Jason McCormick writes about DTC marketing, with a focus on email retention, customer journeys and using AI in marketing activities. His posts discuss practical tactics such as timing replenishment emails and tailoring winback messages to lapsed customers.
Jason McCormick writes about DTC marketing, especially how brands guide customers from first awareness to repeat purchase.
Their posts turn broad marketing problems into practical choices: match a message to the customer’s stage, time a reorder email to buying behavior, and make winback messages specific to a customer’s past purchase.
They also connect marketing operations with brand voice, arguing that teams can systematize production without making communication feel impersonal.
This is useful reading for people looking to make customer journeys more relevant rather than relying on generic campaigns.
McCormick’s distinctive contribution in these posts is linking a marketing principle to a decision a team can act on.
In the funnel post, the four awareness stages call for different messages: name a problem before introducing a product, then show why a known product is different.
In the retention posts, they move from the general goal of repeat purchase to concrete choices: examine customers’ reorder cycles, consider a message three to five days before the expected window, and speak to lapsed buyers about what they previously purchased rather than sending the same discount to everyone.
They present those timings as patterns to test, not guarantees.
The exception is their writing on AI and brand voice, which focuses more on judgment: use AI for research and variations, but keep people responsible for taste and meaning.
Together, these posts offer a practical perspective on DTC funnels, email retention, and marketing systems.
Jason McCormick’s DTC marketing ideas center on matching the message to the customer’s moment.
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Advertising should reflect how much a customer understands the problem and product, while retention messages should respond to purchase history and likely reorder timing. McCormick’s posts also distinguish what AI and systems can scale—research, options and process—from what people should protect: judgment, brand voice and personality.
Match the message to the customer’s stage
In “Nobody cares about your product.
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Not yet, anyway,” McCormick lays out four stages of awareness, each with a different job for the message.
Name the problem before introducing a product; use benefits, comparisons and proof when people are weighing solutions; show how the brand differs when they know it; and evoke life after purchase when they are ready to buy.
These stages belong in one continuous story, not disconnected campaigns.
McCormick also warns that audiences narrow and ads become more expensive further down the funnel, making early emotional groundwork important.
The post’s four-stage framework contrasts an emotional, product-free message for someone who cannot yet name their problem with proof for someone comparing solutions. At the point of purchase, it returns to emotion: what will life look like after buying?
McCormick argues that the first purchase is a transaction, while the second begins a relationship.
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Rather than relying on a generic welcome sequence or repeated full-list promotions, use purchase behavior to anticipate when a customer may return.
For consumables, that window is often around 30 days; McCormick suggests sending a relevant, triggered message three to five days beforehand.
For lapsed customers, acknowledge the gap, refer to what they bought and give them a concrete reason to come back instead of sending another generic discount.
One post contrasts a reorder message sent shortly before a customer’s expected purchase window with a broadcast to the whole list. Another contrasts a generic 10% discount with a winback message that recognizes the customer’s previous purchase and time away.
McCormick describes AI as an operational layer for marketing research and variation—not a substitute for human judgment.
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Examples include competitor-ad analysis, identifying hook patterns, generating landing-page variations and developing creative briefs.
The failure mode is treating AI as a vending machine and publishing generic output without human selection or shaping.
McCormick’s proposed division of labor: use AI to improve inputs and generate options, while people bring taste, emotional intuition and judgment.
McCormick contrasts AI-assisted competitor analysis and copy variations with the human work of deciding what feels right. Posting prompt-in, content-out material as-is, they argue, can make AI output feel generic.
McCormick sees structure as necessary for scaling content, but warns that systems can flatten the voice that makes a brand distinctive.
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Organize processes—such as naming conventions, approvals and publishing cadence—without turning a founder’s voice into a checklist. This complements McCormick’s view of AI: use tools and workflows to support the work while protecting the human qualities audiences notice.
The post contrasts an airtight file-naming convention with a founder’s voice that should not sound as if it went through a committee. Its rule of thumb: systematize the process, never the personality.
See how McCormick connects message choice to customer awareness—and what to say before asking an unfamiliar audience to buy.
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McCormick breaks the customer journey into four stages: problem aware, solution aware, product aware and most aware.
Each calls for a different message: name the problem before introducing a product; use benefits, comparisons and proof when customers consider solutions; show specific differences when they know the product; and return to the feeling of life after purchase when they’re ready.
