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Build an ecommerce marketing budget from CAC, LTV, margin, and growth goals. Apply the 7.7% benchmark carefully, then test spend before scaling.

Ecommerce Marketing Budget: Why 7.7% Misleads Australian Stores

Ecommerce owner reviewing a marketing budget

A sensible starting point for most ecommerce stores sits near 7.7% of revenue, but that figure comes from large companies and shouldn’t be copied blindly. The better method is to build your ecommerce marketing budget from your own numbers: lifetime value, acceptable customer acquisition cost and your growth target, then hold back a tested reserve and measure incrementality before you scale anything.

TL;DR:

  • Calculate acceptable CAC from annual customer gross margin and target payback, then compare it with current acquisition cost before increasing spend.
  • Work backward from the revenue target: divide by AOV for orders, by conversion rate for sessions, then price only paid sessions at expected CPC.
  • Test new channels with capped budgets for two to four weeks or until conversions provide a meaningful sample; scale only after meeting CAC payback targets.
  • Use cohort payback and geographic or audience holdouts to distinguish incremental sales from attribution, and adjust monthly for changing costs and seasonal demand.
  • Newer stores with limited repeat purchase data should prioritize acquisition; established stores with strong repeat rates should test retention spending before pursuing more customers.
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Table of Contents

Start with clear business objectives and translate them into budget goals

Before you open a spreadsheet, decide what the money needs to achieve. A revenue target, a profit target and a customer acquisition target pull a budget in different directions, and conflating them is the fastest way to overspend on the wrong channel.

If your primary goal is revenue growth, you can tolerate a lower return on ad spend in exchange for volume, because you’re buying market share or seasonal momentum. If your primary goal is profit, your acceptable customer acquisition cost shrinks and you’ll spend more cautiously, favouring channels with proven payback. If your goal is new customer count for a fundraising story or a wholesale pitch, you might accept short-term losses on acquisition to hit a number investors care about.

These goals set the guardrails for every allocation decision that follows, so write them down before you touch a budget line. The metrics below are what tie the goal to the spend:

  • Return on ad spend (ROAS): revenue generated per dollar spent, tracked by channel and campaign.
  • Customer acquisition cost (CAC) payback period: how many months of gross margin it takes to recover what you spent to win a customer.
  • Lifetime value (LTV): the gross margin a customer generates over their relationship with your store.
  • Gross margin: what’s left after cost of goods, shipping and payment fees, which determines how much room you have to spend on acquisition.

Acquisition-led and retention-led goals change where the money goes. A brand chasing new customer volume typically weights spend towards prospecting campaigns on search and social, accepting a longer payback period because the long-term value of a growing customer base justifies it. A brand focused on profit from an existing base shifts weight towards email and SMS, loyalty offers and retargeting, where the cost per transaction is lower and the margin on each sale is higher.

Neither approach is universally right. A newer store with thin repeat purchase data usually needs to lean acquisition-led simply to generate enough customers to measure retention against. A more established store with a strong repeat rate often gets a better return from squeezing more value out of existing customers before it spends another dollar chasing new ones. The objective you set here should drive every channel decision in the sections that follow, not the other way around.

Work out the key numbers: how to calculate AOV, LTV, CAC and margin

Unit economics are the backbone of any budget that isn’t guesswork. The calculations are straightforward once you have your order data in front of you.

  1. Calculate average order value (AOV). Divide total revenue for a period by the number of orders in that period. For example, divide a period’s total revenue by its order count to calculate AOV.
  2. Work out purchase frequency. Divide total orders in a year by the number of unique customers who ordered. For example, divide annual orders by the number of unique customers to calculate purchase frequency.
  3. Build a simple LTV figure. Multiply AOV by purchase frequency by gross margin percentage, then by the number of years you expect to retain a customer. Multiply AOV by purchase frequency, gross margin percentage and the expected customer retention period to estimate lifetime gross margin per customer.
  4. Set your acceptable CAC from payback, not guesswork. Decide how many months of margin you’re willing to wait to recover acquisition spend, then divide annual margin per customer by 12 and multiply by your target payback period. Divide annual margin per customer by the number of months in a year, then multiply by your target payback period to estimate an acceptable CAC.
  5. Sanity-check against your current CAC. If you’re already paying more than this to acquire a customer, your budget needs either a higher margin, a longer acceptable payback, or a cheaper acquisition mix before you add more spend.

