Read the Master Article: BigQuery Alternatives, BigQuery Competitors: The Ultimate Data Warehouse Deathmatch

Your CEO just pulled the plug on a lackluster $50,000 ad campaign, and everyone’s looking at you to answer one burning question: Where the hell did all that money go? You know the answer lies in the data, but getting it means untangling the chaos. Enter Stitch, BigQuery, and SQL—your trifecta for marketing domination.

The Problem: Data Lives in Silos

Facebook Ads. Google Ads. Shopify. Google Analytics 4. Each platform hoards its data like a jealous dragon guarding gold. How do you connect it all? That’s where StitchData.com comes in. Stitch is your ETL (Extract, Transform, Load) pipeline, sucking raw data from your platforms and dropping it into BigQuery so you can actually do something with it.

Step 1: Setting Up Stitch

First, you log into Stitch and connect all your data sources—Facebook Ads, Google Ads, GA4, and Shopify. Stitch automates the grunt work, extracting data, standardizing schemas, and funneling everything into BigQuery like a well-oiled machine.

In under an hour, your raw data from disparate sources is sitting in BigQuery, ready for you to tear it apart with SQL.

Step 2: The Query—Where’s the Money Bleeding?

You write a query to analyze campaign performance, blending ad spend, impressions, clicks, and transaction data into a single, cohesive narrative. For example:

SELECT
ad_platform,
campaign_name,
SUM(ad_spend) AS total_spend,
COUNT(DISTINCT user_id) AS total_users,
SUM(CASE WHEN transaction_id IS NOT NULL THEN 1 ELSE 0 END) AS conversions,
ROUND(SUM(CASE WHEN transaction_id IS NOT NULL THEN revenue ELSE 0 END), 2) AS total_revenue,
ROUND(total_revenue / total_spend, 2) AS ROI
FROM
`stitch_dataset.ad_data`
LEFT JOIN
`stitch_dataset.transaction_data`
ON
user_id = customer_id
GROUP BY
ad_platform, campaign_name
ORDER BY
ROI DESC;

Step 3: Insights—Exposing the Truth

Your query tells a grim tale: Facebook ate $30K for breakfast but drove a laughable ROI of 0.5. GA4 reveals a deeper issue — most traffic from Facebook landed on a slow-loading product page with a bounce rate of 85%. Meanwhile, Google Ads campaigns, though smaller, crushed it with a 4.5 ROI.

The Shopify data adds another twist: Facebook users abandon carts twice as often as Google users. Why? Stitch shows the geo breakdown—your Facebook ads were targeting areas with low purchasing power.

Step 4: Action—Fix the Funnel

You walk into the next meeting armed to the teeth with insights:

1. Kill underperforming Facebook campaigns or retarget them with better geographic filters.
2. Rebuild the slow product page and A/B test new designs.
3. Scale Google Ads and funnel those users directly to a high-converting landing page.

The Takeaway: Stitch, BigQuery, and SQL Are Your Data Exorcists

Without Stitch, you’d still be chasing your tail, jumping between dashboards. Without SQL, you’d drown in noise instead of slicing through to the signal. With both, you’ve become the marketing Sherlock Holmes, exposing inefficiencies, plugging leaks, and driving growth.

This isn’t just marketing — it’s tactical warfare. With the right tools and the right mindset, you don’t just survive the chaos — you own it.