What is a good demo to close rate for B2B SaaS?

What is a typical demo-to-close rate across B2B SaaS?

Optifai's analysis puts it at 30 percent for SaaS and 25 percent across all the B2B segments it measured. That is roughly three demos in ten turning into a won deal within 90 days.

Optifai's demo-to-close benchmark covers 939 B2B companies tracked from Q2 2025 to Q1 2026, with data drawn from CRM systems including Salesforce, HubSpot, and Pipedrive and from demo platforms including Gong and Chorus. It divides closed-won deals by demos delivered, and a deal only counts if it closes within 90 days of the demo. The page was last updated on April 20, 2026. Optifai sells a sales pipeline platform and this is its own data, so we read it as one vendor's analysis rather than an independent audit.

The figure usually quoted next to it is HubSpot's. HubSpot's close rate benchmarks put the average sales close rate at 20 percent across industries in its 2024 survey, and 22 percent for software. HubSpot divides deals won by total qualified opportunities, while Optifai divides by demos delivered, and those are two different groups of deals. Averaging them into one "good close rate" gives you a number nobody measured.

We think the comparison worth making first is with yourself. Pull the last two quarters of demos from your CRM, count the ones that closed within 90 days, and you have a rate built on the same definition as Optifai's 30 percent. If your team counts a second demo to a new stakeholder as a separate demo, write that down before you compare. Close rate is one line in a wider plan, which our go-to-market strategy guide lays out.

How much does deal size change the demo-to-close rate?

By 20 points from the smallest deals to the largest in Optifai's data. Deals under 10,000 dollars in annual contract value closed at 35 percent of demos, and deals over 100,000 dollars at 15 percent.

That spread is wider than the 14 points between SMB and enterprise companies in the same analysis. A team selling plans under 10,000 dollars and a team selling six-figure contracts should not hold themselves to one SaaS average.

The cost shows up in the forecast. At 15 percent, a pipeline of deals above 100,000 dollars needs six or seven demos for each win, and a plan built on the all-segment 25 percent would come up short on demo volume every quarter. We would rather plan from the bucket your deals actually fall into. The trade-off is precision, since Optifai's page gives no sample size for each deal-size bucket.

Does company size affect how many demos turn into deals?

Yes, and in the same direction as deal size. Optifai measured 32 percent for SMB companies and 18 percent for enterprise.

We suspect the two cuts overlap, because the larger contracts probably come from enterprise buyers.

There is a question in the method that the page leaves open. A deal counts toward Optifai's rate only if it closes within 90 days of the demo, so an enterprise deal that signs on day 120 never counts as a win in this data. How much of the gap between 32 and 18 percent comes from slower buyers rather than fewer buyers? Optifai does not split the two, and we do not know.

Does the demo format itself change the close rate?

In Optifai's data it does, by as much as deal size. Interactive demos where the prospect drives closed at 38 percent, against 18 percent for a generic screen share.

Format is the one cut here a team can change this quarter. You cannot choose your buyers' company size, and changing your price changes the whole business, but you can stop running the same screen share for every prospect.

A customized demo starts with knowing what this prospect is likely to ask, and the questions buyers raise on calls tend to repeat. Our piece on finding recurring objections in sales calls shows how to pull them out of recordings. Corvan's agents learn what your customers keep asking from the sales calls you upload, and plan posts around those questions.

These are correlations from one vendor's data set. The teams that run interactive demos may also qualify harder before the call, in which case the format is getting credit for work done earlier.