Your Shopify, Meta, Google, and TikTok Numbers - One Question, One Answer
The number that actually governs your scaling decisions - real spend across every channel against real Shopify revenue - lives in the gap between your ad platforms and your store, and right now your team closes that gap by hand. Mad Fish Elements closes it for you. It connects Claude, ChatGPT, Microsoft Copilot, or Gemini to Shopify, Meta, Google Ads, TikTok, Mailchimp, GA4, BigQuery, and 26 more platforms through one governed gateway - with per-seat permissions, a full audit trail, and dashboards your whole team can trust. We’re Mad Fish Digital, and we built it because we needed it too.
The MCP Gateway - the connection layer between your assistant and your platforms - puts Shopify revenue, Meta spend, Google Ads spend, TikTok spend, and GA4 behavior in the same conversation. Ask for blended ROAS by channel, by campaign, by week, and the assistant pulls from every platform in one pass and does the reconciliation your growth lead was doing by hand. The morning spreadsheet ritual becomes a question you ask, and scaling decisions run on store-truth numbers.
2
One instruction, every platform
Batch operations mean “pause every ad for the sold-out SKU across Meta, Google Ads, and TikTok” is a single request - executed everywhere, logged everywhere. Flash sale launching Friday? Update the campaigns, adjust the budgets, and push the landing page change to Shopify or WordPress from the same conversation. Installable workflow Skills let you package the routine - the sell-out drill, the sale-launch checklist - so it runs the same way every time, with no forgotten steps.
3
BigQuery answers without the analyst queue
Because BigQuery sits behind the same gateway as your ad platforms, LTV questions get answered where the budget decisions happen. Ask which acquisition cohorts clear your 90-day LTV threshold, then adjust Google Ads and Meta budgets toward them - in one thread, without waiting on the SQL queue. Your warehouse investment finally shows up in your bidding.
4
Email and paid share one brain
With Mailchimp connected alongside Meta, Google Ads, and TikTok, your assistant sees both sides of the customer. Check which segments email already converted before funding retargeting. Time a post-purchase flow against the product paid is pushing this week. The weekly coordination meeting becomes a sync on strategy, because the data-passing already happened.
5
Fast changes with a full paper trail
Every action through the gateway is tied to a named user via per-user OAuth, permission-checked server-side on every call, and written to a full audit trail. During peak season your team moves as fast as the moment demands - and in December, the postmortem is a query, not archaeology. Automated error monitoring flags failed operations while there’s still time to fix them, not after the weekend’s spend is gone.
The Problems E-commerce Teams Live With
ROAS math split across five dashboards
Meta says the campaign returned 4.2x. Google says 3.8x. Shopify says revenue was flat. Every morning your growth lead reconciles platform-reported return on ad spend (ROAS) against actual store revenue in a spreadsheet, because every platform claims credit for the same order. Blended performance - total spend across every channel against real Shopify revenue - is the only number that matters for scaling decisions, and it’s the one number no single dashboard shows you. So budget calls run on platform-flattered figures, or they wait until someone finishes the spreadsheet.
Campaign and catalog changes done by hand, one platform at a time
A product sells out, and now someone has to pause its ads on Meta, then Google, then TikTok, then update the promo block on the site. A price change or a flash sale means the same fire drill in reverse. Each platform has its own interface, its own quirks, and its own spot where a step gets forgotten - and a forgotten step means paying to advertise a product you can’t ship. The work isn’t hard. It’s fragmented, and fragmentation is where money leaks.
LTV is trapped in BigQuery
You did the hard part: order history, cohorts, and lifetime value (LTV) models live in BigQuery. But the people making bid and budget decisions live in ad platforms, and the analyst who can write the SQL has a two-week queue. So acquisition targets get set on first-order ROAS while your 90-day LTV data - the number that would justify higher bids on the right cohorts - sits unread in a warehouse you’re paying to maintain.
Email and paid don’t talk to each other
Mailchimp knows who bought, who churned, and who’s about to. Your paid team knows none of that when they build audiences and set budgets. Post-purchase flows launch without a glance at which products paid is pushing, and paid retargets customers your email program already converted. Two teams, two tools, one customer - and the coordination happens in a weekly meeting instead of in the data.
