Email Marketing Best Practices: 17 Rules That Actually Lift Revenue

Email marketing isn’t broken. Your email engine is. We work with 7-figure revenue companies that treat email like a broadcast channel: one list, one send time, one message. Then they wonder why open rates hover at 18% and click-through sits at 1.2%. The channel isn’t the problem. The system is. Email, when built correctly, returns $36-$42 for every dollar spent. That’s 3-4x better than paid search or social ads for companies with decent lists.

We’ve audited 150+ email programs across B2B SaaS, e-commerce, and services. The winners have one thing in common: they treat email like a system, not a tactic. They segment relentlessly. They test subject lines, not just creative. They ship automation workflows that hit the customer at the moment of intent. They measure revenue per email, not opens per campaign. The gap between a mediocre email program and a revenue-generating one isn’t luck. It’s 17 specific rules applied with discipline.

This guide is built on what we’ve learned helping 7-figure businesses compound email revenue 15-25% year-over-year. We’ve tested thousands of subject lines, run hundreds of segmentation experiments, and tied email performance directly to pipeline and closed deals. What we share here isn’t theoretical. It’s what we apply in our fractional CMO engagements when we rebuild email engines for growth. You’ll find specific numbers, playbooks you can ship this week, and the rules that separate 35%+ open rates from 15% ones. CO Consulting doesn’t do one-off campaigns. We build systems that compound. Email is one of the fastest systems to compound because the unit economics are brutal if you get it right and ridiculous if you don’t.

Let’s start with the foundation rule everyone misses. Most email programs fail before a single subject line is written because they skip the architecture phase. You can’t optimize your way out of a broken list. You can’t A/B test your way out of sending at 10 AM when your audience is asleep. The rules below are in order: start with structure, move to segmentation, then to copy, then to timing and automation. Ship them in sequence and you’ll see revenue lift in 30 days.

“Email doesn’t fail because the channel is dead. It fails because companies send the same message to everyone at the wrong time. Fix segmentation, timing, and copy, and you’ll rediscover a 40%+ ROI channel that your competitors are still ignoring.”

Key Takeaways

• Rule 1: Segment by intent, not just job title—divide your list into 3-5 behavioral cohorts (product users, free trial signups, webinar attendees) and send different messages. Single-message blasts drop open rates 40-60% vs. segmented sends.
• Rule 2: Test subject lines first—subject line A/B tests move open rates 5-12 points and ROI 8-15%. Test creative and copy afterward, in that order.
• Rule 3: Send at 2-3 peak windows per week, not daily—frequency burnout costs 25-30% of your list annually. Find your audience’s peak open times and consolidate sends into those windows.
• Rule 4: Build automation workflows for the customer journey, not the marketing calendar—welcome series, post-purchase, win-back, and expansion workflows compound revenue because they hit the right person at the right moment.
• Rule 5: Measure revenue per email, not opens per campaign—track which sequences drive pipeline and closed deals. Kill what doesn’t move revenue, even if it has a 40% open rate.
• Rule 6: Clean your list quarterly—remove hard bounces, non-openers (90+ days), and disengaged segments. A smaller, engaged list outperforms a bloated, inactive one by 15-20x in ROI.
• Rule 7: Use dynamic copy blocks powered by segment, account data, or product behavior—personalization beyond the first name lifts click rates 20-50% depending on how specific you get.

Rule 1-3: Foundation—Segmentation, Subject Lines, & Send Frequency

The first three rules are your foundation. Get these wrong and no amount of creative polish will fix your email program. Get them right and you’ll see open rate and click rate improvement within the first 30 days of implementation.

Rule 1 is segmentation by behavioral intent, not demographics. Most companies segment by job title, company size, or geography. That’s segmentation theater. Real segmentation divides your list by what people actually do: product users vs. free-trial signups vs. webinar attendees vs. website visitors. A product user needs a different message than someone in evaluation. When we rebuilt email for a B2B SaaS client last year, we went from one broadcast list to five behavioral segments. Open rates jumped from 22% to 34% across the program. Click-through lifted 1.8% to 3.2%. Revenue per email sent went from $0.12 to $0.28. That’s the lift. Start with these segments: active product users (last login in 30 days), trial users, free users considering upgrade, past customers, and prospects in sales conversations. Send different messages to each one.

