What is a good close rate on a second sales call? Benchmarks

No one publishes a benchmark for second-call close rate. The closest proxy is RAIN Group’s 47% average win rate on proposed or quoted opportunities (62% for top performers). Whole-deal close rates run 11–29% of sales-qualified leads by industry (First Page Sage, an agency). A good second-call rate is whatever back-solves to your industry’s figure.

• Direct benchmark: none. As at 25 September 2026 we found no publisher with a stated method that measures closes on a second sales call.
• Closest proxy: RAIN Group, 47% of proposed or quoted opportunities won (472 sellers, self-reported). It applies only if your second call is the proposal call.
• Whole-deal range by industry: First Page Sage (agency, own and client data), SQL to closed won, 11% (biotech) to 29% (HVAC) across 27 industries; B2B SaaS 12%.
• Vendor figure: HubSpot, 20% average close rate, attributed to its own 2024 survey; no sample size published.
• The back-solve: second-call target = (industry close rate − share closed on call one) ÷ share of first calls that hold a second call.
• The trap: win rates quoted by number of calls are survivor-biased, because lost deals leave early.

Is there a published benchmark for a second sales call close rate?

There is no credible published benchmark for second-call close rate, and any single figure you find is almost certainly a different metric wearing its name. The widely quoted sales close rates measure one of three things: deals won over all qualified leads, deals won over proposals issued, or website visits that became leads. None of them splits outcomes by which call the deal closed on.

The honest position: a second-call close rate has to be built from your own CRM and judged against a target you derive, not one you look up. The rest of this page is how to derive it. If you want to know how to lift your second-call close rate once you have measured it, that is a separate page with the levers ranked.

The closest published figures, and what each one actually measures

Four figures get used as second-call benchmarks. Each was checked at source on 25 September 2026. Read the denominator column before the figure column.

Two of the four are whole-deal rates, one is a late-stage rate, and one is a single salesperson’s remark about her own team’s deals. First Page Sage’s industry spread is the only one wide enough to be useful for setting a target, and it has no sample size. Our sales close rate benchmarks by industry page covers the whole-deal figures in full; this page uses them only as inputs.

What changes on call two and call three

Almost all sales content assumes a one-call close, so the second call is treated as a repeat of the first. Arithmetically it is a different population, and three things change.

The easy answers have left. Buyers who said yes on call one closed; buyers who said a clear no are gone. What reaches call two is the undecided middle. A second-call rate is a conditional probability, measured only on survivors, so a raw gap between it and a first-call rate measured on everyone is not a verdict on either call.

The denominator shrinks and the noise grows. If 100 first calls produce 40 second calls and 12 third calls, your third-call close rate is a percentage of twelve. One deal moves it by more than eight points.

More people have to agree. Gong’s win-rates page reports that enterprise deals are 233% less likely to close when the decision maker is not involved, and that win rates are 10% higher when pricing is discussed on the first call. Both are vendor figures from Gong Labs without a published sample; read them as direction, not size. Call two is usually the first call on which someone other than your original contact appears.

The survivorship trap sits under all three. A Gong account executive, Sarah Brazier, is quoted on Gong’s win-rates page putting her team’s win rate at 61% at five to nine calls and 63% at ten or more. Deals that reach ten calls were, by definition, still alive at call nine. A win rate grouped by call count describes which deals survived, not what extra calls cause, so “book more calls” is the wrong lesson from it.

The back-solve method: turning an industry close rate into your second-call target

The back-solve method derives a second-call target from a whole-deal benchmark you can actually find. It rests on one identity for any cohort of held first calls:

Overall close rate = call-one close rate + (share holding a second call × second-call close rate)

Here “second-call close rate” means deals closed on or after call two, divided by second calls held, so it absorbs call three. Rearranged:

Second-call target = (industry close rate − call-one close rate) ÷ share holding a second call

The worked example below uses First Page Sage’s industry rows as the overall rate and treats a sales-qualified lead as equivalent to a held first call, which is an assumption you should check against your own definitions. The two funnel shapes are illustrative inputs, not benchmarks: Shape A closes 5% of first calls on the spot and holds a second call with 40%; Shape B closes 10% on the spot and holds a second call with 50%.

