Evergreen
What Is a Loyalty Penalty? Meaning and Examples
A loyalty penalty occurs when an existing customer pays more because a supplier expects them not to switch. Learn the evidence needed and common false positives.
What Is a Loyalty Penalty?
A loyalty penalty occurs when a longstanding or identifiable existing customer receives a worse comparable price or term because the supplier expects that customer to stay, renew, or avoid switching.
The phrase does not mean every loyal customer pays more. It does not apply to every expired promotion, market increase, or different online offer. A valid comparison needs equivalent products and terms, plus evidence connecting the worse offer to customer tenure or expected switching behavior.
Where the term comes from
The Competition and Markets Authority examined the phrase in response to a 2018 United Kingdom super-complaint. Its official summary describes longstanding customers paying more than new customers for the same services because suppliers believe they are unlikely to switch.
The investigation covered mobile service, broadband, cash savings, home insurance, and mortgages. These markets often use contracts that renew automatically, introductory prices that expire, or older tariffs that continue until the customer acts.
The CMA identified three recurring patterns.
| Pattern | How the worse offer develops | Evidence to check |
|---|---|---|
| Price jump | An introductory rate ends and the customer moves to a higher standard rate | Original offer, expiry notice, renewal amount, and comparable new offer |
| Price walking | The supplier raises the existing customer's price repeatedly over renewals | Multi-year renewal history and risk-adjusted new-customer prices |
| Legacy pricing | An older tariff becomes worse than current comparable options | Product terms, customer tenure, available alternatives, and switching path |
The phrase describes a market pattern, not a single pricing technology. A company can create a loyalty penalty through a manual renewal rule, a predictive model, a difficult cancellation process, or simple inattention to old accounts.
Why suppliers may charge loyal customers more
Acquiring a customer can be expensive. A supplier may offer a low introductory price to win the account, then recover margin after the customer stops comparing alternatives.
The mechanism depends on switching behavior. Some customers stay because they value continuity. Others face confusing terms, limited time, disability, poor digital access, a mortgage constraint, a bundled product, or the fear of losing service. A supplier may predict that these customers will accept a worse renewal.
In insurance, the Financial Conduct Authority called repeated renewal increases price walking. Its reforms required a home or motor renewal quote not to exceed the equivalent new-customer price.
The same concern appears in energy. In 2024, Ofgem retained its ban on acquisition-only tariffs, which prevented suppliers from reserving lower offers for new customers while existing households could not access them.
The problem is not loyalty itself. The problem is using reduced switching pressure to make a comparable customer worse off while the customer reasonably expects the relationship to help.
A loyalty reward is the opposite
A loyalty program gives an existing customer a benefit based on membership, purchase history, or continued use. The benefit may be a lower price, points, free delivery, access, or another disclosed advantage.
A loyalty penalty makes the existing customer worse off. A loyalty reward makes that customer better off under its stated rules.
The same platform can contain both. A retailer might give loyalty members a lower promotional price while another product line raises renewal prices for inactive customers. The label should follow the specific offer and comparison.
A new-customer discount is not automatically a penalty
The CMA says introductory deals are not necessarily harmful. A temporary, clearly disclosed acquisition offer can help a new business compete and give consumers a reason to try a service.
Concern increases when the customer cannot understand what happens after the offer, the later gap is large, switching is made unnecessarily difficult, vulnerable customers bear the cost, or the service is essential.
The evidence question is whether the disclosed promotion ends as promised or whether the supplier exploits inertia through hidden or repeated differences.
| Situation | Loyalty penalty? | Why |
|---|---|---|
| A clearly disclosed first-month trial expires | Not by itself | The customer knew the time-limited term |
| A renewal price rises above the equivalent new-customer offer because the customer is unlikely to switch | Yes, if the comparison and mechanism are supported | Existing status drives the worse offer |
| A loyalty member receives a lower price | No | The existing customer receives the benefit |
| Two stores charge different local prices | Not by itself | Store and market conditions differ |
| Two accounts see different prices for an unexplained reason | Undetermined | Variation is observed, but loyalty has not been shown as the cause |
How to test whether the label fits
First match the product or service, risk, geography, timing, channel, quantity, eligibility, and material terms. A home insurance quote for a different property or risk is not a valid tenure comparison. A grocery item from a different store location is not either.