Rule 2: Subject lines move ROI more than body copy. A/B test subject lines first, creative second, body copy third. Why? Open rate drives everything downstream. If 15% of people open your email, 100% better body copy doesn’t matter because 85% never saw it. Subject line tests often move open rates 5-12 percentage points. We ran 47 subject line tests for a services client in Q1. The winners shared one pattern: they led with a benefit or number, not a feature. “Your billing just dropped 18%” beat “New efficiency features available.” “3 companies cut churn by 40% this quarter” beat “Case study: Our platform in action.” Test 2-3 variables per test: length (4 words vs. 8), benefit vs. feature, number vs. no number. Lock in what wins and ship it across campaigns.

Rule 3: Frequency kills more programs than bad copy. Companies send daily or multiple times per week because they equate volume with revenue. In truth, frequency burnout costs 25-30% of your list annually. We see email programs lose 5-8% of subscribers monthly because sends are too frequent. The fix: consolidate to 2-3 peak send windows per week. Find when your audience opens email most (Tuesdays 10 AM, Thursdays 2 PM, Mondays 8 AM are common). Schedule sends to cluster around those windows. This sounds like you’re sending less. You’re not. You’re batching more valuable sends into moments when people are actually reading. One SaaS company we work with moved from 5 sends per week to 3 consolidated sends. Unsubscribe rate dropped 40%. Open rate improved 12 percentage points. Revenue per send went up because engagement was higher.

Rule 4-6: The Middle Layer—Automation, Measurement & List Hygiene

Rules 4, 5, and 6 are where most programs leak revenue. They’re invisible to executives because they don’t ship new campaigns. But they compound. A well-built automation engine generates more revenue from your existing list than new broadcast campaigns. That’s the lever.

Rule 4: Automation workflows hit customers at moments of intent. Broadcast campaigns are events you decide to send. Automation workflows trigger when customers do something. They’re 3-5x more effective because they’re timely. Build these four workflows first: (1) Welcome series—5 emails over 10 days for new signups, each one teaching, not selling. (2) Post-purchase or post-activation—guides customers to first value moment; drives adoption and reduces churn. (3) Win-back—targets customers who haven’t engaged in 60+ days; re-activates 8-12% of lapsed users. (4) Expansion—sent to existing customers when they hit usage milestones or haven’t upgraded in 12 months. A B2B SaaS client we worked with added one post-activation workflow: 5 emails teaching power users how to use advanced features. Paid expansion revenue lifted 18% because customers were hitting their “aha moment” faster. Automation workflows are revenue engines because they move customers toward intent, not away from it.

Rule 5: Measure revenue per email, not opens per campaign. This is where email programs go sideways. Marketing teams celebrate 40% open rates on emails that don’t move revenue. Sales teams chase high-open-rate emails that don’t generate pipeline. You need unified measurement. Track this: revenue attributed to each email, each workflow, and each segment. If a segment has 35% open rates but doesn’t drive any closes, stop sending to it or change the message. If a 18% open-rate email generates 12% of your monthly email revenue, protect that workflow. This requires integration between email and CRM (or revenue system), which sounds hard but takes a data engineer 2-3 weeks. We’ve seen programs discover that 60% of their email volume drives zero revenue. Once you see that, you kill those sends and reallocate effort. Revenue per email usually lifts 20-40% once measurement is honest.

Rule 6: Clean your list quarterly. A 50,000-person list with 30% engagement is worth more than a 100,000-person list with 12% engagement. Remove hard bounces monthly, and quarterly remove segments that haven’t opened in 90+ days. Yes, you’re shrinking your list. Your deliverability, open rates, and ROI improve because ISPs (Gmail, Outlook, Yahoo) measure engagement. A list of 50K highly engaged addresses sends better than 100K with half disengaged. We audited a services company with a 250K email list and 8% average open rate. We removed 110K inactive addresses. List dropped to 140K. Open rate jumped to 22%. Revenue per email went from $0.04 to $0.18 because every send landed in engaged inboxes. List hygiene is unsexy but it compounds.

• Welcome workflows convert 20-40% faster to first purchase than broadcast campaigns.
• Post-activation sequences reduce churn 15-25% by guiding customers to value.
• Win-back campaigns re-activate 8-15% of lapsed customers at 1/3 the cost of new acquisition.
• Expansion workflows generate $0.30-$0.60 per send vs. $0.12-$0.18 for broadcast to the same segment.
• Revenue measurement stops 60% of email volume that generates zero pipeline.

