In the opposite of how a pitch normally goes, this time it was Seven Seven Six partner Alexis Ohanian giving the software demo. It was a competitive deal, and his fund had submitted a term sheet to win it. That’s when Ohanian fired up Cerebro. Like its X-Men namesake, Cerebro let Ohanian search through the more than 40,000 contacts in the fund’s network for potential introductions to help the founder.
“The CEO cut me off in the demo and he said, ‘We're taking your term sheet,’” Ohanian said. “I've never had that happen before. I've also never done a demo as part of a close, but I think that's the move going forward.”
Despite investing in high-tech industries, venture capital has been a low-tech business, built on intros and handshakes more than atoms and bits. That’s changing, though, as more firms embrace software and data. Some tools are built in-house, like Seven Seven Six’s Cerebro or IVP’s "Minority Report"-inspired Early Detection System, while other resources come off the shelf.
“Investors never really used a lot of tech. The tech you were competing with in venture was coffee at the Creamery in SoMa and a notebook,” said IVP’s Jules Maltz. “That’s an area where venture as a whole really had to catch up.”
When Ray Zhou first started approaching venture capitalists seven years ago about his CRM company Affinity, he found a lot of reticence from the investor community. Venture capitalists are habitual guinea pigs, open to trying the latest and greatest note-taking app or productivity tool, but because they’d also seen so many products come and go through their course of business, Zhou sensed hesitance from venture firms actually going all-in on the time investment to try new things.
“What we were seeing back then was people were either trying to deploy these old, heavyweight CRMs or they were just going to the most simple thing possible, a spreadsheet,” Zhou said.
These days, it’s a different conversation as more firms are realizing that their spreadsheets aren’t keeping up with the times, and there’s more value in tools that can automatically scrape emails and build a contact database for them. Affinity’s now processed over 18 trillion emails and calendar invites to help investors build records of who they’ve talked to and when, Zhou said. It also paired that info with a deal tracking system that’s akin to Asana, with its venture capital clients keeping tabs on an average of 290 deals a month.
“I've personally seen the proliferation of just how massive venture capital as a field exploded over the last five years. I think it got a lot bigger than anyone's ever realized,” he said.
Some venture firms are reaching for tools geared toward the venture capital space, but investors don’t need their own specialist toolset in every category.
As a new fund, Avid Ventures built its tech stack by mixing venture-oriented tools like Affinity or PitchBook with a mix of tools its portfolio companies use. Founder Addie Lerner is a “die-hard” Zoom fan and a loyalist to Google Workspace. All the firm’s documents are managed between Dropbox, DocSend and DocuSign. She’s built recruiting pipelines in Airtable and scours LinkedIn to find people. Some of the boards she’s on even have their own Slack workspaces.
“Especially as venture firms grow, and especially as having access to data and speed and efficiency become competitive advantages, I do think that there will be more demand and budget for buying additional products,” Lerner said. “There are real firms out there, like Tribe, that have built proprietary datasets and data models and that is their edge, but I don’t think that’s how the majority of firms differentiate.”
It may not be a core differentiation, but venture firms are turning to data sources and building their own analysis layer on top of it to help them gain a competitive edge.
At IVP, that software is called the Early Detection System, or EDS. Inspired by the film “Minority Report,” each week it spits out five to 10 names of startups in red and partners will almost always reach out to them, Maltz said. To spot the “red alert companies,” as it calls them, the firm feeds in data from companies like PitchBook and some of its investments, like App Annie and enterprise software review site G2, so it can tell what companies are taking off. Part of the job of a VC now is connecting those data sources together in a way that gives a strong signal for the type of investing they like to do, Maltz said.
“Twenty years ago, that signal was a lunch with another VC and you'd ask him or her, ‘What are your best companies?’ That doesn't scale, and obviously is no longer how the industry works, so we now use technology to help us get those same signals about what's growing quickly,” Maltz said.
While IVP’s software tools are mostly used in-house, other firms like Scale Venture Partners are making it part of its selling pitch to founders.
Operating partner Dale Chang had been trying to understand the performance of Scale’s portfolio companies, both on an individual level and in aggregate to the industry. He started seven years ago building everything in Excel until it got to the point where he couldn’t open it on his laptop without it crashing.
The firm ended up hiring some engineers to build out what it now calls Scale Studio. It has a database of over 1,000 private companies so it can quickly benchmark how well a company’s performing, increasing the team’s efficiency in evaluating new investments and turning around feedback to founders much faster. There’s even a public version that’s been simplified so founders can use it even if they’re not pursuing a term sheet from Scale. (The data inputted isn’t shared with the Scale team.)
“We can very quickly assess how well the company's performing against the benchmarks and how we think that this company will perform in the future, almost going so far as to make some predictions about what the trajectory will look like,” Chang said. “We share this back out to the entrepreneurs so it really serves almost as a marketing tool for us as well.”
The venture capital industry is clearly catching up on its adoption of software, but Ohanian still wonders how many hours venture firms are really spending in their software products or whether it’s just bells and whistles. Having built Reddit and then the VC fund Initialized, he’s seen both sides of things before. When launching his new fund, Seven Seven Six, he says the mindset going in was, “We are a startup that just deploys venture capital.”
As a result, he now spends nearly his entire day working in the firm’s software Cerebro. In the notes section, everyone at the firm logs the introductions they’ve made, media interviews they’ve done and pitches they’ve listened to. It’s tracked in a timeline so people within the firm can see how everyone is spending their day. Any feedback on deal memos is given anonymously in comments so that anyone feels empowered to speak up. There’s a campaign function so the firm can help founders run large-scale reach-outs for partnerships and be able to track it in the system.
“The reason this is all valuable is because we're ultimately in a business where it behooves us to maintain the best and warmest relationships with the folks who are most supportive to the firm,” Ohanian said. “No one human should remember that, a database should. And that way, whether we're doing year-end gifts or whether we're inviting people to an event, we're prioritizing the people who are actually most beneficial to the firm.”
Tracking everything is one way that Seven Seven Six’s partners can hold each other accountable for their work in an industry that doesn’t have a lot of standards for OKRs. It’s also in service to founders. While “how can I be helpful” is now a meme in the venture industry, Cerebro allows Seven Seven Six to show founders the receipts on the value the firm is actually adding.
“What matters most — the reason we continue to win deals, the reason we get to see the best companies — is because the best founders say that they would be likely to recommend us to another great founder,” Ohanian said. “So if you work backwards from that, it becomes very obvious why you should be building software to optimize every part of that relationship.”
