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.
The State of Mobile Programmatic In India report analyzes the in-app programmatic trends and metrics specific to Indian market based on the hundreds of billions of bid request processed by the RevX platform. This industry-first report will bring new insights and knowledge for brand and mobile marketers around the fast-growing mobile programmatic ecosystem.
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.
We are pleased to announce Dynamic Badges for Native Product Ads, a new distinctive feature making them better than ever. Native ads are high performing, non-obtrusive ad units which adapt itself to the look and the feel of the app where they appear. While this format greatly improves the end user experience, its prescriptive format limits marketing team’s creativity with respect to showcasing the relevant information in product ads. The “Dynamic Badge” feature helps improve the marketing message for the end users by overlaying key product attributes such as brand name, product price, discount, etc. onto the main native ad image in real-time, significantly improving the click-through rate (CTR) and conversion rate.
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.