Adverteering; voluntarily giving an advertiser access to your data to receive quality, timely ads.

Two Main Problems

  • An increase in data accumulation without permission from the individual.
  • Simultaneous rise in compliance enforcement from government bodies.

Both trends lead to increased data management difficulty for companies and individuals, increased abuse of the individual’s data property rights, and most importantly, distrust of marketing messages due to their roots in data being mined from the individual without their permission.


Become an adverteer.

  • Reduced data management
  • Reduced abuse of data property rights
  • Increased trust of advertisers (data users)


How have we gotten to this point? Demographic data used for advertising is nothing new. In the first phase of advertising’s life, there were the traditional mediums; commercials, newspapers, magazines, etc… These mediums gave us limited knowledge about the utility of the message. However, you couldn’t get an accurate gauge of how many people saw the ad. This led to crude and exaggerated assumptions about the effectiveness of these types of ad campaigns.

In the second phase, there were new mediums. Mediums included search engines, websites, videos, emails, etc… This was termed, digital marketing. What digital marketing gave us was the ability to gain an ever-increasing understanding of the customer using digital tracking methods. Tracking data surrounding customer acquisition costs, digital marketing became a better way to gauge a medium’s return on investment. However, these numbers have been average predictions in nature which still lacks substantial intent information about the customers’ willingness to buy. This means that decisions are made using a better guess than traditional marketing, but not the best guess.

We’re entering the third phase. In this phase, there are two converging yet diverging forces (alluded to already). Simultaneous growing customer data abuse and increasing government regulation to combat the abuse. While the gap is also increasing in between them. Meaning, there are always new exploitations of a customer’s data.

The third phase marks the transition from a digital world into a virtual one. Or, as some have referred to it, Web 3.0 (1). In the virtual world, property rights can now be enforced using encryption technology. Compare this to a digital world which, in my definition, is one where paper has an equivalent medium like a webpage.

In the virtual world, you can own things. You can own a virtual pair of rare Air Jordans, for example. If you can own things, you are also, therefore, an owner of yourself. And, yourself includes your data.

The limitations will be what we can define as individual property rights, our data, versus the public’s or natural world’s data.

My prediction is that we will figure this out as our sophisticated understanding of individual rights become more refined and in line with complex data capture methods in the physical and digital world.

The mediums of virtual advertising might be (and, have already started to be to some degree) AR billboards, VR game sponsorships, influencers, the clothes you buy virtually (i.e. Fortnite (2)), etc…The limitations for the third phase are still being understood. In the next few sections, I will describe the best way to marry data and advertising in the third phase.

Advertisers’ Dilemma

Let’s return to the first and second phases to describe the current advertisers’ dilemma in better detail. Remember when the mack-daddy of all commercials were during Super Bowl? As a marketer, we thought this was because millions of viewers saw the ad and they became pop culture (in some cases). Therefore, to the marketers, this was irrefutable evidence of great marketing. Even though the number of people who saw the ad was in the 7 figures or more, the metrics, by today’s standards, not be considered “data-driven”. Data-driven is a term from the second phase and means that marketers rely more heavily on metrics to determine the cost per acquisition of the customer.

To clarify, first phase marketers would point to the correlation of people viewing the ad and people buying the product. I.e., more sales during a given period of time. Second phase marketers would give you an exact number of people who saw the ad then purchased the number at an average cost per acquisition.

In case it isn’t self-explanatory, the reason data-driven marketing became popular was that it was also shorthand for less expensive. Data-driven marketers made the assumption accurate customer profiles (I will describe these in a second) meant better prediction of return on investment. Even though this assumption is mostly true, the data about customers could be more accurate. The same data used to bring down the costs are now targets of regulation which make it harder to comply. In other words, not cheap anymore.

What is a customer profile? It is a collection of data about your customer base averaged and forecasted as 3 to 4 ‘personas’. These personas allow you to form messaging to that group of people. The idea of a customer profile presents a problem, though. That is, how does a company acquire this data? You guessed it, there’s not just one method. White, grey, and black hat methods all apply here. Hence, the initial discussion about the competing forces; data accumulation and regulation.

Negative Feelings Of Distrust

Do you like Mark Zuckerberg? Do you think Facebook handled your data correctly in 2016?

Now, ask yourself, do you trust any company with your data now? Have you ever clicked “Accept” on terms of conditions that you haven’t read?

These are strictly rhetorical questions. The purpose of asking them is for one reason. To make you realize you are growing tired of these advertisements. And more specifically these shady tactics of mining your data to build your customer profile.

