Adam Kitchen audits direct-to-consumer ecommerce brands and shares advice on improving customer retention and lifetime value, including how to use customer research and email marketing.
Adam Kitchen is most useful for auditing DTC ecommerce retention and testing lifetime value assumptions before email work.
Best for
A DTC ecommerce brand with a repeat-purchase problem, open to a retention audit first.
Not for
A B2B SaaS sponsored thought-leadership campaign seeking enterprise IT demo requests from their audience.
Key takeaways
Rising customer value can hide falling repeat purchases and lower post-first-month spending.
First-purchase bundles hurt 180- and 365-day lifetime value at two large brands.
A customer research questionnaire should inform content, timing, positioning, and cross-sells before lifecycle email.
Check first: Confirm their sponsorship terms, audience composition, and whether a paid placement package exists before contacting them.
Main ideas
Rising customer value can hide falling retention · Lifetime value has four levers, and average order value has a ceiling · Research why customers buy and return before sending lifecycle email
Adam Kitchen shares analysis of customer retention and lifetime value for direct-to-consumer ecommerce brands.
Their posts show how they use audit data and customer research to question familiar growth tactics: rising customer value can hide declining repeat purchases, and first-order bundles that seem likely to help may reduce longer-term value.
Readers interested in ecommerce retention can follow their work for concrete examples of how to read customer metrics and test assumptions before building email strategies.
Adam Kitchen connects specific customer data to practical decisions while making room for exceptions.
In one outdoor-brand example, 12-month customer value rose from $112 to $116 as first-month spend increased, but repeat purchase rates and spending after the first month fell.
They use the combined measures to show why higher order values do not, on their own, prove healthier retention.
In another post, Kitchen says first-purchase bundles hurt 180- and 365-day lifetime value at two large brands, despite bundles usually correlating with higher value in their experience.
Together, the examples show a willingness to look beyond headline metrics and test whether a tactic works for a particular business.
Their questionnaire post adds a customer-research step before email campaigns, using answers to inform content, timing, positioning, and cross-sells.
Ask for more information about any signature books, shows, businesses, or earlier work that might also explain name searches before treating this overview as a complete account of their public identity.
Adam Kitchen's distinctive ideas center on treating retention as a set of measurable levers rather than a single revenue trend.
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They argue that lifetime value can rise while repeat purchasing falls, that brands should research why customers buy and return before writing lifecycle email, and that common best practices such as first-purchase bundling must be tested against long-term value rather than assumed. The recurring priority is to diagnose the specific weak lever with cohort data, then use email, SMS, direct mail, product releases, or subscriptions only where the data supports them.
Rising customer value can hide falling retention
Adam Kitchen argues that 12-month customer value or revenue can rise even as repurchase behavior worsens, because average order value optimization can offset fewer repeat orders.
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In an audit of a US outdoor brand, 12-month customer value rose from $112 to $114 to $116, while first-month spend rose from $82.60 to $91.80, meaning the growth came from order value work.
Spend after the first month fell from $29.50 to $27.
The same Shopify data showed month-one repeat purchase rate down from 10.2% to 8.9%, returning customers per new customer down from 0.85 to 0.71, and returning order AOV up from $71 to $82.
Kitchen's point: each number tells a different story alone; together, they tell the right one.
The outdoor brand's newest customers spent more in their first month than any previous cohort, yet were already behind the prior year's cohort by month six. Bigger first orders were masking fewer repeat orders.
Lifetime value has four levers, and average order value has a ceiling
Adam Kitchen frames lifetime value as the product of four levers: how many customers a brand acquires, how much they spend the first time, how often they return, and how much they spend when they do.
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In the audited outdoor brand, the second and fourth levers were being pulled hard while the third declined.
Repeat rates fell in every month after the first order, with the steepest drop in months four to six.
Kitchen argues that average order value optimization is worthwhile but finite, and eventually cannot offset a shrinking repeat base.
The brand was increasing first-month spend and returning order value as repeat rates fell. Adam Kitchen describes it as pulling two levers hard while the third declined.
Research why customers buy and return before sending lifecycle email
Before sending email for a brand, Adam Kitchen runs a structured question set called the LTV Cheat Code to understand what makes customers purchase and return.
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The research is meant to improve ad creatives, positioning, email content, email timing, cross-sell opportunities, and more.
Kitchen argues that without this data, a brand is flying blind and making assumptions about why retention is bottlenecked.
Simple data collection can lead to incremental revenue while reducing ad waste by acquiring better customers.
Adam Kitchen says they run the questionnaire before sending a single email for a brand. The post points to a free Klaviyo audit as a next step for finding retention opportunities.
Broaden distribution and give customers product reasons to return
Adam Kitchen reports that over half the brands audited rely exclusively on email, whose performance is declining, and argues for a proactive text and direct mail strategy to maximize distribution.
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They also recommend releasing complementary products, arguing that novelty drives repurchase rates up, and using subscription or membership models to drive predictable revenue for some consumer-packaged-goods businesses. Kitchen says plainly that subscription is not a golden bullet and works only for some businesses.
For the audited outdoor brand, Adam Kitchen lists complementary product releases, text and direct mail alongside email, and subscription or membership models as ways to lift repeat purchase rates when a category limits how often customers naturally return.
Treat best practices as hypotheses, especially first-purchase bundles
Adam Kitchen argues that what works for one business does not necessarily work for another, and that brands should test best practices over time and pivot using data.
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In two brands with revenue north of $80 million, bundling on the first purchase hurt 180-day and 365-day lifetime value compared with lower-order-value customers who bought items individually. Kitchen says this was surprising because in roughly 95% of instances observed across direct-to-consumer brands, stacking more products into the first purchase correlates with higher lifetime value over time.
The two large brands were exceptions to Adam Kitchen's usual pattern. The result led them to urge brands to test religiously over time and change their approach using data.
Answers the question: how can a DTC brand look healthier on revenue while repeat purchasing worsens?
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This is the clearest starting point for understanding Adam Kitchen’s approach to diagnosing retention.
Adam Kitchen examines a US outdoor brand whose 12-month customer value rose from $112 to $114 to $116, while its first-month repeat purchase rate fell from 10.2% to 8.9%.
First-month spend rose from $82.60 to $91.80, but spend after the first month fell from $29.50 to $27.
Returning customers per new customer dropped from 0.85 to 0.71, even as returning order AOV rose from $71 to $82.
Rising average order value was masking fewer repeat orders.
The post names four lifetime-value levers: how many customers a brand acquires, how much they spend first, how often they return and how much they spend when they do.
It suggests complementary products, text and direct mail alongside email, and subscription or membership models to improve repeat rates.
For brands planning a campaign
For a retention audit, don’t treat rising LTV or AOV as proof that retention is healthy.
Track repeat purchase rate, returning customers per new customer and post-first-month spend alongside first-order AOV.
Then build the lifecycle email strategy around the levers that are actually declining, not just those that are easy to report.
Answers the question: what should a brand know before sending retention emails?
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It’s a practical starting point for lifecycle email strategy, turning assumptions about why customers return into questions.
Adam Kitchen describes an “LTV Cheat Code” questionnaire run before a brand sends a single email.
Its questions gather qualitative research to improve ad creatives, positioning, email content and timing, cross-sell opportunities and more.
The post argues that without this data, brands are flying blind about what is bottlenecking retention; simple data collection can generate incremental revenue while reducing ad waste by attracting better customers.
It also points to a free Klaviyo audit as a next step for finding retention opportunities.
For brands planning a campaign
Before writing a lifecycle email flow, ask customers why they bought, what almost stopped them, what they considered instead and what would make them buy again. Use the answers to shape email angles, timing and cross-sell offers rather than relying on purchase data alone.
Answers the question: should a DTC brand push a bundle on the first order to raise lifetime value?
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It challenges a common retention assumption and shows why Adam Kitchen tests category norms rather than applying them.
Adam Kitchen says audits of two brands with north of $80 million in revenue found that first-purchase bundling hurt 180-day and 365-day LTV compared with lower-AOV purchases where customers bought items individually.
They say this was surprising because, in roughly 95% of instances, adding more products to the first purchase correlates with higher LTV over time.
The lesson: what works for one business may not work for another.
Brands should test best practices over time and be ready to pivot based on data.
For brands planning a campaign
Don’t make first-purchase bundling a default retention recommendation.
