Ecommerce Advertising Strategy: Meta, Google, TikTok in One Framework

If you're running ecommerce ads and you're only using one platform, you're leaving significant revenue on the table.

But if you're using all three, without a unified strategy, you're bleeding money faster.

The difference between the two isn't luck. It's structure.

The Three-Platform Problem

Most ecommerce brands treat Meta, Google, and TikTok as separate channels. They assign different budgets, different goals, different teams. The result is three uncoordinated campaigns that work against each other instead of amplifying each other.

A jewellery brand we worked with was spending $45K/month across all three platforms. Meta was driving awareness at 2.1x ROAS. Google was driving high-intent conversions at 3.8x ROAS. TikTok was... well, they weren't sure. The budget was there, the creatives were there, but nobody had a clear role for TikTok in the overall strategy.

We restructured their approach around a single framework. Within 90 days, same total budget, they'd hit 2.9x blended ROAS. More importantly, each platform had clarity on what it was actually supposed to do.

That's what a unified ecommerce advertising strategy looks like.

The Framework: Full-Funnel Attribution

Before you allocate a dollar, you need to answer one question: what job is each platform actually doing?

Stop thinking of Meta, Google, and TikTok as interchangeable. They're not. They serve fundamentally different purposes in the customer journey.

Meta: Awareness and intent-building. People don't wake up thinking about jewellery. Meta reaches them when they're scrolling, makes them aware they have a gap, and plants the idea that your brand solves it.

Google: High-intent conversion capture. When someone searches "luxury jewellery for engagement," they've already decided they want something. They're just comparing options. Google catches those searchers at maximum purchase intent.

TikTok: Viral awareness and community. TikTok's algorithm rewards relatability and entertainment. On TikTok, you're not selling a product. You're building a reason someone would care about your brand existing.

The framework works like this:

Stage 1: Awareness (Meta + TikTok)

Your job is reach and frequency. You want new audiences to see your brand. You're not trying to convert anyone yet. You're trying to plant recognition. Meta does this through targeted interest audiences. TikTok does this through algorithmic reach and viral potential.

Stage 2: Consideration (Meta retargeting + Google Search)

People who've seen your ads are now thinking about your brand. They're comparing you to competitors. On Meta, you retarget people who engaged with your awareness campaigns. On Google, you're bidding on branded and competitor keywords, capturing people actively researching solutions.

Stage 3: Conversion (Google + Meta retargeting)

This is the handoff. By this stage, Google is the primary driver—high-intent searches convert at the highest rates. Meta retargeting supports by reaching people who visited your site but didn't buy. You're coordinating the messaging: "Still thinking about it? Here's why this solves your problem."

Stage 4: Retention (Email + SMS, not platform ads)

You've made the sale. Platform advertising stops here. Klavioy and SMS take over. (That's a separate strategy, but it matters for your overall plan.)

This isn't just theory. A supplement brand we work with runs this exact structure. They allocate 40% of budget to Meta awareness, 30% to Google Shopping and Search, 20% to TikTok prospecting, and 10% to Meta retargeting. Each channel has a KPI that matches its role. Meta awareness targets CPM (cost per 1,000 impressions) and reach. Google targets ROAS. TikTok targets CAC on new customers. It looks fragmented until you see the connection: each channel's job feeds the next.

The Attention Allocation Problem

Here's where most brands fail: they don't actually allocate budget based on the framework. They allocate based on what they've always done, or what they heard worked for someone else.

You need a real decision tree. Ask yourself:

1. What's your revenue goal this quarter?

Let's say $500K.

2. What's your realistic blended ROAS across all channels combined?

If you're running a mature, optimised account, realistic blended ROAS is 2.0x to 2.5x depending on your niche. (Subscription brands run lower. Luxury goods run higher. Most general ecommerce sits at 2.0x–2.2x.)

3. How much do you need to spend to hit that goal?

If you need $500K revenue at 2.2x ROAS, you need to spend roughly $227K.

4. How do you split that $227K across the three platforms?

This is where the framework applies. You're not splitting it equally. You're splitting it based on what each platform does best for your specific brand.

