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Companies developing artificial intelligence (AI)-powered marketing tools typically claim that their solutions drive strategic decision-making better than software without an algorithmic component. But — as is often the case — the reality is more complicated. AI learns to make predictions from large amounts of high-quality data, and so can be hamstrung (e.g., make mistakes) if that data is not available. The complex nature of marketing stacks, which sprawl across disparate, disconnected systems, can put up logistical roadblocks to implementation.

Brew, a Tel Aviv, Israel-based strategic marketing platform, claims its approach is different from the rest in that it’s more holistic. The company says that it uses AI to automatically map marketing activities, providing “customer-specific” strategic views of a market and a given company’s position in it.

In a show of investor enthusiasm, Brew recently raised $12 million in an oversubscribed seed round led by Aleph and MizMaa with participation from Gefen Capital. With the investment, which was announced today. Brew says that the new capital allows the company to expand the platform across the North American, European, and Middle East and North Africa markets while growing Brew’s R&D and go-to-market teams.

Automating marketing activities

Maayan Levy, the CEO of Brew, founded the company in 2019 with Raviv Ventura, Ronen Idrisov and Gabriel Amram. Ventura previously cofounded Zoliro, a startup that allowed event organizers to create digital “conference bags” filled with promotions from sponsors. Amram served over six years in the Israel Defense Forces before becoming the vice president of R&D at Zoliro. As for Idrisov, he led product development and data efforts at online advertising tech companies Sizmek and Innovid.

“More companies are adopting an agile, digitally led mindset, but transformation needs to be sustainable as companies try to keep up with business, market, and customer needs in an ever- (and faster-) changing market landscape,” Levy told VentureBeat via email. “[T]he focus has [historically] been around building and optimizing the siloed effort, [but] this has now been commoditized. The market makers and category leaders will be those who make all these different aspects, from analytical to creative efforts, work in sync and complete alignment to meet the changing business priorities and create lasting commercial impact.”

The idea behind Brew is to help brands gauge the big picture of their go-to-market progress while identifying gaps and opportunities in ongoing efforts, according to Levy. He says that marketers are increasingly shifting away from focusing on “data-driven” approaches to more targeted, long-term forms of outreach. Pointing to a recent survey from Deloitte, Duke University, and the American Marketing Association, Levy asserts that most marketers feel pressure to prove impact quantitatively in the short term but qualitatively with regard to long-term strategic impact.

Levy claims that the algorithms powering Brew were trained on data from “billions” of marketing initiatives from “millions” of sources, enabling users to explore different markets, audiences, topics, and verticals to see which marketing approaches worked best in specific circumstances. Brew also lets marketers compare strategies against competitors and the broader industry, measuring aspects of campaigns including messaging and brand value.

“Brew looks at the entire World Wide Web and builds a graph containing all entities and activities in any vertical and geography,” Levy explains. “This includes proprietary entity and topic extraction algorithms … The graph also works as the training set for the rest of the models, and as a layer of verification to prevent data skews and biases. Brew has built a model that [sorts] any activity — be it news, content, campaigns, website, PR, [or] live events — into six core dimensions — target vertical, audience and geography across topic, company, and channel — creating a shared strategic language that is the basis of all marketing and sales activities and is key to exploring, ideating and measuring market progress from the strategic and unified perspective.”

Predicting marketing success with AI

Can AI predict the success of a marketing campaign? Levy claims it can, but not everyone believes so. As a recent Harvard Business Review piece points out, an AI prediction system believed to be accurate could be detrimental if it, for example, it unreliably forecasts the sales of low-volume products while reliably forecasting sales of low-margin products. AI systems can also give false positives (for instance, identifying customers who actually stay as probable defectors) or false negatives (identifying customers who subsequently leave as unlikely defectors).

Forbes contributor David Gal, who also works as a professor of marketing at the University of Illinois in Chicago, points to studies showing that AI’s ability to predict who’s likely to buy a product remains low. One recent Facebook campaign only managed to increase the likelihood that someone who saw an ad would buy the advertised product from about 1 in 10,000 to about 1.5 in 10,000. Another paper implied that the use of more sophisticated models yielded only very slight improvements over a simple model in the ability to predict people’s credit card choices– so slight that it was likely a waste of effort.

Levy acknowledges that businesses must have clear expectations — and plans — before adopting and deploying predictive software for marketing. Still, he avers that 22-employee Brew is not only is accurate in its predictions, but stands above rival products (like Alembic) in this regard. There’s certainly no shortage of potential customers, in any case, with interest in AI-powered marketing products continuing to climb. According to Bright Edge, 60% of marketers intended to use AI to develop a content marketing strategy in 2018.

“[We have] over 30 customers, all with multiple users, from chief marketing officers to individual stakeholders in sales and marketing. [Our] customers are hyper growth companies to Fortune 500 across multiple verticals and geographies, from enterprise software-as-a-service and cybersecurity, to law firms and investment banking,” Levy said. “The funding will allow us to accelerate the speed at which we bring forward the planned infrastructure developments to expand the platform’s coverage of broader business challenges, based on the core … technological infrastructure already in place.”

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