Test bundled first orders against individual-item first orders, and measure 180-day and 365-day LTV—not just first-order AOV.
If bundles underperform, use lifecycle emails to introduce complementary products later rather than forcing them into acquisition.
Qualitative customer research before lifecycle email1
Distribution beyond email1
Complementary products and subscription models to lift repurchase1
Challenging best practice on first-purchase bundling1
Retention health versus revenue growth
Adam Kitchen's central audit argument is that rising customer value can hide falling repeat purchasing.
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In an audit of a US outdoor brand, 12-month customer value rose every year while repurchase rate worsened.
First-month spend climbed from $82.60 to $91.80, so growth came from average order value work, while customer spend after the first month fell from $29.50 to $27.
Supporting figures from the brand's Shopify data: month-one repeat purchase rate fell from 10.2% to 8.9%, returning customers per new customer fell from 0.85 to 0.71, and returning order AOV rose from $71 to $82.
The newest cohort spent more in month one than any prior cohort, yet was already behind the previous year's cohort at month six.
Read several Shopify metrics together; each tells a different story on its own.
For brands planning a campaign
For a retention brief, ask for cohort-level tables covering first-month spend, repeat rate by month and post-first-month spend, rather than a single revenue or lifetime value trend. If value per customer is climbing while repeat rates fall, treat acquisition-side order value gains as masking a shrinking repeat base.
Adam Kitchen frames lifetime value as the product of four levers: how many customers a brand acquires, how much they spend the first time, how often they come back, and how much they spend when they do.
Read more
In the audited outdoor brand, the second and fourth levers were being pulled hard while the third declined. Repeat rates fell at every month after the first order, with the sharpest drop in months four to six.
For brands planning a campaign
Use the four levers as the diagnostic frame for a retention audit: establish which lever is underperforming before choosing tactics, and check whether first-order value gains are offset by fewer returning customers.
Adam Kitchen argues that average order value optimization is worthwhile but finite, and eventually stops covering for a shrinking repeat base.
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In the audited outdoor brand, growth came entirely from first-month order value improvement while repeat behavior weakened—the pattern of bigger first orders covering for fewer repeat orders.
For brands planning a campaign
Treat order value work as one lever among several, not a standalone retention strategy. Pair first-order value tactics with measures aimed directly at repeat rate, and set a point at which to review order value gains against repeat performance.
Qualitative customer research before lifecycle email
Before sending email for a brand, Adam Kitchen runs a structured question set called the LTV Cheat Code to understand what makes customers purchase and return.
Read more
The research is intended to inform ad creatives, positioning, email content, email timing, and cross-sell opportunities.
Kitchen says that without this data, brands make assumptions about why retention is bottlenecked.
Simple data collection points can generate incremental revenue while reducing ad waste through better customer acquisition.
A structured set of qualitative questions used as an intake step before email production, followed by an offer of a free Klaviyo audit for retention opportunities.
For brands planning a campaign
Start a retention audit with customer interviews or surveys before drafting flows. Map the answers explicitly to creative, positioning, send timing, and cross-sell decisions so the research visibly changes the campaign.
Adam Kitchen reports that over half the brands audited rely exclusively on email, whose performance is declining, and argues for a proactive text and direct mail strategy to maximize distribution.
Read more
Complementary product releases and subscription or membership models can also lift repeat purchase rates when a category limits how often customers naturally return.
For brands planning a campaign
When email performance softens, evaluate SMS and direct mail as additional owned channels instead of optimizing email alone. Ask what share of the customer base each channel currently reaches and where distribution gaps remain.
Complementary products and subscription models to lift repurchase
Among the levers Adam Kitchen finds effective are releasing complementary products, on the argument that novelty drives repurchase rates up, and using subscription or membership models to drive predictable revenue for some consumer-packaged-goods businesses.
Read more
They state plainly that subscription is not a golden bullet and works only for some businesses.
Adam Kitchen describes subscription and membership as effective for some CPG-based businesses, not as a universal solution.
For brands planning a campaign
For a brand facing a category-driven repurchase ceiling, consider adjacent product releases and, where the product and consumption cycle suit it, a subscription or membership offer. Test whether the category genuinely supports subscription before committing budget.
