by Om RathodIf you're spending on Meta, Google, and TikTok at the same time, you already know the problem. Each platform has its own attribution model, its own dashboard, its own opinion about which channel actually drove a sale. None of them agree with each other. None of them agree with what actually landed in your bank account.
This is the exact gap that good ecommerce analytics for a brand running Meta, Google, and TikTok needs to close. Most teams handle it the same way: someone exports CSVs from Meta Ads Manager, Google Ads, and TikTok Ads Manager into a spreadsheet every Monday morning. That process eats 3+ hours a week, and by the time the pivot tables are done, the data is already a few days stale.
The bigger issue isn't the time cost. It's that platform-reported ROAS from each channel double-counts conversions. Meta claims a sale. Google claims the same sale. TikTok might claim it too, depending on the attribution window. Add up the three "ROAS" numbers and you get a fiction that doesn't reconcile against actual Shopify or Amazon revenue.
Trivas was built specifically for this problem: brands running paid across three or more channels who need one true number, not three competing ones. This isn't a single-channel ad tool with extra dashboards bolted on. It's built around the reality that most serious DTC brands aren't choosing one platform. They're managing a portfolio.
Platform-native reporting exists to make that platform look good. Meta's in-platform ROAS, Google's conversion tracking, and TikTok's pixel data each use their own attribution window and their own definition of a "conversion." A customer sees a TikTok video, clicks a Google search ad two days later, then converts after a Meta retargeting ad. All three platforms can legitimately claim credit. Add them up and your business is spending money it doesn't have, on paper.
Solving this requires a data layer beneath the ad platforms, not another dashboard sitting on top of them. Trivas runs on Amazon Redshift, ingesting raw ad spend and revenue data from Meta, Google, and TikTok alongside Shopify, Amazon, and GA4, then reconciling all of it against actual order data. The order is the source of truth. Everything else gets matched to it.
Here's what that reconciliation typically reveals. Say a brand spends $50k a month split across the three platforms. Add up what each platform reports individually and you might see a combined "ROAS" of 4.2x. Deduplicate the overlapping conversions against real Shopify orders, and the true blended ROAS often lands closer to 2.8x. That gap is the difference between a spreadsheet that flatters you and a dashboard that tells you the truth.
This is also where incrementality matters. Last-click attribution hands full credit to whichever channel happened to close the sale, usually retargeting. It ignores whether that sale would have happened anyway. Brands running three or more channels need a cross-channel view specifically to catch this: TikTok and Meta retargeting the same warm audience, Google Shopping picking up branded search traffic that top-of-funnel spend already generated. Without a unified view, that overlap is invisible, and budget keeps flowing to channels that are just mopping up demand someone else created.
Setup follows a straightforward flow. Connect your Meta, Google Ads, and TikTok accounts alongside Shopify or Amazon and GA4. Data lands in the Redshift warehouse within [VERIFY: sync time], reconciled against your actual order data rather than left as three separate, self-reported feeds.
From there you get a unified spend-vs-revenue view: one table showing spend, CAC, ROAS, and contribution margin per channel, side by side, refreshed daily. No more toggling between three ad managers and a spreadsheet to answer "which channel is actually working right now."
The Wingman AI layer sits on top of this and flags anomalies automatically. A practical example: TikTok CPMs spike 40% week-over-week while conversion rate holds flat. Instead of noticing that three weeks later in a QBR, you get flagged the day it happens, with enough context to decide whether to pull spend or ride it out.
When something looks off, you don't have to leave the dashboard to investigate. Drill down from the channel-level summary into individual ad sets, or into TikTok Spark Ad performance specifically, without exporting anything or opening a second tool. That drill-down is what turns a Monday reporting ritual into a five-minute daily check.
Brands evaluating Triple Whale, Northbeam, or Polar Analytics for cross-channel reporting are usually comparing dashboards. The bigger question is what's underneath the dashboard: who owns the data, and how portable is it.
Trivas is built on Amazon Redshift, which means the underlying data warehouse is yours: queryable, and not locked inside a vendor's proprietary system. Some competing tools keep the data layer closed, which makes it harder to run custom queries or export raw data for your own BI tools down the line. [VERIFY: confirm current data architecture for Triple Whale, Northbeam, and Polar before publishing this claim as stated].
Pricing structures also differ meaningfully between these tools, often tied to order volume, ad spend tiers, or number of connected accounts. [VERIFY: exact current pricing for Triple Whale, Northbeam, and Polar Analytics] before making specific comparisons.
One practical difference worth calling out directly: Trivas combines ad analytics with Amazon marketplace data in the same view. For brands selling on both Shopify and Amazon while running paid social and search, that matters, because Amazon revenue and ad spend often live in a totally separate reporting silo from everything else. Honestly, that silo is the part most competing tools still haven't solved. For the full side-by-side, see the Triple Whale, Polar, and Trivas comparison.
New users get a specific set of views from the first login, not a blank dashboard they have to configure over weeks. That includes a blended ROAS trend line, channel-by-channel CAC across trailing 30, 60, and 90 day windows, and spend allocation recommendations based on where marginal returns are highest.
Layered on top is an AI-driven forecasting view: projections for next month's spend efficiency per channel, based on historical CPMs and conversion trends rather than a flat extrapolation of last month's numbers. This is where the platform starts answering "where should the next dollar go" instead of just "what happened last week."
For the weekly leadership update that used to mean rebuilding a spreadsheet every Monday, Trivas offers exportable reports pulled straight from the live dashboard. Same numbers your team is already looking at, formatted for whoever needs the summary.
Want to sanity-check your current blended numbers before even connecting an account? The ROAS calculator is a quick way to see how far platform-reported ROAS might be drifting from reality.
The ideal fit is precise: DTC brands spending meaningfully across at least two of Meta, Google, and TikTok, usually already running Shopify and often selling on Amazon in parallel. If you're managing real budget across multiple paid channels and reconciling by hand, this is built for you.
The internal buyer is typically a performance marketer or marketing leader who has to defend channel budget allocation to a founder or finance team. "Meta looks better than Google this month" isn't a defensible answer when real money is on the line, and that's the exact conversation this dashboard is built to support. See more on how performance marketers use Trivas day to day.
This isn't the right tool for a single-channel Meta-only shop. Trivas is overkill there. It's built for teams juggling three or more ad platforms who are losing hours every week to reconciliation and still not fully trusting the number they end up with.
Ready to stop guessing? Start a trial and connect Meta, Google, and TikTok alongside Shopify or Amazon. Most teams see a blended ROAS view within a day of connecting accounts.
Running a larger book of spend and want to understand the Redshift architecture or talk through custom reporting needs before committing? Talk to a founder directly.
Either way, the outcome's the same: replace the Monday spreadsheet ritual with a dashboard that updates daily and tells you the truth about what's actually working.
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