The fundamental difference: intent vs interest
Google Ads works because people tell Google what they want. A search for "marketing automation software" signals active buying intent. You show your ad to someone who is already looking — demand capture.
Meta Ads works because it knows who people are, not just what they searched for today. You show ads to people who match the profile of your buyer based on demographics, interests, and behavior — before they are actively searching. This is demand creation.
When to start with Google Ads
Start with Google if there is clear, measurable search volume for your product or service. Use Google Keyword Planner or ask Claude to check search volume for your core keywords. If people are actively searching for what you sell, Google captures that intent at the moment of highest purchase probability.
Google is also the right choice when your budget is limited. A focused exact-match campaign targeting high-intent keywords with a strong landing page can produce positive ROAS faster than a Meta cold traffic campaign that needs time to exit the learning phase.
- Clear search volume for buying-intent keywords (cost, buy, hire, software, agency)
- Short sales cycle where the search-to-purchase window is under two weeks
- Local services where intent + proximity is the key qualifier
- B2B with known job title or company size targeting constraints (LinkedIn is also relevant here)
When to start with Meta Ads
Start with Meta if your product requires education before someone will search for it — or if your category is new enough that search volume does not yet exist. Meta is also stronger when the audience is defined by demographics or interests rather than active search behavior.
Ecommerce brands, direct-to-consumer products, and anything with strong creative assets (video, lifestyle photography) typically find Meta more efficient early because the visual format drives impulse consideration better than search ads.
- Products with low search volume but identifiable audience profiles
- High-visual categories: fashion, home, food, health, fitness
- Long sales cycles that benefit from repeated touchpoints before purchase
- Retargeting — Meta is more cost-effective for retargeting warm audiences than Google display
How to use both platforms together
The strongest paid media strategy uses Meta to build awareness and warm audiences, then Google to capture the search intent that Meta generates. A user who sees your Meta ad three times and then searches for your brand name converts at a far higher rate than a cold search click.
Attribution for this cross-platform lift is hard to measure in any single platform. GA4 with both platforms connected gives you the clearest view of cross-channel paths. MCP Ads lets Claude analyze both simultaneously so you can see where the overlap creates compounding value.
Budget allocation between platforms
There is no universal rule, but a common starting split for growth-stage businesses is 60% Google (demand capture) and 40% Meta (awareness and retargeting). As the Meta pipeline matures and search volume grows from brand awareness, shift more budget toward Google.
Review allocation monthly. Ask Claude to compare your blended cost per acquisition by platform and adjust based on which channel is producing the most qualified downstream results — not just the cheapest leads.
Doing this with Claude connected to the account
The Meta-versus-Google question is usually argued from opinion because the two platforms report in different interfaces with different attribution windows. With Google Ads, Meta Ads, and GA4 connected through MCP Ads, Claude can put the two side by side on a base you both accept.
Prompt 1: "Give me a cross-platform overview for the last 30 days: spend, leads, and cost per lead on Google and on Meta, each using its own attribution, and then the same two channels as GA4 sees them." Claude calls agency_cross_platform_overview for the platform-side totals, then ga4_acquisition_channels to show what GA4 attributes to paid search and paid social. What comes back is three numbers per platform instead of one. As an illustrative example: Google claims 120 leads, Meta claims 140, and GA4 credits 95 and 60 respectively. That does not settle which is better, but it shows how much each platform over-claims relative to the same source of truth.
Prompt 2: "Show me the attribution paths where both a Meta ad and a Google ad appear before a conversion, and how many conversions only touched one." This uses ga4_attribution_paths and meta_ads_attribution_report. The answer is the case for running both: if a third of your conversions saw a Meta ad before searching your brand on Google, cutting Meta will show up as a Google decline three weeks later.
Prompt 3: "Shift $30 a day from the Meta prospecting campaign to the Google non-brand search campaign." Claude uses meta_ads_update_budget and google_ads_update_campaign_budget. Both are writes, so Claude states each campaign, its current budget, and the new one, and waits for you to approve. Nothing moves until you say so, and any new campaign created as part of a rebalance starts paused.
The attribution analysis skill in the library runs this reconciliation on a schedule so the argument happens once, not every month.
Where the manual way still wins
None of the three data sources is the truth. Meta view-through conversions, Google click-through conversions, and GA4 last-click are three different models, and the API cannot give Claude an incrementality test — only a geo holdout or a conversion lift study can. Claude can show the disagreement; it cannot resolve it.
The starting-platform decision also depends on things the accounts do not contain: whether there is existing search demand for what you sell, whether the offer is visual enough for social, and how long the sales cycle is. Answer those first, then use the reconciliation above to check whether the split you chose is holding up.
