Reflection :  Learning Launch

Challenge :

As part of the Innovation team of my Organisation, that primarily deals in healthcare, we were  trying to create solutions to help smokers quit. We went through the design thinking processes  and after the “What wows” stage we narrowed our solutions down to 3 possible ones, one of  which was a digital support system using AI providing personalized counselling at scale. Now  there were 2 things we wanted to check before building the entire AI which required significant  investments in terms of both time and money :

1. Understand how consumers will react to the “system” and what would be our final

outcome(directional) in terms of engagement and efficacy. We needed the answer as  close to reality as possible, in the shortest span of time possible.

2. Check for commercial viability and possible business models around it from a B2C POV.

Selection :

To get the closest answer to reality as possible to had to design an experience that was closest  to reality as well. We decided to use the Learn Launch tool along with some inspiration from  “Sprint” authored by Jack Knapp and decided to do various experiments to understand and fine  tune the experience for best possible outcome.

Application :

We launched the app, to a selected group of people handpicked based on demographic and  psychographic segments within our target set. The front end of the App of designed exactly  how it would be in the final version.

1. The only difference was that instead of an AI, we placed a “Human” at the backend to

act as the AI. The users didn’t know it.  We setup the backend using approved nurse  councilors and gave them a complete flowchart of when to initiate conversation(over  chat) based on usage and progress, the tonality of conversation and the boundaries.  Each interaction was documented to be mapped against outcomes and acted as a  repository to train the AI going forward. With regular counselling we were able to help  32% people quit smoking while for 53% it reduced to less than 20% of what they were  smoking initially .(numbers of cigs smoked in a day)

2. To check for Viability we ran a 4-5 experiments by targeting various users sets with

various business models from subscription based, pay per use, success based to even  pyramid models. We used targeted digital marketing to do this to a selected user base  again based on demographic and psychographic segments.

We ran these experiments for 60days.

Insight :

1. From first experiment we realized that effectiveness of the conversations increased

when it was more personal and people repeatedly asked the BOT(already human in this  case) to connect to a human. Hence we decided that while we use AI to have 70-% of  the conversation, we needed a Human intervention for most cases to achieve success.  Also the consistency of with whom they interacted with was crucial. It was important  that the counselor knew the case history and more importantly they slowly developed a  relationship which again became mission critical to successful outcome.  We changed  the solution design accordingly.

2. B2C didn’t come out to be a viable option at an overall level but people were ready to

pay for continued human intervention. We understood the need to pivot and look for  alternative business model to make this work in the long run.

Approach :

It was deep and scientific approach that we adopted which gave us not only enormous  qualitative data for future development but showed us instantly what worked and what didn’t  within a small timeframe with limited investment. The learning was imperative to make this  platform a success and justify and investment we required to do so.

