Aminat Hammed shares practical advice on email marketing and customer retention for Shopify ecommerce brands, with a focus on using customer behavior to improve Klaviyo segments, automations, and follow-up.
Aminat Hammed is most useful for Shopify email retention, Klaviyo segments, automations, and post-purchase follow-up advice.
Best for
Shopify brands with purchase history and live flows to audit for retention.
Not for
Broad reach sponsorship packages with guaranteed impressions, fixed prices, or produced creative assets.
Key takeaways
Test whether each Klaviyo segment changes the customer message or experience.
Audit last 100 customers: purchases, follow-up, and how many returned.
Campaigns and flows serve different purposes; timing and relevance matter.
Check first: Ask directly about deliverables, price, lead time, audience data, and sponsorship format.
Main ideas
The first purchase is the start of retention work · Customer data matters when it changes what someone sees next · Respond to customer behavior instead of sending more by default
Aminat Hammed writes practical advice for Shopify brands on email marketing and customer retention.
Their central idea: customer data matters only when it changes what a brand does next.
A purchase might prompt product education, a replenishment reminder or a relevant recommendation—not another generic discount.
They distinguish behavior-triggered automations from broader campaigns and argue that product information needs to be clear as shoppers use AI to discover and compare products.
Read their work for concrete ways to rethink the customer journey after the first purchase, rather than simply increasing traffic or email volume.
Hammed turns retention strategy into questions brands can apply to their customer journeys.
The focus is on using behavior—not collecting more data or sending more emails—to make the next interaction useful.
They also caution against treating automation as a cure-all: the discussion of email automations stresses that timing and relevance matter, and that campaigns and flows serve different purposes.
In a post about AI-led product discovery, they note that discovery may happen before a shopper visits a store, but clear product information and a good buying experience still matter.
Across these posts, Aminat Hammed treats retention as a question of what a brand does after a customer buys.
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The recurring test is whether customer behavior changes the next message: a segment should prompt a different decision, and a follow-up should help with a real next step rather than defaulting to another discount.
They also argue that automations should answer customer actions, while campaigns serve broader purposes.
One post applies the same focus on customer decisions to AI-assisted product discovery and the need for clear product information.
The first purchase is the start of retention work
Hammed argues that brands often put effort into acquiring customers but leave the post-purchase journey thin.
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A first order gives the brand information it can use to make the next interaction more relevant.
A Shopify store owner described making sales without customers returning.
Hammed says the gap was no post-purchase education, meaningful product follow-up or clear reason to come back.
The proposed audit asks what the last 100 customers bought, what they were told afterward, when the brand contacted them again, whether it recommended something relevant and how many returned.
Customer data matters when it changes what someone sees next
Hammed's test for useful segmentation is not how many segments a brand has, but what decision each one changes.
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Adding a name or creating more lists is not enough if customers still receive the same message.
After someone buys a cleanser, a follow-up could help them use it, suggest a relevant complement, estimate when they may need more or introduce a suitable next product. Each option uses the purchase to shape the message.
Respond to customer behavior instead of sending more by default
Hammed distinguishes triggered automations, which respond to individual actions, from campaigns, which can announce launches, share offers or maintain contact.
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More automation is not automatically better: the message still needs to arrive at a useful moment. In one post, they cite an Omnisend report's figures that automations accounted for 2% of email sends and 30% of email-driven revenue.
A welcome message after signup or a cart reminder can respond to existing intent. Hammed suggests asking what customer behavior the current program does not respond to yet, rather than only what email to send this week.
A discount should not be the automatic answer to a customer going quiet
Hammed warns that repeatedly escalating promotions can train customers to wait for discounts.
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The alternative is to match the follow-up to what the customer may need next.
Hammed suggests helping a recent buyer get more from a product, reminding someone who may be running low, recommending a relevant complement or tailoring a re-engagement message to past behavior.
Make product information clear before shoppers reach the website
In a post that broadens beyond email, Hammed argues that AI tools are changing how some shoppers discover and compare products.
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Brands may be considered before a shopper visits their site, so product information should explain what an item does, who it suits and how it differs. Discovery alone does not complete a sale; the product page and buying experience still matter.