They also point out that audiences get smaller and ads more expensive further down the funnel, so relying on bottom-funnel ads to explain the problem can be costly.
For brands planning a campaign
For a lifecycle or funnel workshop, map each message to the customer’s awareness stage before choosing creative or spend. The post offers a discussion framework, not a tested campaign case study or performance figures.
See McCormick’s practical approach to repeat purchases: when a brand might contact a customer after the first order, and why a behavior-based trigger may beat a generic broadcast.
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McCormick focuses on the gap after acquisition: brands may optimize the first order, then send a generic welcome sequence or go quiet.
For consumables, they say repurchase timing can follow a predictable cycle, often around 30 days, and recommend sending a relevant, behavior-triggered message three to five days before the expected window.
Treat this timing as a starting point, not a guarantee for every product.
For brands planning a campaign
For a retention talk or workshop, have teams inspect reorder timing by product and build a message for the likely replenishment window. Treat the suggested timing as a hypothesis to test against each brand’s purchase data.
See McCormick’s clearest example of tailoring a message to an existing customer—and what a winback email can do beyond offering everyone the same discount.
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The post distinguishes lapsed customers who have already bought from prospects who have not.
Instead of sending both groups the same promotion, McCormick recommends acknowledging the time away, referring to the customer’s prior purchase and giving a specific reason to return.
The central example: a winback message that feels like a conversation rather than a full-list discount email.
For brands planning a campaign
Use this example to assess whether a retention program separates at-risk customers from the full list and uses purchase history in winback messages. The post advocates this approach; ask for measured lift or a specific brand case before treating it as proven.
See how McCormick thinks about scaling marketing without flattening a brand’s personality: which parts of content production can be standardized and which need to remain recognizably human.
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McCormick frames a tension: brands need systems to scale content, but rigid processes can make the brand voice feel impersonal.
They suggest systematizing production details such as naming conventions and approval steps while protecting human elements—such as a founder’s voice and informal behind-the-scenes content—from becoming committee-written.
The concrete contrast makes the advice easier to apply than a general call to “be authentic.”
For brands planning a campaign
For a brand considering a content or lifecycle-marketing workshop, use this to separate repeatable production steps from decisions that need a distinct human voice. Ask for evidence of improved results before treating the approach as proven.
See McCormick’s view of where AI fits in a marketing team: how to use it for analysis and options without treating generated copy as finished brand communication.
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Rather than treating AI as a replacement for marketers or a way to generate finished posts, McCormick describes it as support for research and production tasks: competitor-ad analysis, hook-pattern identification, landing-page variations and campaign requirements. They assign people the work of judgment, taste and emotional interpretation, arguing that stronger inputs matter more than publishing raw AI output.
For brands planning a campaign
For a workshop on AI-assisted marketing operations, ask teams to identify research and variation tasks AI can accelerate, then define who reviews the results and makes brand and audience judgments. Ask for outcomes from a specific approach before assessing its effectiveness.
McCormick argues that most DTC brands run product-feature ads at people who have not yet accepted they have a problem.
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They split the funnel into four stages, each with a different job: problem-aware buyers need their problem named in emotional terms, without a product pitch; solution-aware buyers respond to benefits, comparisons and proof; product-aware buyers need differentiation through specificity; and most-aware buyers are ready and respond to emotion again, specifically what life looks like after purchase.
They add a cost point: audiences shrink and ad prices rise as you move down the funnel, so skipping the emotional work at the top means paying premium prices to close cold customers.
Their recommendation is one continuous story told in the right order, not disconnected campaigns for each stage.
Names each stage, explains what the customer knows at that point and assigns the message type that fits, rather than treating the funnel as a single creative problem.
For brands planning a campaign
For a brand with weak bottom-funnel conversion, a workshop built around the four stages and the brand's own funnel data would offer a concrete, testable format. Ask for the funnel mapped to the brand's actual campaigns before promising a creative overhaul.
In a post on first-versus-second purchase, McCormick separates acquisition from retention: brands optimize ads, landing pages and checkout for the first sale, then send a generic welcome sequence and lose the customer.
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They say repurchase windows are predictable from DTC email program data, often around 30 days for consumable products.
Most brands either send so much generic content that customers learn to ignore them or go silent exactly when a reorder is likely.
