Awais Nabi creates practical advice and AI tools for Shopify brands, focusing on email marketing, customer retention, and improving the customer experience.
Awais Nabi is most useful for practical Shopify email, retention, and customer experience fixes.
Best for
Shopify DTC brands over $200K monthly needing retention, shipping, winback, and email flow help.
Not for
Paid reach campaigns aimed at shoppers rather than store operators.
Key takeaways
Shipping confirmation is most-opened email, yet most brands never edit it.
Late parcel email can explain melted capsules are safe to refreeze before refund request.
Browse abandonment can split by whether someone viewed product three or more times.
Check first: Ask for engagement or reach figures on recent retention, flow, and deliverability posts.
Main ideas
The emails brands never edit are the ones customers read most · Deliverability is a list problem, not an inbox problem · Split the message by how many times someone has looked
Awais Nabi creates practical Shopify advice and AI tools focused on email marketing, customer retention, and the customer experience.
The posts show a consistent habit: start with a specific moment in the customer journey, explain what the customer is likely thinking, then propose a concrete change.
That might mean sending help before a delayed parcel arrives, adding guidance to a shipping confirmation, or reserving a discount for shoppers who have returned to a product several times.
They also cover list hygiene, refund-aware revenue reporting, signup forms, and store-audit tools.
The posts give readers examples of how they think about ecommerce.
Nabi makes overlooked parts of a Shopify store easier to see as connected customer experiences.
In the Cometeer example, a late delivery is not just a shipping problem: a message sent before the box arrives can explain that melted coffee capsules are safe to refreeze, potentially preventing confusion and a refund request.
In another post, a shipping confirmation becomes a place to answer common product questions before the parcel arrives, using evidence from the support inbox.
The advice is not simply to send more email.
It distinguishes a first-time browser from someone who has viewed a product repeatedly, and argues that the two should not automatically receive the same discount.
They also question the numbers used to judge email performance, pointing out that refunded orders can remain in attributed revenue.
Across these examples, the useful contribution is practical diagnosis: identify a customer’s situation, find the store process or message that fails them, and suggest a specific change.
The posts are useful to people interested in Shopify email and retention because they show that reasoning in concrete cases.
Awais Nabi's recurring argument is that most of a Shopify brand's retention money is sitting in emails and settings nobody has touched.
Read more
The posts usually start from a customer's state of mind at one specific moment, such as a parcel running late or a second visit to a product page, and end with a single change the reader can check in their own Klaviyo or Shopify account.
Two harder positions underpin the practical advice: deliverability is a list-size decision rather than an inbox fix, and reported email revenue should be reconciled to net before anyone relies on it.
Their tooling follows the same logic: small, read-only checks connected to live store data that return a ranked list or a number instead of making changes.
The emails brands never edit are the ones customers read most
Brands spend their retention attention on new campaigns while their highest-open messages—shipping confirmations and delay notices—stay at whatever the store default was.
Read more
They stay that way for boring reasons: transactional email sits in a different part of the platform, is usually configured by whoever built the store rather than whoever runs marketing, and never turns up in a revenue report.
Nabi proposes adding three things to the shipping confirmation: the mistake first-time buyers make, which the support inbox already documents; what to expect and roughly when, in product terms such as how a supplement feels at week two or how apparel sits after a wash; and one line from a person with an actual name.
None of it sells anything, which is why it gets through and survives internal review.
Cometeer ships frozen coffee, and a box left an extra day on a van arrives melted.
The email titled An Update on Your Recent Cometeer Order lands before the box.
It says the shipment was delayed and may have arrived melted, that melted capsules are safe to refreeze, and to reply if anything else is wrong.
The customer never reaches the refund or cancellation decision and reads the brand as paying attention.
Nabi points out that the trigger—a delayed shipment or an exception in Shopify shipping data plus a tracking service—is missing from nearly every Klaviyo account they open, even though those accounts all have abandoned checkout, welcome and post-purchase flows.
Deliverability is a list problem, not an inbox problem
When a brand says its email is going to spam, Nabi says mailbox providers are punishing brands for sending to people who do not want the email, not for sending too much of it.
Read more
The routine they describe: suppress anyone who has not engaged in 120 days, run a three-email sunset sequence first, return anyone who clicks to the active list, and let the rest go.
Nabi states the consequences plainly: a list down 30 to 60 percent, open rates moving from 18 to 38 percent, and roughly double revenue per email.
They compress the argument to this: unsubscribes are free list hygiene.
Those figures come from their client work and are given without methodology, so ask for the underlying data before treating them as benchmarks.
The post also names and answers the instinct the position runs against—that a smaller list is a loss—which is why Nabi writes it as a script for a conversation with a panicking CFO.
