.
Therefore we moved forward with a workaround:
MERGING GA4 DATA WITH CRM AND OTHER DATA SOURCES
The next step was to assign particular ecommerce actions to the specific customers and information about them in the CRM. This was organized in a following way:
Our next step was to visualize the ecommerce funnel with as many details as possible:
MACHINE LEARNING IN BIGQUERY
Next, we moved to the most complex part - machine learning models In BigQuery ML.
The first task was to segment our customer base into cohorts based on the recency, frequency and monetary value of their purchases. We employed a k-means model that clearly splitted the customer base into 5 distinct segments:
This instantly allowed business owners come to multiple conclusions:
Based on this we were able to formulate multiple hypothesis that needed validation. Our final actions made us to come up with the following solutions:
Result:
Result:
CONCLUSION
We’re continuing working with this customer on many fronts: CRO, sales automation, UX/UI, SEO and other aspects of business development. We perceive this case as a pivotal point in our relations due to couple of reasons: