This week, the Bowery Capital team hosted Somrat Niyogi, VP of Business Development at Clari, to discuss “How AI Impacts Sales.” Somrat Niyogi is the VP of Business Development at Clari, transforming the way sales teams work. Prior to this, he founded Stitch, a mobile-first sales productivity platform, which was acquired by SugarCRM in 2015, as well as Miso, a pioneer in the social television space, which was acquired by Dijit Media in 2013. He started his career in various data and technology roles at Salesforce, BMC and Merrill Lynch. Somrat received a BS in Computer Science from the University of Texas at Austin.
Clari is an AI platform that equips sales teams with analytics, allowing them to focus on the right deals and optimize management of their pipelines. The Bay Area startup has been a pioneer in the sales enablement space, having raised over $60M from investors such as Sequoia Capital and Bain Capital Ventures.
AI has transformed all parts of the enterprise, but has arguably had one of the greatest impacts on the sales function in particular. AI impacts sales as it is being used to 1) help sales teams work smarter and better by leveraging data that already exists; 2) enable automation of tasks and achieve scale; 3) drive data-driven decision making to augment intuition. The best companies in this space are the ones going beyond the technology to understand the core of the issue. Given this, the products that are focused on critical issues rather than targeting use cases that are too limited will be the most successful over time. Among these solutions, the products that have been welcomed widely by sales teams are the ones automating tedious, administrative or low value-add tasks that sales people don’t really want to do – finding emails, following up over email, logging interactions, etc – or the ones that complement a seller’s skills and enhance his/her ability to close deals. Ultimately, this is how most sales teams will be performing in the future – alongside AI technology. Hence, good sales leaders should have a deep understanding and futuristic vision of how they want their teams to operate, maximizing the revenue driving time they spend with customers versus on tedious tasks.
Despite its strengths, AI technology also lags in certain aspects. In times of transition, such software may not have sufficient data to make accurate forecasts or recommendations. In addition, its effectiveness rests upon its human counterpart and how the seller interprets or uses AI-enabled suggestions. Here, companies and sellers alike need to be aware of various ethical issues that exist around using AI to sell into customer sets.
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