DEV Community: DTDC Media

Klaviyo vs Shopify Email: When to Switch

DTDC Media — Mon, 05 Oct 2026 10:44:25 +0000

Stay on Shopify Email, now sold as Shopify Messaging, while 10,000 free emails a month covers your sends and your automations fit its templates (Shopify help centre, 4 October 2026). Switch to Klaviyo when profile data, app integrations and flow depth start deciding revenue, and budget from a $60 a month starting price (Klaviyo product page, 4 October 2026).

What are you comparing now that Shopify Email is Shopify Messaging?

First, the name. The page at shopify.com/email now carries the headline "Shopify Messaging", and the product bundles email, SMS and WhatsApp under the line "Email, SMS, and WhatsApp marketing made for commerce" (Shopify Messaging page, 4 October 2026). The help centre URLs have moved under /shopify-messaging/ as well. Shopify Email still exists as the email part of that bundle, and the pricing below is the email pricing.

Second, what it is. Shopify's own pitch is simplicity: "Create simply", "Use templates and skip coding", "Automate emails quickly", with Sidekick AI for drafting, and a claim of "over 500k entrepreneurs" using it (Shopify Messaging page, 4 October 2026). It is available on all Shopify plans with no monthly commitment. It does not describe itself as a CRM, and it does not publish an integration count on the pages we fetched.

Klaviyo describes itself as "the autonomous B2C CRM" with "native integrations with ecommerce platforms like Shopify", "350+ apps" and "205,000+ relationship-driven brands across 100 countries" (Klaviyo product page, 4 October 2026). It also has a foot inside Shopify: "Klaviyo Starter in Shopify" is a free edition with 250 profiles, 500 emails a month, three automated messages live at once, one live sign-up form and Powered by Klaviyo branding (Klaviyo help centre, updated 21 September 2026).

So the comparison is a usage-billed messaging layer built into your store against a profile-billed CRM that plugs into it, and for a new store the honest answer is usually the first one.

Is free email volume the thing you are optimising for?
If the answer is yes, Shopify wins and it is not close.
Shopify Email pricing is per email sent, with no subscription. "Every month, you can send up to 10,000 manual or automated emails for free. After that, only pay for what you use at $1 USD per 1,000 additional emails sent" (Shopify help centre, 4 October 2026). Above 300,000 emails in a month the rate falls to $0.65 per 1,000, and above 750,000 to $0.55 per 1,000. Unused emails do not carry over, and abandoned checkout automations are always free. Those volume tiers date from June 2023 and have not moved since. A store sending 40,000 emails a month pays $30 for the 30,000 over the free allowance. A store sending 8,000 pays nothing.
SMS inside Shopify Messaging is charged separately and only in select countries: $0.012 per message in the US, $0.025 in Canada, plus a $2.15 monthly charge for each approved toll-free number, with 25 free test messages a week (Shopify help centre, 4 October 2026). Shopify paused SMS in Spain on 15 September 2026 and in Austria on 1 October 2026, a reminder that country coverage is Shopify's decision, not yours.
Klaviyo "starts at $60 per month based on active profiles", and the free tier stops at 250 active profiles and 500 monthly sends (Klaviyo product page, 4 October 2026). An active profile is "any profile, regardless of consent status, that can be emailed through Klaviyo" (Klaviyo help centre, 25 March 2026), so you pay for the list, not the send. Klaviyo does not print its tier prices on the page we could retrieve; check the price at your profile count in-product before you budget. Klaviyo SMS is a separate Mobile Messaging subscription billed per message since 13 July 2026, with rates shown in-product only.
The gap is real. A 5,000-profile store sending twice a month is inside Shopify's free allowance and twenty times past Klaviyo's 250-profile free tier. Free wins that comparison until the emails themselves stop performing.

