Research Note
Grocery Basket Comparison Research Note
What evidence and method can support a household grocery comparison without producing a false national ranking or a misleading lowest-price claim?
Grocery Basket Comparison Research Note
Question
What evidence and method can support a household grocery comparison without producing a false national ranking or a misleading lowest-price claim?
Method sources
NIST's unit-pricing guidance defines unit price as cost per standard measure and explains its use in comparing package sizes and identifying shrinkflation. NIST's 2024 update documents current best-practice materials while noting that adoption and regulation vary.
The USDA Food Buying Guide provides yield and cost-per-serving concepts. It also makes clear that raw product price does not capture every labor, storage, or operating cost. The public guide uses this principle cautiously for household comparison rather than importing an institutional procurement model.
The FTC's online-shopping guidance supports comparing seller terms, price-matching practices, and total purchase conditions rather than relying on a headline price.
Stretch's terms provide a product-specific limit. Retailer and manufacturer data can contain errors or expired prices, and users are responsible for verifying offers.
Comparison model
A repeatable comparison needs one household basket, exact product or substitution rules, normalized units, the same collection window, store and channel identity, account and membership state, promotions, fees, tips, taxes where applicable, travel, time, accessibility, missing items, second-trip risk, and confidence.
Time and accessibility should remain household inputs. There is no single universal dollar value for walking, driving, transit, caregiving, disability, or schedule pressure.
Editorial limits
Do not rank grocery stores nationally from one basket or market. Do not call a platform total final when fees, substitutions, or promotions can change at checkout. Do not annualize one trip without a repeated design.
Use a table or worksheet to make the decision inspectable. The method is successful when a household can repeat it and identify which assumption changed the winner.
Sources
Follow the evidence.
- ag.ny.gov: attorney general james demands answers instacart about algorithmic pricingag.ny.gov
- nist.gov: nist sp 1181 unit pricing guide best practice approach unit pricing 2015 ednist.gov
- gs1.org: gtings1.org
- search.ftc.gov: instacart pay 60 million consumer refunds settle ftc lawsuit over allegations it engaged deceptivesearch.ftc.gov
- stretchgroceries.com: privacystretchgroceries.com
- stretchgroceries.comstretchgroceries.com
- linkedin.com: andyellwoodlinkedin.com
- consumer.ftc.gov: online shoppingconsumer.ftc.gov
- steveblank.com: customer development is not a focus groupsteveblank.com
- steveblank.com: customer discovery in the time of the covid 19 virussteveblank.com
- stretchgroceries.com: termsstretchgroceries.com
- andyellwood.comandyellwood.com
- consumerreports.org: instacart stops ai pricing experiments a1176475852consumerreports.org
- foundersfund.com: choose good questsfoundersfund.com
- nist.gov: uniform unit pricing tools consumers fight shrinkflationnist.gov
- gs1.org: global data modelgs1.org
- gs1.org: current standardgs1.org
- ftc.gov: surveillance pricingftc.gov
- nber.org: w24489nber.org
- nist.gov: best practices uniform unit pricing update nist sp 1181 and nist handbooknist.gov
- foodbuyingguide.fns.usda.gov: Aboutfoodbuyingguide.fns.usda.gov
- andyellwood.com: founderandyellwood.com
- company.instacart.com: the truth about pricing tests on instacartcompany.instacart.com
- ftc.gov: ftc surveillance pricing study indicates wide range personal data used set individualized consumerftc.gov
- apps.apple.com: id6748532450apps.apple.com
- consumerreports.org: instacart ai pricing experiment inflating grocery bills a1142182490consumerreports.org