Week 6 — The Price Is Watching You

Some prices change by time, place, demand or shopper. The price on your screen may not be the price on someone else's.

31 August 2026

Core question#

What happens when price changes in response to people and context?

Week 5 looked at price changing over time. This week adds other possible inputs: demand, device, location, login state or browsing history. The number on the screen may be one result from a pricing system whose other inputs you cannot see.

Demand-sensitive pricing vs personalisation#

These ideas are easy to mix up, so keep them separate:

• Demand-sensitive pricing reacts to overall conditions — everyone may see a higher price when demand or costs rise, e.g. a ride-share surge. It doesn’t require knowing who you are.
• Personalisation / segmentation changes price by group or individual: for example, two accounts seeing different prices for the same seat.
• Price discrimination is the economics term for charging different buyers different prices for the same thing. Here it is a technical term, not an accusation against any named company.

Handling evidence carefully#

This course does not claim to know which real platforms use which pricing systems. If we cannot verify a claim about a named company, we do not make it. When we need an example, we use a clearly labelled hypothetical storefront — see Policies.

Why it matters for a buyer#

If price can depend on context you don’t control, then “the price” stops being a single number to compare against a reference price (Week 3) or a history (Week 5) — it becomes a number that might change if you check from a different device, at a different time, or as a different (or logged-out) user. A cautious buyer treats a single quoted price as one sample from a distribution, not as the price.

The $249 headphones#

Hypothetically: a shopper checks the $249 headphones from their phone while logged in, and again from a friend’s laptop in an incognito window, and sees $239 the second time. Nothing about the product changed. What changed is which inputs the price function received — and the $10 difference is data about the pricing system, not about the headphones.

The $239 second reading is invented for this example. It is not a claim that any named platform prices this way, or that checking incognito produces a lower price in practice.

Learning outcomes#

By the end of this week, you should be able to:

• distinguish demand-sensitive pricing from personalisation and segmentation
• define price discrimination as a pricing-strategy term, not an accusation
• explain why a single quoted price should be treated as one sample from a distribution
• state this course’s evidence rule for discussing pricing systems without naming a real company
• identify which inputs, besides time, a price might be responding to in a given scenario

Before class#

If you’re comfortable doing so, check a price for the same item from two different devices, logged in and logged out, or at two different times of day, and note whether it changed. If it didn’t, that’s a valid and common result — the point is running the check, not finding a dramatic gap.

In class#

Given a short hypothetical scenario describing a price that varies by device, location, or login state, classify the pricing system as demand-sensitive, personalised, or ambiguous from the evidence given — and say what additional evidence would resolve the ambiguity.

What you should leave knowing#

Once price can depend on things you cannot see, the number on your screen is one sample, not the whole truth. That is why this course does not name a real company’s pricing system without a source.

Where this goes#

Week 7 stops looking at single transactions and asks what happens when a price repeats every month, whether or not you notice it.