Challenging best practice on first-purchase bundling
Over three months, Adam Kitchen audited two brands with revenue north of $80 million where first-purchase bundling actively hurt 180-day and 365-day lifetime value compared with lower-order-value customers who bought items individually.
Read more
They describe the result as surprising: in roughly 95% of instances observed across direct-to-consumer brands, stacking more products into the first purchase correlates with higher lifetime value over time.
The observed harm to long-term value runs against the pattern Adam Kitchen sees in about 95% of cases, so treat bundle effects as brand-specific rather than general.
For brands planning a campaign
Do not assume a first-order bundle improves long-term value. If a brand bundles, measure 180-day and 365-day lifetime value for bundled versus individually purchased cohorts before scaling the offer, and be prepared to change the first-purchase structure.
Adam Kitchen’s stated approach is to test continuously and pivot using data, on the argument that what works for one business does not necessarily work for another.
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The same stance appears in the retention-audit framing, where several metrics tell the right story only when read together.
For brands planning a campaign
Expect recommendations framed as tests with defined measurement windows rather than fixed playbooks. A brief should specify the cohort comparison and the horizon—such as 180 or 365 days—that will determine whether a tactic stays.
The posts are short-form LinkedIn analysis built on named metric movements from brand audits.
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The outdoor brand example uses a month-by-month table of customer value, first-month spend, and post-first-month spend, plus Shopify repeat-rate and order-value figures.
The bundling post is narrative and references two large brands without naming them.
Client details are anonymized by category or revenue band.
For brands planning a campaign
Expect audit-style posts that show the underlying numbers and reasoning rather than generic retention tips. The examples are anonymized and undated, so ask for the category, cohort window, and measurement method behind any case cited in a pitch.
Adam Kitchen's posts describe audit work for direct-to-consumer ecommerce brands, but identify clients only as a US outdoor brand and two brands with more than $80 million in revenue.
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The only named company is Klaviyo, which appears in an offer of a free audit, not as a stated partnership. Ask for client names or references if they matter to your decision.
Klaviyo
Mention
Kitchen's post on lifetime-value research offers readers a free Klaviyo audit through a shortened link.
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It does not clarify whether they work for Klaviyo, are a platform partner, or use the tool in their own client work. Ask them to clarify their relationship with the company.
Adam Kitchen writes on LinkedIn about ecommerce retention and repeat purchasing, mostly in short audit write-ups that walk through a brand's numbers before naming a fix.
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To follow the thread, start with the posts that read cohort data together—rising customer value alongside falling repeat rates—then the piece on first-purchase bundling, which reverses a rule they had seen hold in roughly 95% of cases.
The pre-email questionnaire post shows the intake step that comes before lifecycle work.
Readers who want the reasoning rather than the tactics will get more from the metric tables and the caveats attached to each recommendation than from any single rule.
For adjacent reading, the creators below approach the same post-purchase problem from different angles: collection before campaigns, recognised returning shoppers, and whole-journey diagnosis.
Marko Mandic publishes practical retention guidance for ecommerce brands in the same list-first style Adam Kitchen uses: conditions that must be in place before retention campaigns work, and email and Klaviyo specifics.
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Both treat retention as something to set up deliberately rather than fix with another discount.
Mandic's material centers on collecting zero-party data and on preconditions: a list of eight requirements for a good retention rate, and a 400-question bank mapped to Klaviyo profile properties. Adam Kitchen starts from audit numbers and asks which lifetime-value lever is failing.
Gary Feuerstein also writes about what happens after an ecommerce order, and how weak customer identification quietly corrupts the data behind email programmes and retention reporting.
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Both focus on the returning customer rather than the first sale.
Feuerstein writes from the position of building a product for shopper identity and cart continuity, including orders placed through AI assistants, and his posts end in demo invitations. Adam Kitchen writes as an auditor working through repeat-purchase and order-value figures.
Ibraheem Hamzat argues against fixing the loudest metric and instead diagnoses where value leaks across the customer journey, using ecommerce economics and staged journey maps.
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That diagnosis-before-tactic stance matches Adam Kitchen's four-lever framing and insistence on reading several metrics together.
Hamzat describes a revenue systems engagement that runs through economics, journey mapping, trust and a prioritization score. Adam Kitchen stays closer to retention and lifetime value, with email, SMS and direct mail as the working channels.