Peak-season fire drills with no paper trail
Black Friday week: budgets change hourly, three people have admin access to everything because there’s no time for permission hygiene, and by Cyber Monday nobody can reconstruct who raised which budget when. The December postmortem is archaeology. High-tempo periods are exactly when you need fast changes and a record of them - and standard platform access forces you to pick one.
Use Cases
The real morning number
“Show me yesterday’s blended ROAS: total spend across Meta, Google Ads, and TikTok against Shopify net revenue, broken out by channel, and compare it to the trailing 7-day average.”
Platforms Meta, Google Ads, TikTok, Shopify
The reconciliation spreadsheet retires. Your growth lead starts the day with the number that actually governs scaling decisions - in under a minute.
The sold-out SKU drill
“The Fern Planter is out of stock - pause every active ad and ad set referencing it on Meta, Google Ads, and TikTok, and list what you paused.”
Platforms Meta, Google Ads, TikTok, Shopify
Zero wasted spend on unshippable product, plus a logged record of exactly what was paused so you can relaunch the moment inventory lands.
LTV-informed budget shifts
“From BigQuery, rank last quarter’s acquisition campaigns by 90-day LTV per customer, then show me which ones are underfunded in Google Ads and Meta relative to that ranking.”
Platforms BigQuery, Google Ads, Meta
Bidding decisions graduate from first-order ROAS to lifetime value without a two-week analyst queue. The campaigns that acquire your best customers finally get the budgets they earn.
Flash-sale launch, end to end
“For Saturday’s 20%-off sale: raise budgets on the three designated Meta and TikTok campaigns at 6 a.m., swap in the sale creative, and confirm the Shopify discount is live.”
Platforms Meta, TikTok, Shopify
The launch checklist runs as one governed sequence instead of three people setting alarms. Every change is logged, so Monday’s review shows exactly what ran and when.
Email-paid audience handoff
“Pull Mailchimp segments that purchased in the last 30 days, and check whether any of our Meta retargeting campaigns are still spending against those buyers.”
Platforms Mailchimp, Meta
Retargeting budget stops chasing people email already converted. The savings go back into prospecting, and the two teams stop discovering overlap in the quarterly review.
Performance Max without the black box
“Summarize this month’s Performance Max results in Google Ads against our standard Shopping campaigns, and show which products are driving conversions in each.”
Platforms Google Ads (including Performance Max), Shopify
Product-level clarity on where PMax is actually earning its budget, cross-checked against store data - a decision-ready readout instead of a shrug at the dashboard.
Five Prompts To Steal
Copy any of these into Claude once you’re connected - swap in your own products and dates and they run as written.
“Break down last month’s Shopify revenue by product line, then show which lines Google Ads and Meta spend is actually funding - flag any line getting budget while its sales shrink.”
A product-line drilldown that catches money flowing to a fading line - usually on the first run.
“How much revenue did our Mailchimp abandoned-cart flow recover in the last 30 days versus the prior 30, and which email in the sequence drives the most completed Shopify checkouts?”
A quick read on your highest-margin automation - and the specific email worth improving first.
“Run a post-mortem on the Labor Day sale - Shopify revenue and orders versus the two prior weekends, spend and ROAS by channel across Meta, Google Ads, and TikTok - and publish it as a dashboard I can share with leadership.”
The promo retro that usually takes two weeks, shipped the same day as a shareable report.
“From BigQuery, show 12-month LTV by first product purchased, and tell me which entry products deserve their own Google Ads campaigns based on the customers they bring in.”
Your warehouse finally talking to your bidding - the entry products that earn higher acquisition budgets, named.
“Draft a three-email win-back sequence in Mailchimp for customers with no Shopify order in 120 days, segmented by their first product category, and save the drafts for my review.”
Written, segmented, and staged - nothing sends until you approve, and the audience logic is already handled.
Data Visualization for E-commerce
Blended Performance Daily
spend by channel across Meta, Google Ads, and TikTok against Shopify revenue and orders, with blended ROAS and customer acquisition cost (CAC) trend lines. Your growth lead and founder read it every morning, and scheduled refreshes keep the 8 a.m. number current.
LTV Cohort Report
BigQuery cohort curves by acquisition channel and first product purchased, with 30/60/90-day LTV against CAC. Your head of growth and finance use it for budget planning and annotate it when a cohort’s trajectory changes.
