Fake discounts make a grocery price look like a deal when it isn’t. Often, the “was” price rose only briefly, or it was never the usual price at all. So shoppers think they’re saving, while brands and rival retailers compete in a distorted market.

Courts are now testing these tactics, too. In May 2026, for example, Australia’s Federal Court found 13 of 14 sample Coles “Down Down” tickets misleading.

This guide covers the common patterns and the rules in key markets. It also shows how to spot fake discounts with price history data.

What Fake Discounts Look Like in Grocery

Fake discounts come in a few common forms:

• Price spike: a product’s price rises for a short time, then drops back as a “deal”.
• Phantom “was” price: the higher price was rarely, if ever, charged in that store.
• Deal that isn’t lower: the promo price matches, or even exceeds, the usual price before the spike.
• Multi-buy trap: “2 for $6” looks good, but one costs $2.80, so two singles cost less.
• Shrinking pack: the price drops, but the pack shrinks more, so the unit price rises.
• Permanent special: a “deal” that never ends, so the deal price is really the regular price.

Each pattern leaves a trace in price history. As a result, the right data makes fake discounts easy to spot.

Why Fake Discounts Are Under Scrutiny

Regulators in several markets now treat fake discounts as a serious problem.

Australia

In May 2026, the Federal Court found that 13 of 14 Coles “Down Down” examples misled shoppers. According to the ACCC, prices rose by at least 15% for a short time. Then they dropped to a “Down Down” price at or above the original price.

The court also said a “was” price likely wouldn’t have misled if it had applied for at least 12 weeks. Penalties are yet to be decided. Meanwhile, the ACCC’s similar case over Woolworths’ “Prices Dropped” deals went to court in 2026, and Woolworths denies misleading anyone.

Other Markets

• US: under the FTC’s pricing guides, a former price must be a genuine price offered regularly. By contrast, an inflated price set up for a big reduction is fictitious.
• EU: the top EU court ruled that price cuts must use the lowest price of the previous 30 days.
• UK: since 6 April 2026, shops must show loyalty prices beside regular prices, with unit prices.
• New Zealand: in May 2025, the Commerce Commission filed criminal charges against Woolworths NZ. They cover alleged pricing errors and misleading specials.

As a result, fake discounts now carry real legal and reputational risk.

How to Spot Fake Discounts: Five Tests

You can check any grocery deal with five simple tests:

1. 30-day low test: compare the promo price with the lowest price of the previous 30 days. If it isn’t lower, the deal may not be real.
2. Duration test: check how long the “was” price applied. In the Coles case, for instance, the court pointed to 12 weeks.
3. Spike test: flag any price rise of 15% or more that’s followed by a deal within a few weeks.
4. Unit price test: compare unit prices for multi-buys and new pack sizes against the single item.
5. Cross-store test: compare the deal with the same product’s price at rival stores.

Shoppers can run some of these tests by hand. However, brands and retailers need them at scale, across thousands of products and stores.

The Price History Data You Need

To spot fake discounts reliably, you need daily price history for each product and store. Typically, each record includes:

Aim for at least 30 days of history before any deal, and ideally 12 weeks or more. So start collecting early, because missed days can’t be filled in later.

For a worked example of daily tracking, see our Blinkit price tracking guide. In addition, our competitor price monitoring service tracks everyday prices across rivals.

How to Build an Automated Fake Discount Check

Once you have daily prices, follow these steps to catch fake discounts:

1. Capture daily prices for each product and store.
2. Store every promo label and “was” price exactly as shown.
3. Calculate reference prices: find the 30-day low before each deal, plus the 12-week median regular price.
4. Compare the promo price and the “was” price with those references.
5. Flag patterns, using the rules below.
6. Review flags by hand, because errors and genuine cost rises do happen.

These thresholds are examples, not legal tests. So agree them with your legal or compliance team.

For example, say a pasta sauce sold at $3.00 for six months. Then it rose to $3.50 for three weeks, before a “deal” at $3.00. In that case, it trips the spike, short “was,” and not-lower flags.

Who Uses Fake Discount Detection

Different teams check for fake discounts for different reasons, for example:

• CPG brands: protect brand value, and confirm that funded deals give shoppers real savings.
• Retail compliance teams: audit their own promotions before regulators or the media do.
• Consumer groups and journalists: investigate claims with evidence, not anecdotes.
• Lawyers and regulators: build timelines of prices before and after each deal.
• Price comparison apps: show only genuine deals, so users trust the app.

Metrics to Track

Then report a few clear metrics:

• Flag rate: the share of promotions that trip one or more flags.
• Real vs claimed discount: the saving against the 30-day low, compared with the advertised saving.
• Flags by retailer and category: where fake discounts cluster.
• “Was” price duration: how long the higher price applied before each deal.

For instance, a “save 20%” claim may give a real saving of 0% against the 30-day low.

How FoodSpark Delivers Price History Data

FoodSpark can collect public grocery prices daily, store by store. So you can check for fake discounts using real history:

• Coverage: major grocers in the USA, UK, Australia, India, and other markets, as listed on our grocery data API hub.
• Fields: regular, promo, “was”, loyalty, and unit prices, as well as promo labels and dates where shown.
• Location: by store, postcode, ZIP code, or pincode.
• Delivery: CSV, JSON, XML, REST API or webhook, along with AWS S3, BigQuery, Snowflake or Google Sheets.
• Free sample: 100 rows in CSV or JSON, so you can test the fields first.

For example, see our Australia, UK, and USA grocery data API pages.

We collect public data only, with no personal user data, payment information, or non-public content. Also, note that our data flags patterns, but it doesn’t decide whether a deal breaks the law.

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Fake Discounts: FAQs

What are fake discounts?

They’re promotions that claim a saving the shopper doesn’t really get. For example, the “was” price may have applied only briefly before the deal.

How can I tell if a grocery discount is real?

Compare the deal with the lowest price of the last 30 days. Then check how long the “was” price applied, and compare unit prices.

How long should a “was” price apply?

It depends on the market. For instance, the EU uses the 30-day low, while an Australian court pointed to 12 weeks.

Are fake discounts illegal?

In many markets, misleading price claims can breach consumer law, such as in Australia, the EU, and the US. However, this isn’t legal advice, so check with a lawyer.

What data do I need to detect fake discounts?

You need daily prices for each product and store, along with promo labels and “was” prices. Ideally, collect at least 12 weeks of history.

Can you spot fake discounts on delivery apps?

Yes, where apps show prices publicly. However, app prices can differ by area, so track the same address each time.

How much does price history data cost?

Overall, it depends on retailers, products, stores, and refresh. So start with a free 100-row sample, and then get a custom quote.