Pro Tip: Build LTV from monthly cohorts rather than one blended average: a cohort acquired during a sale often behaves very differently to one acquired at full price, and blending hides that gap.

These five steps turn a budget conversation from “what can we afford this month” into “what does our margin allow us to pay for a customer”, which is the number that should set every spending decision from here.

Estimate required traffic and translate conversion targets into ad spend

Once you know your acceptable CAC, you can work backwards from a revenue goal to the traffic and spend needed to hit it.

Start with the revenue target and divide by AOV to get the number of orders required. Divide orders by your site’s conversion rate to get the number of sessions you need.

From there, multiply the sessions you need to buy, rather than sessions from organic, direct or email traffic, by your expected cost per click to estimate required ad spend.

  • Creative and landing page quality move both sides of this equation. A stronger ad lowers cost per click through better relevance scores; a stronger landing page lifts conversion rate, which lowers the number of sessions you need to buy in the first place.
  • Platform benchmarks shift by category and season, so pull your own account history before relying on an industry average, and treat any external benchmark as a rough sanity check rather than a planning input.
  • A small test budget should run before you commit the full estimate, because real cost per click and conversion rate on your own account are the only numbers that matter once you’re spending.
  • Revisit the calculation monthly, since conversion rate and cost per click both drift with competition, seasonality and your own creative refresh cycle.

This reverse calculation is what separates a budget built on evidence from one built on an arbitrary increase to last year’s number.

Channel allocation: practical benchmarks and decision rules

Channel allocation: practical benchmarks and decision rules — overview diagram

Channels play different roles, and treating them as interchangeable line items wastes money. Search tends to capture demand that already exists, so it’s reliable for steady-state acquisition but rarely creates new demand on its own. Social carries more of the demand-generation job, introducing your brand to people who weren’t looking for you yet, which means it needs stronger creative to perform. Retail media sits close to the point of purchase and often shows strong attributed performance, though IAB Australia’s analysis found that close to half of retail media investment is a mix of budget reallocated from other channels and genuinely new spend, so it’s worth documenting what a retail media dollar is actually replacing before calling the result incremental.

Video deserves particular attention. Australian internet advertising spend grew 11.5% to reach $18.4 billion in 2025, with search reaching $8.0 billion and video $5.4 billion, representing 29% of total online advertising expenditure. That growth makes video worth testing, but only when your creative, audience targeting and landing experience are strong enough to turn extra reach into profitable orders rather than just more views. Email and SMS round out the mix: they’re the lowest-cost channel per transaction for a store with an existing list, and they’re usually the first place to reinvest once acquisition spend is covered.

  • Test each new channel with a capped, time-boxed budget before folding it into your core allocation.
  • Scale the channels that prove incrementality, not just the ones showing the best last-click ROAS.
  • Avoid shifting large sums between channels without a genuine lift test behind the decision.
  • Review paid ecommerce advertising channels role by role rather than assuming every channel should carry an equal share of spend.

Testing, contingency and the reserve budget: practical guardrails

A budget with no reserve breaks the first time a channel underperforms or a competitor outbids you during a key sale period. Gartner’s 2025 survey notes that marketing budgets can face in-year cuts, which is exactly why planning a base budget alongside a separate tested reserve matters more than chasing a single precise number.

A common structure is to hold back part of total spend as a reserve for testing new channels or formats and running creative or landing page experiments on channels you already use. The rest funds proven, scaling activity.

  • Set a minimum test duration before judging results, typically two to four weeks or enough spend to generate a statistically meaningful sample of conversions.
  • Define a scaling threshold in advance, such as hitting your target CAC payback for two consecutive weeks before increasing budget on that channel.
  • Track early signals beyond last-click ROAS, including click-through rate, add-to-cart rate and assisted conversions, to catch promising channels before the attributed ROAS catches up.
  • Monitor cohort payback alongside blended ROAS, since a channel can look efficient in aggregate while actually eroding margin on new cohorts.

Pro Tip: Keep test budgets small enough that a losing test doesn’t threaten the core plan, but large enough to produce a real signal: a few hundred dollars rarely tells you anything useful about a new channel.

Worked example: step-by-step budget calculation for a hypothetical online store

Say a homewares store sets a monthly revenue target, knows its AOV, conversion rate and gross margin, and has chosen a CAC payback target.

