A startup based in San Diego helps influencers and celebrities with managing their online presence. With Ruuvy, they can organize content on all social media platforms and manage relationships with their audiences.
Python, Pyramid, Angular, Google App Engine
Ruuvy is a platform that helps influencers and celebrities to manage their social media and websites effectively.
Despite high entry barriers, Ruuvy started coopering with various celebs such as Whitney Port. To stay on track, the company hired Ulam Labs to create a completely new product which could collect much more relevant information about celebrities’ website traffic. The idea was to create an attractive looking widget with customisable questions that web page visitors would answer.
The biggest challenge met was to create a solution that would manage a huge number of requests and vast web traffic of over 100,000 active visitors per month.
Ulam Labs created the widget which appeared every time a new visitor entered a celebrity website. Furthermore, as commissioned Ulam built a standard questionnaire connected to an additional analytics tool designed to help Ruuvy better understand visitors’ profiles and web traffic. What is more, celebs received much more focused information about their web visitors.
Ruuvy gained a full view of all the data with seamless queries of data stored in BigQuery’s storage. Both the real-time analytics platform and the website widget empowered Ruuvy on the global market and unlocked the full potential of data gathering from the web. Ruuvy and its customers could smoothly move to data mining and social network analysis creating a new service offered to celebs.
The platform as a service and cloud computing platform for developing and hosting web apps was chosen by Ulam Labs and was implemented to manage the solution on Google’s infrastructure. The container app engine environment made it easy to build and deploy the app that could run reliably even under a heavy load.
The Google’s Bigtable database was created to deal with the massive amount of information that Ruuvy had regularly to deal in. The database could grow to an immense size with data storage distributed across plenty of servers.
The serverless cloud data warehouse with highly scalable and cost effective benefits allowed Ruuvy to make data analysts more productive with an unmatched price performance. The SQL queries allowed the company to analyse all batch and streaming data by creating a logical data warehouse.