LiftIgniter: Creating more personalized, profitable digital experiences with machine learning

About LiftIgniter

LiftIgniter’s mission is to enable more engaging user experiences by helping customers put the best content and items in front of each individual user at each click.

Industries: Technology
Location: United States

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To improve scalability, reduce costs, and keep a focus on product development, LiftIgniter moved to Google Cloud Platform. The company has since grown 400% and processes billions of events per month.

Google Cloud Results

  • Scales to process billions of personalization events per month
  • Increases customers’ total e-commerce revenues as much as 10%, yielding millions of dollars a year in absolute value
  • Accelerates time to market for analytics products up to tenfold
  • Reclaims up to 8 FTEs for product development

Improves CTR up to 240%

If you’re making money in digital advertising or e-commerce, “lift” is what you want more of: more views, more engagement, more sales. Generating lift requires personalizing customer interactions at every digital touchpoint, from websites to mobile apps. If customers aren’t immediately engaged with content, they will go elsewhere, and are unlikely to return.

Personalization technologies have come a long way since they were first introduced. They’re more accurate and effective, helping to provide more satisfying user experiences and increase revenue for online businesses. Recent advances in technology have enabled breakthroughs in building personalization systems at scale, and companies such as LiftIgniter are pushing the boundaries. LiftIgniter’s predictive analytics improve click-through rates on websites and apps, helping some of the world’s largest e-commerce and media companies increase traffic and conversions on their websites and achieve from 20% to as much as a 100% improvement in reaching key goals.

“With Google Cloud Platform, we get mature and scalable cloud services, as well as access to cutting-edge machine learning technology that continues to rapidly improve. Google’s strong commitment to machine learning will be essential to keeping our personalization technology competitive over the long term.”

Indraneel Mukherjee, Founder & CEO, LiftIgniter

LiftIgniter CEO Indraneel Mukherjee is a former Google researcher who founded the company to pursue his vision for improved personalization using cloud computing and machine learning (ML). “Machine learning makes a huge difference in the amount of lift that personalization APIs can provide,” he says. “The challenge is doing it at scale.”

After a period of development on another cloud platform, LiftIgniter entered the Google Machine Learning Competition put on by Google Cloud, winning two of the four prizes in the contest. The company received $500,000 in free credits to Google Cloud Platform, giving LiftIgniter access to unmatched scale and speed to run its sophisticated personalization models. Compared to LiftIgniter’s previous cloud services provider, Google Cloud Platform offers favorable sustained and committed use discounts, lower networking costs, superior global load balancing, and easier management across regions.

“With Google Cloud Platform, we get mature and scalable cloud services, as well as access to cutting-edge machine learning technology that continues to rapidly improve,” says Indraneel. “Google’s strong commitment to machine learning will be essential to keeping our personalization technology competitive over the long term.”

Real-time personalization at scale

The moment a user lands on a website or mobile app that uses LiftIgniter, multiple data signals about the user are sent to the company’s algorithms running on Google Cloud Platform—without collecting any personally identifiable data. In less than 150 milliseconds, personalized recommendations are returned. During periods of heavy load, autoscaling in Google Compute Engine automatically adds virtual machines (VMs) from an instance group, allowing LiftIgniter to maintain consistent performance and high-quality user experiences. When the need for resources is lower, VMs are automatically turned off, reducing costs.

Autoscaling helps LiftIgniter keep employees focused on product development. Further efficiency gains come from using managed services such as Google Cloud Dataproc and Google Cloud Dataflow for the company’s data pipeline that processes billions of events every month.

“We prefer to use Google Cloud managed services whenever possible,” says Indraneel. “If we didn’t use them, we would need to dedicate as many as five team members to infrastructure and operations.”

“Google BigQuery has been a big win for us, allowing us to build analytics products for personalization with far greater ease and achieve up to tenfold faster time to market. It has saved us the productivity equivalent of three full-time developers, and we never have to worry about scale.”

Indraneel Mukherjee, Founder & CEO, LiftIgniter

Tenfold faster time to market

LiftIgniter also uses Google BigQuery, a fully managed data warehouse, to perform real-time analytics on streaming data, enabling smarter personalization while reducing developer and infrastructure costs. Previously, real-time analytics were a challenge, requiring a Druid cluster that was expensive, unreliable, and difficult to manage.

“Google BigQuery has been a big win for us, allowing us to build analytics products for personalization with far greater ease and up to tenfold faster time to market,” says Indraneel. “It has saved us the productivity equivalent of three full-time developers, and we never have to worry about scale.”

Supporting rapid growth

In just one year, the number of LiftIgniter employees grew nearly 400%. To keep employees connected and productive, LiftIgniter uses Google Workspace apps such as Gmail, Google Docs, Drive, Sheets, and Slides.

“It’s impossible to overstate how much value Google Workspace provides in terms of real-time collaboration among our employees,” says Adam Spector, Co-founder and Head of Business at LiftIgniter. “We get seamless and more secure collaboration with every type of business document that matters. It’s incredible.”

“We want to be on a cloud created by the best machine learning company in the world, and that company is Google.”

Adam Spector, Co-founder & Head of Business, LiftIgniter

The next frontier of ML

Using machine learning personalization at scale, LiftIgniter helps its customers build successful 21st century digital businesses. It has already helped high-profile customers achieve a 240% increase in click through rate, 105% lift in conversion, and 159% improvement in time spent on site. LiftIgniter is now enhancing its solution using Google Cloud Machine Learning APIs, such as Google Cloud Natural Language and Google Cloud Video Intelligence, to analyze the content of text and videos and introduce powerful new features quickly.

“By leveraging Google Cloud Machine Learning and artificial intelligence technologies, we will be able to stay ahead by dramatically improving time to market and performance for future products,” says Adam. “We want to be on a cloud created by the best machine learning company in the world, and that company is Google.”

Tell us your challenge. We're here to help.

Contact us

About LiftIgniter

LiftIgniter’s mission is to enable more engaging user experiences by helping customers put the best content and items in front of each individual user at each click.

Industries: Technology
Location: United States