For years, we’ve seen the writing on the wall. Customer data management has been migrating away from purchased third-party data, and GDPR, Google Chrome’s cookies phase-out, and Apple’s iOS 14 update are cementing a transition to first-party data.
First-party data is an asset that companies own. It comes directly from your customers, often with permission, through their relationship with you. It could come from your website, app, an in-store visit, or a phone call with a customer service rep. It’s unadulterated and can capture the entire lifecycle of a customer’s relationship with your company.
Many companies use software solutions, like Customer Data Platforms (CDPs), to gather and organize first-party data from these disparate touch points to build unified customer profiles. These profiles have been a boon for marketing and product teams everywhere to create high impact strategies that power the personalized and customized omni-channel experiences customers have come to expect.
This all works when your customer’s interactions happen on surfaces you own directly, like websites and apps. But what happens when most of your customer’s top-of-funnel interactions happen on Twitter? Your conversions on Discord? Or when all purchases are made on-chain?
In other words, what happens when you own the customer relationship but not the customer data?
With the growth of web3 and community-centric models, companies that understand and leverage the true scope of their data will be better positioned to run effective personalization, customization, and go-to-market campaigns.
Take a look at any web3 brand, freshly minted company, or content creator and you’ll see a new trend emerging: the community model.
If you’re familiar with web3 projects, you’ve likely seen websites like this:
Twitter. Discord. Telegram. Facebook. Instagram. YouTube. Linkedin. Twitch. Reddit.
Medium. Substack. Mirror.
OpenSea. LooksRare. Element. X2Y2.
Web3 projects, along with creators and many newly formed companies, build a community before— or even in lieu of—a software product. In web2, the product was usually software delivered to a customer. In web3, the product is often content, community, relationships, and ownership delivered via software. Examples include:
Nearly all of a web3 project’s interactions with their customers happen on platforms that the project doesn’t own.
While web3 enables cross-platform engagement, it introduces challenges in customer data collection. These projects are still businesses that need to understand who their customers are to develop relationships, inform their product roadmap, and define growth strategies.
In order to get a complete view of their customer, a web3 NFT project would need to link customer touch points across every platform and standardize data inputs. This sounds simple on paper but requires grappling with multiple complex challenges.
Twitter isn’t designed for analyzing your followers, and Discord isn’t built for segmenting your members. These and similar platforms aggregate stats for your account but provide little visibility into behaviors of users.
First consider a platform like Hubspot, designed to capture and analyze user-level behaviors. If I want to use Hubspot to segment my users based on properties to send a targeted email, I can simply filter and sort accordingly.
Compare that to data from social platforms which is generally aggregated to give a summary of your account activity. Take a look at Twitter:
Sure, Twitter analytics provide a summary of account activity, but what if I wanted to see which followers engage with my project most? Or which ones have the highest reach? Or who liked a campaign-specific post?
To make this data useful to manage relationships with your followers and members, it must be disaggregated so that it can be read at the user-level complete with properties (number of followers or tags) and events (mentions, likes, re-tweets).
Conversion events like purchases & trades that take place on marketplaces on-chain add another layer of complexity to developing robust data collection.
Blockchain data is essentially a raw list of transaction-level data linked to the wallets involved. For blockchain data to be useful, it needs to first be parsed into a readable form. This involves setting up pipelines to extract transaction history from blockchain nodes, loading that history into data warehouses, transforming it into a common format, and enriching it with external data to provide context. This process must be tailored for different smart contracts to interpret transactions in a readable way.
Once you aggregate your on-platform, social, and blockchain data, you still need to find a way to link these different identifiers together to create user profiles.
Many web3 projects already ask members to connect their Twitter, Discord, and wallets by using tools like Premint, Gleam, and Google Forms to be eligible for allowlists, whitelists, and giveaways. However, after the mint, many projects leave this information in a spreadsheet where it is rarely referenced.
To run a community effectively and enable the types of personalized and customized experiences community members expect, you’ll need a solution that links this cross-platform data together to get a truly complete view of your customer. While traditional tooling like CRMs and CDPs handle on-platform data, new solutions will be required for off-platform sources.
A web3 native CRM could unify data across all touch points to create comprehensive customer profiles from these fragmented data sources.
This unified dataset can then enable more traditional CRM capabilities like relationship management and member segmentation.
These unified member profiles detailing activity across all platforms can be used to power discovery, targeted campaigns, and automated personalized experiences.
Much remains unknown about the future directions of customer data management in web3, but certain facts are coming clearly into focus.
We know that product targeting, personalization, and customization are table stakes, and doing these well requires data. Good data.
We know that community models in both web2 and web3 are the new norm, and these unfold across many different platforms. Getting organized and usable data from these platforms is hard, and linking this data is even more challenging.
The problems unearthed by this evolving landscape of cross-platform community interactions require new tools, and that's why we’re building Kazm. Stay tuned for more. 👀