Nabi says they get a weekly direct message: “Our emails are going to spam, can you fix our deliverability?” Their specific answer: the cause is 80,000 subscribers who have not opened anything in 18 months, not Gmail.
Split the message by how many times someone has looked
Browse abandonment should not send the same offer to everyone, but most flows Nabi opens do, because the discount is what the template came with.
Read more
They read two real emails side by side.
Girlfriend Collective leads with the offer: “Take another look” plus 30% off.
Charlotte Stone sends “We noticed you noticing us,” then the shoe, the price and a plain link, with no code anywhere.
Neither is wrong, in Nabi's reading, because they answer two different people.
A first-time browser was only looking around, so a discount pays someone who has not decided and teaches them that browsing is how you get one.
A fifth visit means the person wants the product but is held up by price, sizing or whether it will arrive in time; that is where an offer or a straight answer earns its place.
The fix is one conditional split: viewed the product three or more times in the last week, or not.
Nabi says most flows lack it.
The same behavioural idea sits behind the Audience Builder and Reorder Rescuer skills, which build segments from how customers actually behave rather than from tags.
Two named browse-abandonment emails lead to a simple rule: add a conditional split that reserves the offer for repeat viewers and keeps the first-look email light and product-led.
A discount is worth less once the store has taught customers how to get it
In two posts, Nabi makes one argument about discount value: the store, not the customer, sets what a discount costs to obtain.
Read more
They signed up to three DTC brands with an email address only and met the same second screen: “finish signing up for texts to activate your discount,” with a phone field and only a small cross to escape.
They closed it, and the 10% code arrived by email anyway, so the screen was imposing a condition the flow did not actually enforce.
Nabi's reading is that nobody wrote it on purpose; it is the form builder's default second step.
The people who type a number probably would have anyway, while everyone else assumes the deal is gone and leaves before the welcome email lands.
The Black Friday post makes the same point over time rather than at one screen: a new visitor can collect 10% from the popup, 15% from the welcome email, 20% from cart abandonment and 25% from checkout abandonment.
A 30% sale-day offer is only 5% more than what was already available, and the sequence has taught customers that abandoning a cart pays better than buying.
Nabi's fixes: an honest second screen with a skip button that does not read as a penalty, which means slower SMS growth, and an audit of every discount reachable before a sale.
One trainer brand put a countdown game in front of the same screen that never sent a welcome email at all. Its 10, 15, 20 and 25 percent stack sits against a 30 percent Black Friday offer.
Report net email revenue, not the number the dashboard shows
Klaviyo attributes an order when it is placed, and a refund ten days later does not remove it from the board.
Read more
So a slide saying email drove 30% of revenue includes money the brand has given back.
Across the accounts Nabi audits, refunds and cancellations typically shave 3 to 6 percent off attributed email revenue, with supplements and apparel at the high end.
Their fix is a reconciliation, not a new dashboard: export refunds from Shopify, export attributed orders from Klaviyo, and produce net email revenue by flow.
It takes about 15 minutes for the first run and five for later ones.
Nabi also prefers clicks over opens when judging a list, because opens are unreliable.
Run the reconciliation on the last 90 days before a reporting call and bring the net number before anyone asks for it.
Nabi describes their own reconciliation prompt as returning net email revenue by flow. They ran it on a store doing over $200K a month.
Small, read-only Claude skills wired into live store data
Nabi's tooling is a set of Claude skills, each framed as a job a brand would otherwise hire for and connected to live Shopify or Klaviyo account data.
Read more
One post lays out twelve: a Funnel Inspector that reviews the path from product page to checkout and returns a ranked fix list, a Catalog Copy Engine, a Storefront Fixer, a Returns Decoder that reads 90 days of refunds to find which products lose margin, a Stockout Sentinel that cross-checks stock against ad spend, an Audience Builder, a Channel Scorecard that ranks acquisition by retention and margin, a Basket Builder, a Discount Auditor, a Search Capturer, a Feedback Decoder and a Reorder Rescuer.
Setup is described as a single connection through Shopify's AI Toolkit.
The skills return a ranked list, a score out of 100, or a net number; the Black Friday check and refund reconciliation are both read-only.
The roster post describes intended jobs and a one-line setup, not a finished skill running on a live store.
Ask for a live-store demonstration before relying on the capabilities.
Distribution is part of the pattern too: several posts end by asking readers to comment a keyword—PLAYBOOK, BFCM or NET—to receive the setup guide or prompt.
The Black Friday readiness skill connects to a store's Shopify and Klaviyo accounts.
It checks the discounts reachable before the sale, click behaviour, flows that email the same person twice in an hour, whether the list survives a heavy sending week, and old segments still pointed at last year's sale.
It returns the three most expensive problems, with a dollar figure for each.