  1. Orders needed: Divide the revenue target by AOV to estimate the number of orders required.
  2. Sessions needed: Divide the required orders by the conversion rate to estimate the number of sessions required.
  3. Paid session share: Estimate the share of total sessions that paid channels need to supply, with the remainder coming from organic, direct and email.
  4. Estimated spend: Multiply the paid sessions required by the expected cost per click across search and social to estimate paid media spend.
  5. Resulting CAC: Divide estimated paid media spend by the number of orders to estimate CAC per order. The relationship between orders and customers depends on repeat purchasing.
  6. Acceptable CAC check: Multiply AOV by gross margin to estimate gross margin per order, then compare that figure with your acceptable CAC and payback target.
  7. Resulting ROAS: Divide revenue by estimated paid media spend, before accounting for organic and retention revenue that the paid spend helps generate.
  8. Budget split: Allocate most of the budget to proven, scaling campaigns, while reserving portions for testing and retention activity such as email and SMS.

If conversion rate improves through landing page work, the same revenue target needs fewer sessions and the paid budget drops accordingly, which is why revisiting this calculation regularly keeps the numbers honest.

Demand doesn’t arrive evenly across the year, and a flat monthly budget ignores that reality. Peak periods such as major sale events typically carry higher competition and higher cost per click, which means the same dollar buys fewer sessions even as conversion rates often rise because shopping intent is higher.

The practical response is to plan spend as a share of expected revenue for each month rather than a fixed dollar figure, pulling budget forward into high-intent periods and pulling back during predictably quieter months. Build this from your own historical order data where you have it: a store with eighteen months of trading history can usually see its own seasonal pattern clearly enough to plan around it.

Market-level trends matter too. When overall advertising demand rises across a category, as it has with video inventory growing its share of total spend, auction prices for competing formats can shift even outside your own peak season. Reviewing your cost per click and conversion rate monthly, rather than assuming last quarter’s numbers still hold, catches these shifts before they erode a budget that looked fine on paper.

Strategies for scaling marketing budgets effectively as the business grows

Scaling a budget works best as a series of validated steps rather than a single jump. Increase spend on a channel only after it has held its CAC payback target for a sustained period, and do so gradually so you can watch for diminishing returns before committing further.

Diminishing returns show up as rising cost per click or falling conversion rate as you exhaust the most responsive part of an audience. When that happens, the answer is usually to widen targeting or refresh creative before pushing more budget into the same narrow segment. Our guide on how to scale ecommerce profitably covers this pattern in more depth.

As revenue grows, the unit economics calculation from earlier in this guide should be rerun rather than assumed to still hold. Margin often shifts as a business adds staff, warehousing or new product lines, and an acceptable CAC calculated at an earlier stage of the business can become too generous or too conservative over time.

Integration of offline and online marketing budget considerations

Online and offline spend influence each other more than separate budget lines suggest. A promotional item handed out at a market stall or included in a shipped order can drive branded search and direct traffic weeks later, and that lift rarely shows up cleanly in a single channel’s attribution report.

Physical touchpoints such as branded packaging, event presence or promotional merchandise tend to support retention and brand recall rather than direct acquisition, so they’re best budgeted alongside retention channels like email and SMS rather than compared against paid search on a cost-per-click basis. Treating offline activity as a brand investment with a longer measurement window, rather than expecting it to post an immediate ROAS, avoids defunding something that’s working for the wrong reason.

For most ecommerce stores without a physical retail presence, offline spend is a smaller share of the total budget, often reserved for packaging, direct mail to existing customers, or sponsorships tied to a specific audience. The integration question is less about splitting the budget evenly and more about making sure both sides are working towards the same acquisition and retention goals rather than operating in isolation.

Methods to measure and track ROI to optimize budget allocation continuously

Budget allocation isn’t a once-a-year decision. The channels and campaigns that earn more spend should be the ones proving it through ongoing measurement, not the ones that happened to get funded first.

Blended ROAS at the account level tells you whether overall spend is profitable, but it hides which specific campaigns are doing the work. Breaking performance down by channel, campaign and, where possible, cohort shows which dollars are actually driving incremental revenue rather than capturing demand that would have converted anyway.

Incrementality testing, such as holding out a geographic region or a portion of an audience from a campaign, is the most reliable way to separate a channel’s true contribution from its attributed numbers. Running this periodically on your largest spend lines catches cases where a channel looks efficient in last-click reporting but is mostly claiming credit for sales that would have happened regardless.

