Before we look at user acquisition in web3, let us first look at how it was in traditional internet businesses. When early internet businesses started taking off around the late 90s, the user acquisition was varied. Consumer-facing websites would put out ads on leading magazines, TV, Newspapers, etc. but would also do online banner ads where the business model worked exactly like print media Ex. $10,000 for one month’s worth of exposure on the website. No guarantees on click-through, and no guarantee on conversion. Print, TV, and Banner ads were inefficient and it would cost internet retailers in the late 90’s an average of $100 and would sometimes go north of $500 to acquire a single customer. (Source: How to Acquire Customers on the Web, HBR, c. 2000).
This gave rise to affiliate marketing on the internet where strategic alliances with other websites. CDNow once upon a time surpassed Amazon.com in sales and used affiliate links on other music discovery websites to boost its sales. This method was more capital efficient than spending a whole load on ads. When we look at the marketing spends and customer share of CDNow back in 2000, this is how it looked:
Pay close attention to the footnote on the image. It says that the media sources mentioned in italics are the only measurable sources of acquiring new customers. Seems familiar? Doesn’t it look like a stark similarity with what we are seeing in Web3 today? Very few truly measurable sources of new customer acquisition. In Web3 we also have an additional layer of complexity, which is the anonymity of a new user. The users are now reduced down to a wallet address.
More about that later. When the internet moved more towards Web2, with the rise of social media there were more measurable ways to acquire new customers. Modern internet consumer companies today know exactly where their customers come from and can also profile them (Except for a few sources such as word of mouth). In the Web2 world, the algorithms on social media sites are so advanced that customer targeting is now easy. All one has to do is tell their performance marketing team to run an ad that targets users above the age of 30 who are looking for furniture in tier 2 cities in the UK, and that can be executed with relative ease with the sheer amount of data that social media companies have on users. There is no such profiling on Web3 today.
Current Acquisition Methods in Web3
In the current state of the Web3 world, the commonly used acquisition strategies include:
- Performance Marketing
- Waitlists
- Affiliate Marketing
- Token Airdrops
- Events
Performance marketing
The major chunk in the practice of performance marketing is running ad campaigns to a target audience and then measuring its effectiveness in customer acquisition. In Web2 due to lack of anonymity, it is easy to identify a user who came into the landing page and completed the customer journey all the way up to purchase/sign up. Many Web3 organizations do this today and will be able to track a lead’s journey until the landing page, but it is a monumental task to actually see if that exact lead has connected his/her wallet. This break in tracking makes it very hard to judge the actual performance of the ad campaign that has been run.
The only measurable part of the performance marketing exercise is the awareness and maybe intent of a lead to interact with the platform
Waitlists
Waitlists have been great sources of “doxxing” your initial users. Waitlists generally ask interested users for their email/Twitter/Discord IDs and deliver an invite to their platform via unique links. This again becomes problematic when the platform doesn’t know whether xyz@fmail.com is indeed wallet address 0x2328ubduiwbi45. This is again assuming that the users give you the same email that they’ve connected their social profiles with.
Affiliate Marketing
Affiliate marketing involves a small fee/revenue share with influencers or other platforms for generating leads. If a user connects his/her wallet with a code, then the affiliate party gets a small fee/ revenue share. This method is considerably easier to measure the effectiveness of this channel as a whole because you generally know the kind of audience that interacts with these influencers, and may be easier to zero down on the personas at a high level. Once again, the project will not know which particular personas finally turn into active users of the platform.
Token Airdrops
Token airdrops are definitely a novel way to solve a cold start problem when done right. Token airdrops are currently being used to incentivize active contributors to a platform. These contributors generally come in from the early community of the projects. Many projects look it the wrong way by doing token airdrops to seed an initial community. These projects most of the time fail because there is nothing sticky about token airdrops.
