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TATA 1mg grows ad revenue by 700 percent with and Google Cloud

Editor’s note: We invited partners from across our retail ecosystem to share stories, best practices, and tips and tricks on how they are helping retailers transform during a time that continues to see tremendous change. This original blog post was published by Please enjoy this updated entry from our partner.

Tata’s online healthcare entity, Tata 1mg, aims to revolutionize how a consumer finds the right healthcare professional for their needs. The platform offers e-pharmacy services, diagnostics, and health content and has more than 200,000 active brands in its rapidly expanding list of suppliers, sellers and manufacturers. Several of these brands would need regular involvement from the marketplace team in order to set up and run ad campaigns. As one of the largest platforms, Tata 1mg approached to address their growing needs for an efficient Retail Media Monetisation suite to help scale up their existing monetisation efforts. 

Tata 1mg needed more data-driven insights and customizability for their monetisation efforts

Tata 1mg saw several challenges that they needed to address.

Manual effort: Tata 1mg marketplace team’s monetization process was largely manual and required heavy time and resource investment to activate advertisers, which subsequently ate into their overall ad revenues.

Non-scalable framework: Given the fast-growing number of advertisers on their marketplace – well into the hundreds of thousands – it became increasingly clear that their existing monetization framework was not scalable.

Inadequate reporting & analytics: The existing framework facilitated only simple reporting, and brands were not able to draw the deep insights they needed to make data-led decisions and refine their advertising ROIs.

Steep learning curve: Several brands lacked dedicated advertising experts who could bring the experience and skills needed to plan successful ad campaigns and optimize budgets. The involved learning curve led to increased advertiser-churn.

Lack of personalized offerings: The manual nature of Tata 1mg’s monetization framework left little room for customizability, and account managers could offer very little in terms of tailored ad-buying experiences to different types of advertisers.

All of these issues led to regular revenue leakage. Tata 1mg realized the need for a central platform that addressed the above-mentioned issues and would also be able to cater to new ad channels and the requirements thereof. Developing such a solution in house was evaluated, but was found to be expensive and would require a lot of time to build.’s AI/ML-powered solution on Google Cloud offered the automation and flexibility to support modern omnichannel advertising needs

Therefore, Tata 1mg looked to Monetize, an AI/ML-powered retail media monetisation suite on Google Cloud, to help address their needs for a cloud-based monetisation platform that offered the flexibility to support omnichannel advertising models, had automation built in to reduce manual tasks, provided detailed intelligence and analytics, and delivered quick, reliable scalability.

White labeled self-serve platform:’s retail media platform was implemented within a short 4 weeks. After thorough testing and implementation, the platform was successfully launched, and enabled sellers to run ads on a fully self-serve platform. This required zero involvement from the Tata team.

Unified omni channel buying: The team at worked closely with the platform’s core teams to activate and mobilize various advertising products through a self-serve platform, while simultaneously addressing any unique requirements they had.

Omnichannel analytics with AI-led suggestions: Sellers are now also able to generate detailed reports that provide them critical insights into campaigns, and help them make better use of their budgets – enhancing their experience and interest in advertising on the platform.

Personalized buying experiences: The tailored UX offered by’s Monetize helped Tata engage brands of all levels in technical aptitude to use the platform easily. This also allowed admins to configure what types of inventories were available to different brands or advertiser segments. makes use of Google Cloud Dataflow to facilitate computations on real-time streaming. Microservices are deployed on the Google Kubernetes Engine (GKE) platform due to the solution’s well-known ability to handle scale.

In addition, Dataproc is used by the company to run batch processing apps while Cloud Load Balancing helps manage traffic across different regions; all at scale. also uses Memorystore as a database for their ad servers in order to have very low latency, and deploys BigQuery to run analytical applications and facilitate powerful reporting. The bulk of their office applications are deployed on different VMs on Compute Engine, and the company also makes use of Cloud Storage for data storage and transfers between applications.

Learn more about available on the Google Cloud Marketplace.

About, offers a fully white labeled retail media platform which helps retailers unlock additional revenue by activating advertising real estate on their platform. With its AI/ML-powered solution, allows retailers to turn brands of all sizes into advertisers – at scale. Its self-serve platform simplifies the ad buying process, and enhances outcomes with smart automation, boosting ad retailers’ ad revenues by multiples.

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