Hello readers,
As promised, we’re back with more coverage within the Solana ecosystem this week. In particular, we’re sharing our thesis for Hivemapper — a DePIN project seeking to disrupt the global mapping industry.
Topics covered:
Aggregation Theory
Intro to Hivemapper
The Problem
The Solution
Addressable Market
The Product
Progress to Date
Token Economics
Financials
Team
Investors
Community
Risks
Conclusion
Disclaimer: Views expressed are the author’s personal views and should not be taken as investment or legal advice.
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Let’s go.
Aggregation Theory
Before we dive into Hivemapper, I want to revisit the concept of Aggregation Theory —while referencing a report we shared on the subject back in February of last year.
Here’s what we wrote back then:
Aggregation theory was first proposed by Ben Thompson back in 2015. The core idea is that the value chain for any given consumer market is divided into three parts: suppliers, distributors, and consumers/users. Pre-internet, powerful business models made outsize profits in various markets by integrating two of the parts while creating a competitive advantage in delivering a vertical solution.
The internet turned this on its head by collapsing the cost of distribution — which neutralizes the advantage of pre-internet business models that could bundle supply, trust, and distribution.
With the internet, suppliers can easily become commoditized via aggregation — leaving consumers and users as the first-order priority.
Printed newspapers are a powerful example of this concept. Pre-internet, newspapers owned printing presses and delivery services that they could bundle with editorial content and advertising. They controlled supply and distribution via geographic physical constraints. Google broke this down by aggregating trusted digital content via search rankings — which enabled a more effective advertising business model. The impact on both printed and digital newspapers was very real:
Re-read that section a few times if you have to.
We think DePIN Networks could ultimately be seen as the latest expression of aggregation theory. In this case, global distribution can be aggregated on the supply side with tokens as pseudo equity creating the coordination and incentive mechanism.
Intro to Hivemapper
Hivemapper is a DePIN Network (Decentralized Physical Infrastructure Network) built on Solana that aggregates drivers globally — incentivizing them to install dashcams and “map the world.” Contributors to the network are paid in “Honey,” the native token of the Hivemapper Network.
As we’ve covered extensively, one of the most interesting things about crypto is its ability to efficiently bootstrap two-sided networks of supply and demand in a decentralized manner — something incredibly difficult to do.
A quick breakdown of how it works within Hivemapper.
Supply Side
Hivemapper’s product is street-level navigation imagery and mapping data. They produce the product by selling dashcams to people globally who drive a lot (often professionally) — and want to earn passive income in the process.
Demand Side (today)
Hivemapper sells its mapping data B2B. While it may not be top of mind, entities such as Uber (ride sharing), All-State (vehicle insurance), FedEx (shipping), and Governments (local, state, and federal) are all large consumers of mapping data. In fact, per Ariel Seidman, the CEO of Hivemapper Inc., the number three ride-sharing app paid about $30m to Google Maps last year.
Demand Side (future)
A possible future consumer of Hivemapper’s data could be autonomous cars due to forthcoming new regulations. For example, autonomous cars will need to know where they are, what the speed limit is, etc. They could leverage Hivemapper’s street-level data for this.
Furthermore, per Hivemapper’s CEO, the team may strategically move into the “places” layer of mapping in the future — where businesses and other landmarks are inventoried, searchable, and accessible via a proprietary navigation product.
The Problem
Google largely controls the mapping industry today. They’ve accomplished this by building a global network of 1) satellites/image sources, 2) street-view cars, and 3) local business owners. Google then works with thousands of 3rd party data providers to verify the images collected by its global network of contributors.
Over the years, Google has created a seemingly impenetrable network effect — often resorting to price gouging due to lack of competition.
Furthermore, Google’s map data is often stale by several years (or non-existent in some regions).
Given the size and progress that Google has already made in mapping the world, it would be nearly impossible to disrupt its monopoly due to heavy operating and capital costs.
Despite attempts from start-ups and other competitors, a top-down approach has proven to be a losing strategy.
The Solution
Instead, a bottom-up approach, with a unique coordination mechanism is required.
Remember. Pre-internet, newspapers had a unique distribution advantage via geographic network effects. It would have been almost impossible for an upstart newspaper company to supplant the NY Times. But Google disrupted the business model by aggregating content all over the web — and then delivering it to individuals via search.