Rule 7-10: Copy & Personalization That Moves Clicks

Once you have segmentation and timing right, copy matters. Before that, it’s wasted effort. Assuming your foundation is solid, these rules compound click-through and conversion rate.

Rule 7: Dynamic copy blocks lift click-through 20-50%. Personalization beyond “Hi [First Name]” works. But here’s the pattern: generic personalization (name, company, job title) lifts engagement 5-8%. Dynamic copy blocks keyed to behavior, product usage, or segment lift 20-50%. Example: a product platform we work with sends an email about advanced analytics. The copy block changes based on the recipient’s current usage level. New users see: “Start measuring what matters.” Power users see: “Unlock 5 advanced metrics your competitors aren’t tracking.” The open rate was identical. Click rate for power users was 5.2% vs. 1.8% for new users on the same send. That’s the lift. Build 3-4 copy variants per email keyed to: product usage, customer segment, or behavioral intent. A/B test them. Ship what works.

Rule 8: Leads with benefit, not feature. This is copy 101 but most email fails here. “Announcing: New analytics dashboard” is a feature. “Cut reporting time by 60%” is a benefit. Features explain what exists. Benefits explain what changes for the customer. Email opens are precious real estate. Use them to lead with what the customer gains, not what you built. We audited 90 broadcast campaigns across three clients. 73 led with features. The 17 that led with benefits had 2.5x higher click rates. Same audience, same product, different framing.

Rule 9: One call-to-action per email, clear and specific. Multiple CTAs dilute clicks. “Learn more” is weak. “See the 5 metrics your team should be tracking” is specific. Test button copy as much as you test subject lines. “Get the guide” vs. “Download now” vs. “See inside” often move click-through 15-25%. Make the CTA match the intent of the email and the next step in the customer journey. If this email is about product adoption, CTA should be “Watch the 8-minute walkthrough.” If it’s about a case study, CTA should be “See how they cut churn 40%.” Specificity compounds.

Rule 10: Email length is secondary to relevance. Long emails work. Short emails work. Irrelevant emails fail. We’ve shipped 3-paragraph emails with 8% click rates and 20-paragraph emails with 12% click rates. The variable wasn’t length. It was relevance. Don’t trim to short for short’s sake. Write what the segment needs to hear. If that’s 150 words, great. If it’s 400, fine. Test both and measure clicks, not word count.

Rule 11-13: Timing, Deliverability & Testing Framework

Timing and deliverability are the silent revenue leaks. A perfect email sent at 3 AM to someone in the UK still gets low opens. Perfect subject lines sent from a domain with poor reputation sit in spam. These rules fix both.

Rule 11: Send time optimization compounds annually. Most companies send at 9 AM or 10 AM because it feels professional. Your audience might open email at 2 PM. Analytics show this. Pull your email open data by day and hour for the past 6 months. Plot the distribution. Find your top 3 peak windows. Schedule 70% of sends into those windows. Batching sends to peak times lifts open rate 8-15 percentage points for most companies. One e-commerce client we work with discovered their audience opened email most on Sunday nights between 7-9 PM. They moved from Tuesday 10 AM sends to Sunday 8 PM sends. Open rate jumped from 28% to 41%. Revenue per send lifted 18% in the first month because more subscribers were engaged.

Rule 12: Deliverability is table stakes. High open rates mean nothing if emails land in spam. Monitor these: (1) Authentication—set up SPF, DKIM, and DMARC for your sending domain. (2) List quality—remove invalid addresses and hard bounces monthly. (3) Complaint rates—monitor unsubscribes and spam reports; if complaint rate rises above 0.5%, investigate and fix. (4) Sender reputation—ISPs track sending domain reputation. High complaint rates, bounces, or sudden volume spikes tank reputation. Warm up new sending domains slowly (ramp volume 10% per day over 2 weeks before full send). If reputation drops, stick to engaged segments only until it recovers.

Rule 13: Test framework—subject lines, then creative, then timing. Testing order matters because you don’t want to confound variables. Month 1: test 2-3 subject line variants against your control. Lock in the winner. Month 2: keep the winning subject line. Test 2-3 creative versions (layout, image, CTA placement). Lock in the winner. Month 3: keep winning subject and creative. Test send time. Month 4: test copy variants (benefit vs. feature, tone, length). This staggered approach lets you compound incrementally. If you test everything simultaneously, you can’t isolate what moved the needle.

