Reflection: Learning Launch

Challenge:

How do we drive the adoption and use of self-service on digital channels like Apps and Bots to reduce  calls to our contact centre and still ensure that customer satisfaction measured by a high NPS (Net  Promoter Score) is attained?

My team and I faced that question as we looked to increase the penetration and usage of digital  channels to self-serve to reduce the number of inbound calls to the call centre.

As a team, we have been introducing new channels over the past few years and despite the growth in  these channels, we needed to increase the usage and ability of the customers to resolve their issues by  themselves without having to call or contact a live agent by introducing a chat bot.

The use of chat bots within our market was not that common and very few corporates had adopted this  as a means to serve customers. We therefore needed to do something different to get customers  engaged and to use the chat bot to resolve the issues especially for simple and repetitive queries.

The current penetration stood at 40%, we needed to get this to 60% within a period of one year. We felt  this was a high target but we knew we could do it- if we asked the right questions and got the right  solution together with our customers.

Selection:

Having reviewed the different tools, we chose to go with the Learning Launch, as the purpose was to  learn and then improve through running experiments and gathering insights and feedback from real  customers.  The learning launch gave us an opportunity to test, learn and improve on the chat bot  service so we could scale it up to drive engagement and usage with the customers.

Application:

We started the process by first developing a working prototype accessible to customers on an  application they already use to minimize any barriers to them testing the chat bot service.

As the team was already working in agile, we were able to develop this within a couple of sprints and  ensured the integrations to internal systems were working well.

For the first phase of the learning launch, we engaged a number of customers using our online platforms  and informed them we were testing the chat bot service and needed them to give us feedback and  suggestions on services and features they wanted. We ran this for a period of 3 weeks and collected the  feedback both online and within the bot.

After reviewing the feedback from the users and suggestions on what we could do to improve the  service, we spent some more time in development and worked on the quick wins we identified from the  insights and road mapped the items that were more complex and required more time to integrate.

We then took an updated prototype to the customers and observed usage of some of the new features  as well as received additional feedback and this helped firm up the preferred customer journey and  method to engage with the customers using the chat bot before the full launch with a more aggressive  Go to Market campaign.

Insight:

From the learning launch model, we learnt the need to let go of some of the things we thought would  work and was relevant to us but was not that relevant to the customer. We also got additional insights  on the importance of personalization where the customers want the bot to greet them using their own  names and to have additional features that are not necessarily linked to self-service. This insight helped  us introduce brainteasers and riddles to the bot and increased the relatability with especially the  younger users who are the majority of the customers using digital platforms.

These insights together with the others picked during the learning launch phases really helped us launch  a chat bot that stood out from the other corporates and enabled us to achieve the desired growth in  penetration.

Reviewing the suggestions and feedback continuously from the customers and acting on it is necessary  for the long-term success of any product.

Approach:

From the experience we had as a team and a better understanding of Design Thinking through  additional training, we would still use the Learning Launch tool as this enables us to test a hypothesis,  experiment and pick learnings that will create more value.

We would however refine the questions we were asking to get deeper and better insights that would  enable us develop more innovative features that will drive repeat use by the customers and higher  engagement as we meet the business objective to increase self-service usage.


Reflection : Learning Launch Challenge : How do we drive the adoption and use of self - service on digital channels like Apps and Bots to reduce calls to our contact centre and still ensure that customer satisfaction measured by a high NPS ( Net Promoter Score ) is attained ? My team and I faced that question as we looked to increase the penetration and usage of digital channels to self - serve to reduce the number of inbound calls to the call centre . As a team , we have been introducing new channels over the past few years and despite the growth in these channels , we needed to increase the usage and ability of the customers to resolve their issues by themselves without having to call or contact a live agent by introducing a chat bot . The use of chat bots within our market was not that common and very few corporates had adopted this as a means to serve customers . We therefore needed to do something different to get customers engaged and to use the chat bot to resolve the issues especially for simple and repetitive queries . The current penetration stood at 40 % , we needed to get this to 60 % within a period of one year . We felt this was a high target but we knew we could do it- if we asked the right questions and got the right solution together with our customers . Selection : Having reviewed the different tools , we chose to go with the Learning Launch , as the purpose was to learn and then improve through running experiments and gathering insights and feedback from real customers . The learning launch gave us an opportunity to test , learn and improve on the chat bot service so we could scale it up to drive engagement and usage with the customers . Application : We started the process by first developing a working prototype accessible to customers on an application they already use to minimize any barriers to them testing the chat bot service . As the team was already working in agile , we were able to develop this within a couple of sprints and ensured the integrations to internal systems were working well . For the first phase of the learning launch , we engaged a number of customers using our online platforms and informed them we were testing the chat bot service and needed them to give us feedback and suggestions on services and features they wanted . We ran this for a period of 3 weeks and collected the feedback both online and within the bot . After reviewing the feedback from the users and suggestions on what we could do to improve the service , we spent some more time in development and worked on the quick wins we identified from the insights and road mapped the items that were more complex and required more time to integrate . We then took an updated prototype to the customers and observed usage of some of the new features as well as received additional feedback and this helped firm up the preferred customer journey and method to engage with the customers using the chat bot before the full launch with a more aggressive Go to Market campaign . Insight : From the learning launch model , we learnt the need to let go of some of the things we thought would work and was relevant to us but was not that relevant to the customer . We also got additional insights on the importance of personalization where the customers want the bot to greet them using their own names and to have additional features that are not necessarily linked to self - service . This insight helped us introduce brainteasers and riddles to the bot and increased the relatability with especially the younger users who are the majority of the customers using digital platforms . These insights together with the others picked during the learning launch phases really helped us launch a chat bot that stood out from the other corporates and enabled us to achieve the desired growth in penetration . Reviewing the suggestions and feedback continuously from the customers and acting on it is necessary for the long - term success of any product . Approach : From the experience we had as a team and a better understanding of Design Thinking through additional training , we would still use the Learning Launch tool as this enables us to test a hypothesis , experiment and pick learnings that will create more value . We would however refine the questions we were asking to get deeper and better insights that would enable us develop more innovative features that will drive repeat use by the customers and higher engagement as we meet the business objective to increase self - service usage .