Affinity crm4/5/2023 An individual CEO, for example, might have threads going with one or more of our investors, while also speaking to our Talent Partner, our Business Development Partner, and our lawyer on other topics. Those engagements are happening across the firm. Using Menlo as an example: Our firm has a large portfolio of companies we’ve backed and we are constantly engaging with a broader network of potential investments, strategic partners, fellow VC firms, etc. Through machine learning, Affinity can capture a complete view of a professional network and provide unique insights, uncovering how to engage with the right people, and surfacing opportunities for alliance. This data is used to create, update, and enrich every contact and company record on the platform, completely automatically. But Affinity frees its customers from data-entry drudgery and works in the background of their day-to-day, capturing and analyzing the “data exhaust” from every email, calendar invites, etc. They either blow off the chore of maintenance or assign it to junior staff who similarly don’t care. At the same time, these aren’t the type of people who want to do the manual labor required to keep a CRM up to date. For these professionals, finding a connection, understanding the strength of a relationship and the context around it means the difference between closing a deal and losing it. With their focus on relationship intelligence, Affinity has found product-market fit selling into relationship-driven industries like venture capital, private equity, real estate, legal, and more. It’s a modern take on CRM, tailor-made for professionals whose work is more nuanced than sales, the knowledge workers whose professional success relies on their ability to build and nurture their professional network. Affinity has built a “relationship intelligence” platform enhanced by automation, AI, and an intuitive Excel-based UI.
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