Speed
A full set of pricing insights in minutes rather than weeks.
Gazelle Pricing Optimizer
Set prices from evidence, not habit.
Gazelle Pricing Optimizer models your sales data in minutes and turns it into a full set of pricing and promotion insights — customized to your business, and re-run whenever the market moves.
Minutes
to a full set of pricing insights
to a full set of pricing insights
Any sales data
POS, syndicated, invoice
POS, syndicated, invoice
One click
to re-run as markets change
to re-run as markets change
The problem
Price is the biggest profit lever most teams set by rule of thumb.
When pricing studies take weeks, decisions fall back on cost-plus rules, last year’s list price or a one-off consultant report. By the time answers arrive, competitors have already moved.
Pricing studies take weeks, so they are run once a year — if at all.
Your own price changes are analysed, but competitor price moves are not.
Price, pack size and promotion are decided by different teams, in different spreadsheets.
Every new question means another request to an outside vendor.
How it works
From raw sales data to pricing insight — automatically.
A proprietary AI algorithm does the work that normally takes an analytics team weeks.
- 01
Bring any sales data
Point-of-sale scanner data, third-party (syndicated) sales data, invoice data and other sales sources all work.
- 02
Data is cleansed automatically
The AI algorithm prepares and cleans the data — no manual wrangling before modeling.
- 03
The best predictive model is estimated
Custom models are estimated automatically for your business and kept current, rather than fitted once by hand.
- 04
Insights are generated — in one click
Managers and executives run analyses and generate insights themselves from a simple web interface, and re-run them whenever conditions change.
Pricing Optimizer · method
Any sales data
POS scannerSyndicatedInvoiceOther sales data
Proprietary AI algorithm
- 1Cleanses the data
- 2Estimates the best model
- 3Generates insights
One-click insights
ElasticitiesCompetitor effectsPrice scenariosPrice gaps
What it evaluates
What it measures
Own-price elasticity
How strongly demand for each product responds to its own price.
Competitor price effects
How shifts in competitor pricing move your volume — not only changes to your own products.
Competitive price gaps
Where each SKU sits against the competitive band, and which are under- or over-priced.
Margin vs. volume trade-off
Projected gross margin and volume impact of any price scenario before you make the change.
Price-pack architecture
How price points work across sizes and pack formats in a category.
Business conditions
Extraneous factors are accounted for, so a price effect isn’t confused with something else.
Why it’s different
What sets Pricing Optimizer apart.
AI-driven
Sophisticated modeling tailored to your company’s needs.
Cloud-based
Scales to businesses of any size, across industries.
Self-reliant
Your team runs it — no dependency on external vendors for every question.
In development
On the roadmap: AI-based dynamic price optimization — Automatic price recommendations that adjust as conditions change.
See it in action
See Pricing Optimizer on a category like yours.
We show the real product on real data in a 30-minute walkthrough — not a mock-up.
Data & integrations
Works with the data you already have.
Sales data
POS scanner dataSyndicated retail dataInvoice / shipment dataCSV & Excel
Systems
SAPTallyUnicommerceAmazonFlipkart
Results flow to
Power BIGazelle web appExports for decks
Proof
Big Chalk × NorthLight: elasticity capabilities, brought in-house for consumer brands
Big Chalk combines consumer-marketing expertise with data science. Their data harmonization and model prep, combined with Gazelle, lets clients capture shifts in competitive pricing — beyond just their own products.
All client work →Client results
What this has delivered for clients.
PricingFood & condiments
$75MM
revenue growth
Pricing Strategy
Replaced deal-by-deal, one-size-fits-all pricing with a tiered, elasticity-based strategy across the portfolio.
Read the case →PricingSun protection
$15MM
revenue growth
Portfolio Pricing Optimization
Measured shoppers’ willingness to pay item by item, then split the portfolio into premium and competitively priced roles.
Read the case →What data do we need?+
Any type of sales data works — point-of-sale scanner data, third-party syndicated data or your own invoice data. Most onboarding time goes into connecting and harmonizing that data, which our team and partners handle with you.
How quickly do we see results?+
Once data is connected, models are estimated automatically and a full set of pricing insights is available in minutes.
Does it account for competitor pricing?+
Yes. The models capture shifts in competitive pricing, going beyond your own products, and factor in extraneous business conditions.
Can we re-run the analysis ourselves?+
Yes. Analyses can be re-run or updated whenever you want, from the web interface, so you can respond to market changes without waiting for a new study.
Do we need a pricing or data science team?+
No. The platform is built so managers and executives can run analyses themselves. Where you want bespoke work, our Analytic & Consulting Services team can help.
Is dynamic pricing available today?+
Not yet. AI-based dynamic price optimization is in development. Today’s product gives you the elasticities, scenarios and insights to set prices with confidence.
Related solutions
Built on the same modeled view.
Promotion Optimizer
Promotion planning and full calendar optimization for a higher return on every dollar of trade spend.
Learn more →Forecasting Optimizer
Automated, model-driven forecasts that tie directly to business impact — refreshed as market conditions change.
Learn more →Gazelle AI
Ask unstructured business questions in plain language. Interpretation, insights and implications are generated automatically.
Learn more →
See it on your own data.
A 30-minute walkthrough of Gazelle on a category like yours.