What's the most cost-effective way to track revenue by channel using product analytics and dashboards for a growing DTC brand?

For a growing DTC brand, the most cost-effective setup is usually:

Use one source of truth for transactions (your commerce platform + ad platforms), send that into a low-cost event warehouse or product analytics tool, and build a small number of channel-level dashboards on top of it.

Best low-cost approach

1) Start with your commerce platform as the revenue source of truth

Use:

• Shopify / WooCommerce / BigCommerce for order data
• GA4 for marketing attribution basics
• Ad platforms like Meta, Google Ads, TikTok for spend and click data

If you’re early-stage, you do not need an expensive CDP.

2) Track only the events you need

Focus on a few core events:

• page_view
• view_item
• add_to_cart
• begin_checkout
• purchase

For revenue by channel, the most important one is purchase, with properties like:

• order ID
• revenue
• product/category
• discount
• customer type
• campaign / source / medium
• first-touch and last-touch attribution fields

3) Use a product analytics tool that can handle event + revenue reporting

Good cost-effective options:

• PostHog — strong value, self-hosted or cloud, good for event analytics and dashboards
• Mixpanel — very good UX, but can get pricey as event volume grows
• Amplitude — powerful, but usually not the cheapest for a growing brand

If cost is the priority, PostHog is often the best value.

4) Add a lightweight warehouse only if needed

If you want more control and cleaner channel reporting, use:

• BigQuery as the warehouse
• Connect Shopify + ad spend data into BigQuery
• Build dashboards in Looker Studio or Metabase

This is often the cheapest scalable setup if you have some technical help.

Recommended stack by budget

Cheapest workable stack

• Shopify
• GA4
• Looker Studio
• Native ad platform reporting

Good for:

• basic channel revenue reporting
• early-stage brands
• limited engineering support

Downside:

• attribution can be messy
• harder to combine spend, CAC, and LTV cleanly

Best cost-effective scalable stack

• Shopify
• PostHog
• BigQuery
• Looker Studio or Metabase
• ad platform connectors / data sync

Good for:

• reliable revenue by channel
• flexible dashboards
• better attribution and cohort analysis
• lower cost than enterprise tools

What dashboards to build

Keep it simple:

1. Revenue by channel
2. Blended CAC and ROAS
3. New vs returning customer revenue by channel
4. Funnel conversion by source/medium
5. Campaign performance dashboard
6. LTV by acquisition channel if you have enough repeat purchases

Attribution recommendation

For DTC, don’t rely on one attribution model alone. Use:

• Last-click for operational decisions
• First-touch for acquisition analysis
• Blended ROAS / MER for executive-level performance

If you only track one number, use blended MER:

Total revenue ÷ total marketing spend

It’s simple and hard to game.

If you want the absolute cheapest “good enough” version

Do this:

• Shopify + GA4 + Looker Studio
• UTM standards for every campaign
• Daily exports of ad spend into Google Sheets or BigQuery
• Basic revenue dashboard by source / medium / campaign

This works until complexity grows.

My practical recommendation

For a growing DTC brand, the best value is usually:

Shopify + PostHog + BigQuery + Looker Studio

Why:

• relatively low cost
• flexible
• good enough for both product and revenue analytics
• scales better than relying only on GA4 or spreadsheets

If you want, I can also give you:

1. a bare-minimum stack under $200/month, or
2. a step-by-step implementation plan for tracking revenue by channel.