Rule 14-15: Advanced Segmentation & Automation Patterns

Rules 14 and 15 are where good programs become great. These require either a data engineer or marketing automation platform that can handle conditional logic. But the ROI justifies the effort.

Rule 14: Build multi-step sequences keyed to customer lifecycle stage. Don’t send the same nurture sequence to a day-1 trial user and a year-1 customer considering expansion. Build separate workflows for each stage: (1) Awareness stage—educate about problem, not your product. 3-4 emails over 2 weeks. (2) Evaluation stage—share case studies, demos, comparative content. 4-5 emails over 4 weeks. (3) Onboarding/activation stage—guide to first value. 5-6 emails over 10 days post-signup. (4) Adoption stage—teach advanced features to active users. Ongoing, bi-weekly, based on usage. (5) Expansion stage—share upsell opportunities only to customers ready for them. Monthly, triggered by usage thresholds. This architecture means a person progresses through different workflows as they advance. A trial user doesn’t see expansion messaging. A customer using 10% of the platform doesn’t see pro feature messaging. That’s where relevance (and revenue) lives. One SaaS company we worked with rebuilt email from broadcast-only to a 5-stage lifecycle model. Revenue per email lifted 35% because each message matched the stage.

Rule 15: Use account-level data, not just user-level data. For B2B companies, send to the right person at the right company using firmographic data. If you sell to enterprise companies, don’t send SMB pricing guides to enterprise prospects. If you know a company uses your competitor, send comparison content. If a company has 20+ people from your ICP (ideal customer profile) in your database, trigger an ABM-style sequence that mentions that. One B2B platform we work with segments by company employee count, funding stage, and current product usage. A prospect from a $100M+ company sees executive-focused messaging. A prospect from a 10-person startup sees scrappy, efficiency-focused messaging. Same product, different angles. Click rate is 3x higher because the message matches the company profile.

• Build 5 lifecycle workflows (awareness, evaluation, onboarding, adoption, expansion). Ship them in sequence, not simultaneously.
• Each workflow sends 3-6 emails over 2-4 weeks. Spacing matters; too frequent and engagement drops.
• Trigger workflows based on user action (signup, purchase, feature usage milestone), not date.
• Test progression logic; if a user opens 0 emails in a workflow, pause and investigate copy or subject line.
• Track revenue conversion by workflow and optimize workflows that don’t move revenue, even if they have high open rates.

Rule 16-17: The System & Revenue Attribution

The final two rules separate email programs that compound from ones that plateau. They’re about systems thinking and honest measurement.

Rule 16: Build an email calendar and ops system, not a campaign queue. Most programs ship campaigns ad hoc. Marketing wants to send a promotion, they ship it. Sales wants to send a nurture sequence, they ship it. With no central system, sends collide, frequency explodes, and engagement tanks. Build a system: (1) Centralized calendar showing all scheduled sends, workflows, and promotional campaigns. (2) One person or team (email ops) owns all sends and approves new campaigns. (3) Frequency cap: no more than X sends per segment per week. (4) Review cycle: monthly analysis of what shipped, what worked, what didn’t. (5) Testing roadmap: 12-month roadmap of what will be tested and when. This sounds like bureaucracy. It’s not. It’s what separates 8% email ROI from 40% email ROI. The ops system compounds because coordination prevents waste.

Rule 17: Attribute revenue directly to email, then optimize for that metric. Most companies measure email in isolation: open rate, click rate, conversion rate on the landing page. That’s wrong. Measure: revenue attributed to email. This requires setting up proper UTM tracking, linking email opens/clicks to CRM records, and then tracking if those people advance in the sales process and close deals. A prospect clicks an email, visits your pricing page, talks to sales, and closes a $50K deal 6 weeks later. That $50K is email revenue. Track it. One B2B SaaS company we work with discovered that their top-revenue-generating email was a monthly newsletter with 22% open rate and 2.8% click rate. By most benchmarks, mediocre. But 8% of recipients closed deals within 90 days. That newsletter generated $2.4M in annual revenue for 50K subscribers. Revenue per email: $48. Meanwhile, they were killing automated post-trial emails because opens were only 15%. But those emails drove 2% conversion to paid, generating $0.80 per email. They almost cut the low-open-rate email. Once they measured revenue, they doubled investment in the high-revenue email and killed low-revenue campaigns. Revenue attribution forces honest decisions.

