{"id":4008,"date":"2025-02-24T17:45:04","date_gmt":"2025-02-24T17:45:04","guid":{"rendered":"https:\/\/www.warmy.io\/blog\/maximizing-email-deliverability-grouped-vs-randomized-sending\/"},"modified":"2026-04-01T14:31:54","modified_gmt":"2026-04-01T14:31:54","slug":"maximizing-email-deliverability-grouped-vs-randomized-sending","status":"publish","type":"post","link":"https:\/\/www.warmy.io\/blog\/maximizing-email-deliverability-grouped-vs-randomized-sending\/","title":{"rendered":"Maximizing Email Deliverability: Grouped vs. Randomized Sending"},"content":{"rendered":"<p><span>Many organizations suffer the pain of emails ending up in spam folders or being throttled\u2014often because sending practices are widely inconsistent with Outlook 365\u2019s spam filters. At Warmy, our research team continues to do more by figuring out how to get more of your emails delivered, straight to your intended inbox. Our ongoing testing\u2002and analysis will enable you to avoid typical email-sending mistakes that make outreach wasteful for businesses.<\/span><\/p>\n<p><b>It\u2019s a fact: <\/b><span>Every email counts, and even minor missteps in sending strategy can have a significant impact. That\u2019s why we recently conducted an in-depth experiment comparing two distinct methods: grouped sending versus randomized sending.<\/span><\/p>\n<h2>What does sending strategy have to do with email deliverability?\u00a0<\/h2>\n<p><span>It is not only the quality\u2002of the content that decides <\/span><a href=\"https:\/\/www.warmy.io\/blog\/email-deliverability-best-practices-ultimate-guide-to-follow\/\" target=\"_blank\" rel=\"noopener noreferrer\"><span>email deliverability<\/span><\/a><span>. It\u2019s also very much connected to the way you send your emails. How you distribute your messages can have a major impact\u2002on whether or not your email hits the inbox or the spam folder. Of course, it\u2019s not the only factor, but it <\/span><b><i>does<\/i><\/b><span> have an impact.<\/span><\/p>\n<p><span>Different sending strategies send different signals to email service providers:<\/span><\/p>\n<ul>\n<li><span>For instance, sending a bunch of emails at once, or all at the same time, could initiate\u2002\u201cbulk spam activity\u201d and trigger spam filters.\u00a0<\/span><\/li>\n<li><span>Conversely, a more randomized sending approach could well resemble natural user behavior, possibly reducing the chances of being considered spam.<\/span><\/li>\n<\/ul>\n<p><span>So, which approach is more effective? And how much does email-sending strategy really influence deliverability?<\/span><\/p>\n<p><span>In our experiment, we put these two methods to the test, analyzing real-world results to determine <\/span><b>which approach leads to higher inbox placement and better engagement.<\/b><span> The findings might surprise you.<\/span><\/p>\n<h2>The experiment: grouped sending vs. randomized sending<\/h2>\n<h3><strong>What is group sending?<\/strong><\/h3>\n<p><b>Group sending is a method where emails are dispatched in large batches over a short span of time.\u00a0<\/b><\/p>\n<p><span>However, sending a group of emails should also be done in moderation to avoid being flagged by email providers\u2019 spam filters. Even elapsed time changes could be considered too close together after an unanticipated activation, which some providers (like O365) would monitor to detect spam-like activity.<\/span><\/p>\n<p><i><span>In our experiment, we structured group sending to closely examine how these bursts of emails impact overall deliverability, ensuring that the method\u2019s efficiency doesn\u2019t come at the cost of inbox placement.<\/span><\/i><\/p>\n<h3><strong>What is randomized sending?<\/strong><\/h3>\n<p><b>On the other hand, randomized sending is sending emails at different intervals within a time frame.\u00a0<\/b><\/p>\n<p><span>Rather than sending a big batch at once, each email is sent out one at a time and in\u2002a seemingly random order. This approach aims to simulate organic, natural email send traffic which may reduce the probability of being flagged by <\/span><a href=\"https:\/\/www.warmy.io\/blog\/spam-filters-everything-you-need-to-know\/\" target=\"_blank\" rel=\"noopener noreferrer\"><span>spam filters<\/span><\/a><span>.<\/span><\/p>\n<p><span>By avoiding the concentrated burst characteristic of group sending, randomized sending aims to offer a smoother, more consistent deliverability profile.