I build modeling systems that help salty-snack manufacturers — the Frito-Lays, Barcel USAs, and challenger brands of the world — decide how to price, promote, and assort their portfolio across DSD, grocery, club, and c-store.
RGM in salty snacks lives at the intersection of three decisions that compound on each other. Pull one without modeling the others and you leave money on the shelf — or trade margin for volume that never sticks. The system below models all three together.
How price ladders work across single-serve, take-home, family, party, and club packs — and how to close gaps with private label without cannibalizing the next size up.
Lift, baseline cannibalization, and pantry-loading. Which TPRs, BOGOs, and feature/display combinations actually return incremental margin, by channel.
SKU rationalization, pack mix shifts, and channel mix. How portfolio choices change weighted margin per case without losing shopper trips.
Pick a pre-built scenario and the model recalculates volume, revenue, margin, and ROI using realistic salty-snack elasticities and lift factors. All SKUs and prices are illustrative.
The situation. A regional salty-snacks manufacturer was losing margin in convenience stores. The $1.99 single-serve price point had held for three years while COGS climbed 14%. Sales kept pushing for TPRs to defend volume. Finance wanted price up. Nobody had a model that resolved the tension.
What I built. A scenario-based RGM model linking price ladders across the c-store pack tier (1oz, 2.625oz, 3.25oz) to elasticity, competitive price gaps versus Lay's and Doritos, and shopper substitution patterns drawn from IRI panel data. The model also priced in trade spend tradeoffs — every $0.10 of price action mapped to a TPR depth equivalent.
The recommendation. Hold $1.99 on the 1oz to protect the impulse price point. Take +$0.30 on the 2.625oz where elasticity was a tolerable −1.1 and the price gap had over-widened versus Doritos. Pull back BOGOs in c-store entirely — incremental lift was a 0.6x ROI once cannibalization was modeled. Redirect the savings to a 4-week feature + display in grocery on family packs.
Modeled net margin uplift: +$2.4M annualized, with single-serve volume expected to soften less than 2%.
RGM models too often become black boxes nobody trusts. The systems I build are designed to be defensible in a category review — every output traces back to an input you can argue with: elasticity assumption, lift curve, COGS line, channel mix.
Background in CPG analytics with a focus on salty snacks, beverages, and confectionery. Comfortable in Nielsen, IRI/Circana, SPINS, and first-party syndicated. The models here are simplified for the web; production versions hook into your data warehouse.