Lead Scoring for B2B Crypto
Key takeaways
Score accounts on three axes: fit, engagement, and risk. The buyer is an account (a team, a DAO, or a fund), not a single wallet.
Keep the three axes separate. Do not blend them into one number too early.
Use three data sources: the CRM (firmographics, meetings), web and product engagement (pages, connects, and transactions), and onchain data (holdings, protocols, and labels).
Build each signal as a saved segment or a CRM field, then add up points per account in your CRM or warehouse.
Validate the model against last quarter's won and lost deals before sales relies on it.
Lead scoring for B2B crypto ranks accounts (protocol teams, DAOs, funds, and companies) on fit, engagement, and risk, so sales works the best ones first. Fit asks if the account looks like your best customers. Engagement asks if it is acting now. Risk asks if you should trust the data or the account. The score combines CRM data, web and product engagement, and onchain signals from the account's wallets.
What is lead scoring for B2B crypto?
Lead scoring for B2B crypto is a points system that ranks accounts and contacts for a sales team. It fits companies that sell to other crypto organizations, such as RPC providers, custody, data platforms, and protocols that sell integrations. Each signal adds or removes points, and the total sets the order in which sales works the list.
The buyer is an account, and one account has several people and wallets. A protocol team may have engineers who read your docs, a founder who books a call, and a Safe that pays. Our guide to account intelligence for crypto explains how to group those wallets and people into accounts. This article covers how to score them once they are grouped.
How is account lead scoring different from wallet scoring?
Wallet scoring rates one address by its onchain activity and reputation, usually to segment or reward users. Account lead scoring rates an organization for a sales team. It adds CRM and web data, rolls many wallets and people into one record, and measures buying intent, not only onchain value.
Our earlier post on wallet scoring for ranking and segmenting users covers the user-level case. The table shows how the two differ.
Wallet scoring | B2B account lead scoring | |
|---|---|---|
Unit | One wallet | One account: people, wallets, and Safes |
User of the score | Growth, rewards, community | Sales and marketing |
Main data | Onchain activity and reputation | CRM, web engagement, and onchain data |
Main question | How valuable is this user? | Will this organization buy, and when? |
Output | One rank per wallet | Fit, engagement, and risk per account |
Typical action | Target, reward, or exclude | Call, nurture, or disqualify |
What are the fit, engagement, and risk axes?
Fit measures how closely an account matches your ideal customer profile. Engagement measures how much the account interacts with you now. Risk measures how much you should doubt the account or its data. Keep the three separate, because a high-fit account with no engagement needs different action from a highly engaged account with poor fit.
Axis | Question | Example signals | Source |
|---|---|---|---|
Fit | Do they look like our best customers? | Account type, chains they deploy on, treasury size, protocols they use, team size | CRM, public data, onchain |
Engagement | Are they active with us now? | Pricing and docs visits, demo connects, testnet or mainnet transactions, meetings, number of engaged people | Web and product analytics, CRM |
Risk | Can we trust this account and its data? | Sanctioned or sybil-listed wallets, pooled exchange addresses, bot traffic, links that are only inferred | Wallet labels, analytics, CRM |
A simple way to act on the axes is a two-by-two of fit and engagement, with risk as a gate:
High fit, high engagement: sales contacts now.
High fit, low engagement: account-based marketing and outbound.
Low fit, high engagement: self-serve or partner route.
Low fit, low engagement: nurture only.
High risk: review before any outreach.
Which data sources feed a B2B crypto lead score?
A B2B crypto lead score uses three sources. The CRM gives firmographics, contacts, and sales activity. Web and product analytics give engagement on your site, docs, and app. Onchain data gives the account's holdings, protocol use, and trust labels. Each source covers a gap the others leave.
CRM. Account type, region, deal history, meetings, email replies, and the evidence that links each wallet to the account.
Web and product engagement. Page views on pricing, docs, and integration guides; wallet connects; custom events such as "API key created"; contract events from your own contracts. Formo records page views, wallet events such as connect and transaction, custom events, and decoded events from contracts you add in project settings.
Onchain data. Net worth, apps used, token holdings, wallet age, and labels for each wallet of the account. In Formo, net worth is verified token holdings plus DeFi positions net of debt where available, and Solana wallets include token balances only. Labels include verification attestations, published sybil lists, OFAC sanctions status, and behavioural labels such as DeFi Lender or Perp Trader with a USD value.
To profile a prospect's known wallets, such as its Safe, before anyone visits your site, you can import wallet addresses through the Import API (Scale and Enterprise plans) or upload a CSV in Search. Imported wallets count toward monthly active user (MAU) billing, and a CSV upload is checked against your plan's MAU limit. Imported data does not count as activity, so an imported Safe has the lifecycle stage Imported until Formo records a tracked event from it.
How do you build a B2B crypto lead score?
To build a B2B crypto lead score, define your ideal customer profile, turn each signal into a yes or no rule, give each rule points on one axis, and add the points per account. Then test the score against past deals and set thresholds for each action. Keep version one small: about ten rules.