Shows where a retention project can start when the standard flows already exist.
Read more
See how Nabi picks an overlooked asset and turns it into a short, specific edit list.
Nabi starts with the customer’s state of mind when the email lands: they have paid, the money is gone, and they will reopen the same message several times over the next few days to check tracking.
Usually, they get the store default: a tracking number and a button.
That persists because transactional email sits in a different part of the platform, is configured by whoever built the store rather than by marketing, and never appears in a revenue report.
The post proposes three additions: the mistake first-time buyers make, already documented in the support inbox; what to expect and roughly when, in product terms such as how a supplement feels at week two or how apparel sits after a wash; and a line from a named person.
None of it sells anything, which is why it reaches the inbox without internal objections.
For brands planning a campaign
A shipping-flow project here means editing one existing transactional template, not building a new campaign.
Start by identifying the recurring mistake in the support inbox, then address it.
Treat the email as a delivery-stage retention asset, not a logistics notice.
Shows what a winback flow looks like when it targets a delivery delay instead of an abandoned cart.
Read more
Start here for the clearest example of Nabi reasoning from a customer’s state of mind to a specific automated message.
Cometeer ships frozen coffee, and a box left an extra day on a van arrives melted.
Nabi traces the chain: the customer opens a liquid product, decides the shipment is ruined, asks for a refund, cancels the subscription and may leave a review first.
Cometeer sends an email titled "An Update on Your Recent Cometeer Order" before the box arrives.
It says the shipment was delayed and may have arrived melted, that melted capsules are safe to refreeze and drink, and that customers should reply if anything else is wrong.
It’s the same box and the same late van, but the customer sees a brand paying attention instead of absorbing the cost.
The flow is missing from most Klaviyo accounts, even though Shopify knows when an order shipped and a tracking service knows when a parcel is stuck or past its promised date.
Brands have abandoned checkout, welcome and post-purchase flows, but nothing that fires when a parcel is late.
For brands planning a campaign
Concrete retention work: trigger an email when a shipment is delayed or flagged as an exception, acknowledge the delay in plain language, and give a product-specific instruction. Expect the biggest refund and cancellation savings there, rather than in the post-purchase flow.
Useful for anyone assessing whether Nabi can justify a flow decision rather than copy a template.
Nabi compares two real browse-abandonment emails.
Girlfriend Collective leads with the offer: "Take another look + 30% off."
Charlotte Stone leads with "We noticed you noticing us," then the shoe, the price and a plain "Take me there" link, with no code.
Neither is wrong, Nabi argues; they answer different customers.
A one-time browser was only looking, so a discount rewards someone who hasn’t decided and teaches them that browsing earns a discount.
Someone on a fifth visit wants the product but is held up by price, sizing or whether it will arrive in time.
The proposed fix is a conditional split: has the person viewed the product three or more times in the last week?
Most flows Nabi sees lack that split.
For brands planning a campaign
A testable segmentation rule for rebuilding browse abandonment: reserve the offer for repeat viewers and keep the first-look email light and product-led, so you don’t spend the discount on undecided visitors.
Shows how trustworthy the usual Klaviyo revenue number is and gives newcomers a quick sense of the accounting-level scrutiny Nabi brings to retention work.
Read more
Klaviyo attributes an order when it’s placed, and a refund ten days later doesn’t remove it from the board.
So, Nabi argues, a slide claiming that "email drove 30% of revenue" includes money that was given back.
They say refunds and cancellations typically shave 3 to 6% off attributed email revenue, with supplements and apparel at the high end.
The proposed fix is a reconciliation: pull refunds from Shopify, pull attributed orders from Klaviyo, and reconcile the two into net email revenue by flow.
The first run takes about 15 minutes, they say, and later runs about five.
The post asks stores doing over $200K a month to comment in exchange for the exact prompt.
For brands planning a campaign
A reporting check to run before or during a retention engagement: show net revenue by flow instead of the platform default, creating a defensible baseline for attributing later improvements.
Shows why an engaged email programme degrades and lays out the reset step by step.
Read more
Start here to see Nabi challenge a common client instinct.
The post opens with a recurring direct message: emails are going to spam.
Nabi says the issue is usually not the mailbox provider, but years of sending to people who stopped opening.
The routine: suppress anyone unengaged for 120 days, run a three-email sunset sequence first, return anyone who clicks to the active list and let the rest go.
The list can fall 30 to 60%.
The post addresses the internal objection directly, acknowledging the reaction before listing claimed results: open rates moving from 18% to 38%, better inbox placement for engaged users, and roughly double the revenue per email.
The closing line—unsubscribes are free list hygiene—compresses the argument.
For brands planning a campaign
A usable first-week plan for a deliverability or list-hygiene engagement, and a way to set expectations with a client who measures success by list size rather than engagement.
