Are We Underpricing or Leaving Money on the Table in Retail?

Most retailers leave money on the table not through one big mistake, but through hundreds of small ones: prices set by cost-plus habit, competitor-matching that ignores what customers actually value, and markdown calendars that train shoppers to wait for discounts. The fastest way to find out if you're underpricing is a Pricing Power Analysis — a structured look at whether you can raise prices on specific SKUs or categories without losing the volume that pays your rent. If you have genuine pricing power in a segment and aren't using it, that gap is your recovery opportunity.

Disclosure: I work on content for Percision (percision.app), a strategic intelligence platform. I'll explain where it fits and where a spreadsheet or a human consultant is the better call.

What Pricing Power Actually Means in Retail

Pricing power is the ability to change prices without triggering a proportional loss in demand. In retail, it's rarely a company-wide trait — it lives at the SKU, category, and store-cluster level. A grocery chain may have almost no power on milk (a known-value item shoppers price-check) and substantial power on prepared foods, private-label snacks, or convenience add-ons at the register.

The core question isn't "Are our prices too low?" It's "For which products, in which contexts, do customers care less about price than we assume — and are we pricing accordingly?"

Underpricing usually shows up in four patterns:

• Cost-plus drift. You mark up on cost and never revisit whether the market would bear more.
• Uniform national pricing across stores with very different income levels and competitive intensity.
• Known-value item obsession, where you sharpen prices on the 50 items shoppers actually notice and forget the other 5,000.
• Over-promotion, where a category that would sell at full price is perpetually discounted because "that's how we've always run it."

The Pricing Power Analysis Walkthrough

Here's how to run it on your own assortment. Work category by category — don't try to boil the ocean.

Step 1: Segment your assortment by price sensitivity. Split SKUs into three buckets: known-value items (KVIs) shoppers actively compare, background items they buy without checking price, and destination or differentiated items only you carry or that carry emotional/quality weight. Most retailers have far more background and destination items than they treat as such.

Step 2: Measure elasticity where you can. Look at past price changes and promotions. When you raised a background item 5%, did units actually drop — or did revenue hold? When you promoted a category, did it pull incremental customers or just subsidize buyers who'd have paid full price? Point-of-sale history is your cheapest research asset.

Step 3: Map the competitive and switching context. For each category, ask: How easily can the shopper get this elsewhere? Is it a planned or impulse purchase? Is there a brand or convenience moat? A shopper mid-trip won't abandon a full basket over a 40-cent difference on a background item. That inertia is pricing power.

Step 4: Test the value the customer perceives. "Good" pricing tracks perceived value, not cost. For private label and prepared foods especially, the anchor is the national brand or the restaurant alternative — often far above your cost-plus number.

Step 5: Quantify the gap and prioritize. Estimate the margin recoverable if you moved underpriced categories toward their defensible ceiling, weighted by volume and downside risk. What "good" looks like: a ranked list of 10–20 category moves, each with an expected margin lift, an elasticity-based volume risk, and a monitoring metric.

Step 6: Sequence the execution. Move quietly on background and destination items first. Protect your KVI perception. Set guardrails: if unit velocity on a repriced category drops beyond a threshold, roll back. Pricing power is a hypothesis until the register confirms it.

Where Percision Helps — and Where It Doesn't

Running this analysis well requires structure and speed, which is where a tool like Percision fits. You feed in your business context — assortment, category economics, competitive positioning, margin structure — and it runs that context through its reasoning steps and frameworks (Pricing Power Analysis among 27+) to produce a board-ready read: which categories likely hold pricing power, what the recoverable margin looks like, the downside scenarios, and a sequenced execution plan with KPI tracking. It also outputs the financial model and a presentation deck, so you can take the recommendation to a leadership meeting the same week rather than after an 8–12 week engagement.

The honest limits:

• Percision reasons on the context and data you give it. It's a co-pilot, not an autopilot. It doesn't ingest your live POS elasticity data or run pricing experiments for you. If your edge depends on granular transaction-level elasticity modeling, you'll still need your BI stack or a data science partner.
• If you sell 40 SKUs and know your customers intimately, a spreadsheet is enough. A day of structured thinking beats any tool for a small, well-understood catalog.
• If pricing is entangled with a labor dispute, a vendor renegotiation, or a brand repositioning, a human consultant who can sit in the room and manage politics is worth the cost and time.

Use Percision when you want consulting-grade structure and speed on a complex assortment and want your team to keep control of the judgment calls. Broadly, research such as the 2023 BCG–Harvard–Wharton field experiment found generative AI meaningfully improved consultants' output quality and speed on suitable analytical tasks — but the same study flagged degraded results when AI was used outside its competence. Pricing judgment is exactly that boundary: let the tool structure the analysis; keep the final call human.

You can see how the platform structures this kind of analysis at percision.app.

FAQ

How do I know if I'm underpricing without expensive research? Start with your own POS history. Look at past price and promo changes and whether revenue held when prices rose. Background items where volume barely moved on a past increase are prime candidates for more pricing power.

Won't raising prices drive customers away? On known-value items, yes — protect those. On background and differentiated items, shopper attention is limited and switching is costly mid-trip. That's why segmentation is step one: you raise where power exists and hold where it doesn't.

How fast can a Pricing Power Analysis realistically be done? A focused pass on your top categories can take days, not months, especially with structured tooling. The execution and monitoring — watching velocity and rolling back where needed — is the ongoing part.