When does the switch to Klaviyo pay for itself?
The switch pays for itself when the limits of a template tool, not the price of it, are costing you orders. Four signals.
One: you want more than a few automations running at once. Shopify's page promises you can "Automate emails quickly" but does not publish an automation count. Klaviyo's free Starter in Shopify caps live automations at three and forms at one (Klaviyo help centre, updated 21 September 2026); those caps are the free edition's limits. If your plan runs welcome, browse, cart, checkout, post-purchase, winback, sunset and replenishment flows at once, you have outgrown a free tier by definition.
Two: your other apps need somewhere to send events. Klaviyo's "350+ apps" claim (Klaviyo product page, 4 October 2026) is the practical reason most Shopify brands move. The apps around your store, from reviews to loyalty to subscriptions, need an email platform to receive their events and trigger flows from them. Shopify Messaging does not publish an equivalent integration count on the pages we fetched.
Three: your list is the asset. Klaviyo bills per profile precisely because the profile, not the send, is what it manages. If you are building segments on order history and engagement, the CRM framing is the product. If you are sending a monthly newsletter to everyone, it is overhead.
Four: SMS in a market Shopify does not serve, or at a rate you want to negotiate. Shopify publishes a US rate of $0.012 per message (Shopify help centre, 4 October 2026); Klaviyo's rates are in-product, which cuts both ways.
Do not switch for deliverability folklore, for branding on free Klaviyo (it carries Powered by Klaviyo footers), or because an agency only knows one tool. Do switch when the post-purchase email flows you want to run need data Shopify's templates cannot see. In our retention email programmes, [BMO NUMBER: insert the flow-attributed revenue share you measured after moving a brand from Shopify Email to Klaviyo, with account count and window] is the before-and-after figure that justifies Klaviyo's $60 a month floor (Klaviyo product page, 4 October 2026). For the next step up the ladder, Klaviyo vs ActiveCampaign covers the self-serve rival, and Sendlane vs Klaviyo covers the per-send alternative.

What Percentage of Customers Leave a Review?

DTDC Media — Mon, 14 Sep 2026 11:52:35 +0000

Somewhere between two and five orders in a hundred produce a review at most DTC brands. The brands that do this well can reach four times that.

The gap is almost entirely operational, and the number itself is worth knowing before you decide whether your review programme is broken.

The Benchmark

Okendo's own merchant data gives a working benchmark of 2.5% to 5% of orders producing a review, with the top 10% of merchants reaching 22% Okendo, reviews metrics and optimizations.

Treat that as the shape of the distribution rather than as a fixed target.

If you are at 1%, something is likely misconfigured. If you are at 5%, you are around the normal range. If you are at 12%, you have a genuine advantage and should be using that review volume on the product pages that need the most help converting.

Two variables move the baseline before any tactic does.

The first is product category, because a considered purchase often produces more reviews than a commodity purchase.

The second is time to value. A customer cannot properly review a supplement after two days, and asking them too early is how you end up with a three-star review that says “too early to tell.”

Why the Rate Matters More Than It Looks

Reviews are a conversion input, not a vanity metric. Bazaarvoice's network data attributes a 32% increase in conversion to product pages carrying ratings and reviews, rising to a 150% increase where photo and video reviews are present, with a 15% lift in average order value alongside it Bazaarvoice, product detail page conversion. PowerReviews measured a 20% conversion lift from simply seeing reviews and 128% from interacting with them, and found the optimal star rating for conversion sits between 4.75 and 4.99 rather than at a perfect 5.0 PowerReviews, average rating impact on conversion.

That last finding is where many brands go wrong.

A wall of perfect five-star reviews can look filtered. A high rating with visible variation feels more authentic.

Bazaarvoice's 2025 Shopper Experience Index found that 46% of consumers named review authenticity as their top frustration, while looking for reviews was the single most common step shoppers took after discovering a product, at 43% Bazaarvoice Shopper Experience Index 2025, 30 September 2025.

The Four Changes That Move the Number

Trigger from delivery, not from order.

Asking before the parcel arrives suppresses the response rate and can hurt sentiment. Use the carrier delivery event, then add a usage delay appropriate to the category.

Send a second ask.

Most brands send one email and stop. The second request, ideally on a different channel, is where a large part of the gap between a 3% and 12% review rate can live.

The channel decision is covered in SMS review requests.

Reduce the ask to one tap.

A star rating inside the email itself, with the written review optional on the landing page, creates less friction than a request that immediately leads with a blank text box.

You can always ask for written feedback after the customer has already submitted the rating.

Reward with points rather than discounts.

A discount for a review reduces margin on the next purchase and can bias the review.

Points generally cost less and connect directly with the programme you already operate. This is where the loyalty program and the review programme can reinforce each other.

What to Do With the Reviews Once You Have Them

Do not distribute reviews evenly across every product page.

A product with four reviews and a 2% conversion rate can gain far more from twenty additional reviews than a bestseller gains from another two hundred.

Prioritise products with low review volume and weaker conversion first.

Pull photo and video reviews into product pages and reuse them in email creative. The broader strategy is covered in UGC marketing for ecommerce.

And answer negative reviews publicly.

A visible, calm response to a three-star review can do more for perceived authenticity than another hundred perfect ratings.