Hammed cites figures in the post on growth in GenAI referrals to retail ecommerce and U.S. consumers using AI shopping tools, then asks whether a product page would give someone who arrived through an AI recommendation enough reason to buy.
It answers the question "how does Aminat Hammed think the path to a first purchase is changing?" and gives the framing that sits behind the other four posts: the journey as connected stages, not a list of separate tactics.
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The post argues that the familiar ad-to-website-to-purchase path is becoming less predictable as shoppers use AI tools to discover, compare and shortlist products before reaching a brand site.
It cites GenAI referrals to retail ecommerce growing 203% year over year and 51% of U.S. consumers saying they used an AI shopping tool in the past month.
It draws out three consequences: product descriptions must state what a product does, who it is for and how it compares; discovery is less under brand control because people start with questions rather than a homepage; and an AI mention alone does not create a customer—the product page, offer, buying experience and follow-up still have to work.
The post closes with a four-stage breakdown of discovery, consideration, conversion and retention.
For brands planning a campaign
Useful for scoping a retention brief: it identifies what a brand must fix before email can convert. A brand can test the closing question directly: if a customer arrived via an AI recommendation, would the product page give them a reason to buy?
It answers "what does this person actually check when reviewing a Klaviyo account?" and is the clearest statement of the test applied throughout the email posts.
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The post starts from a contradiction: a brand can hold VIP, repeat-buyer, first-time, engaged-subscriber, and lapsed-90-day segments in Klaviyo and still send weak email.
The question it puts in place of segment counts is "what decision does each segment actually change?"
Enrolling ten thousand customers in a segment and sending the message you would have sent anyway, it argues, does no work.
The worked example is skincare: someone buys a cleanser, and that purchase is a specific piece of knowledge that could shape the next message toward product results, complementary items, replenishment timing, or a next product.
The post ends by tying personalisation to conversion, repeat purchases, retention, and lifetime value, and asks reviewers of a Klaviyo account to replace "how many segments do we have?" with "what are we doing differently because we know this about the customer?"
For brands planning a campaign
A ready-made audit question for a Klaviyo review: list the live segments and name the message change each one triggers. Segments that trigger nothing can be rebuilt or retired before new campaigns are added.
It answers "where does this person think Shopify brands should put email effort next?" and is the post with the most concrete numbers behind the recommendation.
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The post highlights a gap from Omnisend's 2026 Ecommerce Marketing Report, drawn from activity across 150,000 brands: automations accounted for 2% of email sends but 30% of email-driven revenue.
Four readings follow.
Timing can matter more than volume, because a welcome email or cart reminder responds to intent that already exists while a generic campaign has to recreate it.
Customer behaviour should shape the message, since someone browsing needs a different note from someone who just bought.
More automation is not automatically better retention, because a badly timed flow still annoys people.
Campaigns and flows have different jobs, and the strongest setup gives each a clear one.
The post closes by suggesting brands ask "what customer behaviour are we not responding to yet?" instead of "what email should we send this week?"
For brands planning a campaign
A defensible starting point for a sponsor brief: an automation audit before a campaign calendar.
The 2%-to-30% ratio can help argue for budget toward flows.
Before using it in a budget case, ask for the underlying report; the figure comes from a third-party report, not Hammed’s own measurement.
It answers "what alternative does this person propose to discount-driven retention?" and is the shortest route into their view of the problem.
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The post describes a familiar ecommerce pattern: a customer buys, the brand waits, sends a promotion, gets no purchase and sends a bigger promotion, until customers learn to wait for discounts.
The alternative is to look at what happened before the next purchase and match the message to it: help someone who just bought get more value from the product; remind someone likely running low before they search elsewhere; show someone who bought one item the obvious complement; or re-engage someone who has gone quiet in a way that matches their past behaviour.
The summary: retention is not about how many emails can be sent, but what this customer needs next.
Email then becomes a matter of timing, not just marketing.
For brands planning a campaign
A discount-suppression test: replace one planned promotion with a behaviour-matched message and compare repeat purchase rate with the promotion it displaced.
