DAU, WAU and MAU Are the New Lighthouse Metric in B2B + AI. Harvey’s a Great Case Study.

For 15+ years, B2B leaders with per seat models treated DAU/WAU/MAU as something B2C companies obsessed over. We had ARR. We had NRR. We had logo retention. Engagement was a “nice to have” buried somewhere on the customer success dashboard, usually phrased as “utilization” that no one tracked for real. And hid from if it was zero.

With agentic apps, that era is over.

In B2B + AI, daily, weekly and monthly active users are now the single most predictive lighthouse metric you have. More than ARR growth. More than NPS. More than seat expansion. In the agent era, engagement isn’t a vanity number. It’s the leading indicator of every other number you care about: renewal, expansion, churn, even valuation multiple.

The CEO at Harvey just shared great metrics showing how usage is arguably the most important metric now in AI + B2B. Versus one we sort of kind of ignored pre-AI, outside of those with consumption-based models:

What Harvey’s CEO Posted

Three numbers from Harvey’s April:

Net new ARR up 6x year-over-year DAU/MAU about to break 50% Average user spending 12 hours a month using Harvey

Those numbers belong together, and most B2B leaders still treat them as separate stories.

A B2B app with 50% DAU/MAU is statistically rare. Slack has it. Notion has it for power users. Most “successful” B2B tools sit at 10-20%. The S-1s of public B2B companies historically didn’t even disclose this number, because it was usually embarrassing.

12 hours a month per user is the more remarkable stat. Roughly 25-30 minutes a day, every working day, in a single vendor’s product. For comparison, the average ChatGPT session in 2025 was about 13-14 minutes. Harvey users are spending the better part of an hour per workday inside legal AI. In some ways, it’s no surprise give what it does for lawyers. But it also means Harvey is a workspace, not a tool.

Then look at the Net New ARR number. 6x year-over-year. Harvey crossed $190M ARR in January 2026 and just raised at an $11B valuation in March. They’re not growing 6x because of marketing. They’re growing 6x because their customers can’t stop using the product, and that engagement converts directly into seat expansion, departmental rollout, and firm-wide deployment.

DAU/MAU went up. Hours/MAU went up. Queries/MAU went up. Net new ARR followed.

In B2B + AI, engagement is the leading indicator. ARR is the trailing confirmation.

Why This Wasn’t True in So Much of Pre-AI B2B

In traditional B2B, you could be a dead product for two years before anyone noticed especially on seat-based pricing plans. You sold an annual contract, sometimes multi-year. The buyer was a VP. The user could be an analyst three layers down. As long as your champion still had a job and the renewal got auto-renewed in procurement, you were “retained.”

Engagement didn’t really matter to the math. You could have a customer with 4% DAU/MAU paying you $200K a year and your CS dashboard would mark them green. That worked because there was nothing better. The switching cost of ripping out an enterprise system was higher than the cost of barely using it.

AI is changing all three legs of that. Replacement costs are dropping to near-zero. Top AI-native software is also creating a higher engagement ceiling. Buyers finally started measuring it. Low engagement used to be a CS problem. Now it’s an existential one.

The Flip Side: Stealth Churn

Stealth churn doesn’t show up in ARR. Yet. It doesn’t show up in logo retention. It shows up in DAU/WAU/MAU 6 to 18 months before the customer cancels. Harvey at 50% DAU/MAU is close to the engagement ceiling. Notion inside SaaStr at 0% is the floor.

The Specific Metrics to Track

If you run a B2B + AI product, these are the numbers that should be on the wall:

DAU/MAU ratio. The single best engagement number you can track. Above 50% means you’ve built something people genuinely depend on. Hours per MAU. Harvey’s 12 hours a month is a remarkable number. This is the most direct measure of how much of the workday you own. Queries or actions per MAU. For agent-era products, this is more meaningful than session count, because one query can replace what used to be a 30-minute workflow. Stealth churn cohorts. Customers paying you who haven’t logged in for 30, 60, 90 days. Power user concentration. What percentage of your usage comes from your top 10% of users?

Make It A Top KPI

The B2B + AI companies winning in 2026 are running their enterprise products like consumer apps. They watch engagement daily, triage drops within hours, and treat DAU/WAU/MAU as the primary KPI with ARR as the lagging confirmation.

Harvey shows everyone what the top of the mountain looks like. 50% DAU/MAU. 12 hours a month per user. 6x net new ARR. That’s the difference between a B2B company that compounds and a B2B company that gets quietly replaced over the next 18 months.