One measured audience fact is published on Adam Kitchen's LinkedIn profile: it showed 23,701 followers on 7 October 2026.
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That is enough to treat LinkedIn as the surface where this audience exists at scale.
It is not enough to say who is in it.
No age, gender, geography, occupation, employer, or seniority breakdown is published, and no audience survey results are published either.
The three posts dated 22 September to 5 October 2026 are about DTC ecommerce retention, lifetime value, and lifecycle email, using worked numbers from brand audits.
That tells a buyer what the content is about and who it is aimed at — operators and brand owners working on retention — but it is not a measurement of follower or reader composition.
Engagement counts, commenter roles, and follower locations are not published, so a statement such as "the audience is mostly DTC founders" is not supported by the posts here.
For a campaign on retention and lifetime value, LinkedIn is the placement supported by the posts here.
If the campaign depends on the audience containing ecommerce decision-makers in particular roles or markets, the concrete next step is to request recent results from sponsored or owned content in comparable topics and formats, and any audience survey or platform demographic data Adam Kitchen can share.
A YouTube-style demographic report answers geography, age, and gender; it does not verify employer, occupation, or job seniority, so those professional attributes need a survey or another documented source.
LinkedIn followers
23,701
Adam Kitchen's LinkedIn profile (linkedin.com/in/adamkitchen1) · 2026-10-07
Adam Kitchen's posts document no brand partnership or sponsorship format.
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The three LinkedIn posts present audit findings and retention advice for direct-to-consumer brands, not sponsored placements, and none includes a sponsorship disclosure, rate card, media kit, or partnership inquiry route.
The only commercial link is a free Klaviyo retention audit offered in one post as a lead-in to their own retention work; it is a service offer, not a documented sponsorship product or inquiry URL.
Brands considering paid placement should ask directly about terms, deliverables, disclosure practice, and pricing.
Need: A DTC ecommerce brand with a repeat-purchase problem wants to improve email retention and lifetime value, and is open to an audit first.
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Decision: strong fit.
Reason: Adam Kitchen’s posts show a concrete method that matches this need.
They analyze cohort-level Shopify data together, separate first-order average order value gains from repeat behavior, frame lifetime value as four levers, conduct qualitative customer research before sending lifecycle email, and treat first-purchase bundling as a testable hypothesis rather than a default.
The brand needs exactly that diagnostic and lifecycle-email work.
The main limit is commercial: the posts describe a service offer—a free Klaviyo retention audit—not a sponsorship format, rate card or partnership terms.
The brand should engage them for a retention audit and lifecycle strategy, then negotiate terms directly.
Do not assume a paid-placement package exists.
Their LinkedIn follower count was 23,701 on 7 October 2026, but the posts don’t identify those followers; if the campaign depends on audience composition, request it.
When to choose a specialist
Need: A B2B SaaS company wants a sponsored thought-leadership series to generate demo requests from enterprise IT buyers, using the creator’s audience as the main distribution.
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Decision: poor fit for this campaign.
Reason: Adam Kitchen’s posts focus on DTC ecommerce retention, lifetime value, lifecycle email, Shopify cohort metrics and first-purchase behavior.
They don’t show B2B SaaS expertise, an enterprise IT audience, or a sponsorship product with deliverables, disclosure practices, pricing or an inquiry route.
The only audience information provided is a LinkedIn follower count, not job titles, industries or buyer seniority.
Kitchen could still write about retention for a subscription business, but this campaign depends on claims the posts don’t support.
The brand should choose a creator with a documented B2B SaaS audience and sponsorship terms, or reframe the engagement as retention and lifecycle consulting, where the ecommerce posts are directly relevant.
A worked campaign example
Angle: “Your first-order growth is hiding a repeat problem.”
Start with a diagnostic, not an email calendar.
Pull 12-month cohort data: first-month spend, repeat purchase rate by month, returning customers per new customer, returning order average order value, and spend after the first month.
If first-order value is rising while repeat rate is falling, make that tension the campaign’s core message.
Run the pre-email customer research questionnaire before writing flows: ask why customers bought, what almost stopped them, what they considered instead, and what would make them buy again.
Map the answers to email angles, send timing and cross-sell offers.
