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Vivun provides a software-as-a-service (SaaS) platform dubbed Hero that automates the management of presales processes. Today the company revealed it has garnered $35 million in additional funding via a series B round led by Menlo Ventures.

While customer relationship management (CRM) software is widely employed to manage sales processes, applications optimized for presales teams — made up of engineers who often have more insights into which deals are likely to close than other members of the sales team — are not widely deployed, Vivun cofounder and CEO Matt Darrow said.

Vivun is focused on presales processes that are especially critical in IT sales involving software and increasingly complex IT infrastructure platforms. The company counts among its customers Autodesk, Okta, Cloudera, and Dell. But industry segments like aerospace face similar presales management challenges, Darrow noted. “These issues apply to all sorts of industries,” he said.

Presales engineers tend to have a better idea of which deals are likely to close based on the attributes of a product. As that data is captured in Hero, the platform applies AI and other data science techniques. It can, for example, identify when enhancements to a product might address a technical gap that had resulted in an organization losing deals. That expert system is invoked via a natural language processing (NLP) engine Vivun developed.


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Hero is designed to enable presales teams to create their own lists to prioritize tasks based on their preferences, as opposed to relying solely on the agenda of a sales team that may not have as deep a technical understanding of a platform’s capabilities. Presales engineers can also receive personalized alerts based on those preferences.

Hero offers a scoring system for rating the likelihood a deal will close using clustering techniques that identify similar sales opportunities that have been closed successfully. Hero can also recommend strategies that have been proven to remedy risky deals or otherwise bolster sales opportunities.

While presales teams have historically been viewed as an adjunct to salespeople, who typically engage the customer first, Darrow said presales teams often have a deeper understanding of each customer’s requirements. Based on that knowledge, they may have a better appreciation for which deals are likely to close based on what they learned during engagements with other customers, Darrow said.

Those insights can be balanced against less technically oriented members of the sales team who often tend to be overly optimistic about the prospects of closing a deal, Darrow said. That doesn’t necessarily mean a deal won’t close. Sometimes salespeople have a deep enough relationship with the customer to enable them to overcome any potential technical obstacles. Nevertheless, the “biggest voice in the room” should not always be allowed to dictate the allocation of limited presales engineering resources, Darrow said.

Organizations have for decades invested billions in platforms to automate sales management processes, with mixed results. A CRM application, for example, is often employed more as a system of record for sales managers and finance executives than as a tool to enable individual salespeople to succeed. Most of those CRM platforms are not designed to maximize the investment in a sales engineering team that needs to support multiple deals before and after they close. In fact, Darrow notes that customers often trust members of sales engineering teams because of their technical acumen.

Regardless of how a deal is closed, the need to manage presale and post-sale engineering processes using a dedicated platform will only continue growing.

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