Learning Launch

Challenge    I work for a company which provides business information via a Web platform.  Currently, almost all customers, who are information consumers, access this Web platform  (Software as a Service, SaaS) to perform queries (based on the input keyword(s)) and get  results about their industry. Those results are rendered as text data in different sections in a  Web page including facets / filters to potentially narrow the results set to more specific ones.  The challenge lies in the fact that customers are reporting that it may be cumbersome and  time-consuming to read all the sections and that it's not always straightforward to derive  knowledge from all the results. How to help customers be more efficient in digesting the  returned data?  In addition, my company provides a set of Application Programming Interfaces (APIs) to  "consume" the information elsewhere. Indeed, sometimes customers need to combine their  internal data with the ones from my company and, in such use cases, APIs are a convenient  way to achieve this goal.  My assumption is that we can solve some of raised pain points by providing pre-computed or  pre-digested information through visual dashboard in addition to text sections using our own  set of APIs along with some graphical libraries.    Selection    I decide to use the learning launch process to test my idea. Why using the learning launch?  Because, in my opinion, it is the best-suited design thinking tool to test such an idea. Indeed,  it allows to implement, quickly and at low cost (a couple of days of a developer and a Web  designer time, definitely less than a week), a Minimum Viable Product (MVP), in our case a  Web dashboard, to check whether or not displaying the information visually would be  beneficial to existing customers and, why not, attract prospects.    Application / Insight    First, to bypass my confirmation bias, I conducted a survey among our existing customer's  base (both Small and Medium Enterprises (SMEs) and large companies) who reported the  pain points mentioned above. With members of different departments, we also visited some  customers to understand their use of the current Web interface and how they derive insights  from the data returned. Observation is really the best way to learn how to improve such user  interface! The goal was to get different points of view or perspectives of the customer's  journey. We were also looking for confirming (or disconfirming) facts from customers to  validate (or not) my assumption that a dashboard would ease the process of getting insights  from data and therefore match some of the customer's needs such as take better-informed  data-driven decisions quicker. The collected data demonstrated that the two categories of  customers were looking for such kind of visual insights. This approach has been useful to look  for the truth (the customer's voice / validation). I'm now confident that it's worth testing my  assumption and not only because I'm convince that it's a good idea ;)

The adoption of the MVP has been immediate! Being able to test an idea with this learning  launch process is really invaluable. Having the customer's positive feedback in such process  was promising but not enough. It wasn't "tangible". The quick and "cheap" MVP really helped  customers envision what they would get in the official product (the one with text sections  only). It also generated feedback to improve the MVP which is the best way to really target  customer's needs.     Approach    Lessons learned from this exercise include the necessity of putting the customers at the  center of all decisions. Ideas must be validated by customers to avoid redo "mistakes" and  ensure we provide as soon as possible the best user interface, in our example, but more  broadly, the best service possible. The service that will match what customers really need and  not the one what we think customers need. Having the chance to visit customers and see  them interacting with the product is the best way to learn how to best match their  expectations. Then, being able to quickly test and iterate thanks to their feedback is a  complementary required step to success.

