Bittensor Brief #19: LeadPoet Subnet 71

Hello everybody and welcome to yet another BitTensor Brief. Today we're going to talk about Lead Poet Subnet 71.

Lead Poet, in short, goes out and mines the internet for leads, hot leads, leads that have intent to buy for whatever product or service it is that you are trying to sell.

Every business has the same problem: How do I find the people that want to buy the thing that I make? Lead Poet basically gives you a pile of highly qualified leads.

These are the Glen Gary leads, like the Glengarry Glenn Ross leads. These are people who want to buy a house. So, if you're a real estate person, and they're expensive houses, knowing who's got money and who wants to buy that house right now is extremely valuable information that is what Lead Poet provides to any business for any purpose.

The two founders, Gavin Zens and Pranav Romesh, ran into the same problem themselves directly. They met at NASDAQ and bonded over a shared experience.

It's really easy to find names, but it's really hard to find buyers. Anyone who's ever done sales spends 90% of their time wasting their time. You're cold calling. People don't want to hear from you or are annoyed that you called them.

Then every once in a while you find that one person who's like, "Oh my god, I'm so glad you called. I'm just thinking about how am I going to find this product?" The right people out there are looking for you at the same time you're looking for them.

The salesperson's job, 90 to 99% of it, is just wasted on cold calling and dead ends. If you could somehow get rid of that 95 to 99% and just find the people who want to hear from you and would love to buy what you're selling, that is extremely valuable.

How do people prospect leads today? Well, most teams rely on legacy lead databases. You go out and buy a database from a company that provides leads, and most of the time those databases are validated only once.

They check the information, make sure they're real people, make sure they're still working at a company, and then it's sort of frozen in time. The company that sold you the leads will resell that same list hundreds of times.

The people who are on that list are getting hundreds of phone calls from all the people that are trying to sell them products. So many times these lists contained outdated roles, so people have left the company or outdated email addresses.

A lot of times there's the email address of the decision maker, but also a lot of times there's like info@comp.com, so sort of catchall domains. Those are on these lists, and they just prioritize volume over accuracy.

They'll give you a list of 10,000 names. Most people will buy 10,000 names because it sounds big, but they haven't really focused a lot on the accuracy of how good those leads are. Are they the Glengary leads for real?

Most of the time these legacy databases are not. The cost of this bad data is your reputation gets damaged as you send out emails to people who don't want to hear from you, and they mark you as spam.

You start getting classified as spam, and if this gets to be a big enough of a problem, then your sending email address gets blacklisted, and you automatically start going into spam folders. You don't want that as a salesperson; that's death.

You get declining response rates and increased domain rotation costs. It's a problem that gets worse over time the more you try to sell. It's compounding damage.

It's extremely bad if you continually are trying to sell people who don't want to hear from you.

How does Lead Poet solve these problems? Lead Poet turns open-source intelligence, including web signals and company context, into decision-ready lead recommendations.

What does that mean? Instead of just handing you a spreadsheet with 10,000 names on it, the system will score who is actively in market to buy.

The system will use AI and scrapes of X and LinkedIn and other things to try to figure out, does this person want the thing I'm selling? A lot of times people will post, "Hey, I'm looking for X, Y, and Z CRM system," or, "Does anyone have recommendations on what the best CRM system is?"

They'll actually talk about it. What Lead Poet does is its AI will go looking for these signals on all these sources like LinkedIn and X and other places.

It'll figure out why they're likely to buy and explain it to you as part of what they deliver, not just the name, but they'll explain why these people are likely to buy. It'll also validate the role of the person.

Are they still at this company? When they were trying to buy, they might have left. Is this a real company? Is the company legitimate? It'll look up the company and be like, "Oh, yeah, this is a real company," or, "No, this is a fake company or they went out of business or whatever."

It'll verify the contact methods are correct and up-to-date before delivering the lead to you. So, it's been prevetted. There's a whole layer of prevetted that is done with AI that they'll do for you.

The second thing that Lead Poet does is something they call double validation. Validation of the fact that this person is a real person and has intent is done twice.

It's done first when the lead is entered into the system. The first time the lead is discovered and put on a list, they make sure it's a legitimate lead.

Then let's say three months later, you come along and you decide you want to buy a list from Lead Poet. But you know that was 3 months ago when this list was made. That validation will be done again at buy time.

When you buy the lead, Lead Poet will cycle through all the names on that list and make sure that they are still active, that they're still looking for your product. The validation happens twice.

Before right before you get it, you can be assured that it's hot out of the oven. It's a fresh lead. It really is the Glengarry leads.

Lead Poet says they sell meetings, not just leads, allowing users to specify their ideal customer profile once and get meetings popping up on their calendar from interested buyers. That's the experience that Lead Poet sells.

Lead Poet values precision over volume. The product is built for precision. Remember I said earlier, if you're a salesperson, you spend 95% of your time wasting your time chasing dead ends.

If you buy a list of 10,000 names and 90% of that is garbage or 95% or 99% aren't really leads or they're old stale leads, I'd rather just have 500 names, but all of them are awesome.

That is what Lead Poet has done. They sift it down to a very small number of names, but these are the right names. That is what it aims for: precision over volume.

How does Lead Poet do this magic? Of course, they use **BitTensor**, which is a decentralized AI network where independent contributors compete for rewards by producing better agent models and higher quality lead data.

Rather than building it in-house and relying on a single vendor themselves and having a single set of brains and ideas, Lead Poet introduces structured external competition which improves the buying intent **inference**, lead validation, and qualification process.

All their miners are competing with each other to do what Lead Poet eventually sells to you the best. There's basically a competition always underway, fierce competition to continuously improve their product which Lead Poet then resells to people like you that want to sell stuff to the world.

This competitive structure enables faster iteration than centralized platforms because performance improves through open competition rather than internal product cycles and meetings.

The result of this is a much higher signal to noise pipeline compared to traditional lead providers.

Here's your call to action. Just like you're trying to sell something to someone else, Lead Poet is trying to sell their service to you.

Direct viewers of this video, you can book a demo to see how Lead Poet can boost your outbound sales.

Link: leadpoet.com

Link: cal.com/leadpoet/discovery

That's how you book a meeting with Lead Poet. They want your business. So if you find this interesting, you want better leads, I would suggest getting on their calendar and the links down below.

My name is Mark Jeffrey. This has been another BitTensor Brief. We'll see you all next time.