Best Time of Day to Cold Call in

• For a starting experiment, compare morning and late-afternoon blocks in the recipient's local time. Gong's benchmark favors morning; Revenue.io's internal team favored late afternoon✓. 12
• Track the actual outcome you want. Gong's published connection definition includes several rep-selected dispositions, including a meeting booked and an opt-out✓. 1
• Keep 2020, 2024 and the later Revenue.io internal analysis separate; pooling their reported peaks would produce a false precision✓. 123

1. Gong's morning finding applies to a specific Engage benchmark

Gong states that the insights in its Engage analytics article derive from 2024 data✓. For the call analysis, it says the data are from Sales Development Representatives only and include dialer calls, with a connected call determined by a rep-selected outcome✓. This is important: a connection is not equivalent to an interested prospect, a qualified meeting or revenue. The listed outcomes include negative dispositions, so a team measuring only booked meetings should not copy the reported connection metric without changing its definition. 1

In that context, Gong says calls made Tuesday and Wednesday mornings from 9 a.m. to noon had the highest connect rates✓. The article says it included hour cells with more than 1,000 dialer calls from flows over a three-month period✓. It does not, in the cited text, publish a universal probability that any specific prospect answers at those hours. It also does not prove the hour caused the difference. Reps may place different types of calls, to different territories and accounts, at different times. 1

The practical implication is modest. Put one morning block into a test calendar if your target recipients are working then. Do not force an entire global team into 9 a.m. on the caller's clock. The article does not specify enough about timezone treatment in the captured excerpt to translate its 9-to-noon window into every team's local operations. Check the recipient's time zone in your CRM and document which clock your own analysis uses.

2. Revenue.io's late-afternoon result is an internal team result

Revenue.io describes reviewing its own sales team's dialer and sequence call connection rates over the preceding 90 days✓. Its article reports peak engagement in the 4 to 5 p.m. hour, and quotes its sales director saying calls around 4 p.m. local time have yielded its team's highest connection rates✓. The audience is that company's prospects, not a random sample of all B2B buyers. The article does not provide a complete count of calls, a confidence interval or segment-level breakdown for this internal window in the quoted material. 2

Revenue.io itself says this result ran counter to its 2019 study✓. That is not a flaw to hide. It shows why a team should treat a published best-time chart as a hypothesis that can expire or fail to transfer. Industry, seniority, phone-number quality, seller behavior and seasonal campaigns can all change who gets called at a given hour. The late-afternoon finding is worth testing, but it is not proof that moving every call to 4 p.m. will cause more conversations. 2

Keep the source's clock clear. Revenue.io describes the 4 p.m. observation in local time✓. For a distributed territory, schedule by recipient local time and store both the timestamp with timezone and the normalized local hour. Otherwise an apparent 4 p.m. peak might combine unrelated cohorts across regions. 2

3. The older ringDNA report measures more than cold calls

Revenue.io's 2020 Sales Prospecting Performance Report says its ringDNA sample's overall call answer rates peaked from 10 to 11:30 a.m., with a secondary spike at 2 p.m. in the call recipient's timezone✓. But that overall chart is not identical to a cold-outbound-only chart. The report separately narrows the sample to first prospecting calls by account executives and sales development reps✓. Revenue.io's later article explicitly warns that its historical platform-wide calls included business professionals with pre-existing relationships✓. 23

Within the 2020 report's prospecting subset, the 8 a.m. answer rate was described as nearly as high as the rate at the peak-volume 10 a.m. hour, despite fewer calls at 8 a.m.✓. That is a useful reminder that call volume and answer rate are separate quantities. A busy hour is not necessarily the best hour. It also means a low-volume hour could have unstable estimates, so ask for the denominator before ranking narrow slices. 3

The report advises companies to monitor their own connection rates because answer rates can vary by industry✓. That caution remains sensible even if a chart's exact hourly pattern changes. The report is dated 2020, while Gong's benchmark uses 2024 data and Revenue.io's article also discusses a later 90-day internal review✓. Neither chronology nor sample size alone makes one of those windows automatically correct for your audience. 123

4. How to test your own calling window

Start with one clearly defined population: for example, first-touch outbound dials to named decision-makers in one geography and segment. Do not mix inbound callbacks, current customers and cold prospects. Fix a call definition before the test: dial attempted, human answered, target person answered, useful conversation and meeting booked are distinct events. Gong's benchmark uses rep-selected connected outcomes, so use a separate field if your business needs a stricter outcome✓. 1

Next, compare at least two recipient-local windows, such as 9-to-noon and 3-to-6 p.m. The first is motivated by Gong's morning finding and the second by Revenue.io's internal afternoon result✓. Assign comparable leads and reps across windows where possible. If reps choose their best prospects for one block, the resulting difference cannot be attributed to time. Random assignment is preferable when the workflow permits it. 12

Record the number of attempts, unique prospects, connected target conversations, qualified meetings and opportunities for each window. Stratify by region, industry, seniority, lead source and number of prior attempts. Review both absolute counts and rates with confidence intervals. A high rate from a tiny cell can be less useful than a slightly lower rate from a stable cell. Keep voicemail and callback rules consistent so one window is not advantaged by a different workflow.

Finally, compare downstream quality. If the afternoon produces more answers but fewer qualified meetings, the operating decision may differ from a connect-rate chart. Write down the tradeoff before the experiment and repeat the analysis after staffing, targeting or season changes. Observational charts can prioritize experiments; they cannot establish a causal scheduling rule on their own.

5. What should your team do tomorrow?

Do not abandon every current call block. Audit a month of calls and tag each by recipient-local hour, new versus existing relationship, and disposition. Then protect one morning block and one afternoon block for a controlled comparison. The published evidence gives reasonable starting windows, but its studies involve different groups and definitions✓. 123

If the data are too sparse for a stable hourly answer, pool adjacent hours and report uncertainty. If you cannot verify recipients' time zones, fix that data problem before optimizing the schedule. And if your business outcome is revenue, do not stop the analysis at pickup or even a meeting. The best time for your team is the window that produces useful, compliant conversations and eventual pipeline for your own target audience.

FAQ

How we researched this

We read Gong's Engage analytics benchmark, Revenue.io's timing article and the original 2020 ringDNA/Revenue.io report on October 1, 2026. We preserved separate dated excerpts and did not combine studies into one pooled estimate. The sources do not provide a common sample, a common call definition and a common outcome. Percentages from unrelated charts are therefore deliberately not averaged here.

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