Peak-Season Command Board
hourly spend pacing, top-SKU sell-through from Shopify, and campaign status across every ad platform during promo windows. The whole growth pod works from it during Black Friday/Cyber Monday - one refreshing report instead of forty spreadsheet copies.
The chart types that tell your story
The right chart makes the decision obvious. Here’s what we’ve seen work on e-commerce dashboards:
Line + area
revenue as the filled area, ROAS as the line on top. One glance tells you whether growth is coming from efficiency or just from spending more.
Funnel
cart to checkout to purchase. When conversion dips, the funnel shows you which step is leaking so you fix the page, not the ads.
Donut
revenue share by channel. It keeps channel mix honest and makes over-reliance on any single platform impossible to miss.
Scatter
CAC against average order value (AOV) by campaign. Campaigns above the line pay for themselves on the first order; campaigns below it need their LTV case checked.
Calendar heatmap
daily sales shaded across the year. Seasonality, promo lifts, and slow weeks jump out, which makes next year’s inventory and budget planning far less of a guess.
Stacked bar
product-line mix over time. It shows which lines are actually growing versus riding a strong quarter, before you commit next season’s buy.
Governed Access Your Finance Lead Will Sign Off On
When marketing spend is your largest variable cost, finance deserves better than shared logins to the systems moving that money. Every seat on Mad Fish Elements connects through native OAuth under the user’s own identity - no API keys to leak, no shared passwords. Read, write, and delete permissions are set per seat, per platform, and enforced server-side on every call: the coordinator who should only read can only read. Every operation lands in a full audit trail, automated error monitoring catches failures early, and the platform is built around documented security controls. Month-end questions about who changed which budget get answered with a record, not a recollection.
E-commerce teams typically pair an Ad Ops plan sized to managed spend with a few Ops seats for the people who work in Shopify, Mailchimp, GA4, and BigQuery. Add Data Visualization for the daily blended-performance report.
Data Visualization is available as an add-on to any plan — pricing on request.
Ad Ops plans run $299/mo + 0.75% of managed ad spend for Basic (read), $799 + 1.25% for Standard (full capabilities), and $1,299 + 1.50% for Premium - with a 0.85% marginal rate above $250K/mo spend, plus multi-client, priority support, and sandbox - and Enterprise custom. Ops seats run $99/seat/mo for Starter (read-only, up to 3 platforms), $299/seat/mo for Growth (read+write+delete, up to 7 platforms), and $499/seat/mo for Agency (all platforms plus multi-client management, priority support, sandbox, BYO OAuth), with Enterprise custom. Data Visualization is available as an add-on to any plan, and taking both lines earns a 15% bundle discount on the smaller one.
Frequently Asked Questions
Can it actually write to Shopify and the ad platforms, or just report on them?
Both, depending on the seat. Growth-tier Ops seats and Standard-or-above Ad Ops plans include write and delete capabilities - pausing ads, adjusting budgets, updating campaigns - while Starter seats and the Basic Ad Ops plan are read-only. Every write is permission-checked server-side and logged.
How does the percentage-of-spend pricing work as we scale?
Ad Ops pricing is a platform fee plus a percentage of managed ad spend: 0.75% on Basic, 1.25% on Standard, 1.50% on Premium. On Premium, spend above $250K/mo bills at a 0.85% marginal rate, so your effective rate declines as you scale. Enterprise plans are custom.
We already have dashboards. Why use Data Visualization?
The short answer: it’s governed, and it lives next to the data source. Reports publish from any connected platform, teams review and annotate in place, and scheduled refreshes update the same report in place - no version sprawl, no stale copies circulating in Slack. It’s available as an add-on to any plan.
Which AI assistant do we have to use?
Whichever your team already uses. Claude, ChatGPT, Microsoft Copilot, and Gemini all connect to the gateway, and the permissions and audit trail work identically regardless of the assistant in front.
What about our repeatable workflows, like weekly promo launches?
Package them as installable workflow Skills. A Skill encodes the sequence - budget changes, creative swaps, Shopify checks - so anyone with the right seat runs it consistently, and every execution is still permission-checked and audited step by step.
Stop Reconciling. Start Deciding.
Your stack already holds every number you need - it just holds them in five places. Mad Fish Elements puts Shopify, your ad platforms, your email, and your warehouse behind one governed gateway so the morning question gets a same-minute answer. See it run on your own accounts.