\u00a0<\/span><\/p>\n<p><i><span>Our experiment put this method to the test, comparing its effectiveness against group sending to see which approach better ensures that emails reach their intended inboxes.<\/span><\/i><\/p>\n<h3><strong>Objective of the experiment<\/strong><\/h3>\n<p><span>In our research, we dug deep into how these varying methods\u2014grouped sending versus randomized sending\u2014impact deliverability. Our goal was to identify which approach aligns better with the criteria used by providers like O365, helping organizations ensure their emails are not just sent, but actually seen.\u00a0<\/span><\/p>\n<p><span>Specifically, the experiment\u2019s objectives were:<\/span><\/p>\n<ul>\n<li><span>To compare grouped sending and randomized sending strategies<\/span><\/li>\n<li><span>To measure impact using inbox placement and spam folder rates<\/span><\/li>\n<\/ul>\n<h2>Tools and methods employed\u00a0<\/h2>\n<p><span>To rigorously test how different sending strategies impact email deliverability, our experiment was designed with clearly defined methodologies, focus groups, and performance metrics. Here\u2019s a closer look at the setup:<\/span><\/p>\n<p><b>Grouped Sending:<\/b><\/p>\n<ul>\n<li><span>2 Focus Groups: 10 senders each (5 established, 5 new domains).<\/span><\/li>\n<li><span>Strategy: Send batches of 20, 100, and 300 emails daily over 3 weeks.<\/span><\/li>\n<li><span>Timing: Work hours (10 AM\u20136 PM) and \u201csiesta time\u201d (12 PM\u20132 PM).<\/span><\/li>\n<\/ul>\n<p><b>Randomized Sending:<\/b><\/p>\n<ul>\n<li><span>2 Focus Groups: 5 senders each (2 established, 3 new domains).<\/span><\/li>\n<li><span>Strategy: Sent emails in staggered batches:<\/span><\/li>\n<li><span>40\/week (8-hour spread), 120\/week (24-hour spread), 300\/week (randomized timing).<\/span><\/li>\n<\/ul>\n<p><span>For both grouped and randomized sending experiments, we used both Gsuite and Custom <\/span><a href=\"https:\/\/www.warmy.io\/blog\/what-is-smtp-and-how-does-the-smtp-server-work\/\" target=\"_blank\" rel=\"noopener noreferrer\"><span>SMTP setups<\/span><\/a><span> to simulate typical sending environments. All emails were directed to Microsoft 365 accounts, ensuring a consistent testing environment across both strategies.<\/span><\/p>\n<p><span>To accurately assess deliverability and <\/span><a href=\"https:\/\/www.warmy.io\/blog\/inbox-placement-test-warmy-io-s-solution-to-email-spam-challenges\/\" target=\"_blank\" rel=\"noopener noreferrer\"><span>inbox placement,<\/span><\/a><span> we used Warmy\u2019s in-house tools alongside Microsoft SNDS. Then, we tracked the following metrics:<\/span><\/p>\n<ul>\n<li><b>Inbox vs. Spam Rates:<\/b><span> To determine the effectiveness of each sending strategy.<\/span><\/li>\n<li><b>Bounce Rates:<\/b><span> To capture instances of emails being blocked or delayed.<\/span><\/li>\n<\/ul>\n<h2>The results: So how do sending methods impact deliverability?<\/h2>\n<p><span>Imagine you\u2019re hosting a grand dinner party. You could either invite everyone all at once\u2014risking chaos at the door\u2014or you could welcome guests gradually, ensuring each one gets the attention they deserve. Our experiment on email deliverability revealed a similar story between two sending strategies.<\/span><\/p>\n<h3><strong>Grouped sending: The high-volume gamble<\/strong><\/h3>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Chart titled Grouped Sending: The High-Volume Gamble showing weekly email statistics. Week 1: 20\/day, Inbox 75%, Spam 20%, Not Received 5%. Week 2: 100\/day, Inbox 65%, Spam 25%, Not Received 10%. Week 3: 300\/day, Inbox 35%, Spam 55%, Not Received 10%.\" height=\"600\" src=\"https:\/\/warmy-blog-wordpress-bucket.s3.amazonaws.com\/wp-content\/uploads\/2025\/02\/11093407\/3-1.png\" width=\"800\" title=\"\"><\/p>\n<p><span>At the start of our experiment, sending emails in large bursts actually showed promise. In Week 1, small batches achieved a decent 75% inbox placement. However, as the volume ramped up by Week 3, the strategy faltered dramatically: more emails were landing in spam (55%) instead of inboxes (35%).<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Line graph titled Grouped Sending: The High-Volume Gamble shows Inbox, Spam, and Not Received percentages over three weeks. Inbox decreases from 60% to 20%, Spam increases from 20% to 65%, Not Received fluctuates slightly around 20%.