We build and run review programmes across email and SMS as part of our review and UGC program services.

The email mechanic itself is covered in the review request email.

Contribution LTV: Why Revenue Alone Can Mislead Ecommerce Brands

DTDC Media — Tue, 01 Sep 2026 07:23:37 +0000

Customer lifetime value sounds simple: estimate how much revenue a customer generates across their relationship with your brand. But revenue alone does not tell you how much that customer is actually worth.

A customer who spends $600 over their lifetime is not automatically a $600 customer. Product costs, discounts, shipping subsidies, returns, payment fees, and acquisition costs all reduce the amount of that revenue the business can actually keep.

That is why ecommerce brands should pay attention to contribution LTV.

Contribution LTV estimates the economic value a customer creates after accounting for the variable costs required to serve them. It gives growth teams a much safer number to use when setting acquisition budgets, evaluating retention programs, and deciding how aggressively to scale.

Revenue LTV vs Contribution LTV

Revenue LTV measures total customer spending.

If a customer places four $75 orders, their revenue value is $300.

But imagine the brand operates at a 55% gross margin. Before considering additional variable costs, that $300 in customer revenue represents only $165 in gross profit.

Add shipping subsidies, payment processing, returns, fulfillment, and promotional discounts, and the amount available to pay for acquisition and overhead falls again.

Using the $300 figure when determining an acceptable CAC can therefore create the illusion of profitable growth even when the underlying economics are weak.

A better approach is to calculate customer value from the margin the customer contributes.

You can establish the starting point using BMO Media's free Customer LTV Calculator, then compare the result with the actual cost of acquiring and serving that customer.

Why Contribution LTV Changes Acquisition Decisions

Suppose two brands both generate $400 of lifetime revenue from an average customer.

Brand A operates at a 70% margin.

Brand B operates at a 35% margin.

Their revenue LTV is identical, but their economic ability to acquire customers is completely different.

Brand A has substantially more contribution available to fund paid acquisition, creative production, agency fees, loyalty rewards, and operating expenses.

That is why CAC targets should never be based on topline customer revenue alone.

The more accurately you understand customer contribution, the more confidently you can decide whether a $40, $70, or $100 acquisition cost is sustainable.

Retention Makes the Equation More Powerful

Contribution LTV is not only an acquisition metric.

It also shows why retention can improve profitability without requiring the brand to win another paid-media auction.

A second or third purchase usually does not carry the same acquisition expense as the first purchase. That means additional orders can contribute disproportionately more profit, especially when they are generated through email, SMS, loyalty, subscriptions, and post-purchase automation.

This is where a strong retention marketing agency can influence the economics directly: not simply by increasing campaign revenue, but by increasing purchase frequency and extending the profitable customer relationship.

Turn Customer Value Into a Working Number

Contribution LTV should not live in an annual strategy deck.

Recalculate it whenever your margin structure, pricing, acquisition costs, return rates, or repeat purchase behavior changes significantly.

Start with your current AOV, purchase frequency, retention assumptions, and margin using the Customer lifetime Calculator. Then compare that value against CAC by channel.

The result gives your team something much more useful than a large lifetime revenue number.

It tells you what a customer is actually worth — and how much you can afford to spend to create more of them.

SMS Marketing ROI: How to Measure It Properly

DTDC Media — Fri, 21 Aug 2026 11:59:59 +0000

SMS marketing ROI is (SMS-attributed profit − program cost) ÷ program cost. The inputs that make it honest: margin-based revenue, all-in costs including carrier fees, and attribution you actually trust. Benchmarks for 2026: automated texts earn around $0.74 per message; campaigns around $0.15. Here is the full calculation, with a worked example.

Count every cost. Platform subscription, per-message and carrier fees, list-acquisition spend (the popup incentive is an SMS cost, even when finance books it as a discount), and management time or agency fees. Per-message economics make SMS unlike email — every send has a marginal price, which is why volume discipline is an ROI lever rather than a style preference, and why "send more" is sometimes the exact wrong answer to a revenue target.

Measure revenue at the margin, with honest attribution. Use your platform's attributed revenue but know its windows, deduplicate against email so one order is not credited twice, and convert revenue to gross profit before computing ROI. A 10× revenue return at 30% margin is a 3× profit return — still excellent, differently sized, and the version your P&L recognizes.