Build the lifecycle strategy around the lever that is actually declining.
If repeat frequency is weak, test complementary product education, SMS and direct mail distribution where consent allows, and a subscription or membership offer only if the product category supports it.
Don’t make first-purchase bundling the default recommendation; measure bundled versus individually purchased first orders at 180 and 365 days before scaling.
Measurement: repeat purchase rate by month, returning customers per new customer, post-first-month spend, and 180-day and 365-day lifetime value, with a defined test window.
Deliverable: a retention audit memo and lifecycle email brief citing the cohort evidence and customer research.
Choose Marko Mandic when the retention problem sits upstream of email.
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The posts frame retention as a set of conditions, not a channel, and list eight prerequisites for a campaign to work: a reason to repurchase, a memorable purchase experience, product education, repurchase timing based on when the product actually runs out, a usage habit, a cross-sell built from what customers buy together, a discount strategy backed by margin math, and a loyalty program with real stakes.
They also centre zero-party data: a 400-question bank across ten DTC verticals, assembled after auditing more than 150 Klaviyo accounts, with guidance on collecting answers and mapping them to Klaviyo profile properties.
For a brand whose repeat rate is weak because its product line gives customers nothing to come back for, or whose email segmentation lacks first-party data, that framing reaches the root faster than a lifecycle calendar.
You trade Adam Kitchen's first-party cohort forensics for a broader conditions framework.
Mandic's posts reason from checklists and a question bank, not cohort tables; they do not show the first-month spend versus repeat-rate reading that catches first-order growth hiding a shrinking repeat base.
The question bank is distributed as a gated resource through a comment and a connection request; ask whether it is also delivered inside a client engagement.
Its eight requirements span packaging, product development and loyalty work well beyond email, so the path from diagnosis to a running lifecycle program is longer.
A brand that needs an audit memo and email campaign plan first should start with Kitchen and use Mandic's list to widen the roadmap.
Choose Gary Feuerstein when the retention leak is technical identity, not messaging.
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The posts describe SessionFlow, which keeps a shopper connected to their identity and cart so a store can recognise them on return, including on another device.
It also reconnects orders placed through AI assistants with existing purchase history and marketing consent.
The failure is specific: a shopper builds a cart on Tuesday, returns ten days later, and the store no longer links the visit to the cart or the person.
Nothing fails loudly in Klaviyo, so the brand keeps optimising flows against an incomplete picture while returning shoppers rebuild carts, activity splits across profiles, attribution drifts and money goes to reacquiring people the store should already recognise.
If cohort work shows a large share of returning traffic behaving like strangers, fix the identity layer before writing more emails.
The tradeoff is product-led scope.
The posts lead to a demo booking for SessionFlow, so the engagement centres on adopting and integrating technology rather than a standalone retention audit.
Feuerstein's material diagnoses data and identity problems well, but does not show cohort-level lifetime-value analysis, customer research questionnaires or lifecycle email design.
If you want someone to read your Shopify cohorts, interview customers, then write and sequence the flows, ask whether that work is included or plan to bring in Kitchen or a comparable practitioner alongside the technology.
Choose Ibraheem Hamzat when the brand assumes retention is the constraint but has not tested that assumption.
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The posts argue that symptoms rarely appear where the problem lives: weak traffic quality can look like a conversion problem, a weak offer like a CRO problem, poor customer experience eventually like a retention problem, and weak retention can make acquisition look more expensive than it is.
The stated starting point is unit economics (average order value, acquisition cost, conversion rate, repeat purchase behaviour, lifetime value), followed by mapping the journey from traffic through retention, separating symptoms from constraints, examining trust and clarity, and prioritising the few interventions with the greatest impact by impact multiplied by confidence and effort.
For a brand about to buy lifecycle email work without knowing why repeat rates are falling, that diagnosis-first sequence is the better first step.
You trade execution for diagnosis.
The reviewed Hamzat posts describe an approach and a sequence, but show no client outcomes, cohort data or lifecycle email program design, copy or send strategy.
A brand that already knows its repeat base is eroding gets less from another framework than from Kitchen's audit-to-brief handoff.
Use Hamzat when the constraint itself is genuinely unknown, and ask what email practitioner they recommend once it is identified.