\" height=\"600\" src=\"https:\/\/warmy-blog-wordpress-bucket.s3.amazonaws.com\/wp-content\/uploads\/2025\/02\/11093408\/1.png\" width=\"800\" title=\"\"><\/p>\n<h3><strong>Randomized sending: The steady performer<\/strong><\/h3>\n<p><span>In contrast, randomized sending told a very different story. This approach consistently delivered strong results\u2014regardless of whether we sent 40, 120, or even 300 emails per week.<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Table titled Randomized Sending: The Steady Performer shows email stats over 3 weeks. Week 1: 40 emails\/week, 90% inbox, 8% spam, 2% not received. Week 2: 120 emails\/week, 80% inbox, 7% spam, 3% not received. Week 3: 300 emails\/week, 80% inbox, 15% spam, 5% not received.\" height=\"600\" src=\"https:\/\/warmy-blog-wordpress-bucket.s3.amazonaws.com\/wp-content\/uploads\/2025\/02\/11093407\/4-1.png\" width=\"800\" title=\"\"><\/p>\n<p><span>Randomized sending showed the following results:<\/span><\/p>\n<ul>\n<li><b>Consistent deliverability:<\/b><span> Inbox rates remained high (80\u201390%) even at 300 emails\/week.<\/span><\/li>\n<li><b>Low spam rates:<\/b><span> Spam placement stayed below 15%.<\/span><\/li>\n<\/ul>\n<p><b>Minimal Loss:<\/b><span> Only 2\u20135% of emails were not received.<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"A line graph titled Randomized Sending: The Steady Performer shows three lines over three weeks: Inbox (%) in green gradually decreasing, Spam (%) in red slightly increasing, and Not Received (%) in blue slightly decreasing. Warmy logo at the bottom.\" height=\"600\" src=\"https:\/\/warmy-blog-wordpress-bucket.s3.amazonaws.com\/wp-content\/uploads\/2025\/02\/11093408\/2.png\" width=\"800\" title=\"\"><\/p>\n<h3><strong>Why grouped sending fails<\/strong><\/h3>\n<p><span>Analyzing the trends and data from the experiment, it became clear why sending emails in large, grouped batches consistently failed over time. The key issues that emerged include:<\/span><\/p>\n<h4>Spam filters<\/h4>\n<p><span>Most email providers (notably Outlook (O365)) have advanced spam detection systems that can recognize when emails are suspicious. When thousands of emails are sent at a time from the same domain, Outlook identifies\u2002this as mass marketing or spam.<\/span><\/p>\n<p><span>So what happened during the experiment was Outlook flagged bulk sends as suspicious, which led to higher spam placement (up to 55%). Additionally, the more frequently a domain engages in grouped sending, the more Outlook reinforces its classification as a potential spam sender.<\/span><\/p>\n<h4>Throttling<\/h4>\n<p><span>High volume triggers temporary blocks or delays, resulting in 10% of emails not being received.\u00a0<\/span><\/p>\n<p><span>Many email servers, including O365, use throttling mechanisms to prevent abuse and protect users from spam.\u00a0<\/span><\/p>\n<p><span>When a server detects a sudden surge in outbound emails, it may impose temporary restrictions, including email delays. Instead of immediate delivery, some emails may get queued, leading to significant delays in inbox placement. The receiving server may also respond with temporary errors and if high-volume sending continues, the sender\u2019s IP or domain reputation may suffer long-term consequences.<\/span><\/p>\n<h4>Reputation risk<\/h4>\n<p><span>Beyond immediate deliverability issues, bulk sending can hurt the sender\u2019s reputation in the long run. If a domain is frequently marked as spam, its emails will be more likely to land in spam folders\u2014even when sending to new recipients. A damaged reputation also means that even well-crafted, legitimate emails may struggle to land in inboxes.<\/span><\/p>\n<h3><strong>Why randomized sending works<\/strong><\/h3>\n<p><span>Meanwhile, here is our analysis on why randomized sending resulted in low spam rates and consistent deliverability\u2014even while sending up to 300 emails in a week.\u00a0<\/span><\/p>\n<h4>Trust building<\/h4>\n<p><span>Email providers have built-in algorithms that assess email-sending behavior. Gradual sending aligns with O365\u2019s expectations of \u201cnormal\u201d email traffic. Though this was automated, it simulated human behavior, which made it more credible to O365. In this experiment, randomizing email dispatch times led to:<\/span><\/p>\n<ul>\n<li><b>Less suspicion from spam filters:<\/b><span> Since the sending pattern resembled that of a typical user rather than a bulk sender, Outlook\u2019s filtering systems were less likely to intervene.