Shows what a new subscriber actually experiences at a typical store.
Read more
An early read on whether Nabi spots small, costly friction as well as big strategic issues.
Nabi signs up for three DTC brands using only an email address.
All three show the same second screen: "Finish signing up for texts to activate your discount," a phone number field and only a small cross to escape.
Nabi closes it, not wanting texts from a brand they found minutes earlier.
The 10% code then arrives by email anyway, making the screen’s claim false.
The likely explanation is that no one wrote it deliberately; it’s the form builder’s default second step.
People who enter a number probably would have done so regardless, but everyone else assumes the deal is gone and leaves before the welcome email lands.
One named example, a trainer brand, also had a countdown game before the same screen and never sent a welcome email at all.
The proposed fix is an honest second screen asking whether the customer wants texts too, with a skip button that doesn’t feel like a penalty.
For brands planning a campaign
A fixed check for signup and welcome-flow work: compare what the second screen promises with what the code actually requires. A false condition can cost the whole welcome sequence.
Shows what kind of tooling they build and what it is meant to catch.
Read more
Start here to see the reasoning behind the free offers, not just the offer itself.
The post describes a free tool that connects to a store's Shopify and Klaviyo accounts and returns a readiness score out of 100 in about 15 minutes.
The argument underneath it is a discount-stacking walkthrough: a new visitor collects 10% from the popup, 15% from the welcome email, 20% from cart abandonment and 25% from checkout abandonment, all before Black Friday.
So a 30% sale day is only 5% better than what was already available, and the sequence has taught customers that leaving a cart pays.
The tool checks five things: every discount reachable before the sale, click behaviour rather than opens on the list, flows that email the same person twice in the same hour, whether the list can survive a heavy sending week, and old segments still pointed at last year's sale.
It is read-only, cannot change the store, and reports the three most expensive problems with a dollar figure for each.
For brands planning a campaign
A useful pre-Black Friday audit outline and an example of Nabi turning an audit into a free lead asset. The argument for stacking is directly relevant to planning any seasonal retention engagement.
The best entry point for a newcomer who wants the overall shape of the work before reading individual posts.
The post lists twelve skills, each framed as an employee a brand would otherwise hire and each connected to live store data.
Among them: a funnel inspector that reviews the path from product page to checkout and returns a ranked fix list; a returns decoder that reads 90 days of refunds to find which products lose margin to returns; a stockout sentinel that cross-checks stock against ad spend; an audience builder that draws segments from behaviour rather than tags; a channel scorecard that ranks acquisition by retention, lifetime value and margin; a discount auditor that names promos moving units while eroding margin; a feedback decoder that clusters reviews and support tickets into themes for product page copy and FAQs; and a reorder rescuer that finds customers past their reorder window.
Setup is described as a single connection through Shopify's AI Toolkit, and the post closes by asking readers to comment for the full setup guide.
For brands planning a campaign
Shows the framing and job list Nabi leads with, and which tasks they treat as highest value for a brand. The returns, feedback and reorder skills map most closely onto a retention engagement; the post is a useful menu when scoping one.
Splits flows by behaviour instead of sending everyone the same email
The browse abandonment post walks through a conditional split: viewed a product three or more times in the last week, or not.
Read more
Girlfriend Collective leads with the offer (“Take another look + 30% off”); Charlotte Stone sends “We noticed you noticing us” with the shoe, the price and no discount code.
Neither approach is wrong: they address two different people.
The one-time browser was looking around; the fifth-time visitor may be stuck on price, sizing or delivery timing, where an offer or a straight answer can help.
The same behavioural idea appears in the Audience Builder and Reorder Rescuer skills, which build segments from how customers behave rather than from tags.
For brands planning a campaign
Ask for the trigger conditions and split logic, not just a flow list. Look for a named condition with a threshold, so it can be reviewed and changed later.
Treats transactional and delivery emails as retention surfaces
Shipping confirmations get opened more than campaigns but mostly go untouched.
Read more
The suggestion is to include three things: what customers commonly get wrong the first time they use the product, what to expect and roughly when, and one human line from a person with a name.
The late-parcel post makes the case with Cometeer: an email arrives before the box, warning that a delayed shipment may have arrived melted and explaining that the capsules are safe to refreeze.
That can head off a refund or cancellation decision.
The trigger is a shipment delay or exception, using Shopify shipping data plus AfterShip or carrier status.
Ask how carrier or AfterShip exception data will be wired into the late-delivery flow; the post assumes that setup is already in place.
For brands planning a campaign
A retention brief can cover the post-purchase window—shipping and delay emails—which often sits outside the campaign calendar and the remit of whoever runs marketing.