For a new DTC brand with no audience yet:

• 50% Meta (awareness building—you have nobody to retarget yet)

• 30% TikTok (viral reach, community building)

• 20% Google (high-intent conversion, brand searches)

For an established brand with an existing audience:

• 30% Meta awareness (maintaining reach)

• 20% Meta retargeting (converting warm audiences)

• 35% Google (capturing high-intent traffic)

• 15% TikTok (testing viral content, community building)

For a seasonal brand (fashion, gifts, holiday products):

• Heavy Meta and TikTok in awareness phase (Aug–Sep for Q4)

• Heavy Google in conversion phase (Oct–Dec)

• Balanced maintenance year-round

The split changes with your business. But the framework stays the same: awareness → consideration → conversion, with each platform handling the stages it's best at.

Platform-Specific Mechanics You Need to Know

Each platform optimises differently. If you're running them in parallel without understanding the mechanics, you'll make decisions that sound good but tank performance.

Meta: ABO + Broad Audiences

Stop using detailed interest targeting. Meta's algorithm is better at finding customers than you are. Run Advantage+ (Meta's automated targeting) or, if you're in testing phase, use Automatic Broad Audiences in ABO mode. Set a cost cap, let it run, and give it 7–10 days of data before adjusting.

The mistake: founders see their CPA climb on Day 3 and panic. They cut the budget or change the creative. Day 3 is useless. Meta is still learning. You're optimising for 48 hours of data. That's noise.

For consideration and retargeting campaigns, use Custom Audiences (people who visited your site but didn't buy). For awareness, let broad targeting run.

Google: Shopping Ads + Search Intent

Google Shopping is your highest-converting channel on Google. Prioritise Shopping campaigns. Performance Max (PMax) is Google's newer, AI-driven option—it works, but Shopping is more transparent and typically outperforms.

On Search, bid on three layers:

• Branded keywords (your brand name)—high ROAS, relatively low volume

• Category keywords ("luxury jewellery", "engagement rings")—medium ROAS, higher volume

• Competitor keywords ("[competitor brand] alternative")—medium ROAS, medium volume

Allocate budget proportional to volume and ROAS. Don't over-bid on competitor keywords just because they convert—high bid prices on low volume is capital inefficiency.

Set a target ROAS of 3.0x–4.0x on Google. It's higher than your blended goal because Google's customers are already intent-ready. You can afford to be more aggressive.

TikTok: Broad + Creative Velocity

TikTok's algorithm doesn't care about your targeting data. It cares about whether your creative is entertaining enough to watch, engage with, or share.

Your TikTok strategy should be: test a LOT of creatives, and scale the ones the algorithm identifies as winners (high CTR, low CPC). Don't overthink targeting—let broad targeting run, and the algorithm self-selects the right audience.

Budget $1,000–$2,000/week minimum on TikTok. Below that, you don't have enough data to identify real winners. Run 8–12 ad variations. Kill anything under 50% of average CTR after 3 days. Scale winners 20% per day once identified.

The Coordination Layer: Data & Attribution

This is the hard part. You need to know which channel is actually driving revenue, not just which channel is showing the last-click conversion in your analytics.

Most ecommerce platforms (Shopify) default to last-click attribution. It's broken. If someone sees your Meta ad on Monday, sees your Google ad on Friday, and converts on Friday, Google gets 100% of the credit. Meta gets zero. But Meta did the work of awareness.

Here's what to do:

Use a unified analytics platform like Polar Analytics, Triple Whale, or Littledata that pulls data from Meta, Google, TikTok, and your e-commerce platform simultaneously. It's not perfect (no attribution model is), but it's better than last-click.

Implement UTM parameters correctly:

• For all paid ads, use utm_source (meta, google, tiktok), utm_medium (paid, organic—keep it consistent), utm_campaign (campaign name), utm_content (ad set or ad name)

• This creates a trackable path from ad click to transaction

• Not all transactions will track correctly (some users clear cookies, use private browsing, etc.), but you'll capture 60–70%

Monitor contribution profit, not ROAS:

• ROAS = revenue ÷ ad spend

• Contribution profit = (revenue × margin) − ad spend

• A channel with 2.0x ROAS on a 30% margin product generates $0.60 of profit per dollar spent

• A channel with 3.0x ROAS on a 20% margin product generates $0.60 of profit per dollar spent

• Same profit, different ROAS. Make decisions on contribution profit, not ROAS

Set platform-specific targets, not one blended number:

• Meta awareness: target CPM (cost per 1,000 impressions) or reach at $1–$3 per 1,000 impressions

• Meta conversion: target ROAS 2.0x–2.5x

• Google Search: target ROAS 3.5x–4.5x

• Google Shopping: target ROAS 3.0x–4.0x

• TikTok: target CAC (cost per new customer) $15–$60 depending on niche

Each platform optimises to a different metric. Stop expecting them all to hit 2.5x ROAS. It won't happen.