It answers "what does this person do when a brand has sales but no repeat customers?" and is the most concrete worked example in the set, making it a good second read after the segmentation post.
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A Shopify store owner tells Aminat Hammed the store is getting sales but customers are not coming back.
Looking beyond revenue, Hammed finds the store doing what most brands do: chasing more traffic, sending more campaigns, offering more discounts and finding more new customers.
The gap was after the first purchase: no post-purchase education, no meaningful product follow-up, no clear reason to return—and an assumption that a customer who liked the product would buy again.
The post argues that a first purchase is not proof the journey worked; it is when the brand finally has enough information to make the next interaction relevant.
Hammed then offers an audit of the last 100 customers: what did they buy, what was said afterwards, when was contact made again, was anything relevant recommended, and how many came back?
The conclusion: the biggest growth opportunity may be getting more value from customers the brand has already paid to acquire rather than buying more traffic.
For brands planning a campaign
This can be used almost as written for a retention audit at a Shopify brand. The five questions produce a small dataset on post-purchase communication that a campaign brief can target directly.
Aminat Hammed argues that Shopify brands spend most of their energy acquiring a first order and very little on what happens next.
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In one worked example, a store owner said sales were coming in but customers were not returning.
Looking past the revenue number, the problem was a lack of post-purchase education, product follow-up and a clear reason to come back.
Hammed frames the first purchase as the point when a brand finally has enough information to make the next message relevant—not as proof that the journey worked.
A five-question audit of the last 100 customers: What did they buy?
What did the brand tell them afterward?
When did it contact them again?
Did it recommend anything relevant?
How many came back?
The goal is to locate the gap between purchase and second purchase, not add traffic.
For brands planning a campaign
A lifecycle campaign aimed at improving retention should position Hammed as a retention diagnostician.
The natural first deliverable is an audit of an existing customer list and post-purchase contact, not new top-of-funnel creative.
Include purchase and repeat-purchase data so the audit is usable.
Hammed argues that a Klaviyo account can hold dozens of segments—VIPs, repeat buyers, first-time customers, engaged subscribers, lapsed buyers—and still deliver weak personalization.
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The test is not how many segments exist, but what decision each one changes.
The illustrative case is a cleanser purchase: once someone has bought skincare, the next message can help them get better results, understand what pairs with it, know when they will run out or find a relevant next product.
Personalization means using what is known about the customer to choose what they see next, not adding a first name or splitting a list further.
For brands planning a campaign
A practical hygiene check for an existing email program: ask the brand to show, segment by segment, the different message each receives.
If the answer is “the same one,” the segment is a reporting artifact, not a targeting decision.
This review is most useful when the brand has purchase history to work from.
Citing Omnisend’s 2026 ecommerce marketing report, based on activity from 150,000 brands, Hammed highlights that automations accounted for roughly 2% of email sends but about 30% of email-driven revenue.
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A triggered welcome or cart reminder responds to existing intent, while a generic campaign has to create interest from scratch. The practical recommendation is to give campaigns and flows distinct purposes—campaigns for launches, offers and staying in touch; flows for responding to individual customer actions—and start by asking what customer behavior is not being addressed, rather than what to send this week.
Uses third-party benchmark data from a named industry report to reframe the budget conversation, then distinguishes the channels by the job each does, not by send volume.
For brands planning a campaign
A brand deciding where to put next quarter’s email effort gets a defensible case for reviewing flows before adding campaign volume. For an email-program review, ask for a list of the triggered flows already live and the customer behaviors none of them address.
Discounts should not be the default retention message
Hammed describes a common retention pattern: a customer buys, time passes, the brand sends a promotion, the customer does not buy, and the brand sends a bigger promotion.
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They argue this trains customers to wait for discounts.
The alternative is to respond to what happened before the next purchase: help a recent buyer get more from the product, remind someone likely running low before they search again, show the obvious complement they did not buy or give a quiet customer a re-engagement reason that matches their past behavior.
The goal is email that feels well-timed, not promotional.
Hammed does not rule out discounts; they object to making discounting the automatic retention move when a behavior-based message would better fit the moment.