Frames deliverability as a list-size problem, not an inbox problem
The argument: mailbox providers punish sending to people who do not want the email, not sending a lot of email.
Read more
The week-one fix: suppress anyone who has not engaged in 120 days, run a three-email sunset flow first, move clickers back to the active list and let the rest go.
Claimed results: a 30–60% smaller list, open rates rising from 18% to 38%, and revenue per email doubling.
Unsubscribes are described as free list hygiene.
For brands planning a campaign
Deliverability work here means suppressing large segments. Ask whether the brand will accept a materially smaller list in exchange for inbox placement.
Cleans up reporting on refunds, discount stacking and attributed revenue
The refund post points out that Klaviyo attributes an order when it is placed and retains the revenue after a refund, so an “email drove 30% of revenue” figure includes money given back.
Read more
Across audited accounts, the stated effect is 3–6% off attributed email revenue, with supplements and apparel at the high end.
The fix: export Shopify refunds and Klaviyo attributed orders, then reconcile them into net email revenue by flow.
The Black Friday readiness skill checks discounts a patient visitor can already reach—popup 10%, welcome 15%, cart abandonment 20%, checkout abandonment 25%—against a sale offer of 30%.
It also checks click rates rather than opens, flows that email the same person twice in an hour, spam survival under heavy sending, and old segments still pointed at last year's sale.
For brands planning a campaign
Expect email performance to be judged on net revenue and on how much a sale discount really discounts. A brand reporting gross attributed revenue may need to reconcile its figures before results are assessed.
Delivers the work through Claude skills connected to store data
One post lays out twelve Claude skills, each handling a job a brand might otherwise hire for: Funnel Inspector, Catalog Copy Engine, Storefront Fixer, Returns Decoder, Stockout Sentinel, Audience Builder, Channel Scorecard, Basket Builder, Discount Auditor, Search Capturer, Feedback Decoder and Reorder Rescuer.
Read more
Setup is described as a single connection through Shopify's AI Toolkit.
The Black Friday skill connects to Shopify and Klaviyo, checks five things and returns a score out of 100, the three most expensive problems and their dollar cost.
Refund reconciliation works the same way, from a prompt run against exported data.
The skills are described as read-only, connected to the brand's Shopify and Klaviyo accounts, and returning a scored or ranked list of problems to fix.
The roster post describes intended jobs and a one-line setup; it does not show a finished skill running on a live store or walk through configuration.
For brands planning a campaign
Ask for a demonstration using the brand's own store data, and confirm the read-only boundary and setup requirements before treating the tooling as production-ready.
Uses a consistent structure: a scene, a named example, one fix and a question back
Most posts follow the same structure: a short scene—a signup form, a late parcel on a van, a dashboard number—followed by a named example where one exists: Cometeer for the delay email, Girlfriend Collective and Charlotte Stone for browse abandonment.
Read more
Then comes an explanation of what is broken and what it costs, one specific change and a closing question that sends the reader to their own account, such as “Go and open your own shipping confirmation and read it back. Does it help?” or “If you checked yours today, what would the fifth-time visitor get?”
For brands planning a campaign
Request the same shape in a client deliverable: one named example, the mechanism, a single recommended change and a test the team can run without help.
Awais Nabi's posts state no sponsorship, affiliate, employment, investment or named-client relationship.
Read more
Klaviyo and Shopify are the platforms they audit and build in; Claude is the assistant they use to create store-focused skills.
The posts refer to client work — "every new client", "across the accounts we audit" — but name no client business.
Three DTC brands and one trainer brand in the signup posts also remain unnamed.
Named brands appear as case studies, not stated partners; the posts do not establish ongoing contracts.
Klaviyo
Mention
The email and lifecycle platform Nabi works in.
Read more
They describe auditing Klaviyo dashboards, browse-abandonment flows and list hygiene, and note that Klaviyo attributes revenue at order placement, leaving refunds on the board until reconciled out. No sponsorship or partnership with Klaviyo is stated.
Nabi builds store-focused Claude skills connected to Shopify data, names Shopify's AI Toolkit as the setup connection, and calls Shopify's default shipping confirmation untouched retention space that most brands never edit. No sponsorship or partnership with Shopify is stated.
Anthropic's assistant serves as the base for the store skills Nabi writes and gives away: a free Black Friday readiness check that connects to Shopify and Klaviyo, and a refund-reconciliation prompt that returns net email revenue by flow.
Read more
No sponsorship or partnership with Anthropic is stated.
Cometeer is Nabi's example of a brand that emails customers when a parcel is delayed, before the box arrives, so a melted coffee shipment does not become a refund.
Read more
They use it to argue that most stores have no late-parcel email at all. No relationship with Cometeer is stated.