<\/span><\/li>\n<li><b>Improved domain reputation:<\/b><span> The lack of bulk activity helped maintain a positive sender score, ensuring future emails were trusted by the receiving servers.<\/span><\/li>\n<\/ul>\n<h4>Engagement wins<\/h4>\n<p><span>The time an email arrives in someone\u2019s inbox can significantly impact whether they open it. Recipients are more likely to open emails that arrive at staggered times.<\/span> <span>Bulk emails often get buried under other promotional emails sent at the same time. When emails arrive at varied intervals, recipients are more likely to see and interact with them, leading to higher open and response rates.<\/span><\/p>\n<h4>Minimal loss<\/h4>\n<p><span>A key metric in the experiment was email acceptance rate, and randomized sending showed a clear advantage. Only 2\u20135% of emails were not received, compared to the 10%+ failure rate observed with grouped sending. Since emails were sent in a steady flow instead of overwhelming the server, Outlook accepted them more consistently.<\/span><\/p>\n<h2>The conclusion: key findings from the experiment<\/h2>\n<p><span>The findings from this research make one thing clear: randomized sending significantly outperforms bulk email sending when targeting Office 365 recipients. By understanding how Outlook\u2019s filtering systems interpret email activity, we can see why a strategic approach to email distribution is essential for long-term deliverability and sender reputation.<\/span><\/p>\n<h4>Inbox placement: more emails landing in the right place<\/h4>\n<p><span>Randomized sending achieved an impressive 80\u201390% inbox placement rate, compared to bulk sending\u2019s 35\u201375%. That means\u2002more emails land in the recipient\u2019s main inbox, where they have a better chance of being opened and acted on.\u00a0<\/span><\/p>\n<p><b>Why this matters:<\/b><span> The greater the number of emails that land in the primary inbox, the more likely they are to be\u2002seen, opened and taken action on\u2014improving engagement and conversion rates.<\/span><\/p>\n<h4>Spam rates: reducing risks of being flagged<\/h4>\n<p><span>Bulk sending saw up to 55% of emails flagged as spam, and randomized sending kept spam rates between 7\u201315%. A major factor here\u2002is the reputation of the sender and avoiding blacklists.<\/span><\/p>\n<p><b>Why this matters:<\/b><span> That\u2019s not just a challenge for\u2002that particular email campaign; every email flagged as spam has a cumulative effect. Once flagged, it\u2019s much more likely that subsequent emails from the same sender will be filtered out as spam as well, making it even harder to reach those intended recipients.<\/span><\/p>\n<h4>Delivery reliability<\/h4>\n<p><span>With randomized\u2002sending, only 2\u20135% of randomized emails were undelivered, versus 5\u201310% in bulk sending. This ensures your messages aren\u2019t lost to throttling or blocking.<\/span><\/p>\n<p><b>Why this matters:<\/b><span>\u00a0 Lost emails result in lost effort,\u2002lower outreach success, and missed chances to reach recipients<\/span><\/p>\n<h4>Recap: why randomized sending works<\/h4>\n<p><span>Randomized sending mimics natural email behavior, which aligns with O365\u2019s spam filters and reputation algorithms. By sending emails in smaller, staggered batches, you avoid triggering red flags associated with high-volume campaigns. This approach not only improves deliverability but also enhances recipient engagement, as emails arrive at more natural intervals.<\/span><\/p>\n<h4>Recap: why bulk sending fails<\/h4>\n<p><span>Bulk sending, while efficient for large campaigns, often backfires with O365. The platform\u2019s filters interpret sudden spikes in email volume as suspicious activity, leading to higher spam placement, throttling, and even temporary blocks. Over time, this can damage your sender\u2019s reputation, making it harder to reach inboxes in the future.<\/span><\/p>\n<h2>The verdict: which strategy wins?<\/h2>\n<p><span>For businesses aiming to maximize email deliverability and engagement with O365 recipients, <\/span><b>randomized sending is the superior strategy.