DeepBench provides the tools and network necessary for organizations to access the right knowledge. They provide both expert search and expert network licensing, for internal and external use.
Boston, MA
DeepBench had been quite successful at targeting smaller enterprises for their flagship expert network product, which offers consultation with experts in a given field for a fraction of the cost of traditional expert networks. However, they knew the real opportunity was in selling to larger enterprise consumers, who could agree to a much higher volume of purchases after seeing the superiority of DeepBench's product.
We were able to connect DeepBench with a consultant to help them explore new revenue channels. DeepBench also received a list of large enterprise SaaS companies and late stage venture capitalists to target as potential customers (in the VC case, using the venture funds as intermediaries in order to sell to their large enterprise portfolio companies). DeepBench likewise received intros to a group of college students working in the expert network space.

We helped DeepBench better quantify their key metrics: advisors on their platform, projects assigned to DeepBench, inbound leads, sales calls scheduled, revenue from projects, and degree of automation of their end-to-end process. These were tied to weekly goals, enabling the team to quickly figure out what was going well and what wasn't.

DeepBench was able to use this new metrics-driven approach during a rebranding and marketing effort. By looking over weekly snapshots of advertising dashboards, we were able to figure out together which platforms and copy worked the best for maximizing click-through rate. This enabled DeepBench to plan their scaling, getting estimates of the cost of both acquiring new customers and improving the depth and breadth of their expert advisors.

We arranged sit-down sessions between DeepBench and two other companies dealing with similar issues. DeepBench learned how to speed up their onboarding process for new advisors, improve and measure an operations platform shift, anticipate potential issues with their push for increased automation, better segment their push for smaller vs. larger enterprise customers, and update their website user experience.
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