Another mistake that early founders and early growth teams make is that they confuse token holders and active users of the platform. Both are mostly independent of each other. Token holders are to be looked at as stakeholders in the protocol vs users who interact with the protocol. If you think about it, all of us passively use many crypto protocols. For example, we passively use Uniswap or some other while swapping tokens on Metamask whilst not holding the native token of the DEX.
Once tokens are airdropped into a particular wallet, there is no guarantee that they will turn into active users. Airdrops are a good token distribution or a rewards mechanism over a growth mechanism.
There is hardly any correlation between active users and airdrops. Stellar dedicated about $125 MM worth of tokens for airdrops, and they do airdrops on the 15th of every month. The airdrop was announced in late 2018 and below is the chart of active users
If airdrops were a sustainable user growth metric then there would’ve spikes around the 15th of every month with the number of active users/ addresses. A similar non-correlation can be seen in other projects that have pursued the airdrops approach.
Events
Crypto and Web3 as new industries have been riddled with a high volume of events running throughout the year from online meetups to in-person meetups to large events like Permissionless and EthCC. When done right a lot of business can actually be carried out at these large conferences. We’ve seen companies put up unique QR codes at the stalls they put up in the events and see how much traffic actually came in from the event itself. The growth team still faces the same problem faced in the performance marketing channel, “Is the user whose email I’ve got exactly the wallet address that is interacting at the moment?”
Community
Saving the best for the last, we’ve seen strong communities being extremely key to the growth of a project. Communities help unlock word of mouth because they are either invested in the protocol or they absolutely love the product and/or the mission statement. A community well built is a growth engine in itself. Community members generally post on behalf of the protocol and unlock word of mouth to a great extent for future growth. The success of a community cannot be measured, but if you’d like to learn more about community building check out this piece from last month: The Early Community Playbook
Roadblocks (Problems to be Solved)
What is actually stopping from Web3 growth becoming truly measurable? On a broad level, it is the following:
- Complete Anonymity
- No way to measure Network Effects
- Lack of Structured Data
Complete Anonymity
On a wallet level, there is only holding and transaction data available as of today. How much can a project know about a user if there are only two kinds of data available? You can know how rich a wallet is, what kind of protocols the wallet interacts with, and maybe some patterns of interaction. There is just not enough data on a wallet level to actually profile it. A user can have multiple wallets interacting with a single protocol too, which is why sometimes DeFi protocols can never know whether they are actually dealing with a “whale” wallet or not.
Measuring Network Effects
We have seen communities being key to the success of many protocols on web3, how does one measure the success of a community? A community is truly successful when the value derived from the community is greater than the value derived from the underlying product. Essentially, the strength of the network effects. Nobody has been successful in absolutely measuring network effects because the derived value from another individual or a group of individuals in the community cannot be measured. A good primer has been provided by the Network Effects Bible by NFX and hopefully, we all live to see community engagements be measurable in the future.
Lack of Structured Data
A lot of companies are trying to solve this on a high level such as Covalent, but at a protocol level, there is no structured data available. There has to be a very strong data team to identify user behavior based on wallets, events, and timelines. This is again a very hard thing to do because of the lack of data granularity that is available on-chain. It is hard to determine the “why” behind the user/wallet behaviour without granularity of data and this makes it all the more difficult to devise future growth and retention strategies.
Closing Words
The North Star metrics for growth managers still remain to be DAUs and MAUs. The various channels and watering pools of crypto enthusiasts can also be identified and marketed through (Twitter, Telegram, Reddit, etc.). The problem is that growth managers today can never surely know how a wallet came into the system and who the user is behind the wallet, and then plan further growth with it. There are some great growth managers in Web3 out there in the top protocols looking at product, marketing, and community as a full piece and seem to be maximizing their North Star metrics. There is surely no absolute metric-driven approach as to “why” a wallet or a user is behaving like it is on-chain and also no information on the user to understand core motivations based on personas. Having said all of this, we are quite optimistic about how internal data teams at top protocols identify user behaviours and how Decentralized Identification can come in help growth teams in Web3 do a better job than they already are!