One of two contrasting browse-abandonment examples: the email leads with a 30% offer, which Nabi reads as paying a one-time browser who had not decided anything.
Read more
The example comes from Klaviyo's roundup of real flows. No relationship with the brand is stated.
Awais Nabi writes short LinkedIn posts about the emails and settings a Shopify brand already has and rarely revisits.
Read more
Each usually ends with a check readers can run in their own Klaviyo or Shopify account.
The work covers shipping and delivery emails, browse and cart abandonment flows, signup and discount capture, list hygiene and deliverability, and refund-to-net revenue reporting.
Two positions run underneath the practical advice: deliverability is a list-size decision rather than an inbox fix, and reported email revenue should be reconciled to net before anyone relies on it.
Several posts describe free Claude skills connected to live store data that return a ranked list, a score out of 100, or a net number rather than making changes.
The roster post describes intended jobs and a one-line setup.
Before relying on these tools, ask to see a skill running on a live store.
To see the method rather than the tooling, start with the Cometeer late-parcel email, the two named browse-abandonment emails, and the refund reconciliation, then read the chapter-like posts on shipping confirmations and popup second screens to see how the diagnostic approach repeats.
Both work on ecommerce email and CRM programs for clients and put Claude at the centre of how that work gets done.
Read more
Biller describes building an onboarding flow with custom forms, documents and emails in Claude, connecting project management so tasks are created automatically, and having Claude review the CRM, chats and email each day to produce a task list. Biller also walks through a client build that includes email capture forms, welcome flow, browse abandonment, cart abandonment and campaigns.
Biller's posts read as an agency operator describing the systems behind serving clients, with AI in a back-office role running CRM and onboarding plumbing.
Awais Nabi's posts take one default flow or email, show what that default costs the brand, and point readers to their own account.
The Claude work they describe is packaged as free, read-only checks that return a ranked list or a number, rather than as an internal agency process.
Both use AI tools as a practical way to do Klaviyo work.
Read more
Corto describes turning Claude Code into a Klaviyo execution engine that analyses an account, finds opportunities and runs CRM workflows, with a documented 10-minute setup and parallel workflows for flows, campaigns, segmentation, deliverability and analytics. The follow-up post describes pairing a model with a CRM workflow to plan a monthly campaign calendar, build lifecycle flows, and write headlines, copy and calls to action.
Corto emphasizes production at speed: generating a month's campaign concepts and lifecycle flows inside one workflow, packaged as a setup guide. Awais Nabi's posts mostly diagnose one email or flow, use named brand examples, and describe skills that are explicitly read-only: they return a score, a ranked fix list or a net revenue figure rather than producing campaigns.
Both work on store problems that arise while a customer is waiting for an order.
Read more
Hussain's post on post-purchase disputes traces them to customers not knowing whether or when the product will arrive, and recommends stating delivery time on the product page and emailing at order confirmation, warehouse dispatch, parcel location and delivery. Awais Nabi's late-parcel and shipping-confirmation posts cover the same delivery-expectation territory, each from the symptom of one specific store.
Hussain frames the work as conversion-rate optimization on Shopify stores, using numbered root causes and step lists.
One of Awais Nabi's posts also addresses an on-site page problem: removing a 23-second hero video to fix attention mismatch, page speed and a fake in-video call to action.
Nabi's other work stays inside Klaviyo and email: which flow, which trigger, which conditional split, and what the email should actually say.
The only published audience figure is Awais Nabi’s LinkedIn follower count: 3,091 on 9 October 2026.
Read more
It confirms an active account, but not reach, engagement or who is reading.
The eight posts, dated 24 May to 28 September 2026, target people running Shopify stores and managing retention: they cover Klaviyo deliverability and list suppression, browse-abandonment flows split by visit count, shipping-confirmation emails, discount leakage before Black Friday, and reconciling refunds against attributed email revenue.
The implied audience is store owners, email or retention managers, and the agencies serving them—not general consumers.
For a Shopify retention and winback campaign, ask Nabi for engagement or reach figures on recent retention, flow and deliverability posts, along with each post’s format and depth, so you can compare like-for-like.
The follower count does not verify audience geography, age, gender, employer, occupation or seniority.
If decision-makers at DTC brands are essential, ask whether they have audience survey results or another documented source, such as campaign performance they are permitted to share.
LinkedIn followers
3,091
LinkedIn profile record for Awais Nabi · 2026-10-09
Awais Nabi builds AI-assisted tools and audits for Shopify and DTC brands: a Black Friday readiness check that reads Shopify and Klaviyo data, a refund-reconciliation tool aimed at stores doing over $200K a month, and twelve Claude skills for funnel, catalog, retention, and inventory jobs.
Read more
They share these with readers who comment on a post.
