Consumption Pattern Analysis for Email Campaigns

Email frequency matters more than most marketers assume. An analysis of 53,000 emails and 5,300 purchases across 200 customers revealed a clear pattern: the best results come when brands tailor frequency to buying behavior.  The optimal monthly cadence: ↳ 5-7 emails for frequent buyers ↳ 6-10 for medium buyers ↳ 12-14 for occasional buyers When customers aren’t segmented, 7 emails a month deliver the strongest performance. The highest open rates and most purchases over time. Sending only 4 emails reduces lifetime profit by 32%, while sending 10 cuts it by 16%. The reason is simple. Frequent buyers already know the brand, so too many emails create fatigue. Occasional buyers, on the other hand, read more when they’re still exploring and learning. This makes segmentation strategy the real growth lever. Instead of treating every subscriber the same, match communication frequency to purchase behavior. The balance is all about timing and relevance. The right message to the right segment builds stronger engagement, higher retention, and more revenue over time. How often do you adjust your email frequency based on buyer type?

We analyzed over 27 million cold emails. Here are key insights into mailbox activity and performance: 📊 open rates: - Across all non-agency campaigns globally, the average open rate is 26%. - Open rates remain stable across workdays but drop 6-9% on weekends. 📊 reply rates: - Smaller, highly targeted campaigns (1-50 prospects) have a reply rate nearly 3x higher than mass campaigns with 1001-5000 prospects. - Campaigns with a bounce rate under 2% enjoy a 60% higher reply rate than those with 20%+ bounce rates. - Initial emails have the highest reply rates (~1%), with subsequent follow-ups seeing diminishing returns (30% as effective by the 5th or 6th email). 📈 mailbox volume and performance: - Mailboxes sending 1-20 emails daily have reply rates four times higher than those sending 101-200 emails daily. - 21-50 daily emails see a balanced performance, with over twice the reply rates of high-volume senders. 🔑 key takeaways ↳ Personalized, concise, and well-segmented campaigns drive higher engagement. ↳ Maintaining a low bounce rate and optimizing email volume per mailbox is critical for maximizing results. ↳ Send no more than 3 messages in sequence. Have you noticed similar patterns in your campaigns?

We've just released our latest consumer survey about subscribers' email preferences during the peak sale season, and it’s a serious reality check for marketers. First, demand is high: 67% of consumers want to hear from brands at least weekly during this period. But nearly half unsubscribe because of message overload, meaning the line between engaged and annoyed is razor-thin. When asked what drives unsubscribes, “too many emails” topped the list (43%), followed by “misleading subject lines or fake urgency.” In other words, honesty matters just as much as frequency. Here's one of my favourite findings: 55% of consumers want full transparency about tariffs or price changes in their emails, led by Gen Z (63%) and Millennials (62%). Again, authentic communication builds trust, especially when money is tight. What do people actually want to see in their marketing messages? Early access to sales (66%) and exclusive discount codes (65%). Value and recognition still rule. Lastly, timing matters more than you think. Overall 63% want emails before Thanksgiving, but Baby Boomers (with the most spending power!) are twice as likely as Gen Z to prefer them after. The emphasis during the peak sale season is shifting from sending more to sending better. Focus on trust, transparency, value and timing. Our full data is linked in the comments. How early did you start your Black Friday email campaigns this year — and how are you managing your sending volume and frequency? #EmailMarketing #HolidayMarketing #ConsumerInsights

Multiple times I've onboarded brands where their last agency told them to either: - Send all emails at 6am - Send all emails at 8pm The rationale is always some weird combination of "you'll be the first thing in their inbox in the morning" or "you'll get them when they're shopping at night". Ecom is not so binary. You have many cohorts of customers who shop at different times. And these customers have changing habits throughout the year. Some people are morning shoppers. Some during the work day. Some while they are in the train commuting home. Some after dinner. Some after some 🌿🍸 at 3 in the morning. If all you do is send emails at one fixed time, you're probably only tapping into one slice of your customer's available shopping times. Analyze your site traffic. When do people browse? When do they place orders? How does it change by state? By time zone? By day of week or month? It sounds daunting, but you can more or less analyze this for your brand in ~30 minutes and have 3 or 4 "best" send times to cycle through. When big holidays (like Black Friday) come up, you can always look back at the more specific behavior of that specific day in past years. If you're sending SMS campaigns on the same day as your emails, it's even more important to have this analysis down. It lets you pick the two best times in a day to send to maximize your reach for a campaign. Happy sending 📨

