Selfcare Application Learning Launch

Challenge  I work as a software development manager at a telecommunications company which is seeking  to go beyond its traditional services, such as voice calls and value-added services. To establish  this vision, the company created a new division, called Digital, aimed at creating new digital  revenue streams. This division then started a series of design thinking activities that resulted in  several promising ideas. One of these ideas, for which I was in charge, was to transform our  Selfcare mobile application into a SuperApp that would enable our users to enjoy digital services  as well. These services could range from e-governmental (such as utility bill and toll payment) to  e-tourism (such as ticket and hotel reservation) and even entertainment (such as watching live  TV channels). Our ultimate goal was to provides almost every service that the users need. In this  way, the users could use our application for most of their day to day activities, and the company  could establish new digital revenue streams it envisioned. However, around 30% of the  company’s revenue was generated through traditional services sold on the Selfcare application,  and we needed to ensure that introducing digital services will not detract current loyal users.

Selection  To overcome this challenge, we used Learning Launch tool because we had no idea how  customers would react to this huge transformation, and we needed validated insight. In other  words, we needed a way to measure the enthusiasm of our users towards new digital services,  and which services in particular they are interested in, if any. In this way, we expected to prevent  huge investments in a new application that might fail, prevent detraction of current loyal users,  and delivering an application that our users will fall in love with. This experiment had to be done  quickly and with limited budget spending.

Application  For this Learning Launch, we decided to create a separate version of our application that  included a shortlist of promising digital services in addition to all current telco related features.  We called this version SelfLove, and we planned to launch it for only 100 users selected  rigorously among our userbase based on specific criteria such as age, gender, occupation, and  history of application usage. Our goal was to select these users in a way to represent our whole  userbase. The digital services that SelfLove should delivered, were also selected carefully to  represent the majority of the categories of services we envisioned. Based on this constraint, we  selected utility bill payment, flight ticket reservation, grocery shopping, and live TV services.

In addition, all user interactions had to be measured in SelfLove to enable us to learn how users  interact with the application. For instance, we measured the average time the users spent on each  digital service, and the average amount of money they spent on it. Secondly, we planned a  feature to enable SelfLove users to send invitations to other people, so that we can measure how  likely they recommend this new experience to other users. Thirdly, we planned a capability  inside the application to enable the users to voice any concerns they have. Above all, we had to

measure the usage of our traditional services to make sure that the digital services will not detract  our current users.

To create this application as quickly as possible and within a limited budget, we partnered with  third-parties that already delivered the services we shortlisted. In this way, all we had to do was  to embed these third-party applications inside SelfLove and deliver the measurement  capabilities. As a result, it took us only 2 weeks to deliver the first version of SelfLove. An  instruction was then sent to the 100 users we selected through SMS and email in which we asked  for their engagement to create the best Selfcare application together.

Insight  The results of the learning launch were surprisingly good. Not only the majority of the selected  users participated in this initiative, but they also invited more than 7400 other people to join  SelfLove as well. This enabled us to measure the outcome in an even bigger audience. Finally,  through the measurements and users' feedback, we concluded that our users welcome  introduction of digital services into our Selfcare application in general, but, not all categories of  services are interesting to them. In addition, they would like our current services to be more  accessible in comparison with new digital services. Based on this insight, we are now building  the next version of our application.

Approach  We initially planned to run the Learning Launch for a period of one month. However, given the  positive feedback we received, we decided to continue this experiment for over 2 months.  Although this enabled us to gain more insight on our users' behavior, the result of our  measurements did not change drastically compared to the first month. As a result, we wasted  over 2 month that could be spent on delivering the real product which could be used by the  whole userbase. Next time, we will definitely stick to a short duration for our Learning Launch.


Selfcare Application Learning Launch Challenge I work as a software development manager at a telecommunications company which is seeking to go beyond its traditional services , such as voice calls and value - added services . To establish this vision , the company created a new division , called Digital , aimed at creating new digital revenue streams . This division then started a series of design thinking activities that resulted in several promising ideas . One of these ideas , for which I was in charge , was to transform our Selfcare mobile application into a SuperApp that would enable our users to enjoy digital services as well . These services could range from e - governmental ( such as utility bill and toll payment ) to e - tourism ( such as ticket and hotel reservation ) and even entertainment ( such as watching live TV channels ) . Our ultimate goal was to provides almost every service that the users need . In this way , the users could use our application for most of their day to day activities , and the company could establish new digital revenue streams it envisioned . However , around 30 % of the company ’s revenue was generated through traditional services sold on the Selfcare application , and we needed to ensure that introducing digital services will not detract current loyal users . Selection To overcome this challenge , we used Learning Launch tool because we had no idea how customers would react to this huge transformation , and we needed validated insight . In other words , we needed a way to measure the enthusiasm of our users towards new digital services , and which services in particular they are interested in , if any . In this way , we expected to prevent huge investments in a new application that might fail , prevent detraction of current loyal users , and delivering an application that our users will fall in love with . This experiment had to be done quickly and with limited budget spending . Application For this Learning Launch , we decided to create a separate version of our application that included a shortlist of promising digital services in addition to all current telco related features . We called this version SelfLove , and we planned to launch it for only 100 users selected rigorously among our userbase based on specific criteria such as age , gender , occupation , and history of application usage . Our goal was to select these users in a way to represent our whole userbase . The digital services that SelfLove should delivered , were also selected carefully to represent the majority of the categories of services we envisioned . Based on this constraint , we selected utility bill payment , flight ticket reservation , grocery shopping , and live TV services . In addition , all user interactions had to be measured in SelfLove to enable us to learn how users interact with the application . For instance , we measured the average time the users spent on each digital service , and the average amount of money they spent on it . Secondly , we planned a feature to enable SelfLove users to send invitations to other people , so that we can measure how likely they recommend this new experience to other users . Thirdly , we planned a capability inside the application to enable the users to voice any concerns they have . Above all , we had to measure the usage of our traditional services to make sure that the digital services will not detract our current users . To create this application as quickly as possible and within a limited budget , we partnered with third - parties that already delivered the services we shortlisted . In this way , all we had to do was to embed these third - party applications inside SelfLove and deliver the measurement capabilities . As a result , it took us only 2 weeks to deliver the first version of SelfLove . An instruction was then sent to the 100 users we selected through SMS and email in which we asked for their engagement to create the best Selfcare application together . Insight The results of the learning launch were surprisingly good . Not only the majority of the selected users participated in this initiative , but they also invited more than 7400 other people to join SelfLove as well . This enabled us to measure the outcome in an even bigger audience . Finally , through the measurements and users ' feedback , we concluded that our users welcome introduction of digital services into our Selfcare application in general , but , not all categories of services are interesting to them . In addition , they would like our current services to be more accessible in comparison with new digital services . Based on this insight , we are now building the next version of our application . Approach We initially planned to run the Learning Launch for a period of one month . However , given the positive feedback we received , we decided to continue this experiment for over 2 months . Although this enabled us to gain more insight on our users ' behavior , the result of our measurements did not change drastically compared to the first month . As a result , we wasted over 2 month that could be spent on delivering the real product which could be used by the whole userbase . Next time , we will definitely stick to a short duration for our Learning Launch .