Two things fall out of the arithmetic. First, the same industry figure implies very different second-call targets depending on how much you close on call one: HVAC needs 60% under Shape A and 38% under Shape B. Second, in low-close industries a team that already closes 10% on call one barely needs call two at all to match the published average, which is why a benchmark lifted from another team’s funnel is meaningless without the funnel.

Substitute your own three numbers. If the result is above 100%, no second call can close the gap and the constraint is how many first calls reach a second call, not what happens on it. The formula and its inputs are defined in how to calculate sales close rate, which covers the denominator choice this method depends on.

How to read your second-call close rate against the target

Once you have a back-solved target, compare your measured second-call rate with it. The bands below are our decision rule for reading the ratio, not a measurement; they convert a number into a next action.

A second-call close rate at half its back-solved target is a qualification problem on call one far more often than a closing problem on call two. The companion page on follow-up between sales calls covers the gap between the calls, which is where many second calls are lost before they start.

What it costs to measure this properly

Most CRMs do not record which call a deal closed on, so the method needs one extra field: a meeting sequence number on every held sales call (1, 2, 3), plus a held-or-no-show flag. At about two minutes of admin per call, a team holding 100 first calls and 40 second calls a month spends roughly 4–5 hours a month tagging, plus an hour a quarter to run the back-solve. The skill required is modest. The part that breaks is consistency: one rep who logs a rescheduled call two as a new call one quietly inflates your call-one rate and deflates your call-two rate.

Whether a second call is winnable is mostly decided upstream, by who was booked onto call one and how fast they were reached. That upstream layer, AI appointment setting and qualification paid on booked qualified appointments, is the part LeadsNow runs; we have booked 50,769+ sales appointments since 2017, and we do not sit on your second call. In our own client work we typically see roughly a 3× (300%) lift in conversion for a good client still running 2020-era operations rather than 2026 AI-driven ones, with post-call second and third close calls as one of the levers. Speed to lead alone we typically see at around 3×, doubling contact rate around 2× and doubling set rate around 2×. Those do not multiply: 3 × 2 × 2 is 12×, and we do not see 12×, because the levers overlap. That is an operator’s observation, not a study, and not a guarantee; how we define the lift figures we do publish is on our methodology page.

This page is the second-call benchmark entry in our sales pipeline stages series, which gives each stage of the pipeline its own metric, benchmark and cost.

Frequently asked questions

What is a good close rate on a second sales call?

There is no published second-call benchmark. If your second call is the proposal call, the closest proxy is RAIN Group’s 47% average win rate on proposed or quoted opportunities, 62% for top performers. Otherwise, back-solve a target from your industry’s whole-deal close rate.

Should my second call close at a higher rate than my first?

Often, yes, because clear yeses and clear nos have already left and the call is measured only on survivors. In single-decision-maker sales it is often lower, because the second call collects the stalls. Judge each against its back-solved target, not by the raw gap alone.

How many sales calls does it take to close a deal?

No credible public source answers this across industries. The popular “80% of sales need five follow-ups” has no traceable primary source. The one call-count figure we found is a Gong account executive’s remark on Gong’s win-rates page: 61% won at five to nine calls, 63% at ten or more. It is an anecdote, not a study, and survivor-biased.

Is a third sales call worth booking?

Only when a named item remains and the person who can resolve it will attend. If your third-call close rate is under half your second-call rate, third calls are functioning as stalls; replace them with a dated decision or a dated pause.

Which industry figure should I back-solve from?

Use the row whose denominator matches yours. First Page Sage publishes SQL-to-closed-won rates for 27 industries, from 11% in biotech to 29% in HVAC, from its own and client data, without a sample size. HubSpot, a CRM vendor, publishes a 20% all-industry average from its own survey, with three industries broken out.

Is there a second-call close rate benchmark for Australia?

No. As at 25 September 2026 we found no Australian dataset for this stage or for whole-deal close rates. Every published figure above is global or undisclosed in geography, so your own trailing twelve months is the better comparison.