A worked example. Suppose a 10,000-subscriber list gets four campaigns a month — 40,000 sends — plus roughly 6,000 automated messages from cart, browse, and back-in-stock flows. At the Omnisend benchmark rates of $0.15 and $0.74 per message, that models to about $6,000 of campaign revenue and $4,400 of automated revenue: $10,400 total. At 60% product margin, $6,240 of profit. Against, say, $1,500 of platform, message, and carrier costs plus management time, the channel clears a healthy multiple — and the automated 15% of sends produced over 40% of the revenue, which is the mix insight the blended average hides.

Benchmark the split, not the average. The channel's economics concentrate in automation: Omnisend's 2026 data shows automated SMS converting at 0.77% versus 0.12% for campaigns, and Postscript's benchmarks put abandoned-cart texts at $3.52–$10.95 earned per message for the middle half of Shopify stores. Our own programs land in that band — Darc Sport's campaigns earned $7.89 per message sent, with SMS revenue up 29.8% in two months. If your automated-to-campaign split leans campaign, your ROI problem is a mix problem before it is anything else.

Account for list growth as an investment, not a cost of the month it happened. The popup discount that captures a subscriber books as an expense today, but the subscriber pays back across their whole messaging lifetime — Postscript's benchmarks put SMS subscriber lifetime value between $25 and $553 across the 25th to 90th percentile of stores. Amortize acquisition incentives against that horizon and list growth usually reads as your best-returning SMS line rather than your worst: a $10 welcome incentive against even the low end of that value band clears quickly. The reverse discipline applies too — a subscriber who never converts is not free, since every message sent to them carries marginal cost. Prune the never-engaged on a schedule; a smaller list with clean economics beats a padded one on both the ROI math and deliverability.

The incrementality caveat. Attributed is not incremental — some SMS-credited orders would have happened anyway through email or direct visits. The clean check is a periodic holdout: suppress a random slice of the audience from a campaign and compare purchase rates. Even one holdout test a quarter keeps the ROI number honest and usually strengthens the case for flows over blasts.

The two silent ROI killers. Over-sending — each marginal blast costs real money and burns goodwill measurable in opt-outs — and consent shortcuts, where compliance exposure converts into legal risk no ROI line captures. Both are program-design failures; the guardrails are in our SMS best practices.

Platform choice moves the denominator. Pricing models differ meaningfully between the leading platforms — usage-based tiers versus negotiated contracts — and at volume that difference is an ROI input, not a procurement detail. The cost architecture comparison is in Attentive vs Postscript. And if measurement itself is the blocker, it is a solvable one: our SMS programs ship with deduplicated attribution reporting as a standing deliverable, because an unmeasured channel is an unmanaged one.

Average Customer Lifetime Value in Ecommerce: Benchmarks

DTDC Media — Thu, 20 Aug 2026 09:24:18 +0000

There is no single average customer lifetime value in ecommerce — the honest range runs from under $30 to over $500 per customer depending on category, margin, and purchase frequency. Postscript's 2026 benchmark across 17,000+ Shopify stores puts SMS subscriber lifetime value between $25 and $553 from the 25th to the 90th percentile — a 22× spread inside one dataset. The useful question is not "what is average" but "what should MY number be." Here is how to benchmark it properly.

Why the spread is so wide. CLV multiplies four inputs — order value, purchase frequency, relationship length, and margin — and every category weights them differently. A supplement brand with $45 orders and monthly replenishment can out-earn a furniture brand with $900 orders and a five-year repurchase cycle. Margin widens the gap further: two stores with identical revenue-per-customer and a 25-point margin difference are not in the same business. That is why copying a published "average" is useless; your benchmark has to come from your own cohort math. (The full formula with a worked example lives in our customer lifetime value guide.)

Pick the right horizon before you compare anything. CLV is quoted over wildly different windows, which is how apples get compared to orchards. A 90-day CLV is an acquisition metric — it tells you what a new customer returns fast enough to fund ads. A 12-month CLV is the planning metric — solid enough data, near enough horizon to act on. A three-year CLV is a valuation metric, useful for board decks and dangerous for budget decisions when your store is younger than the window. When someone quotes you an "average CLV," ask the window first; the number is meaningless without it.

Benchmark against structure, not averages. Three comparisons beat any industry table. Your 12-month CLV against your CAC — the ratio should clear roughly 3:1 on margin. Your subscriber CLV against your non-subscriber CLV — run the math on both groups, because subscription customers should be a multiple, not a rounding error; if they are not, the program leaks, and subscription churn math shows where. And your owned-channel customers against paid-only customers — people on your email and SMS lists reliably out-spend those you can only reach by paying an auction again.