<\/b><span> It\u2019s a minor change that has big\u2002effects: more emails in inboxes, fewer in spam boxes, and better performance all around.<\/span><\/p>\n<p><span>Instead of bulk sending (which poses the\u2002risk of spam filters, blacklisting, and delivery failures), controlled, strategic email distribution guarantees inbox placement success, lower spam levels, fewer delivery failures, and a cleaner sender reputation.\u00a0<\/span><\/p>\n<p><span>With simple modifications in how emails are sent\u2014the business can see improved email marketing effectiveness; providing a boost in open rates,\u2002response rates, and potential improvements in the long run.<\/span><\/p>\n<h2>From experiment to execution: Warmy\u2019s role in email success<\/h2>\n<p><span>The experiment clearly showed that randomized sending triumphs over bulk, grouped sending. But what does this mean for your email campaigns? Getting the email sending strategy down pat is great, but it\u2019s just one factor that affects your overall deliverability\u2014and here\u2019s where <\/span><a href=\"http:\/\/warmy.io\" rel=\"noopener\" target=\"_blank\" rel=\"noopener noreferrer\"><span>Warmy.io<\/span><\/a><span> comes in.\u00a0<\/span><\/p>\n<p><span>Warmy\u2019s platform is built on the very principles our research confirmed: consistency, natural email flow, and smart timing. <\/span><b>Here\u2019s a quick overview of Warmy\u2019s capabilities<\/b><span>:<\/span><\/p>\n<ul>\n<li><span>By harnessing advanced deliverability tools and real-time analytics, Warmy automates the process of \u201cwarming up\u201d email accounts by mimicking natural email activity.\u00a0<\/span><\/li>\n<li><span>It can handle up to 5,000 emails per day while simulating human-like interactions like sending, replying, and marking emails as important.\u00a0<\/span><\/li>\n<li><span>Additionally, Warmy\u2019s new Domain Health hub gives users the ability to monitor deliverability at the domain level. This includes spam rates, inbox placement, and deliverability trends on a weekly &amp; monthly basis.<\/span><\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"Dashboard with Domain Health Overview title. Shows a score of 85. Panels display Mailboxes status, Google Postmaster Metrics, DNS Records, and Inbox Placement Test for Gmail, G Suite, Outlook. Last updated on Sep 24, 2024.\" height=\"585\" src=\"https:\/\/warmy-blog-wordpress-bucket.s3.amazonaws.com\/wp-content\/uploads\/2025\/02\/11093408\/Unavngivet.png\" width=\"779\" title=\"\"><\/p>\n<p><span>For a more comprehensive breakdown of the numbers this experiment churned out, you can download the full report here.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Many organizations suffer the pain of emails ending up in spam folders or being throttled\u2014often because sending practices are widely inconsistent with Outlook 365\u2019s spam filters. At Warmy, our research team continues to do more by figuring out how to get more of your emails delivered, straight to your intended inbox. Our ongoing testing\u2002and analysis [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":4698,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[104],"tags":[],"class_list":["post-4008","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-email-deliverability"],"acf":[],"lang":"en","translations":{"en":4008},"pll_sync_post":[],"_links":{"self":[{"href":"https:\/\/www.warmy.io\/blog\/wp-json\/wp\/v2\/posts\/4008","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.warmy.io\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.warmy.io\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.warmy.io\/blog\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.warmy.io\/blog\/wp-json\/wp\/v2\/comments?post=4008"}],"version-history":[{"count":1,"href":"https:\/\/www.warmy.io\/blog\/wp-json\/wp\/v2\/posts\/4008\/revisions"}],"predecessor-version":[{"id":5474,"href":"https:\/\/www.warmy.io\/blog\/wp-json\/wp\/v2\/posts\/4008\/revisions\/5474"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.warmy.io\/blog\/wp-json\/wp\/v2\/media\/4698"}],"wp:attachment":[{"href":"https:\/\/www.warmy.io\/blog\/wp-json\/wp\/v2\/media?parent=4008"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.warmy.io\/blog\/wp-json\/wp\/v2\/categories?post=4008"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.warmy.io\/blog\/wp-json\/wp\/v2\/tags?post=4008"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}