Their fix is a behavior-triggered message sent three to five days before the expected reorder window, written personally rather than blasted to the full list.
They claim that single, well-timed flow can outperform broadcast campaigns.
Anchors the recommendation in observed reorder cycles and purchase behavior rather than a loyalty program or broad retention campaign.
For brands planning a campaign
A session on retention timing is easy to scope: ask for a review of the brand's replenishment cycles and one timed trigger flow instead of a full loyalty build. This is a narrow, measurable engagement.
McCormick describes a segment most brands leave alone: customers who bought once or twice, spent real money, then drifted after life got in the way.
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They sit in an at-risk or needs-attention list while the brand keeps sending the same full-list promotions and generic discounts to everyone from loyal buyers to two-year lapsed customers.
They argue these customers are not gone; their recency has slipped, but their lifetime value is proven.
What works, in their account, is a message that acknowledges the gap, references what the customer bought and gives a specific reason to return, framed as a conversation rather than a broadcast.
They call winback one of the highest-ROI things a DTC brand can build because reactivating a lapsed customer costs a fraction of acquiring a new one, and point to the list already sitting inside a brand's Klaviyo account.
For brands planning a campaign
Winback is a bounded, high-intent project a brand can hand over quickly. Ask for segment-specific copy that references past purchases, not another sitewide discount.
McCormick frames the AI question as settled: AI will not replace the marketer, but it will replace the marketer who refuses to learn it.
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In their teams, AI handles what they call the research layer, including competitor ad analysis, hook pattern identification, landing page copy variations and creative development.
That leaves humans to provide judgment, taste, emotional intuition and a sense of why something feels right before data confirms it.
They identify the mistake as treating AI like a vending machine: prompt in, content out, posted as-is, producing output audiences immediately recognize as generic.
Their guidance is to use AI to sharpen the inputs rather than replace the outputs.
Describes a division of labor inside McCormick's teams rather than a general argument, so the examples come from marketing workflows they say they run.
McCormick draws the line between mechanics and meaning, not between AI and no AI: they neither claim AI can supply judgment or taste nor argue against using it.
For brands planning a campaign
A practical AI session focused on how AI fits into a brand's research pipeline and where human review stays is a credible format. Pair it with McCormick's retention content if the brand wants both.
Human-feeling content as the differentiator against AI sameness
McCormick opens with a tension they say brands have not resolved: AI-generated content is everywhere and audiences are getting good at sensing it, so the brands that cut through are the ones that feel human.
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Their examples are a founder appearing on camera imperfectly, behind-the-scenes content nobody asked for, and an email that reads like a person wrote it.
They argue these are becoming competitive advantages precisely because they are becoming rare.
The other half is structural: SOPs, naming conventions, approval workflows and publishing cadences are necessary to scale but can flatten a brand voice into a checklist.
Their conclusion is to build structure around the process, protect the personality and know where the systems end and the humans begin.
States the scaling tension explicitly, then resolves it with a boundary rule rather than a choice between structure and authenticity.
For brands planning a campaign
Useful when a brand is worried that volume content has made it interchangeable. A talk built on the structure-versus-personality boundary, using the brand's own templates as examples, would address that concern more directly than generic AI commentary.
Jason McCormick writes short LinkedIn posts about DTC marketing, mostly where email and funnel thinking meet.
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The clearest entry point is the four-stage funnel post: problem-aware, solution-aware, product-aware and most-aware buyers each need a different kind of message, and pitching product features to people who have not yet accepted they have a problem is why so many campaigns fail.
The retention posts put that argument into practice: when repeat purchases tend to happen, why showing up three to five days before that window beats a list-wide blast, and how a winback message to lapsed customers should reference what they bought and name the gap rather than offer the same generic discount everyone else gets.
Two later posts cover how McCormick thinks about AI and brand voice: AI handles research, competitor analysis and copy variations while people keep judgment and taste; a related warning says the systems that scale content can flatten the personality that makes it worth reading.
Expect compact, argument-first posts built on reasoning and example sequences.
Ask for client case studies or performance figures if you need evidence beyond the examples in the posts.
Works the same territory: ecommerce email marketing for DTC brands, covering what brands get wrong, welcome flows, segmentation, post-purchase follow-up and how much email revenue brands quietly leave on the table.
