Tempr has raised $5 million for its prediction and automation platform aimed at rebooting the way user acquisition is done by mobile marketers.
The Paris-based company raised the money from Adikteev, an app retargeting and cross-promotion platform company. Tempr’s vision is about shaping an automated and maximized mobile marketing industry, globally, said Cloé Dana, CEO of Tempr, in an interview with GamesBeat. Lots of the potential customers are game companies.
Tempr is a software-as-a-service company that helps mobile advertisers realize the full potential of their user acquisition operations and maximize their returns. The platform combines its AI technology with application programming interfaces (APIs), which aggregate and pull data from clients’ mobile advertising partners, to develop high-accuracy revenue predictions.
“We’re very excited about our partnership with Adikteev; we believe they will help us significantly accelerate our growth and democratize the use of our innovative technology for mobile marketers worldwide,” said Dana.
These predictions help advertisers optimize their budgets, bids, and creatives for their connected partners. They can all be pushed directly into the various marketing channels with the click of a button, eliminating manual processes.
Since its launch early this year, Tempr has focused efforts on Europe, Middle East, and Africa (EMEA) region.
The funding will enable the company to expand into North America, grow the team with experts, increase productivity in developing partner APIs, and improving the tech.
While it has only been a few months since launch, app developers have voiced their interest in Tempr’s ability to maximize their revenue and increase their budget efficiency, the company said.
“We are very excited to invest in Tempr. We have been very impressed by the achievements of the team and we share their vision of providing leading app developers with sophisticated predictive technologies,” said Xavier Mariani, CEO of Adikteev, in a statement. “With the recent changes within the mobile advertising ecosystem, it’s becoming more challenging for publishers to grow and scale UA budgets profitably.”
He added, “Tempr provides a data-driven approach to solve that issue by predicting performance across different campaigns and channels. We think that the time to market couldn’t be better and we want to support the further acceleration of their growth by providing financial resources and access to our extensive client portfolio.”
Adikteev provides services for performance-driven app marketers. It helps the world’s top-spending app publishers increase retention and drive incremental revenue. App marketers rely on Adikteev to deliver made-to-measure strategies, creatives, and algorithms. It works with companies like Twitch, Mattel, IQ option, and Vivino.
Origins
Tempr started as a mobile marketing agency with the aim of helping mobile apps makers with marketing, consulting, and other strategies.”That’s how we understood that two pain [points] that were really not addressed with the products on the market,” Dana said. “Concerning user acquisition, it was really something I wanted to dig into. I really wanted to understand our clients and to search for something that could help them in their day-to-day work, as we were dealing with pretty big mobile apps and advertisers.”
She added, “We understand that even when they spend a lot of money in advertising every month to get more users, they do not necessarily have a data science team internally that came help with optimizing budgets in real time. The second thing was that they were spending a lot of time with manual tasks.”
While there are a lot of ad automation tools for Facebook and Google, the mobile app ecosystem is closed and often requires specific application performance interfaces (APIs) and specific tools that you have to use. There isn’t enough competition for those tools that handle automation of mobile app campaigns.
“We identified those two pain [points] and understood that there was a market for a project like Tempr. Tempr is a prediction and automation technology. We connect our clients’ APIs to Tempr and connect marketing channels like Facebook, Google, Apple Search Ads, and Tiktok,” Dana said.
The company collects data from the campaigns that comes from other tracking tools like AppsFlyer or Singular. Then it puts that data into its prediction algorithms to look at the performance of each campaign and then predict what kind of revenue it will generate. Tempr runs thousands of scenarios to see what is the best use of the budget, the bidding process, the creatives for ads, on each campaign and each channel.
“So we’re able to say, ‘OK, you should, for instance, move 10% of your budget on Facebook and put it on Apple or Snapchat because it will be more efficient in the whole picture,” Dana said. “That’s the first phase of what you should do. It has an easy interface and actionable insights. The second part is to put that into action.”
Apple’s privacy push
Dana said that Apple’s emphasis on user privacy over targeted advertising, with changes to the Identifier for Advertisers (IDFA), changed the market. Now, marketers need new tools.
“The data privacy era has really changed the rules,” she said. “Before that, we had a lot of data on everything. Now predictions are mandatory because you don’t have a lot of insights from your users anymore. We have a data science team working on really evaluating, thanks to historical data, things related to outside inputs, things related to the trends that we can see and the actions of the users. We can predict their lifetime value or their return on ad spend.”
I asked if such data science is still possible post-IDFA (which went into effect last spring).
“Our technology is not user-level based at all. We didn’t want to be user-level based because we knew that the market was going toward privacy,” she said. “It’s more based on cohort and campaign levels. So we really look at the performance of the campaigns, we look at the creatives for the ads, and we tell you what to change on those without knowing the users.”
For Apple iOS campaigns, Tempr focused on a prediction model looking at conversion values.
“Before you knew exactly what the user would do at any time,” she said. “Now, with the data privacy era, you know just one value for one download. We’ve been working a lot on how to extrapolate from this value, when it was triggered, compared to the organic behaviors, and compared to the previous behaviors inside of your historical data. We extrapolate the lifetime value of a campaign, thanks to those values that we get. We’re compliant with data privacy. Everything has been built around that. And predictions are more important than ever.”
Getting traction
That’s why Tempr has been able to get traction and the company is talking to the makers of big mobile apps and games. They see Tempr as a way to increase automation and decrease their dependence on risky manual practices.
Tempr got to know Adikteev as a partner. They did trade shows together and Tempr happened to be talking to venture capitalists to raise money. Adikteev came in with the investment and it had a lot of presence in the U.S. market where Tempr is expanding.
“Their counsel will be very great,” she said.
Tempr has about 25 employees, with some based in Paris, London, and Barcelona. The company started during the pandemic and it has been working remotely, with just one office.
In the user acquisition industry and data science, Dana is a rarity as one of the only women CEOs. She said she wants to encourage more women to go into the field.
Rivals include Bidalgo, which was acquired by IronSource. Another one is Bidshake, which was acquired by Voodoo, a maker of hypercasual games. And then there is AlgoLift, which was acquired by Vungle.
“We’re really entering the market at the moment where demand is pretty high,” said Dana.
She said her firm emphasizes quick onboarding for clients and integrating with the marketing channels that companies already use. They can connect Tempr and then from day one maximize their return on ad spend, she said.
“We don’t have to wait for the algorithm to have a lot of detail as we use a lot of their historical data,” she said. “We’re not a big vendor. We’re a solution that can help. We’ve really gathered like a small team with expertise. We’re really excited to see how clients can use this solution, for both smaller and bigger companies. We make it easier for marketers to maximize their value.”