Datafy: Customer Analytics as a Service Platform
Recently, I worked on a side project for a client in the e-commerce space. The business had been around for about 5 years now and no detailed understanding about its customers. For a while now, most of my side projects (data related) have been non-commercial, no direct financial gains. However, this was a lot different for me as the client was willing to pay but I didn’t know how much to charge.
From the get-go, the scope of the project was defined — “help us know how our business has been performing since inception”. The takeaways from the project planning was very clear — Business Intelligence/Business Performance Measurement. But I knew the data available was way more valuable than gleaning insights from the past.
In summary, we got the data out from a relational database and built a simple data warehouse with a flat table (apologies to the BI experts and star schema/snowflake fanatics) and created dashboards for the stakeholders using Metabase (open source visualization tool that connects multiple data sources). This is was done within a week. However, there was more!!.
Interestingly, during the project planning, the client said in passing: “I know some people do customer retargeting, but I don’t know if that’s possible with the data that we have.”. Right there, something sparked in me — “This is the aha! moment” — like Archimedes, “Eureka!!!”. I knew if I could solve this, it would change the game.
Enough of my client meeting. I did the analysis, presented my findings and advised on how the business could retarget its customers. The comment I got was “Lekan, this is good.. very good (excitement)”. Suddenly, a burst of retargeting ideas started popping up and more questions to ask the data filled the atmosphere.
Take-way: “Torture the data, it will confess anything” — Ronald Coase.
The Problem Statement
So many business, small and medium scale, have not been able to torture their data till it confesses who their customers are and how they behave. In the light of this, I remembered this quote from 1769 by Matthew Boulton writing to his partner James Watt: “It is not worth my while to manufacture [your engine] for three counties only; but I find it very well worth my while to make it for all the world.” And so I decided to convert the analysis to a self-service customer analytics platform for the whole world (the question of scale will be answered later).
How the service works is simple:
— Register your business
— Verify your account
— Upload your customer data in CSV (with headers: “user_id”, “amount”, “date”)
— Click on the model/service you want (Customer Segmentation, Customer Retention (Cohort) Analytics, Customer Scoring and Customer Lifetime Value analytics)
As of this writing, the platform is in 60% alpha phase with an MVP (Customer Segmentation) release due for 30th March, 2017.
Pricing model for platform usage will discussed in a later post. Also, should you want to be part of the development, feel free to contact me. Development is done in Python for backend and AngularJS powers the frontend.
Thank you for reading