For brands planning a campaign
Relevant when a brand’s retention problem is margin as much as repeat rate. The campaign angle is a message audit that maps each stage of the customer lifecycle to a non-discount trigger and identifies when a promotion is genuinely the right tool.
Hammed argues that the ecommerce funnel is shifting before a customer reaches the brand’s site, as more shoppers use AI tools to discover and compare products.
The figures cited are 203% year-over-year growth in GenAI referrals to retail ecommerce and 51% of U.S. consumers saying they used an AI-powered tool for shopping in the past month.
The implication is that product information has to explain what a product does, who it is for, how it differs, how it compares and why someone would choose it—because a brand may be one of several options under consideration before it has a chance to introduce itself.
Hammed also stresses that discovery does not complete a sale: the product page, offer, buying experience and follow-up still determine whether the customer converts and returns.
The only post in the reviewed set focused on discovery and content quality rather than email or retention, it broadens the topics beyond lifecycle marketing rather than reinforcing them.
For brands planning a campaign
Useful when a brief includes product content or discoverability alongside retention, or when the brand wants a creator who follows wider ecommerce shifts. This is also the clearest example of Hammed building an argument from published industry data before drawing a practical conclusion.
The posts do not disclose any sponsorship, client, employment, ownership, affiliate, or investment relationship for Aminat Hammed.
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Klaviyo and Shopify recur as the tools and platform underpinning the advice, but no post states a commercial tie to either. Ask for clarification if an official brand relationship matters.
Klaviyo
Mention
Klaviyo underpins the email advice: posts walk through auditing an account, questioning whether segments change anything, and using purchase behavior to shape follow-up messages.
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One post carries a Klaviyo hashtag. No sponsorship, client work, or partnership is disclosed.
Shopify is the store platform assumed throughout the retention advice.
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One post opens with a store owner describing sales without repeat customers; another carries a Shopify hashtag. The posts do not state an employment, ownership, or partner relationship with Shopify.
A post on email automation cites Omnisend's 2026 Ecommerce Marketing Report (150,000 brands; 2% of sends generating 30% of email revenue) and links to the source.
Aminat Hammed focuses on what happens after a first purchase: using customer behavior to decide the next message, giving Klaviyo flows and campaigns distinct jobs, and treating discounts as one option rather than the default retention move.
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Start with the post about a Shopify store owner who had sales but no repeat customers, then follow the segmentation and automation arguments, and finish with the outlier on AI-driven discovery.
The tag list below groups the work by topic and specialty.
Similar creators offer adjacent perspectives on retention: Alejandra Salomon diagnoses churn across acquisition and product experience, Bogdan Birtom covers Klaviyo platform features and email operations, and Gary Feuerstein connects AI-assisted orders to known customers after purchase.
Writes about retention as more than email or SMS, tracing churn to acquisition promises, product experience, and the customer journey before the retention team can act.
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Their posts use cohort behavior and customer tagging to show where a relationship starts to break.
Salomon focuses on cross-functional diagnosis, showing leadership how retention depends on acquisition and product. Hammed's posts spend more time on Klaviyo segmentation logic and specific lifecycle message design.
Works in the same Klaviyo and ecommerce email space, reviewing platform releases, transactional email migration, subscription flows, deliverability, and A/B testing for retention teams.
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Birtom tracks product features and operational migrations in Klaviyo and similar ESPs; Hammed focuses more on customer-behavior strategy and post-purchase messaging than on platform feature breakdowns.
Focuses on what happens after an ecommerce order, especially AI-assisted purchases that arrive without normal browsing history or marketing consent, and on abandoned-cart recovery when returning shoppers are not recognized.
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Feuerstein frames the problem around identity, session continuity, and a product called SessionFlow; Hammed focuses more on email and lifecycle marketing decisions than on technical recognition tools.
Aminat Hammed’s posts suggest a fit for Shopify ecommerce brands focused on email retention, covering Klaviyo segmentation, behavior-based automations, and post-purchase follow-up.
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Before deciding on audience fit, request dated LinkedIn audience data and, if a campaign targets specific professional roles or seniority, a documented audience survey or other information about those attributes.
Aminat Hammed's reviewed LinkedIn output shows no partnership or sponsorship format.
