Our goal is to become the go-to tool that people visit to learn professional insights that aren’t easily discoverable via Google.
Overview
DeepBench began in early 2017 at MIT as a tech-enabled expert network. (Forbes)
Our core strategy has always been and continues to be:
1. To bring down the cost of supplying knowledge;
2. To drive more engagements where knowledge is exchanged; and
3. To generate more data that further enables #1
We are well on our way in fortifying this feedback loop. However, to become the go-to information source for questions that Google can’t answer, we need many more engaged professionals on our platform.
Our core product today
DeepBench’s platform today is mainly centered around paid 1 hour phone consultations. (Expert network industry overview) This is the main mode of engagement for our users.
But this type of engagement is purely transactional, it’s not enough to create a truly vibrant community of users.
The core product that DeepBench sells is knowledge. Paid phone consultations are merely the form factor with which we chose to start. But knowledge exchange can take place via many other form factors.
Future evolution of DeepBench
Every single professional needs knowledge to grow and succeed. In particular, we desire to stay up-to-date with the cutting edge — especially as it relates to our own interests.
In the years ahead, DeepBench will evolve into a media platform alongside our original expert-network model. The exact form factor of our media content is TBD — it could be newsletters, discussion groups or something else entirely.
With our data, we can map people’s professional expertise and interests. We can tailor content to those niche interests. And we can crowdsource & curate content from our users as well as partner with external media organizations.
User-generated content platforms
Traditionally, companies that monetize user generated content have been focused on a) consumers and b) ad revenue. YouTube is the prototypical example.
On the enterprise front, there aren’t many platforms focused on user generated content. Two that come to mind are PluralSight & Smartkarma.
· PluralSight is a $1bn market cap company that sells user generated tutorials to enterprises who wish to train their employees to use various new technologies.
· Smartkarma is a post-Series B company backed by Sequoia Capital that provides independent investment research to institutional investors.
Both Pluralsight & Smartkarma have cracked the code for monetizing user-generated content via enterprise subscriptions. They charge their customers a subscription fee, take a cut for themselves, and split the pie with their content creators based on proportional consumption.
Implications for DeepBench
Just as Smartkarma and PluralSight pay their content creators, so too will DeepBench will pay our users for their knowledge. We already do this today via the 1-on-1 phone call model, and in the future, we will do it at a bigger scale, using different form factors.
Given the wide variety of professionals on DeepBench’s platform today, if we can pull this off with a small niche, I see no reason why it wouldn’t work with a larger group.
And if it works, the scale at which it could work is massive. There is only one professional platform company today which operates at that scale, and that is LinkedIn.
Just as LinkedIn does today, so too will DeepBench have different tiers of membership, with different levels of access to knowledge. And of course — we will continue to empower paid 1-on-1 consultations as well.
The goal is create as many touchpoints as possible with our users so that DeepBench’s platform can intuitively understand:
1. What they know already, and
2. What they want to learn about.
And then of course, we can use that data to:
3. Enable our users to more easily find what they need, and
4. Fortify the feedback loop.
How we think about competition
Q: There are many expert networks out there, and LinkedIn already exists, what is DeepBench’s edge?
The answer is: product focus.
Unlike LinkedIn, DeepBench is purely focused on knowledge.
Unlike traditional expert networks, we are focused on empowering self-service, low-cost consumption of knowledge over the long run.
We are so focused on our platform and confident in our technology that we uniquely license our software via a SaaS model to help enterprises build their own knowledge networks.
Conclusion
We are excited by the journey ahead, but we know we can’t do it alone. We are always looking to meet with potential new hires & business partners. If this article strikes a chord — please feel free to drop us a line! inquiries@deepbench.io
Read more about our mission & cultural values here
Sincerely,
-Yishi Zuo (CEO, DeepBench)
