The 120,000-Contact List That Stopped Opening
Trailhead Supply sells hiking gear online to 120,000 email contacts and sends four campaigns a week to the entire list, each featuring a different product category. Over 12 months the average open rate fell from 31% to 18% and click rate to 0.9%, while spam complaints sit at 0.08%. About 45% of contacts have not opened anything in 12 months, and hard bounces run 2.1% per send. Last quarter the growth team imported a 10,000-contact list bought from a sweepstakes partner without any re-permission step. The only automated email is a single welcome message sent immediately at sign-up. Email drives 14% of revenue. To grow that number this quarter, the team proposes doubling send frequency to eight campaigns a week, arguing that more sends mean more chances to click.
1. Assess the frequency proposal and lay out the sequence you would run instead.
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Doubling to eight sends a week to a list where 45% of contacts are dormant and 10,000 never consented will accelerate the damage already visible: complaints at 0.08% are near the 0.1% threshold mailbox providers watch, and bounces at 2.1% are above the 2% level that triggers reputation problems. More sends to unengaged addresses mostly generate deletions, complaints and spam-trap hits, which push the whole domain's deliverability down, including for the engaged subscribers who actually buy.
Sequence, in order: (1) quarantine the purchased 10,000 and either drop them or send one explicit re-permission email that excludes them from all other sends - purchased lists generally violate the consent standards of major mailbox providers; (2) build engagement segments on clicks, not opens, since open rates are inflated by privacy features that pre-fetch images; (3) run a three-email win-back to 12-month non-openers with a real incentive, then suppress anyone who still has not clicked; (4) set frequency by segment - engaged get three a week, lapsed get one; (5) rebuild the welcome flow. Expect the list to shrink by 35-45% and revenue per send to rise. Track complaints, bounce rate and revenue per recipient, not open rate.
2. Redesign the welcome series: how many emails, what timing, and one job per email.
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Four emails across the first 14 days, each with a single primary call to action and one job.
Email 1, sent immediately: deliver the promised value and the bestseller, confirm what the subscriber will receive and how often, and offer a frequency preference link. Its job is to be opened, not to sell hard, because the first message sets the sender reputation for everything after it.
Email 2, day 2: the gear guide or sizing help. Its job is to be useful and establish expertise, which is what separates Trailhead from the discount sites.
Email 3, day 5: social proof - reviews, a customer story, and a first-purchase incentive with a stated expiry if margin allows. Its job is conversion. A 65%-margin product can absorb a modest offer; a thin-margin one cannot, so check the numbers before including one.
Email 4, day 12: branch on behaviour. Opened or clicked the hiking boot content, get boots; otherwise get the top category. Its job is relevance.
Measure the flow on 30-day revenue per new subscriber against a holdout group that receives only the single legacy welcome email. Do not judge it on open rate, and suppress anyone who never clicks after the flow ends.
3. Design the first A/B test, including the variable, the split, and the guardrails.
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Test frequency, because it is the disputed decision and the one with the largest downside if wrong. Take the engaged segment - subscribers who clicked at least once in the last 90 days, perhaps 55,000 people. Randomly split 20,000 of them into two equal groups of 10,000 and leave the rest untouched as a safety buffer. Group A receives two campaigns a week for four weeks; group B receives four. Everything else is held constant: same templates, same products, same send days, same time of day.
Primary metric: revenue per recipient over the four weeks, which accounts for both click rate and unsubscribes. Guardrails: spam complaint rate below 0.1%, unsubscribe rate, and hard bounce rate - any of these breaching means the test stops early regardless of revenue.
Run the full four weeks before deciding; frequency effects accumulate and a one-week read will mislead. Then apply the winning cadence to the engaged segment only, and keep the lapsed segment on a lower frequency. One variable per test: do not change subject-line style in the same test, or you will not know which change moved the number.