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The five posts published between 1 and 9 October 2026 cover Klaviyo segmentation, email automation, discount-driven retention, post-purchase follow-up, and AI-driven product discovery.
None discloses a brand partner, sponsored placement, affiliate arrangement, rate card, media kit, or booking process.
This does not establish that they never work with brands; it means buyers should ask directly about deliverables, pricing, lead time, and approval process before planning a campaign.
A Shopify ecommerce brand looking to improve email retention and lifecycle marketing is a strong match for the work reviewed.
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All five posts read in full speak directly to that job: Klaviyo segmentation, behaviour-triggered automations versus scheduled campaigns, discount-led re-engagement, and post-purchase follow-up.
More useful than topical overlap, the posts already read like scoping documents.
A brand can hand over purchase and repeat-purchase data and apply the last-100-customers audit almost as written: what did those customers buy, what did the brand tell them afterwards, when did it contact them again, was anything relevant recommended, and how many came back?
The segmentation post offers a second test that needs no new data: list the live segments and name the message each one changes.
If the answer is the same message, the segment is a reporting artefact.
The automation post makes the case for shifting effort from campaign volume to triggered flows, while the discount post offers a counter-position for brands whose retention problem is as much about margin as repeat rate.
The audience section shows content fit, not measured audience composition, so treat reach as unknown.
The partnerships section lists no published sponsorship format, rate card or booking route; agree scope, price and lead time directly.
Fit is strongest for brands with purchase history and live flows to audit; it is weaker for a brand-new email programme with nothing yet to assess.
When to choose a specialist
A materially different campaign need—a broad-reach awareness push delivered as a booked sponsorship package with defined assets, a guaranteed impression or reach target, and a fixed price—is not supported by Aminat Hammed's posts.
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Three gaps create the mismatch.
First, the posts are short-form LinkedIn commentary; no video, podcast, newsletter or long-form piece by Hammed appears here, so a campaign requiring produced creative assets cannot be assessed.
Second, the posts show no partnership or sponsorship format: no named partner, sponsored placement, affiliate arrangement, rate card, media kit or booking process.
A brand cannot plan deliverables, pricing or approval steps from this evidence; none should be assumed.
Third, the posts provide no audience composition or reach data, so a campaign dependent on a guaranteed number of impressions, seniority or job roles, or a specific buyer segment cannot be assessed.
The content may attract the right readers, but that is not measured delivery.
There is also a narrower topical limit: four of the five posts focus on email and retention, and one on AI-assisted product discovery.
There is little material to assess a campaign about brand awareness, product-launch creative or non-ecommerce audiences.
For brands seeking exposure, the evidence points to a specialist retention commentator, not a documented distribution channel.
Plan around a retention deliverable, or ask for audience and sponsorship details before proceeding.
A worked campaign example
Campaign need: a Shopify skincare brand with steady first orders, a stalled repeat-purchase rate and a habit of running a promotion whenever a month looks soft.
Goal: lift repeat purchases over 90 days without deepening discounts.
Angle: run a retention diagnostic first, then spend the campaign budget only on the gaps it finds.
Week 1–2, audit: pull the last 100 customers and answer five questions—what they bought, what the brand told them afterwards, when it next made contact, whether anything relevant was recommended, and how many returned.
In parallel, list every live Klaviyo segment and note the message difference each triggers.
Rebuild or retire segments that trigger the same message as everyone else.
Use the cleanser example as a model: a cleanser purchase is a specific fact, so the next message should help with results, pair the product with an obvious companion, or predict when it runs out.
Week 3–4, flow-versus-campaign split: give each channel one job.
Flows respond to behaviour—welcome, cart, replenishment timing, post-purchase education, and quiet-customer re-engagement matched to past purchases.
Campaigns handle launches and offers and stay on the calendar.
Week 5–12, discount-suppression test: pick one planned promotion, replace it with a behaviour-matched message, and compare the repeat purchase rate against that of the promotion it displaced.
Report the audit findings, rebuilt segments and test result as the campaign deliverable.
Agree the deliverable format, working hours, timeframe and price directly before starting; nothing public sets them.