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Ahmad writes diagnostic lists and strategy-transfer arguments—eight reasons an email program slips, or why one brand's email strategy will not carry to another.
McCormick builds single frameworks, such as the four-stage funnel and the reorder window, and reasons from them.
Read Ahmad for a checklist of what may be broken; read McCormick for a timing- and message-matching argument.
Writes from inside retention and lifecycle email work, naming Klaviyo and SMS platforms, and tackles the same questions as McCormick about lapsed customers, winback flows and why retention spend does or does not pay back.
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Salomon pushes back on the retention team's ability to fix churn with email, arguing that churn often starts in acquisition, offer or product experience, and that no flow can manufacture loyalty the brand never earned.
McCormick stays closer to the tactical fix: what to send, when and to which segment.
Read Salomon when you need a reason to question a campaign aimed at reducing churn through email; read McCormick when you want the sequence to send.
Works on the same DTC ecommerce growth questions from the paid-media side: diagnosing a sudden sales drop in a fixed order, checking whether the tracking is real before blaming creative, and treating acquisition and post-purchase as one system.
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Paxton centres Meta and Google ad accounts, retargeting mix, contribution margin and 12-month seasonality, making the case with client numbers.
McCormick centres email and lifecycle, and argues from customer awareness stages and reorder timing.
They meet at post-purchase: Paxton's home-goods case adds a post-purchase sequence and raises the free-shipping threshold; McCormick would start with when the customer was likely to reorder.
For a DTC ecommerce brand seeking a lifecycle-marketing talk or workshop on email retention and funnel conversion, Jason McCormick is a plausible practitioner pick.
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Their posts address practical buying questions: funnel-stage creative, winback timing, repurchase windows and AI-assisted marketing workflows.
The content is geared toward DTC marketers, founders and retention operators.
They have 2,931 LinkedIn followers as of October 9, 2026, a small professional following.
Before booking, ask for recent LinkedIn audience analytics or a short audience survey covering role, seniority, industry, geography and decision influence, plus results from a recent retention or lifecycle talk delivered to comparable DTC teams.
LinkedIn followers
2,931
LinkedIn profile data with the post sample; follower count only, with no demographic breakdown. · 2026-10-09
No partnership formats are documented in the material reviewed.
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Jason McCormick's published posts offer editorial commentary on DTC email and funnel strategy—problem-aware messaging, winback campaigns, repurchase timing and AI-assisted marketing workflows—but announce no sponsorships, paid formats, rates or inquiry route.
For a DTC email-retention brief, contact them directly about a talk, workshop or consulting engagement rather than choosing from a published menu of packages.
Ask them to confirm scope, deliverables, turnaround, availability and terms in writing before committing a budget.
Treat any figure quoted elsewhere for this creator as unverified until they confirm it directly.
Brief: a DTC ecommerce brand selling a replenishable product wants to improve email retention and lift bottom-funnel conversion, and is weighing a talk or a workshop.
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This is a strong fit: the reasons come from the work itself, not the follower count.
The posts set out a funnel model with a job for each stage: name the problem in emotional terms before pitching a product to problem-aware buyers; use benefits, comparisons and proof for solution-aware buyers; differentiate with specifics for product-aware buyers; and return to the feeling of life after purchase for the most-aware.
That maps directly onto a brand that suspects its bottom-funnel ads are doing work the top of the funnel should have done—the cost argument in the same post.
On retention, the recommendation is narrow and testable: treat first and second purchases as different problems, read the reorder cycle from the brand’s own email data (around 30 days for consumables), and send a personal, behavior-triggered message three to five days before that window instead of another broadcast.
The winback post offers a second bounded project: separate customers who have already bought from prospects, acknowledge the gap, reference the previous purchase, and give a specific reason to return rather than another sitewide discount.
A workshop could work through the brand’s own Klaviyo segments and reorder intervals without new tooling.
These are arguments and observed patterns, not published case studies, lifts or benchmarks, so check the 30-day figure and trigger timing against the brand’s data.
No sponsorship packages, rates or inquiry route are documented; agree scope, deliverables, timing and fee directly, and confirm them in writing.
When to choose a specialist
Brief: a B2B software or enterprise services company with long sales cycles and committee buying wants a keynote on demand generation, plus a sponsored content package with committed reach.
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This is a weak fit based on what Jason McCormick’s posts say.
