Leveraging Data-Driven Discovery to Enhance Customer Experience

    Leveraging Data-Driven Discovery to Enhance Customer Experience

    Building intuitive solutions that will resolve the customer issues and lead the conversion issue is often the misconception most enterprise brands have. This only leads to higher failure rates in the digital adoption of products.

    Enterprise brands are under extreme pressure to develop products that will lead to high conversion rates and customer satisfaction. Today, over 91% of enterprises are actively participating in some kind of digital transformation initiatives. But the scenario is not as perfect as it seems.

    Over 70% of enterprise brands are failing in their digital transformation initiatives leading to a poor customer experience. There are many parameters involved when it comes to this enormous failure rate. However, a few things that are directly hampering the digital transformation and customer experience include not understanding the customer’s problems, their constraints and motivation.

    Having a website that echoes the poor customer experience is a significant sign that enterprise brands need to take into consideration. This raises the question of what brands can do to ensure the fundamental disconnect between their customer’s digital expectations and their actual customer experience?


    One way to address this issue by focusing on various discovery stages of digital project:

    The initial phase in the digital project, discovery, aims to develop an in-depth understanding of the users and the issues they are trying to resolve. It focuses on constraints and a solution that must be operated within as well as any technical considerations that have relevance to the end solutions.

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    By diversifying their data gathering exercises and user research methodologies, the discovery team will have a thorough understanding of who their target audience is, what issues they are facing with a particular problem, as well as what goals they expect to achieve from the particular solution.

    Why prioritize Data-driven Research?

    While teamwork cross-functionally, it is important the enterprise brands prioritize, collect and follow the data.

    Since most teams are subject to stakeholder pressure to develop specific features, they end up having high reservations due to the complexity and impact on customer’s end goals. By creating clickable wireframes of proposed features and running remote moderated user test programs, the teams can get a good idea of developing features that will help their customers provide feedback on the solution.

    Discovery Process Outcomes

    By integrating discovery processes in practice, brands have a clear understanding of a specific problem and evidence that details the impact of the particular problem and why it is of utmost importance for users.

    By combining high-level wireframes/specifications, the team will be able to develop a service blueprint that visualizes the relationship between platforms, processes and people.

    The outline also helps to ensure that enterprise brands have documented every customer touch point and how this is aligned with goals that the customers desire to achieve.

    Leveraging the Insights and Converting them into Actions

    In the last phase of discovery, the team concludes to have an understanding of what viable service they are able to build that would make it easier for their customers to solve their issues.

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    Even though the enterprise brands have a huge amount of data at their disposal, without an effective strategy and steps to process the data, their desire to provide an exceptional solution to enhance customer experience are likely to go in vain. Hence, by using data discovery power, brands can be assured that their digital transformation steps will only lead to success.