CM announced the planned acquisition on its website Tuesday (Dec. 14), saying Building Blocks’ combination of data science software and services allows its customers to “build more relevant and personalized interactions across their businesses.”
The past three years have seen the company’s annual recurring revenue (ARR) increase by 97% per year on average, adding up to an ARR of roughly 4 million euros ($4.5 million), thus helping CM increase its ARR and core gross margin.
Founded in 2013, Building Blocks has offices in the Netherlands and about 40 employees. Its consumer AI solutions focuses on consumer guidance, engagement and care, and serves customers including Samsung, Basic-Fit, Corendon and Sligro.
CM.com says the acquisition will be funded through a combination of cash and equity consideration but declined to offer exact terms as negotiations were ongoing. The transaction is expected to close in the first quarter of 2022.
“We have been working alongside Building Blocks on various joint customer accounts,” said Jeroen van Glabbeek, CEO of CM.com.
“As a result, we got to know the team and their AI technology very well. We are convinced that incorporating the Building Blocks’ portfolio into our mobile cloud solutions makes perfect sense and will further empower customers to turn consumers into loyal fans,” he said.
van Glabbeek said the acquisition offers CM.com a number of advantages, including the addition of high value consumer AI functionalities to its product portfolio, while helping develop the company’s recurring revenue base in keeping with its goal to move to a more Software-as-a-Service driven business model.
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As PYMNTS noted recently, the number of companies engaged in widespread AI initiatives is growing, from 65% before the pandemic to 78% last month.
“It wasn’t that they didn’t expect it, or that they didn’t believe in the technology,” Jha said. “But it was hard for them to justify a big investment. So they could do small steps, and there was a much longer period where we were doing a lot of experimentation without a lot of really big uses of AI. What happened with the pandemic was a ‘do or die’ kind of situation. Prioritization became easier.”