Learning Launch and Virtual Agent for University Campus – Experiment

Among the Design thinking approach,  “Learning Launch:  is a quick and  inexpensive Experiment with Market. It is about testing the key customer  segment and checking our assumption and a hypothesis. The idea is to learn by  testing. At the beginning of the experiment, we decide what must be true for this  to be a Good Idea, and at the end of the experiment we should determine  whether our key assumptions are true or not true.

In our experiment, we thought of testing a Virtual Agent - a computer application/  Robot would provide counselling to the Students for the first day of Joining. This  application will work on Natural Language Processing and will have answer for  around 50 FAQ’s commonly expected from the students who joins the university  on the first day. We selected Learning Launch as a tool to experiment this project,  as it is cost effective and it directly tests customer perception and provides the  results quickly.

If more than 7 students (from the day’s average of 150 joiners) speak to this  virtual agent for their doubts clarifications, i.e 5% of the total population and  without again going to Human counselor, it is considered as success and this  Project can be taken up in a big way and can be implemented for other campuses  as well. If every person, who talk to this Virtual Agent, again approaching the  human counsellor, it considered to be not suitable. Either more sophisticated  language processing is required, or more data base need to be added, or people  mind set need to be changed to use more and more virtual agents.

On the day of Opening, learning launch was tested, we have selected 3  volunteers, just to explain to the students about what services are offered  through this virtual agent. They have covered almost 100% population and  provided them with the opportunity to talk to the Virtual Agent.  There were 12  students approached this virtual agents and 5 of them could not get their answers  due to their spoken accent, the same question was answered by the virtual agent  when a volunteer repeated it. So by and large, the mission was success, but one  of our initial assumption was true, that is this is an useful tool, but more technical  upgradation ( more semantic, context based understanding is required for the  robot/virtual machine ) but people are excited to talk to a virtual agent and  patient enough to experiment.

So the key assumption of improvement required in the language got proved with  the data and it has been taken for further development for large scale and more  fine tuned application development.

