The Client And The Setting
This seed-funded company uses technology to deliver online services. While they have always had a robust technology and data collection practice, they hadn’t yet invested in data science.
However, when they were going in for their Series A funding, they found that their lack of investment in data science and artificial intelligence was holding them back.
Everyone in our sector claims to be “doing A.I”. You see all the companies that are raising money – some of them don’t even have working products but they all claim to be using A.I.
Now, we have a great product, but haven’t yet used A.I. I know that our tech is good. We have robust data collection practices, and we have plenty of data.
Can you take a look and help us figure out how we can incorporate A.I in our product? We would very much appreciate a prototype.
This was a classic “data diagnosis” kind of case. My standard process here is to go on a two-fold exploration – talk to the company leadership and simultaneously “talk to the data”. The two need to be done simultaneously since they feed into each other.
After one round of conversations with the founding team, I was clear about the product that the company offered, and also the competitive landscape. It became very clear that the data that the company had been collecting had indeed been robust.
An understanding of the company’s priorities in the forthcoming years made it clear what the direction of product development would be. And then I went into the data, armed with a bunch of hypotheses on how the product could be enhanced.
This set off the classic data analysis “positive feedback loop”, as analysing the questions gave rise to more questions, and soon there was a long list of possible interventions that the company could do to in order to enhance their product using artificial intelligence.
Once again in consultation with the founding team, I shortlisted a small set of initiatives to prototype, and delivered them.
Results and Outcomes
The company’s technology team quickly put the prototypes I put out into production, and the company’s customers are now enjoying an enhanced product.
A year later, having implemented some of my recommendations and prototypes, the company won an award for “dynamic use of artificial intelligence in <sector>”.