10 billion words that tell the future of expert networks

May 2, 2018

Matt Conger

You've heard of the $300 "tap on the shoulder", right? Hundreds of times per day, executives are getting LinkedIn messages or cold calls inviting them to make $300 (or more) by sharing their expertise in hour-long phone calls.

Such brokers are called expert networks. Bloomberg recently reported that some investors are paying up $1300 USD for a single hour of an expert's time.

I've been working around this industry my entire professional career. My first two jobs at Bain and Company and Hudson Capital Management required me to conduct about 100 interactions with expert networks. Now as CEO of Cadence Translate, we are a vendor to this industry. We've delivered about 3,000 transcripts and interpreters in just a few years. This illustrates the growth overall of the industry, which AlphaSights' co-CEO Max Cartellieri sees as 5-10x expansion in the coming years.

In recent months, I've chatted extensively with the teams at these expert networks, both C-level and entry-level about their growth initiatives. I've also spoken with some of the world's biggest buyers of this service to get their thoughts on the future of expert networks.

Expert networks are going upmarket

Expert networks are adding more value-added services: surveys, channel checks, or even hosting + summarizing the calls themselves.

In a world where they "just" provide phone calls, it is not uncommon for people at Bain or other firms to create a slide like the one above. It shows a conclusion before actually having arrived at that conclusion. Indeed, one of Bain's tenets is to be "answer-first" with its clients, and that is true of how case teams operate internally. We'd do two passes of analysis: we'd get enough information to arrive at a probable hypothesis, then start building an answer-first deck to support it. Expert networks, then, were often used for that first phase only. I see this changing.

In a big due diligence effort, an expert network client like Bain has probably carved out a single slide (or two) in advance that will be populated by what is gleaned from the expert network. But with higher value-added services, expect expert networks to eventually produce entire decks.

Expert networks know their clients well. Bain alumni have created two of the world's biggest expert networks: Third Bridge and Capvision. And a buzzy new player, NewtonX, is from two former McKinsey and BCG consultants.

1:1 > 1:N

The CEO of CB Insights Anand Sanwal wrote in a recent newsletter of how he asks his clients "Can you read 1 million words per hour?". His point was that listening to calls is tremendously inefficient, and instead, his clients should use their repository of transcripts.

A variant on this argument is playing itself out in the expert network world. Researchers and equities analysts have a research budget. Would they prefer to spend $1,000 and use 100% of their attention for a 1:1 call? Or would they pay a fraction of that for access to a knowledge base containing (in theory) the same information?

Traditional vendors like AlphaSightsGLGGuidepoint, and Third Bridge offer 1:1 calls. Some intriguing new vendors like Slingshot Insights and Tegus offer 1:many calls with access to a transcript.

Imagine if a 1:1 with Jeff Bezos could be arranged through the expert network (which is unfathomable given how he talks to investors for only six hours a year). Would you pay $1,000 for that 1:1 call or $100 to get access to a transcript from a multi-party conference call with him? What if it was $10,000 versus $10?

Everyone wants the 1:1 with Bezos, but why? Information disclosed on these calls (whether 1:1 or 1:N) must all be publicly available information, so there is no "edge" to be gained by having a 1:1 call. Unless, of course, an investor thinks they are a better interviewer and/or better able to interpret body language and tone. But that's precisely the issue. Investors love to pay for a perceived advantage, no matter how trivial or fleeting.

So based purely on price points, look for institutional investors to spend money on the 'traditional' expert networks, and only retail investors to show interest in the crowdsourced variants.

The Marty McFly Problem

Source: a Python script I wrote along with an open-source word cloud generation library and a public earnings call.

I made a word cloud! Any lawyers reading this need not fret: it is generated from a public earnings call. Even without knowing context for this call, your brain is already starting to look for patterns and words that took you by surprise. Are you as tempted as I am? I see data (numerical or text), and I'm highly tempted to do some mining and see what emerges.

There are about 5,000 calls happening per day in the expert network industry. We are used as transcribers and interpreters on a lot of calls, which gives us metadata on how many things are being discussed. If the industry has 5,000 calls per day and we apply the average words per minute spoken on these calls, you're looking at 10 billion words per year.

It shouldn't be surprising then that more and more expert networks are becoming Big Data companies. GLG announced a new CEO last month whose LinkedIn profile calls out his passion for analytics and data.

This presents an incredible temptation then to use the billions of words flowing through conference call bridges every year. They are understandably moving very cautiously into this world considering the legal and privacy implications of building a taxonomy and repository of data based on 1:1 conversations.

But just like Marty McFly in Back to the Future realized that knowledge of the future could wipe out his existence by revealing it in the present, so too do expert networks face an existential problem. They conduct so many calls with so many smart people that they may very well be able to help their clients achieve alpha (i.e., above-market returns) just by looking at the metadata in their networks.

The dark side of this is that it just takes one data scientist at one expert network to misuse this information, and the whole industry may lose years of progress. The industry took a few years to regain its footing after an insider trading case in 2012 was unknowingly facilitated by an expert network. Imagine the harm this time around if such behavior was conducted willingly by a bad agent within the network.

So my prediction, which I hope doesn't materialize, is that there will be a high-profile collapse in the industry of a player who tries to profit from their knowledge of the future.

Slide into my DMs, Bezos

Expert networks have been, and will remain, one of my favorite industries in the world. As a client, they helped me immensely with investment theses. As a vendor, they are a pleasure to serve, and they provide a breadth of challenges that my team loves to take on. And Jeff Bezos, if you're reading this, I'd love to see a screenshot of one of the first "taps on the shoulder" you've gotten from this industry.