Three measurement mistakes that inflate the number. First, counting revenue before returns and refunds — apparel and footwear brands can overstate CLV by double digits this way, since return rates concentrate in exactly the categories with the highest gross figures. Second, skipping the margin adjustment: a customer who generates $400 of revenue at 35% margin is worth $140, and every acquisition decision made against the $400 figure overpays. Third, survivorship in aging cohorts — if you compute "average lifetime" only from customers who stayed, the churned majority disappears from the math and the relationship length stretches flattering. The clean discipline: net revenue, margin-adjusted, full-cohort denominators, fixed horizon. It produces a smaller number than the one in most pitch decks, and it is the only version that will not mislead a budget.

What actually moves the number. In our client work the biggest single-quarter CLV movements come from automation and channel orchestration, not acquisition: for Spoonful of Comfort, owned channels carried 46.1% of total BFCM revenue after we restructured email and SMS together — repeat behavior you can see directly in cohort value. Subscription programs compound it further, converting purchase frequency from a probability into a schedule; that is why subscriptions sit inside our retention stack rather than beside it.

Get your number in two minutes. Put your AOV, purchase frequency, and margin into the free customer lifetime value calculator. You will get a defensible CLV to hold against your CAC and your category — and the baseline every retention program you fund from here should be measured against. Rerun it quarterly; a benchmark you never revisit is a guess with a birthday.

How Long Does Email Marketing Take to Show Results?

DTDC Media — Mon, 17 Aug 2026 16:31:57 +0000

Email marketing shows first revenue movement in 30–45 days, meaningful program results at 90 days, and compounding returns from month four onward. Flow rebuilds pay back fastest; list health and repeat-rate gains take a quarter. Anyone promising a transformed channel in two weeks is describing luck. Here is the honest timeline, stage by stage, with what to measure at each gate.

Days 1–30: configuration revenue. The first month is audit, authentication (SPF, DKIM, DMARC), and rebuilding the core flows — welcome, abandonment, post-purchase. Some revenue moves immediately, because broken flows start catching intent again the day they go live. But the real product of month one is a machine that can compound. If deliverability was impaired, fixing it IS the result, even though it looks like nothing on a dashboard — placement recovers on the receiving servers' schedule, and everything else waits on it. Gate metric: flows live, authentication passing, baseline documented.

Days 31–60: the automation layer earns. Flows are where email concentrates its money — Klaviyo's 2026 benchmarks show automations generating about 41% of email revenue from just 5.3% of send volume, at click rates of 5.58% versus 1.69% for campaigns. By day 60 the rebuilt flows have enough data for first optimization passes, segmentation deepens, and campaign cadence stabilizes. This is when the channel starts visibly outearning its old baseline. Gate metric: flow share of email revenue, trending up.

Days 61–90: the honest read. Now the numbers mean something: flow share climbing toward the benchmark band, list engagement rising while the list grows, repeat behavior starting to move. In our own client programs this is where compounding becomes visible — Darc Sport's automations reached 30% of total email revenue as the program matured, not in week two. Gate metric: 90-day revenue against the documented baseline, reconciled to your store's numbers rather than platform-reported attribution alone.

Months 4–6: the part nobody sells. The quarter after the proving quarter is where email's structural advantage shows. Assets persist: a flow built in February earns in November; a segment built once serves every future send; each test result compounds into the next calendar. This is the difference from paid media, where spending stops and revenue stops with it — and it is why our email programs are scoped in quarters, not weeks.

Write two numbers down before anyone starts. Day-zero baselines are what make day-90 an evaluation instead of an argument: record email's current share of store revenue and flows' current share of email revenue, both from the same attribution windows you will use later. Screenshot them, date them, put them in the working doc. Every "results in 90 days" dispute we have seen traces to a missing baseline — the agency measures against launch, the brand remembers a better month, and both are arguing from memory. The same two numbers also calibrate expectations honestly: a program starting with flows at 10% of email revenue has fast, visible headroom against the benchmark band around 41%, while one starting at 35% is buying refinement, and its early wins will be quieter. Baselines are free, take ten minutes, and convert the whole timeline conversation from feelings to arithmetic.

What should never take 90 days: a written strategy with numbers in it, and visible weekly execution. Slow results are physics; slow activity is a vendor problem. The month-by-month deliverable arc — and the nine services that should all be moving — makes a practical accountability checklist whether you run email in-house or through a full-service partner.