Nabi says they sign DTC brands as direct clients rather than taking paid placements, with hands-on work in email, lifecycle, and parcel communication.
For brands, that points to a project or consulting engagement arranged in conversation, not a packaged sponsorship slot.
The tools are read-only and require access to a brand’s Shopify and Klaviyo accounts, so data access is part of scoping.
Ask Nabi directly about format, deliverables, pricing, and usage rights; no terms are published in these posts.
A Shopify DTC brand doing over $200K a month wants help with retention: its shipping and winback flows, and the email programme around them.
Read more
This is the closest match to what Awais Nabi's posts show.
The posts cover the exact assets this retention project needs.
Shipping: a post argues that transactional email is the most-opened message a brand sends and usually the least edited, then offers three additions — the mistake first-time buyers make (which the support inbox already documents), what to expect and roughly when, and one line from a named person.
Late parcels: the Cometeer example sets out a flow triggered by a shipment delay or exception, using Shopify shipping data plus carrier or AfterShip status to send one plain email before the box arrives and pre-empt a refund-and-cancellation decision.
Winback: browse abandonment split by whether someone viewed the product three or more times in the last week, with the offer reserved for repeat viewers and backed by two named, contrasting real emails.
List health: suppress anyone unengaged for 120 days, after a three-email sunset sequence.
Reporting: reconcile Shopify refunds against Klaviyo attributed orders into net email revenue by flow — the measurement a retention project needs to justify itself.
Two further things help.
The proposed work edits emails and flows the brand already has, suiting a small scope and fast start rather than a rebuild.
The reasoning is also presented in a form a marketing team can check: a named condition with a threshold, one change, and a test the team runs in its own account.
Before commissioning, ask for a live-store demonstration, case studies or results data, and pricing.
The refund-reconciliation offer was aimed explicitly at stores doing over $200K a month, so smaller brands should ask whether the same approach applies.
When to choose a specialist
A consumer brand wants a paid creator to put its product in front of a large new audience: short-form video or sponsored posts measured on reach, views and follower scale, aimed at shoppers rather than store operators.
Read more
Awais Nabi's posts do not support this paid-reach campaign.
They show 3,091 LinkedIn followers as of 9 October 2026, but no engagement rate, impressions or demographic data to assess the reach such a campaign depends on.
No video, podcast or long-form channel appears.
The subject matter is operational advice for people who run Shopify stores, not product-led content written for shoppers, and the posts include no sponsorship, rate card or media kit.
The commercial shape shown is a project or consulting engagement arranged directly, not a packaged sponsored placement.
A related need fails for a different reason: a brand not on Shopify or Klaviyo, or one with a very small list.
The described work relies on Shopify's AI Toolkit connection to store data and Klaviyo flow structure; the refund-reconciliation prompt was offered specifically to Shopify stores over $200K a month.
The methods may transfer, but the posts do not show them applied elsewhere.
For a reach-led campaign, ask directly for platform performance data, any video or sponsored work, and audience composition.
If the stack is different, ask how the tooling and flow analysis would change.
A worked campaign example
A 30-day flow-repair sprint for a Shopify DTC brand on Klaviyo, doing over $200K a month, with roughly 60,000 subscribers who have been mailed heavily.
Week one — baseline.
Download Shopify refunds and Klaviyo attributed orders for the last 90 days, then reconcile them into net email revenue by flow.
That gives the client a defensible starting number instead of the dashboard's gross attributed figure, which Awais Nabi's posts put 3–6% high for supplements and apparel.
Also pull the existing flows and check their defaults: what the signup second screen promises against what the form actually requires, what the shipping confirmation contains, and whether browse abandonment sends the same discount email to a first-time browser and a fifth-time visitor.
Week two — post-purchase and delivery.
Rebuild the shipping confirmation with three additions: the first-use mistake the brand's support inbox already documents, what to expect and when in the brand's own product terms, and one human line from a named person.
Then build the missing flow: trigger on a shipment delay or exception and send one plain email before the parcel arrives, acknowledging the delay, explaining what to expect, and saying what to do if it arrives in a poor state — no discount code.
The Cometeer pattern applies directly to perishable or temperature-sensitive products; for most brands, the email is an acknowledgment plus instruction.
Week three — winback and lifecycle splits.
Split browse abandonment by whether the person viewed the product three or more times in the last week.
Repeat viewers get the offer and a straight answer to the usual blockers (price, sizing, delivery timing); first-look visitors get a light product-led email with no code.
Add the reorder-window segment from the described skill set, and check for flows that email the same person twice in an hour.
Week four — list condition and review.
Where engagement is poor, suppress anyone unengaged for 120 days, but run the three-email sunset first and move clickers back to the active list.