Then compare customer state. Identify whether one offer is for a new customer, an existing customer, a renewing customer, a loyalty member, or someone whose prior behavior predicts low switching.
Finally connect the state to the outcome. Renewal rules, product specifications, test assignments, internal models, communications, or a regulator's evidence can establish the link. A higher price alone does not reveal the rule.
flowchart TD
A["Worse price or term observed"] --> B{"Comparable product and conditions?"}
B -->|No| C["Not a valid loyalty comparison"]
B -->|Yes| D{"Existing status or expected non-switching caused the difference?"}
D -->|Supported| E["Loyalty penalty"]
D -->|Unknown| F["Cause remains unverified"]
D -->|No| G["Another pricing rule applies"]
The diagram is an evidence test, not a legal definition. Laws and regulatory rules differ by market and jurisdiction.
Is personalized pricing the same thing?
No. Personalized pricing changes an offer for an individual or segment. A loyalty penalty is one possible result when the relevant feature is customer tenure, renewal state, or predicted unwillingness to switch.
A personalized discount can reward a loyal customer. A randomized price test can show different prices without using loyalty at all. Dynamic pricing can change a public price because demand or inventory changed. Surveillance pricing can use personal data for an individualized offer whether or not the person is loyal.
These categories can overlap, but they should not be used as synonyms.
Did the Instacart test prove a loyalty penalty?
The 2025 Consumer Reports investigation documented simultaneous item-price variation in coordinated Instacart sessions. It did not establish that repeat purchase history, customer tenure, or predicted switching behavior caused the assignments.
Instacart said the groups were randomized by product category and store location and denied using personal, demographic, or user-level behavioral information to set item prices. Consumer Reports observed the outputs but did not publish a complete independent audit of that internal rule.
E095 uses loyalty penalty as Dalton Anderson's framing and concern: what if a shopper's repeated purchases become evidence that the person will tolerate a higher price? That is a legitimate research question. The reported test did not answer it causally.
[[What Consumer Reports Found in Its Instacart Pricing Test]] provides the full record. [[How to Audit an Online Pricing Study]] explains the evidence needed to move from different prices to a supported cause.
What a consumer or product team should ask
The consumer question is whether an equivalent new or less-established customer can receive a better offer and why. The product-team question is whether retention models, renewal rules, or switching predictions create systematically worse outcomes for people who stay.
The answer should be visible in price histories, eligibility rules, renewal notices, experiment designs, model inputs, and outcome analysis. If the organization cannot reproduce the comparison, it cannot reliably distinguish a loyalty penalty from ordinary variation.
A fair system does not require every person to receive the same offer in every setting. It requires a defensible reason for the difference, a clear explanation, and a way to correct mistakes or leave without artificial friction.
This explainer was developed from CMA and FCA records, current energy-market examples, the Consumer Reports investigation, Instacart's response, and the preserved E095 transcript. It is consumer education, not legal advice. AI assistance was used for research organization, drafting, and validation. Publication remains unauthorized.
Sources
Follow the evidence.
- ag.ny.gov: attorney general james demands answers instacart about algorithmic pricingag.ny.gov
- itl.nist.gov: pri332itl.nist.gov
- instacart.com: promotionsinstacart.com
- ftc.gov: ftc surveillance pricing study indicates wide range personal data used set individualized consumer pricesftc.gov
- consumer.ftc.gov: online shoppingconsumer.ftc.gov
- company.instacart.com: instacartpricingcompany.instacart.com
- gov.uk: tackling the loyalty penaltygov.uk
- company.instacart.com: instacart makes it easier for customers to save on groceries with acquisition of eversightcompany.instacart.com
- instacart.com: 1586544648instacart.com
- usa.gov: online purchase complaintsusa.gov
- company.instacart.com: ending item price tests on instacartcompany.instacart.com
- company.instacart.com: the truth about pricing tests on instacartcompany.instacart.com
- itl.nist.gov: pri11itl.nist.gov
- fca.org.uk: fca confirms measures protect customers loyalty penalty home motor insurance marketsfca.org.uk
- consumerreports.org: instacart ai pricing experiment inflating grocery bills a1142182490consumerreports.org
- investors.instacart.com: 9e9aff2c 95db 4f75 bdf1 0f4025e1468cinvestors.instacart.com