Strategy & Planning

How to run a pricing analysis as DTC Brand Founders

Strategy & PlanningFor DTC Brand Founders3 apps12 steps~24 min to set up

Your pricing decisions live in a Google Sheet that mixes last quarter's COGS estimates with a margin target someone typed in 18 months ago. You know your ad costs have climbed — Meta CPMs are up, your blended CAC on the hero SKU crossed a number that should have triggered a price review — but connecting that spend data to your actual selling price requires pulling exports from Shopify, cross-referencing Plaid transactions for COGS payments to suppliers, and eyeballing the Klaviyo email revenue attribution report that may or may not be double-counting. By the time the analysis is done, the sale you were trying to price competitively is already live. You need a current picture of margin by SKU, not a spreadsheet archaeology project.

Build this on Starch → See the apps used

Strategy & PlanningFor DTC Brand Founders3 apps12 steps~24 min to set up

Outcome

What you'll set up

A live pricing dashboard that pulls Shopify order data, Plaid bank transactions (supplier payments, COGS outflows), and ad spend so you see contribution margin by SKU in one place, updated on a schedule.

A scenario model comparing 2–3 price points side-by-side — showing how a $4 price increase on your top SKU changes gross margin, CAC payback, and 90-day runway given your current burn.

A weekly digest that flags when your blended CAC on a channel crosses your margin threshold for any SKU, so a price review is triggered by data, not a gut feeling at midnight.

The Starch recipe

Apps, data, and prompts

The combination of Starch apps, the data sources they pull from, and the prompts you use to drive them.

Apps used

Scenario Analysis Transaction Insights Growth Analyst

Data sources & config

Starch syncs your Plaid bank account data on a schedule (supplier payments, COGS outflows, operating expenses) and connects directly to Stripe for revenue and subscription data on a schedule. Shopify is connected from Starch's integration catalog; the agent queries it live when the pricing dashboard or scenario model runs. PostHog is connected from Starch's integration catalog and queried live for the weekly growth digest. Gmail is connected directly to Starch and syncs on a schedule for digest delivery.

Prompts to copy

Connect my Plaid account and Stripe. Build a scenario analysis that shows my current contribution margin per SKU at today's price, then models what happens to gross margin and 90-day runway if I raise the price on SKU 'Linen Tote — Natural' by $5, $8, and $12. Assume current unit volume holds in scenario 1, drops 10% in scenario 2, and drops 20% in scenario 3.

Pull all Plaid transactions from the last 6 months. Categorize outflows to my top 3 suppliers and show me month-over-month COGS trend by vendor. Flag any month where a supplier payment was more than 15% above the prior month average.

Connect PostHog and Gmail. Every Monday at 8am, send me a digest that shows conversion rate by traffic source for the past 7 days, flags any channel where my blended CAC has increased more than 20% week-over-week, and notes which product pages had the biggest drop in add-to-cart rate.

Run these in Starch → or paste them into your favorite agent

Walkthrough

Step-by-step

1 Connect Plaid in Starch — Starch syncs your bank transactions on a schedule, so supplier payments and COGS outflows are available without any manual export.

2 Connect Stripe — Starch connects directly to Stripe and syncs charges, invoices, and payouts on a schedule. This gives you net revenue per order to anchor your margin math.

3 Connect Shopify from Starch's integration catalog — the agent queries it live when your pricing app runs, pulling order-level data including SKU, quantity, selling price, and discount codes applied.

4 Open the Scenario Analysis app from the Starch App Store and describe your baseline: tell Starch which Plaid outflow categories map to COGS for each SKU and which Stripe revenue stream maps to each product line.

5 Run your first scenario prompt — ask Starch to model 2–3 price points for your top SKU, holding volume flat in the first scenario and applying realistic demand elasticity assumptions (you supply the number; Starch holds the math).

6 Review the side-by-side output: runway, gross margin %, and CAC payback period under each price assumption. Starch surfaces the break-even unit volume for each scenario so you know exactly how much volume you can afford to lose.

7 Open Transaction Insights and prompt Starch to categorize the last 6 months of Plaid outflows by supplier. Confirm your COGS numbers match what you've been modeling — this step frequently surfaces supplier invoices that weren't in the original sheet.

8 Adjust your scenario inputs based on the actual COGS data from step 7. Re-run the scenario model with corrected numbers.

9 Connect PostHog from Starch's integration catalog and set up the Growth Analyst app. Configure it to send a weekly Monday digest covering conversion rate by channel and CAC trend per SKU page.

10 Add a trigger to the Growth Analyst digest: if blended CAC on any channel exceeds 60% of your current contribution margin for that SKU, include a pricing review flag in the digest with the specific SKU and channel called out.

11 Export the scenario analysis output as a slide-ready summary — describe the layout you want and Starch formats it. Use this as the pricing section of your next board update instead of rebuilding the chart in Google Slides.

12 Set the scenario model to re-run monthly when Plaid and Stripe data refresh, so your pricing baseline stays current without a manual trigger.

See this running on Starch

Connect your tools, describe what you want, and the agent builds it. Closed beta is free.