Expect the sendable list to fall materially and brief the client beforehand; the argument is that deliverability improves as a result.
Close by comparing net email revenue by flow against the week-one baseline, then list the two or three most expensive remaining problems with a dollar figure for each, mirroring how the Black Friday check reports its findings.
Before starting, ask for a live demonstration of the audit skill on the client's own store data, confirmation of the data access required for the read-only connection, and a scope naming which flows are in and which are out. Results depend on the brand's product, list condition and carrier data; the posts describe a method and outcomes from accounts they audit, not a guaranteed uplift for this brand.
A better fit when the brand wants the whole lifecycle built and maintained as an ongoing engagement, rather than one or two flows diagnosed and repaired.
Read more
In the posts, Biller describes a new client whose onboarding is complete: email capture forms, welcome flow, browse abandonment, cart abandonment and campaigns are all built and waiting on seasonal stock before the first send (August 2026).
The posts also show Claude building client-facing forms, documents and emails; generating a daily task list from CRM, projects, messaging and email; and creating a deliverability dashboard for Klaviyo users.
For a brand looking to install the lifecycle and keep it moving, this is closer to the described approach than a diagnose-one-thing-and-retest engagement.
The tradeoff is what a buyer can verify.
These posts describe the build and internal automation, but don’t review a named brand’s email line by line, identify a trigger and threshold, or show the late-parcel email that arrives before the box.
A brand commissioning a few specific flow fixes, with the reasoning open to inspection, has less to assess here.
A brand seeking a complete programme that will be installed and operated—and judged on its operation rather than a close reading of one email—has more.
A better fit when the need is Klaviyo production throughput—a month of campaigns, lifecycle flow concepts, creative directions and copy from one pipeline—rather than repairs to a handful of flows.
Read more
The October 2026 post documents a Claude Code setup running separate workflows for flows, campaigns, segmentation, deliverability and analytics in parallel, turning Klaviyo data into actions the marketer reviews and approves.
The September 2026 post shows a monthly pipeline from campaign calendar to finished concepts and copy, with speed identified as the main gain.
For a brand that needs volume and consistency across a heavy sending calendar, this is a closer match.
The posts describe the marketing process—analyse performance, identify gaps, prioritise opportunities—and deliver concepts ready to recreate inside Klaviyo.
They don’t spell out specific fixes: a browse-abandonment split after three or more views, the late-parcel email that arrives before the parcel, 120-day suppression after a three-email sunset, or a named brand’s email reviewed as an example.
A brand with one or two costly flow problems that needs to show its finance lead a net figure before and after would be taking on more production than the problem requires, while still having to rebuild and test the drafts in Klaviyo.
A better fit when the problem is disputes or chargebacks and the fix involves the storefront as well as email.
Read more
The March 2025 post links PayPal and bank disputes to customers not knowing whether or when a product will arrive, and to fears of fraud caused by late delivery.
It recommends stating delivery times on the product page before checkout and sending a sequence of emails: order confirmation, dispatch from the warehouse, the parcel’s location, its arrival in the customer’s city and delivery day.
The March 2026 post identifies a slow homepage hero video that didn’t match fast-scrolling ad traffic, and replaces it with a static image and clear call to action.
For a brand whose first screen and product-page delivery expectations are part of the problem, this covers the page-level work a flow-only brief would miss.
Awais Nabi’s posts touch on shipping communication, but offer less detail and are older: two posts, one from March 2025, describe delivery emails as a cadence rather than specifying a trigger, a template or a message for when the parcel is already late or arrives in poor condition.
That exception case—a flow triggered by a shipment delay or exception and arriving before the box—is the specific gap the other posts address.
The posts also don’t describe Klaviyo flow structure, list conditions or email-revenue reconciliation.
A brand focused mainly on its email programme should ask for details on those points.
This profile draws on eight LinkedIn posts by Awais Nabi, read in full rather than from headlines or search snippets.
The posts cover Shopify and Klaviyo email work: shipping and delivery emails, browse and cart abandonment, discount capture, list hygiene and deliverability, refund-aware revenue reporting, and free read-only Claude skills connected to store data.
The posts do not show publication dates, so nothing here claims an order in which the ideas developed.
The account showed 3,091 LinkedIn followers as of 9 October 2026; no engagement, impression or demographic data is available in the posts here.
Comparisons to other creators draw on posts from three other LinkedIn accounts, dated March 2025 to October 2026, covering CRM and onboarding automation, Klaviyo execution workflows built on AI models, and Shopify conversion-rate audits.
The posts here include no videos, transcripts, client case studies, pricing or published partnership terms, and state no sponsorship, affiliate or named-client relationship.
A remaining gap is name-search identity research: the posts here do not establish whether signature books, shows, businesses or earlier career work also explain searches for the name.
