消费者决策、信任与本地适配

Follow one pair of running shoes. The student's old pair has holes, so she becomes aware of a need. She searches: a friend mentions a brand, she types a query, then scrolls a short video. She evaluates two sellers, reading reviews, checking the size chart, the delivery date and the return address. She purchases, then waits. After delivery she decides whether the shoes fit, writes a review, asks for an exchange or returns them. Section 3.1.1 calls these five stages need awareness, information search, evaluation of alternatives, purchase and post-purchase behaviour.

The stages are useful because each one asks a different question. At need, the buyer asks whether this product solves my problem. At search, she asks which words and categories will find it. At evaluation, she asks whether this seller, size, price and delivery promise are acceptable. At purchase, she asks whether payment is safe and the address is right. After purchase, she asks whether the product matched the promise and whether a problem can be fixed. A page that answers the first three questions and then offers only a card payment and a foreign return address has broken the sequence at the last moment.

The textbook gives four reasons why people buy online: price, convenience and availability, more categories to compare, and lower overall cost. Price is often the first consideration, and convenience may be second because a buyer can browse in about five minutes. More categories make comparison easier. Overall cost is the subtle one: it includes time, freight and risk, not only the tag price. A US$28 shoe with a US$9 return and a three-week wait may cost more in the buyer's terms than a US$34 shoe available locally with an exchange at the counter.

Here the lesson needs a boundary. The five stages describe the buyer's psychology. A sales funnel describes the seller's actions and aggregate metrics: impressions, clicks, product views, add-to-cart, purchase and repeat. The two can be mapped, and marketers often do map them, but they are not the same object. A funnel is a dashboard for the seller; a stage is a question in the buyer's head. One buyer can loop back from post-purchase to search after a bad experience, while a funnel report shows only that a cohort dropped. Lesson 13 will build the seller-side funnel; this lesson keeps the buyer-side stages separate so that the funnel does not pretend to be a mind.

Trust enters at evaluation and purchase, but it is built earlier and tested later. A cross-border buyer cannot touch the shoe, cannot visit the seller and may not know the local consumer-protection rules. She therefore looks for evidence. This lesson groups the evidence into four kinds: reviews and buyer photos, a clear return and refund policy, payment protection or a platform guarantee, and consistent brand or platform backing. The list is a teaching synthesis of §3.1 and §3.1.2, not a standalone textbook entry. Its value is practical: each kind answers a different worry, and a page can be audited for which kinds are present.

The four kinds are not interchangeable. Reviews answer the question whether the product worked for people like me, but they can be faked or irrelevant to my size. A return policy answers what happens if it does not fit, but only if the address is reachable and the cost is stated. Payment protection answers whether my money is safe if the seller disappears, which is different from whether the seller is friendly. Brand or platform backing answers whether someone with a reputation stands behind the transaction. A seller promise is weaker than a platform guarantee because the buyer has no independent route when the seller refuses.

Local adaptation is where trust and decision stages meet the details. The lesson uses six dimensions: language, sizing, payment, delivery, returns and festivals. Language is the most visible, but it is also the easiest to fake. Sizing requires conversion tables and, for shoes, width and model-specific fit. Payment requires a method the buyer already uses, which may be a wallet, a bank transfer or cash on delivery. Delivery must match the network, including pickup points and agents. Returns must name a place the buyer can reach. Festivals change the timing of need, gifting and delivery promises. A page that is translated but keeps European sizes, card-only payment and a foreign return address has adapted the wording, not the purchase.

Section 3.1.2.2 gives the conceptual distinction. Personalisation changes the advertising message or the content shown to a user; customisation changes the product and service according to user preferences. Local adaptation is mostly customisation. The textbook also reports a survey in which about 95% of marketers implemented some form of personalisation and 97% of those reported a lift; the two percentages have different bases and should not be multiplied or read as proof of causation. Search advertising is described as four to ten times as effective as traditional advertising because a query reveals explicit intent. Those numbers support a simple point: matching the offer to the moment and the market beats generic reach.

Return to the abandoned cart. The student is probably not stuck at need or search; she has already found the shoes. She is stuck at evaluation, because the evidence needed to justify the purchase is missing: only model photos, 11 reviews, European sizing, card-only payment and a return address in China. The first changes should be the ones that answer her actual questions: a local centimetre chart with width notes, buyer photos from the region, a reachable return or exchange point, and a payment method she uses. A discount would not fix an evidence gap. That is the practical test of this lesson: diagnose the stage, name the missing evidence, then adapt the detail.

The close is a bridge. Once the buyer can evaluate and trust the offer, the next question is how she finds it at all. Search, recommendation and social content are the discovery channels that bring her to the page. Lesson 11 takes those channels apart, including the difference between paid and organic search, how recommendation systems rank candidates, and why the two US$90 billion figures in the textbook measure different things.