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Worked example

April 2026 SKU Pricing Review — Linen Tote Line

Sample numbers from a real run

Stripe net revenue (Linen Tote — Natural, last 90 days)	41,200
Plaid outflows — primary supplier (Tessile Co.)	15,800
Plaid outflows — fulfillment & 3PL fees	5,100
Meta Ads spend attributed to Linen Tote (Shopify UTM)	7,400
Contribution margin at current $68 price point	12,900
Projected contribution margin at $76 price point (–8% volume assumed)	15,600

You've been selling the Linen Tote — Natural at $68 for two seasons. Meta CPMs climbed through Q1 and your blended CAC on that SKU crossed $31 in March, up from $22 in January. The Growth Analyst digest flagged it two weeks in a row. You open the Scenario Analysis app and describe what you want: 'Show me contribution margin on the Linen Tote at $68, $74, and $76, using actual Plaid COGS from Tessile Co. and 3PL fees from the last 90 days, with Stripe revenue as the baseline. Assume volume drops 5% at $74 and 8% at $76.' Starch pulls the $15,800 in supplier payments and $5,100 in fulfillment costs from your synced Plaid data, crosses it with $41,200 in Stripe net revenue, and builds all three scenarios. At $76 with an 8% volume haircut, contribution margin goes from $12,900 to $15,600 — and CAC payback drops from 6.2 weeks to 4.8. You raise the price. The Transaction Insights app had also flagged that Tessile Co. invoices ran 18% above their prior-quarter average in February, a cost increase you hadn't yet baked into any model. That catch alone justified the setup time.

Measurement

How you'll know it's working

Contribution margin % by SKU (net revenue minus COGS and variable fulfillment)

Blended CAC by channel relative to SKU contribution margin

CAC payback period in weeks at current average order value

Supplier COGS as % of SKU revenue, trended month-over-month

Gross margin impact of a 5–10% price move at realistic demand elasticity

Comparison

What this replaces

The other ways teams handle this today, and how the Starch version compares.

Google Sheets + manual Shopify/Plaid exports

Free and familiar, but the model is always behind — you're running pricing decisions on last month's COGS and last week's ad spend, and reconciling the exports takes 2–3 hours every time you want to update it.

Shopify Analytics + Triple Whale

Good for ad attribution and top-line revenue, but neither tool connects to your bank transactions for actual COGS outflows, so your margin math still lives outside the platform.

Causal or Mosaic (FP&A tools)

Purpose-built for financial modeling and genuinely strong for scenario planning, but require a finance hire or significant setup time to map your DTC data model, and don't connect to your ad platforms or do anything outside the finance workflow.

Looker Studio (Google Data Studio)

Free and connectable to Shopify and Google Ads, but it's a reporting layer — it shows you what happened, not what changes if you adjust a price. No scenario modeling, no anomaly alerts, no action taken on the data.

On Starch RECOMMENDED

One platform — scenario planning, transaction insights, growth analyst all running on connected data. Setup in plain English; numbers stay current via scheduled syncs and live agent queries.

Try it on Starch →

FAQ

Frequently asked questions

Does Starch actually connect to Shopify, or do I have to export a CSV?

No CSV needed. You connect Shopify from Starch's integration catalog and the agent queries it live when your pricing app or scenario model runs. Order-level data — SKU, quantity, selling price, discounts applied — is pulled automatically.

My COGS aren't in Shopify — they're in bank transfers to my supplier. Can Starch see those?

Yes. Starch syncs your Plaid bank transactions on a schedule with full categorization. You tell Starch which outflow payee maps to which SKU's COGS, and it uses that mapping in every scenario calculation going forward.

Can Starch pull my Meta Ads spend to include in the CAC calculation?

Meta Ads is reachable from Starch's integration catalog — connect it and the agent queries your spend data live. You can describe a custom app that pulls Meta spend by campaign, maps it to the SKU being promoted (using UTM parameters from Shopify), and includes it in your contribution margin math.

I don't have a Stripe account — I process payments through Shopify Payments. Does that break the scenario model?

It doesn't break it. Shopify Payments revenue shows up in your Shopify order data, which Starch queries live from the integration catalog. You'd use that as your revenue baseline instead of Stripe. Plaid covers your bank-side COGS outflows regardless of which payment processor you use.

Will the scenario model stay current, or is it a one-time snapshot?

You can set it to re-run on a schedule — monthly is typical for a pricing review cadence. When it runs, it re-pulls the latest Plaid COGS data and Stripe revenue so your baseline reflects the current business, not the numbers from three months ago when you first built it.

Is Starch SOC 2 certified? I'm sharing bank transaction data here.

Starch is not SOC 2 Type II certified today. That's worth knowing before connecting your Plaid account. It's on the roadmap. If SOC 2 is a hard requirement for your business right now, that's an honest reason to wait.

I already pay for a dozen SaaS tools. What does Starch actually replace here?

For a DTC pricing workflow specifically: it replaces the manual export-and-reconcile loop from Shopify, Plaid, and your ad platforms into Google Sheets. The Scenario Analysis app replaces the spreadsheet model you'd otherwise rebuild every time an input changes. The Growth Analyst weekly digest replaces the Tuesday morning ritual of opening four dashboards to figure out if CAC moved. It doesn't replace your accounting software or your ad platforms — it connects them so the output of one feeds into decisions in another.