Last month, we announced aiCube, our intelligent engine for mobile advertising. As one of the early partners of Google Ad Exchange in the APAC region, and the first DSP platform out of India, RevX has been at the forefront of the programmatic advertising. Over the years, our scalable infrastructure has helped us onboard several new ad exchanges and invest efficiently in building the optimization engine for the programmatic media buy. aiCube is a significant upgrade to RevX’s integrated technology stack that combines key platform pillars: App Intelligence, Audience Intelligence, Ad Intelligence, and Artificial Intelligence and is focused on delivering results in a brand-safe, programmatic ecosystem for top mCommerce apps across the APAC.
We are excited to introduce a new Product Release series which will be highlighting all the improvements and fresh feature roll-ups we launch, to keep you easily up-to-date on what’s new. Let's delve into our August release- ‘Bulk Edit of Strategies’.
Our new feature ‘Bulk Edit of Strategies’ allows Account Managers and Self-Serve Advertisers to update strategies for various targeting and optimizing parameters such as Bid Price, Bid Type, Frequency Cap etc. across campaigns in bulk, helping them make multiple optimizations at once along with saving considerable amount of time.
Being a data-driven marketing platform, performance has always been at the core of our vision. At RevX, we use our proprietary machine learning model to predict the right bid price for the right user to deliver the most effective ads in real-time. Our team of data scientists strive to ensure that each campaign reaches its maximum potential and ROI goals. In this blog, we will give you a sneak-peak into what goes behind building a sophisticated prediction model and the challenges that come its way.
The Auto Scaling functionality provided by AWS makes it easy to scale application clusters using spot or on demand instances - however it does not have the ability to fall back to an on-demand instance if a spot instance is not available or try getting instances in other availability zones. Another issue is that while AWS provides a spot termination notice, it does not guarantee it – so clean up actions like moving logs to a persistent store before instance terminates become tricky. This blog talks about how we implemented our own auto scaler framework to overcome these shortcomings.
Building efficient user interaction is critical for the success of any web application. Multiple interactive features, one like type-ahead, in a web application poses a greater challenge from design and operations perspective. This blog talks about how we leveraged AngularJS filters and directives to implement custom libraries for interactive web applications.
RevX is a programmatic technology platform that connects to ad exchanges via Real Time Bidding (RTB) protocol. We use sophisticated analytical models to predict the probability of desired outcomes (ad click or post-click purchase) and compute the bid price at which we can meet KPIs (margin & ROI) set by our advertisers for every ad auction.
RevX is a mobile performance technology platform that participates in close to 20B+ programmatic ad auctions on a daily basis. For every auction, the platform evaluates complex targeting rules and budget constraints across all active campaigns and finally choses a single ad for which a bid is placed.
In today’s digital world, a seamless user experience is critical to ensure effective user interaction with brands. Along with other components, the look and feel of an ad along with its load time play a key role in grabbing user attention.
A programmatic ad-tech platform like RevX generates terabytes of data on a daily basis. To effectively process and leverage this data, we use big data tools like Hadoop for reporting and analytics. Our infrastructure is hosted in Amazon AWS across multiple locations globally.
This blog talks about our learnings of building a Hadoop cluster in AWS and comparison of various options based on total cost of ownership (TCO).
RevX platform processes billions of ad requests per day and we are poised to further grow this volume as we onboard new supply partners. The cost of listening to the traffic is one of the most important factors in the economics of ad business because not all requests can be monetized.
We at RevX strive for enabling a good ROI for our advertising partners. Most of our customers measure ROI in terms of eCPA (Cost per Acquisition). RevX technology intelligently buys media on programmatic exchanges and prediction models are central to achieving the twin goals of delivering good ROI for customers and ensuring the business runs on healthy margins.
RevX processes terabytes of data on a daily basis. This imposes unique challenges in terms of volume and speed at which data can be processed. At RevX, we experimented with two data processing patterns. In this blog, we will talk about pros and cons of both patterns based on our experience of dealing with large volume of real-time data.
I have been involved with digital ad technology for the past six years and have had the privilege of both witnessing and participating in the fastest-growing and one of the most demanding technology landscape today.
Today, I give you a glimpse of this journey – about the humble beginnings of RevX technology stack and how it has evolved into a programmatic beast, with several parts working in tandem to make cross-channel performance marketing efficient and effective for our advertisers.