- A lead scoring model learns from your own won and lost leads, so the score reflects who actually buys, not only who showed interest.
- H2O Driverless AI builds the model from behavior, firmographic and campaign data, with a reason code on every score.
- Reason codes tell each sales rep why a lead ranks high, so the first call starts from what matters to that buyer.
- Scores feed the CRM and marketing systems you already run; H2O is not a campaign tool.
Your team is working the wrong leads
Your reps have more leads than hours. When the list is sorted by form fills and email opens, they spend the week on people who were curious but never able to buy, and the quarter slips.
Rule-based scores reward interest, not fit. A contact who downloads everything can rank above a buyer with budget and a real project, because the rules only count clicks. The cost shows up in the pipeline: missed targets, reps who burn out on poor leads, and marketing and sales arguing over what a qualified lead means.
How AI lead scoring works
Your marketing operations team builds an explainable conversion model and sends the scores to your CRM.
Step 1: start from lead outcomes
Pull past leads from your CRM and marketing automation system, labeled by whether each one became an opportunity, a deal and revenue.
Step 2: add the signals
Join behavior on your site and emails, company size, industry, role, source campaign and past purchases.
Step 3: train the conversion model
H2O Driverless AI builds classification models with automatic feature engineering, tested on leads the model has not seen.
Step 4: score and explain every lead
Each lead gets a score and reason codes, such as Shapley values, that show which factors drove it.
Step 5: route and monitor
Scores flow into your CRM queues, and your team watches for model drift as campaigns and markets change.
Working under the CRM you already run
H2O is not a campaign tool. It is the scoring layer under the CRM and marketing cloud you already run, such as Salesforce, Adobe or SAS, and your reps keep working in the tools they use today.
Keeping marketing and sales aligned
A shared, explainable score gives marketing and sales a common definition of a qualified lead, backed by what actually converted rather than by a debate. As campaigns and markets shift, retraining on fresh outcomes keeps that definition current instead of letting it go stale.