Bing Ads is Microsoft’s online advertising platform which enables advertisers to connect with target consumers across multiple digital touch points through both brand and direct marketing messages. The objective is to enable advertisers to reach the right audience, at the right time with the right message. It also aims at enabling publishers (e.g. search engines, websites, apps) to monetize their assets while optimizing for end user experience of the publisher medium. The Bing Ads team at MSIDC, Bangalore works in the areas of Search Advertising and Display Advertising, with contributions to platform development, algorithm development, and data analytics.
Platform development: An online advertising platform requires the ability to serve a huge volume of traffic from various sources like search, content providers, and also be able to process the terabytes of data which flows in every day. This involves not only pushing the current infrastructure to its very limits, but also be able to design new systems using the cutting edge in hardware and software development. The engineers working on platform development are constantly evolving their systems, and challenging the status quo, and do this very quickly while ensuring their solutions can also stand the test of time.
Algorithm development: Online advertising provides an amazing opportunity to combine some of the most challenging areas of computer science including algorithms, machine learning, economic theory, natural language processing and information retrieval, and apply them to large scale practical problems. One of the toughest challenges which the team deals with everyday is to take ideas from cutting edge research and then transform them to scalable solutions and do this very quickly. The engineers and scientists working on these problems have a lot of experience in these domains with multiple publications in leading conferences and journals.
Data analytics: The volume of data generated in online advertising necessitates that the very advanced of data analytics are used to ensure that not only the signal-to-noise ratio is high, but also that the signals derived are useful and impactful. Additionally the platforms in place should support that this can be done quickly, so that data insights can be acted upon while its still actionable. The data analytics team works closely with both the platform and algorithm developers, to create a highly effective development cycle.