Customers

Fluent

Find out how data.ai-powered insights helped digital marketing firm Fluent keep existing clients and find new ones.

Key Results:

  • data.ai helped Fluent increase their prospect conversion rate by 14%
  • Increased efficiency: 20% time saved a week with data.ai

In the world of digital marketing it’s easy to get carried away with technology and process. But digital marketing is like any other business: it’s about results. This focus on outcomes is what has made New York based Fluent one of the most enduring companies in the space.

The firm was founded in 2010 with a mission to help clients acquire new customers through its owned and operated digital media inventory. Fluent leverages cutting-edge data science and a proprietary optimization technology so that advertisers can reach hundreds of millions of high-intent customers. 

But, as we said, that’s the method. The real measure is results. So how about this? When Credit Sesame wanted to improve take-up of its free credit score tools, Fluent’s approach delivered a 20% boost in sign-ups that added 130,000 new mobile web users.

Or consider Shavekit, a subscription service offering high-quality razors. Its concern was high cost per acquisition and a poor return on investment. Working with Fluent reduced CPA by 76% and drove a 5x improvement in return on as spend (ROAS).

Fluent achieves these impressive results by combining its in-house processes with a deep understanding of user behavior, market dynamics, and the competitive landscape. It works closely with data.ai to surface these critical metrics.

We sat down with George Eames, AVP of Strategy & Growth at Fluent to find out more.

 

When did you first start working with data.ai?

That was in 2016. We had recently broken into the mobile app business, and we were getting good results. As a smaller company back then, we tried to do a lot of our analytics on our own. But we reached a point when we realized that the manual process and lack of robust market data was slowing us down. We needed to ingest huge amounts of data, and we struggled to do that on our own. So we approached data.ai.

 

How did things change after that?

We suddenly added speed and scope to our analytics. This gave us information we could use to service existing customers in meaningful ways that yielded results. It also helped us speak to prospective clients, by identifying their existing partners we integrate with well.

Today, we use data.ai across the organization – marketing, sales, product, account management, and media.

Can you recall a specific instance where data.ai tools made a difference?

The first time was when we were preparing a quarterly review for one of our biggest clients. We needed some important insights so, rather than asking the client, we pulled high quality information from data.ai. The insights actually yielded smart opportunities for the client. They felt like we really understood their business. It led to a much closer relationship.

 

And can you share an ‘aha’ moment for you personally?

I think it was when we first started using the Cross Web/App usage tool. We had a casual gaming client, and we wanted to find look-alike customers and campaigns. In the past, this would have required educated guesswork. But with data.ai, you can launch the Cross-App/Web usage tool, enter Casual Gaming App A, and see what other apps the user is engaging with. This was huge for us. It has proved the best way to uncover new synergies and opportunities for our existing clients. 

Now that you are more familiar with data.ai services, what are the top business goals they help you to accomplish?

I would divide them into the following:

 

Prospecting

We use the Top Charts and Rank History to see who is climbing or falling in the charts. And we use Cross-App/Web Usage to search for campaigns that are resonating with our audiences. They both help us identify other apps/games that a user is most likely to engage with. 

 

Sales pitches

When a new client approaches us, they want to know we can work with their existing partners. So, we use the data.ai SDK tool to see which SDKs are embedded into their app. It means that, at the pitch, we can get ahead of those questions and show how we can integrate with all their partners.

Creative testing 

data.ai’s Creatives Gallery report lets us see what creatives our partners (and competitors) are running. This gives us inspiration for launching our own executions.

Can you name which data.ai tools best help specific departments?

For user acquisition, it’s Cross-App/Web Usage, and for the growth team, it’s Rankings and Top Charts. The Market Research team uses Cross-App/Web Usage, and Product Development accesses general info on ranks, install volume, revenue and so on.

 

Can you quantify the benefits for any particular department?

Using the data.ai tool helped us convert 14% more prospects to paying customers. Not only that, my team has increased efficiency by 20% thanks to time saved leveraging data.ai. 

 

What’s on the horizon for how you’ll use data.ai next? 

We would like to achieve an even deeper level of integration. We want to see sales using the tools for more pitches, marketing to incorporate them into its lead-gen processes, and account management use them to take our quarterly business reviews to the next level. 

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