Calibrate your expectations to your inputs. Timelines stretch when the list is cold, the catalog is seasonal, or deliverability starts damaged; they compress when flows merely need repair rather than construction. The 30/60/90 arc above assumes honest effort against a real list — and it is the standard to hold any partner to, including us.

How Big Should a Subscribe & Save Discount Be?

DTDC Media — Mon, 10 Aug 2026 11:46:38 +0000

Subscribe & save discounts drift upward for a predictable reason: the discount is doing a job the product experience should be doing.

Start with the math. A subscription's value is margin × orders retained — so a deeper discount only wins if it buys meaningfully more orders. Give away 20% to a subscriber who churns after two deliveries and you've built a discount program, not a subscription program. Most consumable brands land at 5–15%: enough to signal commitment, not enough to hollow out margin. Whatever the number, model it against realistic retention, because why subscribers cancel usually has nothing to do with price — it's surplus product, billing surprises, and failed payments.

Three sizing rules that hold up:

Discount the relationship, not the first order. A modest ongoing rate beats a deep first-box hook that attracts deal-seekers who never stick.
Pair the rate with the right cadence. A discount can't fix a shipment arriving before the last one runs out — that's timing, the same logic as a replenishment email.

Add perks before percentage. Free shipping, early access, and member pricing on add-ons raise perceived value without touching the base margin.

The discount gets a subscriber to order three. What happens between orders — onboarding, flexibility to skip or swap, dunning that recovers failed payments — is what gets them past it. That system is the subject of our subscription retention playbook.

Running a subscription that grows top-line but leaks margin? Our subscription management services start with the economics — get in touch.

Your Sold-Out Page Is a Demand Sensor

DTDC Media — Wed, 29 Jul 2026 12:44:06 +0000

An out-of-stock page gets treated as a failure state. Something went wrong upstream, a customer arrived at the wrong moment, and the job now is damage control. That framing costs brands more than the lost sale does, because the sold-out page is the one place on your site where a customer tells you precisely what they want, at the price you're asking, with no discount attached, and receives nothing in return. That's not a dead end. That's the cleanest piece of first-party demand data your brand owns.

Consider what makes it clean. Wishlist saves are cheap and ambiguous. Add-to-cart is polluted by browsing behavior and price-checking. Survey responses tell you what people say they'd buy. A back-in-stock signup costs the customer something real — they handed over a contact detail to get a product they cannot have right now. There's no other reason to do it. And the signal is unbiased by your own merchandising, because nobody signed up as a result of a homepage feature or an email push. The product wasn't available to promote. Demand arrived on its own.

Start with the most obvious thing that data can tell you and that most brands never extract: variant-level demand. Aggregate product demand tells you to reorder the style. Variant-level demand tells you the size curve, the shade ratio, the scent split, the color mix. Most brands buy roughly the same ratio they bought last time, sell through the middle sizes, and then discount the tail for the rest of the season. Your notify-me list is a free forecast for that exact split, built from people who were ready to pay full price, and it exists before you commit a dollar of inventory capital.

It tells you about price too, if you read it right. How quickly a list builds, and how deep it gets before it stalls, is a rough measure of how much slack sits in your pricing. A variant that quietly accumulates hundreds of waiting customers at full retail while receiving no promotional support is telling you that price is not the constraint on that product. Meanwhile a product that sold out fast and then generated a thin list wasn't a hit — you simply bought too few of something ordinary, and buying deeper into it is a mistake dressed up as a data-driven decision.

The problem in most organizations isn't the data, it's the geography. The notify-me list lives in the marketing platform, owned by the person writing the alert emails. The person deciding next season's buy is in a spreadsheet, working from last year's sell-through and a supplier deadline. Those two people often never speak about this. Fixing it costs nothing: a weekly export, ranked by variant, with signup dates attached, dropped into the buying meeting. It is probably the cheapest forecasting improvement available to a growing brand, and the mechanics of the alerts themselves are worth getting right alongside it — BMO's rundown on back-in-stock alerts covers that side properly.

One thing will limit how much of this signal you actually capture: a large share of people who land on a sold-out page will not give you an email address. They're on a phone, mid-scroll, and typing an address into a field to be told about a product later is more friction than the moment can support. Those people leave, and their demand never gets counted, which means your sample is skewed toward customers who were already willing to join your list.

That's the case for capturing the signal in more than one way. Web push notifications take a single tap, no typing, no inbox, and no commitment that feels like a relationship — which both widens the number of people you can alert and, more valuable long term, widens the demand sample you get to read. Two customers wanting the same variant should both register, whether or not one of them wanted to be on your email list.