They are framed for consumer DTC: the four-stage model assumes a short purchase path, an emotional top of funnel and a single buyer, none of which describes a multi-stakeholder enterprise deal or a months-long evaluation.
The one concrete timing example is a reorder cycle, roughly 30 days for consumable products, which has no equivalent when the same account may not buy twice inside a year.
The posts do not discuss SQL pipelines, sales and marketing handoff, account-based programmes or paid acquisition for considered purchases, so they do not describe that work.
The commercial side is thinner still: they do not describe sponsorship or paid formats, and provide no rates, deliverable list, inquiry channel or audience breakdown beyond a LinkedIn following of 2,931.
A package with reach commitments cannot be scoped or verified from the posts.
The overlap is AI-assisted marketing operations and keeping content human at scale, which could support a narrower session for a B2B team.
Treat that as a separate need, not part of a demand-generation keynote.
A worked campaign example
Worked angle for the DTC retention brief: a 90-minute working session followed by one built and tested flow, framed as a retention reset rather than a strategy presentation.
Before the session, ask for the last twelve months of order and email data, reorder intervals by product, the current automation list, and the brand’s definition of at-risk and lapsed.
Open with a 15-minute segment on the four funnel stages, using the brand’s live campaigns to show which ads target people who do not yet accept they have a problem.
Spend the next 30 minutes on timing: pull the actual repurchase distribution by product, pick one product with a readable cycle, and mark the send window three to five days ahead of it.
Then build the trigger live, writing the copy in the room so the team can compare personal, specific messaging with the generic discount email going out now.
Close with the winback segment: pull customers who bought once or twice and have gone quiet, write one message that names the gap and references what they bought, and test it against the standard promotion.
Deliverables: one triggered replenishment flow, one winback message, and a one-page test plan naming the metric, the window and the decision rule.
Agree success criteria in advance: the new flow beats the existing broadcast on revenue per recipient, and winback outpaces the standard discount over the agreed window.
The timing and lift figures in the posts are patterns from the creator’s experience, not results from this brand or measured case studies.
No partnership format, rate or turnaround is published, so settle availability, scope and fee directly and confirm them in writing before committing budget.
When a brand needs to audit its email program rather than fix one stage.
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Ahmad's posts read as a checklist: unclear strategy, a weak welcome flow, blasting everyone the same message, leaning on discounts, ignoring data, no post-purchase follow-up, no testing and no zero-party data.
Teams that suspect several parts of the program are broken would get a usable sweep.
Ahmad also argues that a playbook that worked for one DTC brand will not necessarily transfer to another, citing differences in audience psychology, lifetime-value goals, journey length, tone and promise.
For teams about to copy a competitor's flows, this is the argument against it.
Ahmad covers breadth, not sequence or timing.
Unlike McCormick's four-stage funnel model and reorder-window guidance, the posts offer no specific send timing, winback message structure or worked example with numbers.
A brand focused on bottom-funnel conversion or a mistimed replenishment trigger would have less to act on.
When churn likely stems from outside email and the job is to convince leadership.
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Salomon argues from inside retention that a team can be held responsible for customers it never had a chance to keep: a weak acquisition channel, a discount-driven offer or a product experience people do not want to repeat.
The practical advice is to stop discussing churn in isolation, tag customers, show the cohorts and pinpoint where behaviour starts to break down.
For brands whose cancellation feedback mentions product, pricing or shipping, that framing is more useful than another flow.
Salomon is stronger on diagnosis and the cross-functional argument than on building email.
Compared with McCormick's replenishment and winback material, there is little on sequencing, trigger timing or copy.
Teams that already see retention as an experience problem and want tactics would get less from this.
When a revenue drop is not clearly an email problem and the brand first needs to investigate tracking, the store, paid accounts and seasonality.
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Paxton offers a four-step triage for a sudden sales drop and a worked case: a home goods client taken from $120K to $280K a month, with retargeting cut from 65% to 25% of spend, a three-step post-purchase sequence added, the free-shipping threshold raised and weak SKUs removed.
The case focuses on contribution margin rather than ROAS.
Brands concerned that email fixes may sit atop a wider funnel problem would get a broader lens here.
Paxton focuses on paid acquisition and performance diagnosis.
Email retention is one thread in a wider recovery, not the main subject.
Brands focused on lifecycle flows and retention timing would get less specific help than from McCormick's posts.
