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In the enterprise, revenue analysis involves canvassing the total revenue generated by a company’s activities to identify strengths and weaknesses. Revenue analysis can reveal which products and services are selling well versus poorly in the context of historical sales, for example, and spotlight areas in which revenue can be increased with the least amount of investment.
It’s been suggested that AI could help to support revenue analysis by finding patterns in data that humans might miss. In a recent article, analysts at Boston Consulting Group (BCG) argued that AI can “improve the accuracy of forecasts” and “[enable] real-time decisions” to — among other tasks — “improve throughput, develop products, and deliver services in the most resource-optimal way.” But in a 2020 survey, BCG found that while almost 90% of executives agree that AI represents a revenue-boosting opportunity, only 18% have set out to use it for that purpose.
Oren Zamir and Raviv Turner, the cofounders of CaliberMind, argue that the low adoption of AI for revenue generation can be blamed partly on organizations’ lack of resources. It’s difficult to ingest the volume of data being thrown at revenue teams and translate it into actionable insights, they say, which is why some companies are turning to platforms like CaliberMind’s for prebuilt solutions.
CaliberMind today announced that it raised $8 million in a series A round co-led by IAG Capital Partners and Lavrock Ventures with participation from Bombora CEO Eric Matlick and Denver Angels. The company says it’ll put the funding toward growing its engineering team, product development, and go-to-market efforts across marketing, sales, and customer success.
AI-powered revenue analysis
Of course, Zamir and Turner have a horse in the race. The two cofounded Denver, Colorado-based CaliberMind in 2016 with the goal of cornering the nascent AI revenue analysis market. But they might be right in saying that some companies are struggling to apply AI to the task of analyzing revenue. According to McKinsey’s 2021 Global Survey on AI, AI’s revenue benefits have held steady or even decreased since 2020.
Prior to CaliberMind, Zamir was a principal software engineer at Dell EMC, where he leads user interface design. Turner was a mentor at Techstars and CEO at NYKB, a Manhattan-based interior design firm using graphic software.
CaliberMind integrates with different revenue-focused data sources and stiches them together, including web, ads, and customer relationship management (CRM) data. It looks across an organization’s customers and attempts to link them to actions and intent, optionally routing the analysis back into CRM systems or marketing automation platforms for campaign targeting.
“CaliberMind integrates with … key data sources and then does the hard work of stitching together all of that raw information into a coherent story about [a] business,” Westerkamp told VentureBeat via email. “CaliberMind leverages machine learning and deep analytics to help revenue operations teams gain significant insights into what activities and tactics work best. Augmented with full workflow and automation tools, CaliberMind is a central platform for them.”
CaliberMind normalizes, deduplicates, and unifies data, even going so far as to automatically convert sales leads into contacts. According to CEO Eric Westerkamp, CaliberMind can show which sales campaigns and channels are top performers for organizations, showing which people and accounts are trending in each stage of the buyer journey.
“One of the biggest challenges that enterprise … organizations face in leveraging machine learning is the ability to create accurate insights that are actionable. Marketers in particular struggle with the number of data sources and frequency of platform changes,” Westerkamp continued. “CaliberMind solves this problem by automating all of the training, setup and configuration — all of the hard data engineering work — while enabling marketers to focus on the insights and actions.”
While AI can be useful in revenue analysis, not every organization is convinced that even managed platforms like CaliberMind can deliver on their promises. This is particularly true in industries like health care, for example, where the data being analyzed is of a more sensitive nature. A Change Healthcare study found that 60% of health care organizations are concerned about whether AI for revenue lifecycle management — i.e., managing the process through which payments flow — will deliver return on investment. Deloitte reports that 56% of companies in health care are slowing the adoption of AI technologies because of the emerging risks.
The general skepticism around AI doesn’t appear to have slowed CaliberMind’s momentum. According to software-as-a-service database Lakta, CaliberMind hit a $432,000 revenue run rate in 2022 with a dozen customers. Revenue grew 200% year-over-year.
“Our customer base is largely business-to-business (B2B) technology vendors, with over 300 active users at approximately 50 customers. CaliberMind customers include name brands like NetApp, numerous companies in the Fortune 100, and many of the fastest growing technology companies like InvoiceCloud and Zelis,” Westerkamp said. “B2B marketing and sales motions are completely changing due to two major drivers. The first is that most buyers are switching to digital first — relying on digital channels for up to 90% of their information. The second is the huge change in marketing from relying on third-party data to first party data. These two drivers means that every B2B marketing organization will have to have a centralized solution to help them manage and leverage their first-party data.”
To date, 25-employee CaliberMind has raised over $14 million in venture capital.
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