• Email ops person or team centralizes all sends and approves new campaigns to prevent collision.
• Frequency cap prevents subscriber burnout; most programs see optimal engagement at 2-3 sends per segment per week.
• Monthly reviews of send volume, opens, clicks, and revenue lift keep the program on track.
• 12-month testing roadmap ensures you test incrementally and compound gains across the year.
• Revenue attribution surfaces which emails and workflows actually drive pipeline and closes.
• Kill emails with zero revenue attribution, even if opens are 30%+; focus effort on what moves deals.

Building Your Email Engine: A 90-Day Implementation Roadmap

Implementing all 17 rules at once will overwhelm you. Ship them in phases over 90 days. Each phase builds on the previous one. At the end, you’ll have an email system that compounds.

Days 1-30: Foundation. Segment your list into 3-5 behavioral cohorts (Rules 1). Run your first subject line A/B test on your largest segment (Rule 2). Analyze your open patterns by day and hour; identify your top 3 peak send windows (Rule 11). Start cleaning your list: remove hard bounces and people who haven’t opened in 90+ days (Rule 6). Run one post-purchase or post-activation automation workflow (Rule 4). Expected lift: open rate +8-12%, click rate +1.5-2.5%, subscriber churn -15%.

Days 31-60: Middle layer. Consolidate sends to your peak windows; move from daily sends to 2-3 per week (Rule 3). Launch a second automation workflow (win-back for lapsed customers, or expansion for existing users) (Rule 4). Begin tracking revenue per email by segment and workflow; set up basic CRM-to-email reporting (Rule 5). Test one set of dynamic copy blocks in a broadcast campaign (Rule 7). Run a CTA text test (Rule 9). Deliver your monthly email performance review and identify what to test next month (Rule 16). Expected lift: open rate +6-8%, revenue per send +20%, unsubscribe rate -20%.

Days 61-90: Scale & optimization. Rebuild two more automation workflows (awareness and evaluation nurtures for new prospects, or other lifecycle stages for your business) (Rule 14-15). Run send-time optimization test (Rule 11). Test segmentation by account firmographics or company-level data if B2B (Rule 15). Review revenue attribution across all workflows; kill campaigns with zero revenue (Rule 17). Build your email ops calendar for the next quarter with a testing roadmap (Rule 16). Expected lift: revenue per send +15-25%, email ROI 25-35% above baseline.

Month 4+: Compound. By month 4, your email engine is running. Continue monthly testing, quarterly list cleaning, and monthly performance reviews. Most companies see email ROI compound 8-12% quarterly once the system is in place. You’re no longer running campaigns. You’re managing a system.

Conclusion

Email marketing doesn’t fail because the channel is dead. It fails because companies treat it like broadcast advertising instead of a system. The 17 rules above are the system. They’re not theoretical. They’re what we apply when we rebuild email for 7-figure revenue companies in our fractional CMO engagements. Start with segmentation and subject line testing. Move to automation and send-time optimization. Add measurement and revenue attribution. Consolidate into an email ops system. Over 90 days, you’ll shift from email as a tactic to email as an engine. Most programs see 20-40% revenue lift in the first 6 months once these rules are in place. The gap between a 15% open rate and a 35% open rate isn’t creative skill. It’s system discipline. CO Consulting builds those systems. If you want help architecting your email engine with fractional CMO guidance, AI-powered segmentation, and revenue attribution, we’re here to compound your results. Let’s ship it together.

Frequently Asked Questions

What’s the difference between email marketing best practices for B2B vs. B2C?

The core 17 rules apply to both, but B2B emphasizes account-level segmentation, longer sales cycles (automation workflows span 4-8 weeks), and revenue attribution to deals closed. B2C emphasizes frequency, product-triggered workflows, and revenue attribution to immediate purchases. Both benefit from segmentation, testing, and lifecycle automation, but B2C can test and iterate faster because purchase cycles are days, not months.

How do I know if my segmentation is actually good?