This fatigue makes you question everything. An Instagram story makes you wonder if your phone’s mic is recording you, for example. You might wonder “How in the world did they know you were craving pasta for dinner?” Then realizing, “Wait, didn’t I just text that to my partner?”

A Better World: The Adverteer

The cure for this fatigue is in its infancy. However, there is one thing we do know.

When you volunteer your data you feel better about allowing an advertiser to use it.

The current attempts don’t count, however. At least, they don’t count as being up to my standards of being considered voluntary data collection.

Examples include cookie opt-ins on websites, privacy agreements where you click “accept” without reading, or filling out a form on a website, only to have that data sent to a data broker.

The best solution is a volunteer portal for individuals to become their own data brokers. Imagine in your iPhone settings, you scroll to your data profile and tick the off switch for your most recently shared customer profile. Maybe you set this up when you bought a puppy so you could receive quality, timely introductions to potential products for your puppy. You answered a few questions like, “Will you need organic dog food?”, “Will you need a leash?”, or maybe, “Do you need a dog bed?”. Turning off your data stream seems like magic, but it’s not.

Using encryption technology, you can hold the keys to your data and customer profile. Once you turn off that stream of data, it will be removed from the network. How? this technology checks to see if the keys are valid. If they aren’t, the data stream is removed from the network automatically.

Why Advertisers’ Want This Adverteer Network

Let’s return to the reason why this is a profitable network for advertisers. Remember earlier we mentioned how customer profiles are only a good guess of who might become a customer? It is because they do not provide a guarantee that someone is looking for a particular product or service within a given timeframe.

Compare that to someone who voluntarily submits their data to receive the best ads for products or services they are interested in buying. Which includes a timeframe they want to buy this product or service. If you’re an advertiser, would you pay to send dog bed ads to someone who already bought one? Probably not. Your money is better spent somewhere else.

What about incentives for individuals? There will be an auction market like a lot of ad networks. The difference, in my proposition, is the network is a direct-to-consumer marketplace. The ad broker is a simple automated blockchain protocol that sorts prioritizes price auction data and a medium to deliver the messages to the customer. Since the hypothetical ROI is pretty high for these types of customers, companies will be excited to dish out enough cash to entice customers to buy. Small fees accrue to the broker as a percentage of the engagement cost and everybody wins.

That’s right, this solution pays the customer more than the network. Remember that feeling of distrust? That is quickly turned on its head. The customer controls their data and is compensated for their property (customer profile). The company gets access to the highest intent signals on the market which equates to incredible ROI. The broker receives enough to keep the cogs turning.

Simple Sample Model

Dozens of advertisers are willing to spend $500.

The auction tops out at $20 for the next inventory medium rotation.

The top three advertisers spend $20, $19, and $18 to be introduced to the customer.

The customer has just told the network, “I am looking to buy X in the next X days”. Say it took 11 days for the customer to purchase a product. The costs of the 1st advertiser is $20 x 11 (days) = $220

The intent signal is matched to the auction network and the customer gets exposure to the advertiser’s message.

  • Advertiser Cost: $220
  • Customer Paid: 85% = $187
  • Network Receives: 15% = 33


Problem: White-hat data management by advertisers is increasingly expensive and difficult.
Solution: Advertisers don’t need to store data.

Problem: Regulatory complexity causing expensive compliance by the networks.
Solution: Individuals own data and control it. The network does not see data.

Problem: Distrust of advertiser networks.
Solution: Compensation of voluntary data access to ad networks feels good and improves trust with individuals. Individuals’ data are recognized as property by law while the incentives repulse creeping data mining.

Problem: Increasing expensive ad inventory on digital channels
Solution: DTC marketplace ensures quick easy communication. Eliminated compliance costs previously levied on the network.

There were quite a few assumptions made to come up with this solution to an increasingly difficult problem. It comes after managing ads and data professionally in my career for 12 years. My interests have also been in technology that gives individuals more control.

There were implications and questions not addressed. Such as, what if someone wants to set up unlimited time-frame data streams and never purchases a product? Meaning, no return on investment for the company. A solution might be an anonymous review system that describes the customer as only having very low engagement or purchasing fewer products than others. What I am demonstrating is that there should be continually addressed issues with incentives the right incentives. This adds flexibility and anti-fragility to the network.

I’d like to close by asking you to think seriously about the following. What data in your life do you want to control? How much is it worth to you? And, how would you solve a problem like this?


(1) I thought Naval did a great job summarizing Web 3 in this podcast –

(2) A store to buy virtual promotional clothing for Fortnite –