User-Facing Analytics in Action at LinkedIn and Uber Eats

Companies today are generating and collecting massive amounts of data. Data Analytics has been playing a crucial role in analyzing user behavior, growth potential, revenue spend, and so on, enabling employees and executives to make key business decisions. There is an increasing need to unleash this analytical capability directly to the end users to democratize decision making. This or “User-Facing Analytics” is a new frontier that will shape the products of tomorrow and push the limits of existing technology.

Some early examples of this new trend showcase the transformative experience for the users.

Customer-Facing Analytics

An example of a customer facing analytical application is UberEats Restaurant Manager which allows the restaurant owner to respond quickly if the number of inaccurate orders suddenly increases. This tool provides custom insights for each restaurant which is immensely useful for day-to-day operations.

Consumer-Facing Analytics

LinkedIn is a great example of consumer facing analytical use cases wherein members leverage personalized insights regarding their Posts to improve the content quality and social selling index.

Similarly, consumers of wearable devices can adapt their eating and sleeping patterns based on real time insights into their personal stats as well as historical trends. In general, User Facing Analytics helps the customer deeply connect with the product, thus boosting monetization opportunities for the business.

Analytics is no longer limited to the 100s or 1000s of internal company users. User-Facing Analytics demands a solution that will scale to millions of users to provide fast, real time insights. This was the primary motivation behind Apache Pinot and is currently being used by a lot of big data companies such as LinkedIn, Uber, Stripe, Walmart to power rich user-facing analytical applications. With StarTree, our mission is to enable companies of all sizes to be able to build such use cases on top of Apache Pinot effortlessly, in a cost-effective manner.

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