Here's the practical first step. Export the last 90 days of notify-me signups, broken out by variant, and set it beside your most recent purchase order. If the two documents disagree, you already know which one was written from evidence.

The 30 Days After Checkout Decide Whether You Have a Customer

DTDC Media — Mon, 20 Jul 2026 13:10:11 +0000

Most brands treat the order confirmation as the finish line. It's actually the starting gun. A first-time buyer isn't a customer yet — they're a trial. Whether that trial becomes a repeat customer is decided almost entirely in the thirty days after checkout, and most brands leave that window completely to chance.

Consider what a new buyer is feeling right after they pay. A small amount of doubt: did I choose well? A bit of anticipation. And a rapidly closing window in which your brand is still front of mind before daily life crowds it out. What you do in that window decides everything.

Do nothing, and the most common outcome is silence. The product arrives, gets used or doesn't, and the customer forgets you existed until they happen to need something again — by which point a competitor may have found them first. A single margin-thin order, and a customer you paid full acquisition cost to acquire, gone.

The brands that grow treat this window as a system. Well-built post-purchase email flows do four jobs in sequence: reassure the buyer they chose well, help them actually get value from the product, ask for a review at the right moment, and set up the second order. None of it is loud or salesy. All of it compounds.

The review request is worth dwelling on, because timed well it does double duty. Ask once the customer has genuinely used the product, and a strong review program turns that satisfied buyer into social proof that lowers the cost of your next sale. The post-purchase window is where reviews are won.

For consumable products, this is also the natural moment to introduce a subscription. Not at first checkout, when the customer doesn't trust you yet, but after the product has arrived and delivered on its promise. A subscribe-and-save offer at that moment — when they've just experienced the value and can see they'll need more — converts far better than one shouted at a stranger.

Timing is the whole discipline. Ask for a review before the product arrives and you get silence. Push the second order before they've experienced the first and you look greedy. The sequence has to be paced to the real customer experience — delivery time, usage time, replenishment cycle — not fired off on a generic schedule.

What makes the post-purchase flow so valuable is that it works on customers at their most engaged, using an audience you've already paid for. There's no acquisition cost to add. You're simply refusing to waste the most important thirty days in the entire relationship.

The metrics tell you whether it's working. Watch your first-to-second-order conversion rate, the share of customers who leave a review, and how quickly repeat purchases happen. Move those and you've changed the trajectory of the whole business, because a brand that reliably earns the second order can afford to spend more to acquire the first, and outbid competitors who can't. That's the quiet compounding advantage a strong post-purchase window buys you.

None of it requires a bigger ad budget or a bigger list. It just requires refusing to let your most engaged audience go cold in the exact window where a nudge does the most work.

Get it right and the effect compounds quietly: more second orders, more reviews, more subscribers, all from customers you already had. It's the single highest-leverage flow to build after cart recovery, and it's core to how a lifecycle partner like BMO Media turns first-time buyers into repeat revenue.

The Retention Channel Most DTC Brands Are Still Ignoring

DTDC Media — Mon, 13 Jul 2026 10:37:22 +0000

Every DTC brand obsesses over email. Most have finally taken SMS seriously. Almost none have done anything meaningful with push. That gap is one of the cheapest opportunities left in ecommerce retention, and it stays open mostly because brands misunderstand what push is actually for.

Here's what makes it unusual. Push costs effectively nothing per message. There's no per-send fee like SMS, no inbox to fight through, and no deliverability score quietly deciding whether your message gets seen. Most importantly, it captures people who will never give you an email address or a phone number. A shopper who won't fill in a form will often click "Allow" without a second thought, and that shopper is otherwise invisible to you forever.

That's the real argument for push: it reaches an audience your other channels structurally cannot.

The opt-in is everything. This is where most brands ruin the channel before it starts. They enable the native browser prompt, it fires the instant someone lands on the homepage, the shopper reflexively hits "Block," and that's permanent. You don't get a second chance at a browser permission.

The fix is a two-step approach. Show a branded, on-brand primer first, explaining what the shopper gets: restock alerts, early access to drops, price-drop notifications. Only when they say yes to your primer do you trigger the real browser prompt. Opt-in rates on a well-designed two-step setup dramatically outperform the blunt instant prompt, and you preserve the option for everyone who says "not now."

Timing matters too. Asking someone to accept notifications three seconds into their first visit is asking for commitment before you've given them a reason. Trigger it after they've shown intent: viewed a couple of products, spent real time on a page, added something to cart.
What push is genuinely good at. Not everything. Push is short, it's interruptive, and it has no room for storytelling. Use it where immediacy is the whole value:

Back-in-stock alerts, which are close to the highest-intent message in ecommerce.