Just as Google disrupted newspapers by aggregating content (supply), Hivemapper seeks to disrupt Google Maps by aggregating drivers (supply). This is accomplished via crowd-sourcing using tokens as the incentive mechanism to coordinate a global network of drivers that don’t know each other — or the Hivemapper team for that matter. By giving drivers equity-like ownership (tokens) to participate in the collective process of mapping the world, Hivemappper has solved the challenge of coordination at scale necessary to collect mapping data at cheaper costs and greater velocity than Google.
The output?
Faster global mapping & complete coverage. Hivemapper has already mapped 17% of the globe in less than 2 years — a milestone achieved 5x faster than it took Google.
Fresh, quality data. Per Hivemapper, they are able to see (and map) locations 24-100x more frequently than Google Street View.
Lower costs to produce the data. It is estimated that a Google Mapping vehicle costs $500k, excluding the cost of labor. A single Hivemapper dash cam costs $469 and Hivemapper has zero labor or marginal operating costs for its fleet.
Equity-like participation in the growth upside of the network from a global network of drivers via crowd-sourcing (incentive alignment).
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Addressable Market
Per Grand View Research, the global digital map market size was $18b in ‘22 and is projected to grow at a compound annual rate of 15.8%, reaching $58b by 2030.
Meanwhile, Markets & Markets predicts the size of the global mapping market to be $37b in just 2 years.
The Product
Hivemapper sells its “Bee” dashcam product starting at $469 (WiFi only) ($569 WiFi + Cellular LTE). It takes 15-20 minutes to set it up. The first payment of 2,000 Honey tokens is paid out after the first 2,000 KM are mapped ($300 at current token prices). Per Hivemapper, the average driver on the network maps 800 km per week.
The data is collected by Hivemapper, Inc. which interfaces with the Hivemapper DAO to license and sell the data B2B.
There are two ways to make money as a contributor to the network:
Buy a dashcam and become a driver.
Play “games” and train Hivemappers AI (similar to captcha challenges).
Interaction with Solana
Today Solana is used only for the issuance and accounting of Honey tokens and payouts to drivers (driver dashcams are tied to their Solana wallet addresses). With that said, the team has indicated it may use Solana at some point for important map data (such as the recording of boundaries).
Progress to Date
17% of the world has been mapped in about 2 years.
Over 8,000 dashcams sold (over $3.6m in revenue at an average cost of $450)
Total contributors = 113,042 (includes drivers + AI trainers)
Total regions = 4,231
A view of Hivemapper’s progress:
via Hivemapper
Token Economics
Circulating Supply: 1,093,484,210
Total Supply: 10,000,000,000 (10.9% currently circulating)
Token Holders: 77,071
Ticker: Honey (available on Coinbase)
Token Allocation:
Source: Hivemapper
The Token Model
Consumers of Hivemappers mapping data purchase “map credits” with USD. Map credits are then exchanged for mapping data. The protocol then uses the credits to purchase Honey tokens on the open market — which are then “burned” and removed from circulation.
An equal amount of Honey tokens are then re-minted by the protocol and distributed to the contributors that mapped the data sold.
The team refers to the token model as “burn-mint-equilibrium.”
In Summary:
When someone buys mapping data, the Hivemapper contributor gets paid in Honey tokens, but the customer never has to interact with the blockchain (pays in USD).
Mapping revenue is split 87% to the contributor, 10% to Hivemapper Inc., and 3% to AI Trainers.
The minimum issuance period for all Hivemapper tokens payable to contributors is 10 years — ensuring that Honey tokens are available to incentivize contributors in the long run.
Takeaways:
Hivemapper appears to have a sound burn-mint-equilibrium model that allows consumers of the mapping data to never have to interact with the blockchain while paying off-chain in USD.
The team has allocated over 4 billion Honey tokens to contributors over the next 10 years — plenty of incentives to finish mapping the world and bring some of the highest quality, fresh mapping data to the market.
Some buy pressure on the Honey token in the open market is a result of Hivemapper selling its products.
With that said, we should also acknowledge sell pressure coming from contributors — who may sell tokens to pay for gas or other operating expenses (similar to Bitcoin miners).
Token rewards are tied to map progress — elegantly aligning incentives with the network of contributors.
The token model has proven to be quite efficient to date — Hivemapper has already mapped over 17% of the globe, but has paid out only 238 million Honey tokens (6% of the 4 billion allocated to contributors).