The Calendar: When to Shift Spend

Your advertising strategy doesn't exist in a vacuum. It exists in a year with seasons, trends, and periods when people are actually ready to buy.

For most ecommerce brands, 60% of annual revenue happens in Q4 (Oct–Dec). You cannot run the same budget split year-round. You have to shift allocation dynamically.

Seasonal adjustment framework:

During peak season (Q4 for most):

• Increase total budget by 40–60%

• Shift allocation toward Google (high-intent capture)—allocate 45% to Google, 35% to Meta, 20% to TikTok

• Reduce creative testing on Meta (winners are already known)

• Run seasonal creative exclusively (holiday messaging, urgency, limited-time hooks)

During shoulder season (Jan, Sept):

• Maintain baseline budget

• Balanced allocation: 30% Meta, 30% Google, 25% TikTok, 15% retargeting

• Heavy creative testing—figure out next season's winners

During off-season (Feb–Aug):

• Reduce budget by 20–30%

• Focus on Meta and TikTok for awareness building

• Test new audience segments, new hooks, new product angles

• Google gets less priority (lower intent traffic anyway)

A fashion brand we work with runs this exactly. Off-season (March–July), they allocate 60% to Meta awareness and TikTok. When August hits (back-to-school shopping season), they shift 50% of budget to Google. By October, it's 45% Google, 40% Meta, 15% TikTok. It's the same business, same creatives, same products—just the calendar driving the allocation.

The Execution: Getting It Live

You can have the perfect framework and still fail at execution. Here are the non-negotiable steps:

1. Set up tracking first. Before you spend a dollar, make sure your analytics is configured. UTM parameters set, platform pixels firing, attribution model chosen. You cannot optimise what you cannot measure.

2. Launch low spend ($200–$500/day combined across all three platforms). Validate that the tracking is working, that creative is rendering correctly, that there are no technical issues. Spend a week here.

3. Scale gradually. Once validation is done, increase spend 20% per week for four weeks. This gives each platform time to gather data and optimise. Meta needs 7–10 days to exit learning phase. Google needs data to model conversions. TikTok needs volume to identify winners.

4. Monitor the top-level metrics weekly:

• Total ad spend

• Total revenue attributed

• Blended ROAS

• Contribution profit

Monthly, dig into platform-specific metrics. Did Meta hit its CPM target? Did Google hit its ROAS target? Did TikTok's CAC come in under budget?

5. Adjust based on data, not gut. If Google is outperforming, increase its allocation by 10%. If TikTok isn't hitting CAC targets after three weeks, drop the budget or change the creative. Wait for data, then act.

The Second-Order Effect: Team Structure

A lot of brands fail at multi-platform advertising because they don't structure their team to match. One person manages all three platforms. They're constantly switching contexts. Nothing gets the attention it needs.

If your brand is spending $10K+/month on ads, you need at least two people:

• One person owns Meta and TikTok (awareness and creative velocity)

• One person owns Google (high-intent conversion capture)

If you're spending $30K+/month, you need three:

• One Meta strategist (audience, campaign structure, creative briefs)

• One Google specialist (Shopping, Search, bid management)

• One creative lead (video creation, iteration, testing protocol)

They should meet weekly to sync data, share insights, and adjust allocation based on performance. This prevents silos. It also forces conversation about the framework itself—is awareness spending actually feeding conversion? Or is the messaging broken?

The best ecommerce teams we work with operate this way. Each person is responsible for their channel's performance. But once a week, they sit together and answer: "Is our overall strategy working? Are the numbers validating the framework we built?"

The Reality Check

This framework isn't magical. It won't turn a terrible product into a bestseller, and it won't fix a broken brand position.

What it does: it gives structure to something that's otherwise noise. It forces clarity on what each platform is supposed to do. It prevents the wasteful pattern of throwing budget at channels and hoping something works.

The brands that scale past $100K/month in ad revenue—not total revenue, just ad-driven revenue—are almost always running something like this. Not necessarily exactly this. The details change based on their niche, their margin structure, their competitive position.

But the thinking is the same: each platform has a role. The roles connect. The budget allocation matches the role. The data validates whether it's working.

If you're currently running ads without this kind of clarity, the first step isn't optimising creative or bids. It's answering: what is each channel actually supposed to do? Once you have that answer, everything else gets easier.

Book your Growth Diagnostic Call to walk through your current strategy and see where the framework applies to your specific business.