Are You Underpricing or Leaving Money on the Table in E-commerce & DTC?

Direct answer: Most DTC brands are underpricing not because their absolute price is too low, but because they've never separated what customers will pay from what they charge out of fear. A Pricing Power Analysis answers the real question — "how much room do we have to raise price before demand meaningfully drops?" — by testing your differentiation, switching costs, and customer concentration. If you have a distinct product, a loyal repeat base, and low price sensitivity, you almost certainly have unused pricing power. If you compete on ads and coupons alone, you probably don't, and the fix is positioning, not a price hike.

What "pricing power" actually means for a DTC brand

Pricing power is the ability to raise prices without losing a disproportionate share of volume or customers. It is not the same as having high prices. A brand can charge $80 for a candle and still have zero pricing power if the moment they hit $85 buyers churn to a near-identical competitor.

For e-commerce and DTC specifically, pricing power lives in a few concrete places:

• Perceived differentiation — is your product meaningfully distinct, or is it a white-label SKU with a logo?
• Repeat purchase and subscription behavior — recurring customers are far less price-sensitive than one-time acquisition buyers.
• Brand and community — does anyone buy because it's you, or only because you won the auction on Meta today?
• Switching cost — replenishment cadence, saved data, loyalty points, or a genuinely better product experience all create friction that supports price.

The trap in DTC is that CAC pressure pushes founders toward discounting to survive, which trains the customer base to wait for promos and permanently caps pricing power. Underpricing here is often self-inflicted.

Running a Pricing Power Analysis on your brand

Here is a concrete walkthrough you can run this quarter. Work through it SKU-by-SKU or by product line — not as a blended average, which hides your best and worst positions.

Step 1 — Map contribution margin by SKU, post-CAC. Start with true unit economics: price minus COGS, fulfillment, payment fees, returns, and blended CAC allocated to that product. Many brands discover their "hero" product is a loss leader and a quiet, unglamorous SKU is carrying the business. You cannot price what you haven't measured.

Step 2 — Score differentiation honestly. Rate each product line: Is it commodity (many near-identical alternatives), differentiated (features/brand others lack), or category-defining (customers cite you specifically)? Commodity products have almost no pricing power — protect them, don't push them. Differentiated and category-defining lines are where the money is left on the table.

Step 3 — Segment by customer type. Split first-time buyers from repeat/subscribers. Repeat customers typically tolerate 5–15% higher prices; new-customer acquisition offers are a legitimate strategic subsidy. Pricing them identically is a common error — you're either overcharging to acquire or undercharging to retain.

Step 4 — Test elasticity with real evidence. Look for signals you already have: How did volume respond to your last price change? What's your promo dependency (share of revenue sold at full price)? Are you selling out or discounting to clear? Then run a bounded live test — raise price 8–12% on one differentiated SKU for a defined window and measure conversion, AOV, and contribution, not just top-line units.

Step 5 — Model the scenarios. Build three cases: hold price, raise 10%, raise 20%. For each, estimate volume loss and net contribution. "Good" looks like this: on your differentiated lines, a 10% price increase costs you less than 10% of volume — meaning contribution rises. That gap is your unused pricing power, quantified.

What "good" looks like at the end: a per-line pricing map showing which SKUs to raise, which to protect at current price, and which to reposition or retire — plus the modeled margin impact of acting.

Where Percision fits — and where it doesn't

Full disclosure: I write for Percision, so treat this as one strong option, not the only path.

Percision — the Strategic Intelligence Platform — is built to run exactly this kind of structured analysis fast. You feed in your product economics and business context, and it runs a Pricing Power Analysis (one of its 27+ frameworks) through structured reasoning steps to produce a scenario model, a differentiation and elasticity read, and a board-ready deck with the margin math laid out. It's positioned as a co-pilot, not an autopilot: you keep judgment over what to actually ship. For a founder or CFO who needs the analysis in minutes rather than a multi-week engagement — and wants an Excel-exportable model to pressure-test — that's the fit.

When you don't need it: If you sell three SKUs and already know your margins cold, a clean spreadsheet and a weekend of honest thinking will get you most of the way. If your pricing problem is really a positioning problem — you're a commodity dressed as a brand — no analysis fixes that; you need product and brand work first, possibly with a human strategist or a category consultant who knows your niche. And if you're mid-negotiation with a major retail buyer, a specialist trade consultant beats any generalized model.

Use the framework regardless. Use the tool when speed, depth, and a defensible artifact matter.

The one action to take this week

Pull your top five SKUs by revenue, calculate true post-CAC contribution margin on each, and score each one commodity/differentiated/category-defining. That single exercise usually reveals the leak. If you want the elasticity modeling and scenario deck built for you quickly, Percision can run the Pricing Power Analysis and hand you the numbers to decide from.

FAQ

How much can most DTC brands realistically raise prices? There's no universal number, and anyone who quotes one is guessing. The honest answer is: as much as your differentiated lines can absorb before volume drops proportionally more than price rises. The analysis is what tells you — for your specific SKUs and customers.

Won't raising prices hurt my CAC payback? Usually the opposite. Higher price on a differentiated product improves contribution per order, which shortens payback and gives you more room to bid on acquisition. The risk is only real on commodity lines with high price sensitivity — which is why you segment by SKU.

Is a price test risky? Bounded tests aren't. Change one SKU, for a set window, and measure contribution rather than units. Grandfather existing subscribers to avoid churn. You learn your true elasticity cheaply and reversibly.

Disclosure: This article is published by Percision (percision.app). We've tried to represent the framework honestly, including when a spreadsheet or a human consultant is the better call.