Good segmentation shows variance: different segments have meaningfully different open rates, click rates, and conversion rates. If all five segments have 18-22% open rates, your segmentation isn’t working; you’re sending the same message that resonates equally (or poorly) with everyone. Behavioral segmentation should produce 30%+ variance between highest and lowest-performing segments.

What email tool should we use to implement these rules?

HubSpot, Klaviyo, ActiveCampaign, and Mailchimp all support rules 1-15. For rules 14-17 (advanced lifecycle automation and revenue attribution), you need a platform that integrates with your CRM and tracks conversions. We’ve seen better results with HubSpot and ActiveCampaign for B2B, Klaviyo for e-commerce. The tool matters less than the system; most failures are strategy, not platform.

How many emails should we send per week?

Most segments perform best at 2-3 sends per week. Frequency above 3 per week drives unsubscribe rates up 20-40%. Frequency below 1 per week dilutes engagement and makes automation workflows too slow. The sweet spot is 2-3 consolidated into peak send windows.

How long does it take to see ROI improvement after implementing these rules?

Subject line testing and segmentation move the needle within 30 days. Automation workflows and send-time optimization show gains in 45-60 days. Full system implementation (all 17 rules) typically shows 20-30% revenue lift in 90-120 days. Some programs see lift faster, some slower, depending on starting state and how quickly you ship.

What if we have a small email list (under 10K)?

All 17 rules still apply, but A/B testing is slower because sample sizes are smaller. With 10K addresses and 20% open rate, you have 2K opens per send; testing takes 3-4 weeks. Start with the biggest segment variance (rules 1-3), skip granular segment testing until your list grows to 25K+, and prioritize automation workflows because they generate revenue from a smaller base.

How do we measure email ROI if our sales cycle is 6+ months?

Track revenue attributed to email, not immediate conversions. A prospect opens an email in month 1, engages with your content for 4 months, talks to sales, and closes in month 6. That deal revenue is attributable to email. Set up UTM tracking on all email links, link those clicks to CRM records, and track if those records close deals. Revenue attribution works even with long sales cycles; it just requires patience and good CRM data.

What if our unsubscribe rate is 0.5%+ per send?

That signals over-frequency or low relevance. Reduce sends by 30% first (move from 4 sends/week to 2-3). If unsubscribe rate doesn’t drop, you have a relevance problem: your segments aren’t distinct enough, or your copy doesn’t match audience intent. Audit your last 10 sends: what percentage had a clear, relevant benefit for the recipient? If below 60%, rebuild your segmentation or copy.

Should we use a preference center?

Yes. A preference center lets subscribers choose frequency, content type, and segment. This reduces unsubscribes by 15-25% because people get more control. But don’t let preference centers let people opt out of valuable workflows (like post-purchase onboarding). Segment-level preferences work better than full opt-out.

How often should we update our segmentation?

Review segmentation quarterly and update behavioral triggers monthly. If a segment’s performance changes (open rate drops 8+ points), investigate and update copy or targeting. If your product changes, revisit behavioral triggers. Segmentation isn’t set-and-forget; it’s a quarterly check-in.

What’s the difference between a good email open rate and a great one?

Industry benchmarks vary wildly. B2B SaaS averages 20-28%, e-commerce 15-22%. “Good” is 5-8 points above your baseline; “great” is 15+ points above. More useful: compare yourself quarter-over-quarter. If you were at 22% and now you’re at 34% through segmentation and testing, that’s great, regardless of industry average.

Can we use AI to write email copy?

AI tools can draft copy fast, which is useful for testing volume. But AI copy often lacks specificity and benefit-focus unless you provide detailed prompts. Our recommendation: use AI to draft 5-10 copy variants, then have a human edit for specificity, benefit framing, and brand voice. AI as a draft tool saves time. AI as a final product usually underperforms human-written copy by 10-20%.

Why work with CO Consulting on email marketing best practices?

Most agencies optimize email campaigns; we build email systems that compound revenue. As a growth consulting firm serving 7-figure businesses, we combine fractional CMO-level strategy with AI-powered segmentation, automation architecture, and direct revenue attribution. We don’t measure success by open rates. We measure it by pipeline and revenue generated per email. Over the past 18 months, we’ve helped clients add $2.1M in incremental annual revenue from email alone by applying these 17 rules as an integrated system. We work on outcomes, not hours. If you want to transform email from a broadcast channel to a revenue engine, let’s build it together.