Investor unlocks began recently and are potentially adding 166.6 million tokens to the circulating supply through November. These are big numbers relative to the circulating supply and something investors need to be mindful of in the short run — especially if the token sees significant volatility to the upside. We think investors were already selling pretty aggressively into the recent run from $.02 to .28/token from late November ‘23 into year-end.
Financials
Over the last 28 days, Hivemapper has paid out about $3.2 million to its contributors. If we assume about 10,000 drivers on the road (8k dashcams sold as of Nov. ‘23), this amounts to about $310/driver (after backing out the 3% paid to AI Trainers). Given that the new Bee Dashcam Model starts at $469, the average driver has a payback period of less than 6 weeks. For what it’s worth, we found this recent comment in the Hivemapper subreddit as evidence of a happy driver:
Hivemapper Inc. (the developer of the dashcams and protocol) takes a 10% cut of all mapping data sold. Therefore, if the amounts paid out to contributors over the last month were purely from customers of the mapping data, Hivemapper Inc. would have earned $350k in revenue. We, unfortunately, do not have the data on this but we think most of the amounts paid out to drivers were token incentives — rather than customer demand.
In addition to the mapping data revenue, Hivemapper Inc. earns revenue today from selling its dashcams. The recently announced Bee model has already pre-sold 30,000 units ($14m in revenue at the lower price point).
Team
Ariel Seidman, CEO. Previously CEO and Founder of Gigwalk, a mobile innovation company that was named one of the top 10 mobile innovations by Fast Company. Ariel also worked at Yahoo and Oracle as a product manager.
Evan Moss, CTO & Co-Founder. Previously a software engineer at Scale AI, Minerva Project, and EarthX.
Maria Karpenko, Head of Marketing. Previously held marketing roles at Nanome, Voxel, and Remedly.
Stuart Trautenberg, Head of People. Also the CEO at S.A. Traut Associates (talent agency).
In total, the Hivemapper Inc. team is comprised of 38 employees, primarily residing in the US.
Investors
The team raised an $18m series A round in April of ‘22 led by Multicoin with Craft Ventures, Solana Ventures, and Shine Capital participating.
Community
Twitter: 41k followers
LinkedIn: 4.4k followers
Reddit: 1.3k members
Ariel Seidman Twitter: 9.7k followers
In addition to the team’s distribution channels and community, Multicoin’s presence as a lead investor provides additional narrative and market awareness on Twitter and crypto podcast networks.
Risks
Execution risk (mgmt team & their ability to produce and sell the data).
Technology & platform risk (bugs, hacks, reliance on Solana, etc.)
Competition (Google, Mobileye, Tesla).
Regulatory risk.
Potential saturation of drivers, disincentivizing crowdsourcing, making it difficult to map the world and create a superior product to Google.
Token unlock risk and liquidity risk (the Honey token has low liquidity, trading just $1-$2m/day currently).
Conclusion
Hivemapper is introducing a new model for building, operating, and updating global mapping data — and it’s working. They’ve mapped 17% of the world in two years with a team of 38 employees! It took Google 5x the amount of time to achieve similar progress. Furthermore, Hivemapper can produce the data in a shockingly more cost-efficient manner (it costs an estimated $500k for every vehicle Google deploys for street-level mapping and $469 for every vehicle Hivemapper deploys).
Given the progress and potential of the protocol, we think Hivemapper has a chance to catch the DePIN narrative later in the cycle. If this were to happen, we believe it’s possible that the Honey token could make its way into the top 100 crypto projects. High risk. High reward potential.
We initiated a position in Q4 of last year and are long-term investors in the project.
Thanks for reading and please do your own research.
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Disclaimer: Individuals have unique circumstances, goals, and risk tolerances, so you should consult a certified investment professional and/or do your own diligence before making investment decisions. The author is not an investment advisor and may hold positions in the assets covered. Certified professionals can provide individualized investment advice tailored to your unique situation. This research report is for general educational purposes only, is not individualized, and as such should not be construed as investment advice. The content contained in the report is derived from both publicly available information as well as proprietary data sources. All information presented and sources are believed to be reliable as of the date first published. Any opinions expressed in the report are based on the information cited herein as of the date of the publication. Although The DeFi Report and the author believe the information presented is substantially accurate in all material respects and does not omit to state material facts necessary to make the statements herein not misleading, all information and materials in the report are provided on an “as is” and “as available” basis, without warranty or condition of any kind either expressed or implied.