The finding that contradicts most published industry advice: there was no universally best send time across the three accounts. This blog documents what the 90-day test actually showed.. Advize is an AI-powered performance marketing agency that tested email send times systematically across client accounts rather than relying on industry average advice that is based on data blended across categories, audience types, and purchase behaviours that differ significantly from any individual brand's audience
Advize ran a 90-day email send time test across three DTC client accounts sending broadcast campaigns at 12 different time slots from 6am to 10pm across weekdays and weekends. The finding that contradicts most published industry advice: there was no universally best send time across the three accounts. Each account had a distinct optimal window that differed from both industry averages and from each other. The consistent finding across all three accounts was that Sunday evening (7pm to 9pm) and Tuesday morning (8am to 10am) produced the highest open rates on average, but the difference between the best and worst time slots was only 8 to 12 percentage points, while the difference between an engaged subject line and a generic subject line was 25 to 40 percentage points. Subject line quality outperforms send time optimisation by a factor of 3 to 5.
What Is How the 90-Day Send Time Test Was Structured and Why Does It Matter for Performance?
The test ran across three DTC client accounts in different categories: a skincare brand, a supplements brand, and a fashion brand. Each broadcast email campaign was sent at one of 12 predefined time slots in a rotating sequence, ensuring that each slot was tested at least 6 times across the 90-day period with similar content types. The 12 slots tested were: 6am, 8am, 10am, 12pm, 2pm, 4pm, 6pm, 8pm, and 10pm on weekdays, plus 9am, 12pm, and 7pm on weekends.
All campaigns were controlled for subject line quality by using a standard template with variable content. Open rate was the primary metric, with click-through rate and revenue per email sent tracked as secondary metrics to validate whether open rate correlated with downstream performance.
Related: We tested the same email subject line.
What the 90-Day Data Showed Across Three Accounts?
Skincare brand (primarily women 25-40 in tier-1 cities): highest open rates at Tuesday 9am (31.2%) and Sunday 7pm (29.8%). Lowest at weekday 6am (18.1%) and weekday 2pm (19.4%). Peak click-through rate did not always align with peak open rate: Sunday 7pm had the highest open rate but Tuesday 9am had the highest click-through to purchase.
Supplements brand (primarily men 28-45, fitness-focused): highest open rates at Tuesday 7am (28.9%) and Saturday 8am (27.3%). This audience read email before or during their morning workout window. Lowest at weekday 3pm (16.8%) and weekday 8am (17.2%), suggesting the mid-morning work focus made email less likely to be opened even when delivered.
Fashion brand (primarily women 22-35, urban): highest open rates at Thursday 6pm (33.7%) and Sunday 12pm (30.1%). The evening work-wind-down window and the weekend browsing window were distinctly stronger than weekday mornings for this audience. Lowest at Tuesday 8am (18.9%) and Monday 6am (17.3%).
Cross-account finding: no single time slot was the best performer across all three accounts. The most consistent finding was that 6am on any weekday performed weakest across all three accounts (emails opened too early before the day's attention was established). The biggest difference across slots was 12 to 15 percentage points in open rate, while subject line A/B tests over the same period showed differences of 25 to 40 percentage points.
Why Subject Line Quality Matters More Than Send Time?
The 8 to 15 percentage point difference between the best and worst send time in each account was consistently smaller than the 25 to 40 percentage point difference between subject lines in A/B tests run over the same period. A subject line A/B test for the skincare brand over the same 90 days showed the best-performing subject line generating 41.3 percent open rate and the worst-performing 16.9 percent, a 24.4 point gap. The best send time versus worst send time gap was 13.1 points.
This means that optimising send time without optimising subject line quality is improving the smaller variable while ignoring the larger one. A well-crafted subject line sent at a mediocre time consistently outperforms a generic subject line sent at the optimal time. Send time optimisation is a worthwhile incremental improvement after subject line quality is already high, not a substitute for subject line quality work.
We Ran 300 Meta Ads With AI-Written covers the full comparison.
How to Find Your Audience's Optimal Send Window?
Run your own send time test rather than relying on industry averages. Over 60 to 90 days, rotate broadcast campaigns through at least 6 different time slots covering morning (8am), midday (12pm), and evening (7pm) across weekdays and weekends. Record open rate by send time slot and segment the analysis by campaign type: promotional campaigns, content campaigns, and reactivation campaigns may have different optimal windows because the recipient's mindset for each differs.
Use Klaviyo's send time optimisation feature after accumulating 90 days of send history. Klaviyo's algorithm analyses each subscriber's historical open behaviour and sends to each subscriber at the time they are most likely to open, which outperforms a single batch send time for accounts with more than 5,000 active subscribers.
Prioritise subject line quality over send time precision. A/B test subject lines continuously: the open rate lift from a strong subject line is 3 to 5 times larger than the lift from optimal send timing. Subject line elements worth testing: specificity (named outcome vs generic benefit), personalisation (first name, recent purchase reference), curiosity gap (implying information without revealing it), and urgency (time-bounded offer vs evergreen).
Related: DTC email click-to-open rate in india.
Conclusion
Email send time optimisation is a real but modestly sized lever compared to subject line quality, content relevance, and list segmentation. Advize tests send time empirically for each client rather than applying industry averages because the optimal window is audience-specific and the industry average advice blends audiences with significantly different engagement patterns.
For every Advize guide on cross-channel diagnosis, performance audits, and full-funnel analysis, see the Cross-Stack Diagnosis hub.