Well into the Information Age, people are becoming increasingly aware of the large amounts of data they generate while participating in the technological landscape, and thus the massive amount of this data different companies collect. Because of this, customers are increasingly interested in getting insights into the data that their products are collecting, and product teams would be smart to start using the data to their benefit.
All businesses can employ and benefit from customer-facing metrics. And, though the most top-of-mind examples involve depicting a large amount of data for the end-user, the ultimate goal of customer-facing metrics is quality rather than quantity.
For example, Google Analytics is a platform that delivers an abundance of metrics to its users. As an analytics service used by many companies to measure customers’ interaction with websites, Google Analytics offers specific insights into many different aspects of web traffic by measuring advertising ROI and tracking Flash, video, and social networking sites and applications. All of this data is useful for business owners to take a deep dive into their web traffic to reach their goals. However, for embedding this data directly into applications, this amount of data would typically be overwhelming.
In other instances, scaling back on the number of embedded metrics makes the most sense. Take for example Netflix. The media giant changed from a star rating system to a more simplified thumbs-up/thumbs-down feature a few years ago, but the whole time the platform has only had this one, single customer-facing metric. With the new feature, Netflix runs an algorithm based on individualized up or down votes and recommends new shows and movies by showing a percentage match score based on previous preferences. This lone customer-facing metric is simple and unobtrusive yet refined and essential for helping customers find new content. And ultimately, one of Netflix’s primary goals is to encourage customers to stream more content.
Instagram is another site that is considering changing its customer-facing metrics by eliminating the “like” functionality. Currently, Instagram provides metrics on the number of posts, followers, and accounts followed for each user as well as the number of comments and likes for each individual post. Recently, the company realized that showing the number of likes on each post contributes to social competition between users, perpetuating low self-esteem for users and incentivizing unhealthy behaviors in the platform. Identifying this issue created by metrics and wishing to alter the types of usage and behaviors of the users, Instagram proves that being thoughtful about the type and amount of metrics featured on an application can create a better product experience for their users.
There is no one right way to deploy customer-facing metrics. Each business has unique needs, goals, and users that may benefit from dozens of customer-facing metrics or just one, and we can help you figure out what works best for your company and your customers.
Contact our solutions team today to learn more about how you can optimize your product with customer-facing metrics.