Pull last year's deals. List won and lost accounts with their type, size, and sales cycle.
Find the shared traits. Compare won and lost accounts on CRM, web, and onchain data. Keep traits that clearly separate them.
Write each trait as a rule. For example, "a member visited pricing in the last 14 days" or "the account Safe holds more than $1M".
Build rules as segments. In Formo, save each wallet-level rule as a segment, using labels, net worth, lifecycle stage, apps, tokens, attribution, and behavioural event filters.
Tag wallets with the account. Write your CRM account ID on each known wallet as a custom label, so segment members map back to accounts.
Move the data to where you score. Export segments as CSV or read profiles through the Search Profiles API. Data sync to Google Cloud Storage or Amazon S3 is in development; contact Formo support for access.
Add up points per account. Sum fit, engagement, and risk separately in your CRM or warehouse.
Set thresholds and test. Score last quarter's accounts and check that won deals rank near the top.
Formo does not produce a single lead score field. The score lives in your CRM or warehouse, and Formo supplies the wallet, web, and onchain inputs.
Here is an illustrative model for an RPC provider that sells to protocols. The rules and points are examples, not benchmarks. Set your own from your data.
Rule | Axis | Points | Source |
|---|---|---|---|
Account is a protocol or wallet team on a chain you support | Fit | +20 | CRM |
Account Safe or treasury net worth above your threshold | Fit | +15 | Formo net worth |
Members use protocols in your target category | Fit | +10 | Formo apps and behavioural labels |
A member viewed pricing or rate-limit docs in 14 days | Engagement | +15 | Formo page events |
Two or more people from the account engaged in 30 days | Engagement | +15 | Formo plus CRM |
A member wallet is a Power user or New on your app | Engagement | +10 | Formo lifecycle |
Meeting held in the last 30 days | Engagement | +20 | CRM |
Any linked wallet carries the OFAC Sanctioned label | Risk | Block | Formo labels |
Wallets on a published sybil list | Risk | +20 risk | Formo labels |
Account links are inferred only, none deterministic | Risk | +10 risk | CRM evidence label |
In Formo, lifecycle stages are New, Returning, Power user, At Risk, Churned, and Resurrected. The defaults are 30-day windows and 5 active days for a Power user, and you can change them in Settings > Lifecycle. An active day is a UTC day with any event that carries the wallet's address.
How do you roll wallet signals up to an account score?
Roll wallet signals up with clear rules per signal type. For fit, take the strongest value across the account's wallets, such as the largest treasury. For engagement, count distinct engaged people and recent actions, so one busy developer does not outweigh a whole buying group. For risk, any single bad wallet raises the account's risk.
Use the maximum for fit. An account is as large as its largest treasury, not the sum of every personal wallet.
Count people for engagement. Breadth across roles predicts deals better than repeat visits by one person.
Decay engagement. Halve engagement points after 30 days and drop them after 90, so old activity does not keep an account hot.
Use any-match for risk. One sanctioned wallet in the account blocks outreach until compliance reviews it.
Avoid double counting. In Formo, wallets linked by a shared device or user ID appear together in Clusters. Count a person once, even when they use three wallets.
How do you validate and maintain the score?
Validate the score by checking that accounts with high scores convert more often than accounts with low scores. Then review it on a schedule, because your product, market, and data change. A score that sales does not trust will be ignored, so share the test results with the sales team.
Back-test. Score last quarter's accounts with today's rules. Won deals should cluster in the top band.
Watch conversion by band. Track the rate from MQL to opportunity and from opportunity to won for each score band.
Collect sales feedback. Ask sales to flag high scores that were wrong and low scores that closed.
Check data coverage. Some signals are missing for some accounts. For example, Solana wallets have no DeFi positions in Formo net worth, so DeFi rules will not match them. Do not read a missing signal as a negative one.
Review each quarter. Remove rules that do not separate won from lost deals.
Frequently asked questions
What is lead scoring in B2B crypto?
It is a points system that ranks crypto organizations for a sales team. It uses CRM data, web and product engagement, and onchain signals from the account's wallets, and it scores fit, engagement, and risk.
How is lead scoring different from wallet scoring?
Wallet scoring rates one address by onchain activity and reputation. Lead scoring rates an organization for sales, combines many wallets and people into one record, and adds CRM and web engagement data.
Should I combine fit, engagement, and risk into one number?
Keep them separate at first. Fit and engagement together decide the action, and risk works as a gate. You can add a combined number later for sorting, but keep the three parts visible.
Can I score a DAO or a Safe?
Yes. Treat the Safe as the account's treasury and score fit from its holdings. Score engagement from the people behind it, such as delegates or core contributors who visit your site.
Does Formo have a lead score field?
No. Formo supplies the inputs: segments, lifecycle stages, wallet labels, net worth, and attribution. You add up the points in your CRM or warehouse.
How often should I update the scoring model?
Review the rules each quarter, and back-test them against the deals that closed in that quarter. Recompute the scores themselves as often as your data refreshes in the CRM.
Related articles
Glossary: customer health scores, customer personas, wallet segmentation.