Supply purchase history, repeat-purchase data, a live flow list, and access or exports from the email platform.
Choose Alejandra Salomon when a brand's repeat-purchase problem may sit upstream of email — in the acquisition channel, discount offer, product experience, or cancellation reasons — and the internal conversation has become 'retention owns churn.' Salomon argues against treating churn in isolation: show the customer story before the churn, tag customers and compare cohorts, and ask whether an acquisition channel, offer, messaging, or product experience created a customer who was never going to return.
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That's a useful first move for a Shopify brand whose retention team is being asked to fix repeat rates with flows while the cause appears to be mismatched acquisition or product fit.
The tradeoff is operational depth in the email platform.
These posts make the case for looking beyond email and SMS but do not lay out the Klaviyo segment test, flow-versus-campaign split, post-purchase audit questions, or discount-suppression test in Aminat Hammed's reviewed work.
If the brand already knows the problem is lifecycle messaging and needs a concrete audit and automation plan, Hammed's posts are closer to the task.
If the brand needs to establish whether email can solve the problem at all, Alejandra Salomon is the stronger starting point.
Choose Bogdan Birtom when the buyer's task is platform-level: evaluating whether Klaviyo can absorb subscription and transactional email, or understanding recent Klaviyo feature direction before committing to a lifecycle stack.
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Birtom's posts include a Klaviyo feature breakdown — custom objects, channel preferences, engagement ranking, SMS automatic conversations, an omnichannel campaign builder, Customer Hub, and analytics recommendations — and an account of moving Recharge flows into Klaviyo, covering cohesive branding, a unified customer view, advanced segmentation, transactional deliverability, A/B testing, and consolidated reporting. That fits a brand migrating from a separate subscription platform or deciding whether Klaviyo should be the system of record.
The tradeoff is recency and strategic focus.
Bogdan Birtom's posts were published in 2025, so platform details and pricing questions may have moved; no 2026 post from Birtom was available for a current check.
Ask for an updated review before relying on those details.
The posts also focus on what the platform can do rather than a retention operating plan.
Hammed's posts supply the retention audit, segment rationale, campaign-versus-flow split, and discount-suppression logic a Shopify brand would use after choosing the platform.
Use Birtom for migration and feature evaluation, not as the source of the retention strategy itself.
Choose Gary Feuerstein when the retention problem is identity and journey continuity rather than message content.
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Feuerstein's posts focus on AI-assisted orders that arrive without a normal storefront visit, abandoned-cart recovery that only counts shoppers the tech recognized, and returning shoppers whose carts and profiles split across sessions or devices.
The diagnostic is specific: if a shopper builds a cart on Tuesday and returns ten days later, the store may no longer connect that visit with the original shopper, so Klaviyo flows look healthy but the measurement excludes people the store never recognized.
This is the better choice for a brand whose email programme is missing returning shoppers, has unreliable attribution, or is seeing AI-channel orders it cannot turn into known customers.
The tradeoff is that the posts are product-led around SessionFlow, a session and identity tool, rather than platform-neutral lifecycle strategy.
They explain the problem and point to a demo, while Hammed's posts cover email content, segmentation, automation logic, the Klaviyo segmentation test, post-purchase education audit, discount-replacement test, and flow-design decisions.
A brand that cannot reliably recognize returning shoppers may get more from Gary Feuerstein first: better flows on incomplete identity data will still miss customers.
Aminat Hammed's five LinkedIn posts cover Klaviyo segmentation, email automations versus campaigns, discount-led versus behavior-led re-engagement, post-purchase follow-up, and AI-assisted product discovery.
The posts have no per-post timestamps, so they show Hammed's current topics and working method rather than how the ideas have changed over time; the LinkedIn profile is considered as of 9 October 2026.
Three adjacent creators — Alejandra Salomon, Bogdan Birtom, and Gary Feuerstein — provide comparison.
This covers LinkedIn posts only: no longer articles, video, newsletters, other channels, or earlier posts.
The posts here contain no sponsorship, client, or partnership documents, and no audience composition or reach data appears here, so the partnership and reach conclusions remain open rather than settled.