Price-drop alerts on products a shopper actually viewed.
Cart and browse abandonment, as a fast, low-cost recovery layer.
Drops, launches, and restocks where speed decides who gets the product.
Final-hours urgency on a sale that's about to close.

What push is bad at is long-form persuasion and daily promotional noise. Send too often and people don't unsubscribe politely the way they do with email. They disable notifications at the browser level, and you lose them permanently. Frequency discipline isn't optional here.
Getting the balance right is why a growing number of brands hand web push notifications to a specialist rather than treating it as a plugin someone toggles on and forgets about.

Coordinate, don't compete. Push works best as the safety net inside a coordinated lifecycle. A shopper abandons a cart. The email lands and goes unopened. They're not on your SMS list. A push notification the following morning is the only remaining way to recover that sale, and it costs you nothing to send. That's the compounding logic: push isn't another megaphone, it's the channel that catches what the others miss.

Segment it like any other channel. The lazy version of push is a single broadcast to everyone who ever clicked "Allow," and that's precisely how you train people to block you. The browser hands you behavioral data, so use it. Target by the product someone actually viewed, what they left sitting in the cart, the category they keep browsing, and how recently they visited. A restock alert sent only to the people who looked at that exact product feels like a service. The identical message sent to your entire subscriber base feels like spam, and it gets treated accordingly.

Measure opt-in rate, click-through, revenue attributed to push, and, just as importantly, your opt-out and block rates as an early-warning system that you're pushing too hard.

This is exactly how BMO Media approaches it. Push is built into the retention ecosystem alongside email, SMS, loyalty, reviews, and subscriptions, sharing the same customer data and the same frequency rules, so it strengthens the journey instead of adding noise to it. For a channel that costs almost nothing to run, that's a remarkable amount of revenue most brands are still leaving on the table.

What "good" actually looks like inside a Klaviyo account

DTDC Media — Fri, 26 Jun 2026 09:39:15 +0000

Open two Klaviyo accounts side by side and you can tell within minutes which brand is leaving money on the table. The platform is the same. The difference is entirely in how it's set up and run. If you've ever wondered whether your account is actually healthy or just busy, here's what a strong one looks like under the hood.

Start with the split between flows and campaigns. In a well-run account, a large share of email revenue comes from flows — the automations that run on their own — not from broadcast campaigns. If almost all of your email revenue comes from campaigns, it means the automated layer is underbuilt, and you're leaving the highest-intent, lowest-effort revenue uncaptured. A healthy account has the core flows live and optimised: welcome, browse abandonment, cart and checkout recovery, post-purchase and win-back, each earning its keep.

Next, look at segmentation. A weak account sends most things to "everyone," or at best to a single "engaged" segment. A strong account is sending different messages to different people based on what they've bought, how often, how recently, and how they behave. This isn't complexity for its own sake — it's the difference between a message that feels relevant and one that gets ignored. Relevance is what protects your engagement and, by extension, your deliverability.

Speaking of which, deliverability is the quiet foundation underneath all of it. A healthy account actively manages list hygiene: it sunsets people who've stopped engaging, sends based on engagement rather than blasting the whole list, and protects the sender reputation that decides whether your emails land in the inbox or the spam folder. A brand that sends everything to everyone is slowly poisoning its own deliverability, and most never realise it until open rates quietly collapse.

Then there's measurement. A strong account is judged on revenue you can attribute — revenue per recipient, flow revenue, campaign revenue — not on opens and clicks. Opens have become an unreliable metric, and clicks only tell you so much. If your reporting stops at "the open rate was 42%," you don't actually know what your email program earned. Good operators always tie the work back to money.

Finally, the best accounts treat email and SMS as one coordinated program. The two channels share suppression rules and a single view of the customer, so messages complement each other instead of colliding. A cart abandonment might open with an email and follow with a single well-timed text only for high-value carts. That coordination is invisible to the customer, which is exactly the point.

None of this requires a bigger list or a bigger budget. It requires someone who knows what they're looking at and what to fix first. That's also the hardest part to hire for, because "we do Klaviyo" is something almost every agency and freelancer says, and very few can actually back up. If you're trying to figure out who should own this for your brand, we wrote a practical guide to hiring a Klaviyo expert — the questions to ask, the red flags to avoid, and how to tell a specialist from a generalist before you commit.