Google Cloud Platform > Case Studies > AntVoice: Enhancing Customer Targeting with Predictive AI on Google Cloud

AntVoice: Enhancing Customer Targeting with Predictive AI on Google Cloud

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Technology Category
  • Analytics & Modeling - Predictive Analytics
  • Functional Applications - Computerized Maintenance Management Systems (CMMS)
Applicable Industries
  • Cement
  • Construction & Infrastructure
Applicable Functions
  • Maintenance
  • Sales & Marketing
Use Cases
  • Construction Management
  • Infrastructure Inspection
Services
  • Cloud Planning, Design & Implementation Services
About The Customer
AntVoice is a French startup that helps brands and merchants identify and target new clients using a mix of behavioral analysis, powerful algorithms, and advanced AI techniques. The company began as a social media application publisher in 2011 before pivoting to work on its recommendation algorithm for ads. In 2018, AntVoice went to market and now counts some of France’s biggest brands as clients. The company's proprietary algorithms predict what its clients’ customers are likely to need in the near future, providing more relevant and interesting ads for products. AntVoice's goal is to create a win-win situation for both retailers and customers.
The Challenge
AntVoice, a French startup, was faced with the challenge of improving the effectiveness of online advertising. Traditional ad selection methods, which analyze customers’ recent shopping history and target similar products, often resulted in customers seeing ads for products they’ve already bought. This not only wasted money on redundant ads but also risked tarnishing the brand's reputation. AntVoice aimed to solve this problem with its “predictive targeting” AI, which required a robust infrastructure to handle large volumes of data and perform complex computations at high speeds. However, as the company grew, it became clear that their existing infrastructure was not sufficient to support the heavy-duty requirements of their final product.
The Solution
To address these challenges, AntVoice turned to Google Cloud. Initially, the company used Compute Engine virtual machines for research and prototyping. However, as the need for a more robust solution became apparent, AntVoice evaluated various cloud providers and ultimately chose Google Cloud for its pricing and ease of use. With BigQuery, AntVoice was able to store and analyze large volumes of data. The company also migrated to Pub/Sub and Dataflow, which allowed them to ingest large streams of data without worrying about provisioning new servers or manually adding more memory. Most of the infrastructure, which was previously running on virtual machines, was moved to Google Kubernetes Engine (GKE) for better scalability. GKE also helped the company handle an increase in activity, from 200 requests per second at the start of 2018 to an average of 8,000 requests per second.
Operational Impact
  • The adoption of Google Cloud has not only allowed AntVoice to handle large volumes of data and perform complex computations at high speeds, but it has also reduced costs and time spent on maintenance. This has enabled developers to focus on creating the best possible recommendation algorithm for their clients. The transition to Google Kubernetes Engine has helped the company handle an increase in overall activity, ensuring that the infrastructure can easily accommodate the growing number of requests. Furthermore, Google Cloud's global network of data centers has simplified AntVoice's expansion to international markets, complying with local data security requirements and allowing the company to replicate its infrastructure quickly and easily across multiple locations.
Quantitative Benefit
  • Quadrupled its client base in just 18 months
  • Scales automatically to accommodate up to 8,000 requests per second with Google Kubernetes Engine
  • Reduces infrastructure costs and maintenance

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