I've been tracking what people actually buy from product highlight campaigns. And what I learned might surprise you... Here's what most people assume happens: You send an email featuring a specific product, people read it, get convinced, and buy that product. But when you look at the actual purchase data, something different is happening. People click through and often buy products you weren't even highlighting. I started noticing this when we began tracking not just campaign revenue, but what specific products people purchased after clicking. A campaign would have good numbers on all the right value metrics. But the featured product wasn't always the top seller from that campaign. Sometimes it wasn't even in the top 3. People were using the email to get back to the site, then buying what they actually needed in that moment. This pattern showed up consistently across different brands and categories. Here's what's actually happening. 80-90% of people buying from your campaigns are existing customers. They already know your products and have formed preferences. When they see your email, they're not looking for a sales pitch about one specific product. They're seeing a message from a brand they trust, and it reminds them to come back and shop. The email functions more like an ad impression than a direct product pitch. It creates awareness, maintains top-of-mind presence, and drives traffic. Once they're on your site, they browse and buy based on their actual needs, which might be completely different from what you featured. This doesn't mean the campaign failed. It means the campaign did exactly what it's supposed to do. Got attention, drove clicks to you, brought customers back to make a purchase. Understanding this has shifted how we build campaigns for clients. Instead of spending hours debating which product to feature or crafting elaborate pitches, we focus on what actually drives results. Creating compelling hooks that get emails opened. Writing opening lines that generate curiosity. Designing emails that make clicking easy. The detailed product pitch matters less than getting people back to the site, because that's where they make their real buying decision. This also simplifies campaign production significantly. You don't need complex segmentation based on predicted product preferences. You don't need ten different versions of the same campaign for different segments. Broader campaigns focused on driving traffic work extremely well and take much less time to produce. This frees up resources to focus on what actually converts. Your product pages need clear descriptions, compelling benefits, strong social proof, and intuitive navigation. That's where customers make purchase decisions, not in the email. Email's job is straightforward: Get opened. Create interest. Drive traffic. Once you understand that's the real function, you can build campaigns that are both more effective and more efficient to produce.

Agency owners: Are you still segmenting email campaigns based on who opened your last few emails? Here's a simple way to make yourself look like a hero to your clients (because you'll make them at least 15% more email revenue). Most email campaigns target based on static rules: - Who opened emails in the last 30 days - Click activity from recent campaigns - General "engaged subscribers" The engagement approach focuses on who interacted recently, which is a helpful signal and good for deliverability. It fails to consider behavioral signals of intent. Behavioral intent signals work differently. Instead of asking "who engaged?" they ask "what's the likelihood this person would buy right now?" These AI predictive segments update in real-time based on behavioral intent shown by shoppers like: - Price sensitivity from past purchases - Pattern matching against your highest-value customers - Category browsing patterns that predict purchase timing - Which sources drive best results This creates a massive difference in targeting. Your customer who engaged heavily 25 days ago might be completely uninterested today. Meanwhile, someone who hasn't engaged for 60 days just came to your site and fits the exact profile of customers who make their second purchase around this timing. AI (Machine learning) makes this possible by analyzing customers that show similar behaviors, buying timing, and price sensitivity. The impact is undeniable. One customer of ours saw a 321% increase in revenue per recipient (full transparency - the actual number was WAY more but 321% already sounds crazy). Most agencies stick with engagement-based campaigns because they're easy and "safe." But with predictive segments there's TWO really simple plays: 1. Send the emails you're already sending to these predictive segments and make more money 2. Send more tailored emails to these predictive segments and make EVEN MORE money Either way, you drive more incremental revenue for your client and look like a hero. Drop a comment: Have you tested segments outside of engagement or static rules? What results did you see?