Campaign and holdout groups compared for incremental sales

Cohort payback monitoring closes the loop: tracking how long it actually takes each monthly cohort of new customers to repay their acquisition cost tells you whether your acceptable CAC assumption from earlier in this guide still holds, or whether margin pressure or slower repeat purchasing means it’s time to recalculate.

Considerations for competitive analysis and market positioning influencing budget decisions

How much your category spends on advertising sets a ceiling on how cheaply you can acquire attention within it. A crowded category with aggressive bidders on search and social pushes up cost per click, which raises the sessions-to-spend ratio in the calculations from earlier sections and can push your acceptable CAC closer to its limit.

Positioning offers a way around pure spend competition. A store with a clearly differentiated product or a specific audience niche can often win cheaper clicks by targeting more specific keywords and audiences than a direct competitor fighting for the broadest, most expensive terms. Watching where competitors are visible, on which channels and with which offers, helps you decide whether to meet them head-on or find a cheaper, more specific angle into the same buyer.

Budget decisions should also account for how saturated a channel already is in your category. A channel that’s cheap today because few competitors use it tends to get more expensive as others notice the same opportunity, which is another reason to treat channel allocation as a living decision rather than a fixed annual split.

Practitioner perspective: why senior strategists and measurement-first approaches improve budget outcomes

The gap between a budget that works and one that doesn’t usually isn’t the dollar amount, it’s how fast you learn what your numbers actually support. A store running its first serious test cycle without someone who has read dozens of these cohorts before often spends months rediscovering lessons that are visible in the data from week one.

Creative testing and conversion rate optimisation matter more than channel selection in most underperforming accounts, because a weak landing page or flat creative set will make every channel look expensive. Before scaling anything, prioritise fixing what the data already shows is broken.

Whether to bring in outside help or run the tests yourself comes down to how much internal time you can give to the analysis. A founder juggling fulfilment and customer service rarely has the hours to run a disciplined test cycle alongside everything else.

— Liza

How we help ecommerce stores build and scale a profitable marketing budget

We build ecommerce marketing budgets the same way this guide does: from your margin and acquisition cost, not from a borrowed percentage. Our strategists work directly with you, without outsourcing the analysis, to turn your order data into a budget and channel plan you can actually execute.

Moormarketing

  • Ecommerce strategy and channel management across Google, Meta, Pinterest and TikTok, built around your acceptable CAC rather than a generic allocation.
  • Website design and conversion rate optimisation on Shopify and WordPress, because a stronger landing page lowers the traffic you need to buy.
  • Email and SMS growth marketing to build the retention side of your budget alongside acquisition.
  • Short, intensive programs such as the 12 Week DOUBLE Your Revenue Challenge for stores ready to test and scale quickly.

An engagement typically starts with a numbers-first audit of your current spend and margin, followed by an action plan and a test roadmap you can review before committing further budget. If you want help building that plan, book a session with our ecommerce strategy team or explore Convert More Customers for a closer look at how we manage channels and CRO together.

FAQ

What is the 70-20-10 rule in digital marketing?

This rule of thumb divides budget between proven channels, promising channels and experimental tests. It’s a simple way to keep most spend on what already works while still funding discovery of what might work next.

What is the 80/20 rule in eCommerce?

This rule of thumb suggests that a small share of customers or products may generate a large share of an ecommerce store’s revenue. Applied to budgeting, it means checking whether your top customer segment or product line is getting a proportionate share of retention and acquisition spend.

What is the 3-3-3 rule for marketing?

Definitions of the 3-3-3 rule vary by source and aren’t tied to a single authoritative standard, so treat any specific version with caution. Some marketers use it loosely to describe testing a few channels, creative variations and audience segments before scaling, but it isn’t a fixed industry benchmark.

What is a good budget for digital marketing?

Gartner’s 2025 survey found marketing budgets have settled around 7.7% of overall company revenue, though this reflects mostly large companies rather than emerging ecommerce stores. A more reliable approach for a smaller store is calculating budget from acceptable customer acquisition cost and lifetime value rather than applying that percentage directly.

How much should I set aside as a testing reserve?

A common structure holds back part of total marketing spend for testing new channels and creative experiments, with the remainder funding proven, scaling activity. This protects the core budget from being disrupted by an underperforming test.

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