EcommerceLayer
AI pricing (Demand)

Stop guessing prices. Let data drive your profit growth.

Demand tracks live competitor prices for every SKU you sell, models the click + conversion uplift of any price change, and recommends the optimal strategy — Volume Push for thin-margin movers, Margin Push for premium items.

Try free demoGet started

What you get

Dream outcome

Every SKU priced at its profit-maximizing point, automatically — no more leaving margin on the table or undercutting yourself.

Perceived likelihood

Live competitor data plus your real unit costs feed an uplift model grounded in your actual conversion history. Recommendations are explainable, not a black box.

Time saved

Skip the weekly price-check spreadsheet. The dashboard flags every mispriced SKU and shows the profit you would gain by adjusting.

Effort removed

Volume Push or Margin Push is assigned automatically per SKU based on margin and price elasticity. One click pushes the new price to your store.

How it works

  1. STEP 01

    Connect your catalog + unit costs

    We ingest every SKU from Shopify, BigCommerce, or CSV, and pair each with its unit cost so the model can reason about real margin — not just revenue.

    Catalog feed
    1
    Adidas Samba OG
    Sneakers · in stock
    1.000 kr.
    2
    NB 2002R Protect.
    Sneakers · in stock
    1.350 kr.
    3
    Ecco Soft 7 Leath.
    Sneakers · in stock
    1.100 kr.
    4
    Adidas Gazelle
    Sneakers · in stock
    900 kr.
    Unit costsCSV / API
    Adidas …450 kr.
    NB …620 kr.
    Ecco …500 kr.
    Adidas …400 kr.
    Margin tracking ready
    Catalog on the left, cost data on the right. Margin tracking starts the moment both feed in.
  2. STEP 02

    Track live competitor prices

    Demand scrapes the same SKU across every competitor in your market on a rolling schedule and shows you where you are highest, lowest, and where the price gap is widening.

    Live competitor prices
    Tracking 142 SKUs
    ProductYouComp AComp BComp C
    Samba OG1.000895910950
    Gazelle900850795880
    NB 2002R1.3501.2501.1951.299
    NB 5501.1009509991.050
    Refreshed 4 min ago2 you-are-lowest
    Side-by-side competitor prices, refreshed automatically. Lowest column is flagged green.
  3. STEP 03

    Predict click + conversion uplift

    For each SKU, Demand models the relationship between price, click-through rate, and conversion rate to surface the price point that maximizes total profit, not just revenue or units.

    Price → profit curve
    Adidas Samba OG
    Your price
    Optimal · 895 kr.
    +18.4%
    Click uplift
    +24.2%
    Conv. uplift
    +44k kr.
    Profit
    The curve shows total profit at every price point. The green dot is the recommended price.
  4. STEP 04

    Pricing Strategy: data-driven profit growth

    Every SKU is tagged Volume Push or Margin Push based on margin and elasticity. The table shows suggested price, predicted uplift, and the total profit potential across your catalog.

    Pricing Strategy
    Data-driven profit growth
    ProductYouSug.ClickConv.ProfitStrategy
    Samba OG1.000895+18.4%+24.2%44kVolume
    NB 2002R1.3501.195+32.1%+45.8%57kVolume
    Soft 71.100995+22.0%+38.5%49kVolume
    NB 990v61.9002.150+0%−5.0%123kMargin
    Samba Ltd.1.0501.250+0%−8.0%110kMargin
    5 of 142 SKUs · sorted by potential+423k kr. potential
    Volume Push for thin-margin movers, Margin Push for premium items. One click applies the new price.

Frequently asked questions

How does Demand get competitor prices?

A mix of live scraping, marketplace APIs, and shopping-feed aggregators. Coverage depends on the vertical, but for most retail categories we track every meaningful competitor automatically.

Will it auto-update my Shopify prices?

Optional — and bounded. You can let Demand push approved recommendations directly to your store, or keep it review-only. Guardrails (min margin, max swing per day) are configurable per SKU.

What if my product has no direct competitor?

Demand falls back to a cost-plus + category-elasticity model for SKUs without comparable competitors. The model is conservative when data is thin and surfaces a confidence score for every recommendation.

How accurate is the uplift prediction?

The model is calibrated against your store's own click and conversion history, not a generic benchmark. Accuracy improves as more pricing experiments run. Every prediction includes a confidence band.

Stop leaving margin on the table.

Let Demand price every SKU at its profit-maximizing point.

Try free demoGet started