A finished MKT-832 Topic 7 platform incentive separation analysis example that maps each delivery-app action against platform revenue and customer goals, then tests a browsing trend against a ranking change. Searches like "mkt 832 topic 7 assignment example", "mkt832 topic 7 sample" and "mkt-832 topic 7 example" land here.
What a finished MKT-832 Topic 7 platform incentive separation analysis looks like
An incentive map is the centerpiece of the finished analysis. Each customer action on the composite platform appears in a row with two entries: the revenue it brings the platform and the goal the customer appears to be pursuing. Most rows align, since both parties want an order placed. Three diverge. Promoted restaurants ranked above better-rated ones earn advertising fees while lengthening the search. Minutes spent scrolling carry sponsored placements the platform sells. A delivery subscription is offered at the moment a fee appears. Rochet and Tirole's account of two-sided markets explains why a platform balances charges across its sides rather than serving any one of them. The analysis then reads the browsing trend against the map, with illustrative session data, and finds longer time to order tracking a ranking change more closely than any change in appetite.
How an MKT-832 Topic 7 example is structured
The analysis opens with the platform's claim and its own counterclaim, so the reader knows which trend is under examination. A framework section explains two-sided markets and why a platform earning from restaurants, advertisers and customers at once can profit from actions that serve only one of them. The incentive map follows, one row per customer action, with divergent rows marked. Each divergence then receives a paragraph naming the design feature involved and the revenue attached to it, with illustrative figures. A section on the record lists what the platform measures, orders, taps and minutes, and what it does not, such as whether the meal was what the customer wanted. The browsing trend is then tested against the timing of a ranking change. The analysis closes by answering the objection that customers can leave for a rival app at any time.
Enjoyment claimed, ranking suspected
The platform's reading of longer browsing as delight in discovery is stated first, beside the analysis's own claim that a ranking change produced it.
Three sides, three sources of revenue
Restaurants pay commission, advertisers pay for placement and customers pay fees, so the platform can gain from actions that benefit only one party.
Rows where interests part
Promoted placements above better-rated restaurants, sponsored slots within long scrolls and a subscription offer timed to the fee screen are the three rows marked divergent.
A trend that follows the ranking
Illustrative session data show browsing time rising in the month promoted listings moved upward, with no matching rise in orders or in meal ratings.
Measures kept, measures never built
Orders, taps and minutes are logged in detail, while whether a meal matched what the customer wanted is recorded nowhere the analysis could find.
Switching costs and the exit objection
Customers can move to rival apps, the objection holds, and the reply points to saved addresses, loyalty credit and similar ranking practices across competitors.
Where marks go in MKT-832 Topic 7
Analyses lose the most by treating platform data as a neutral record of what customers do, when the record was designed around what the platform sells. Close behind is the paper that describes a platform's incentives in general terms, as profit-seeking, without mapping them onto specific customer actions. Many drafts assume the platform's interests and the customer's are always opposed, which ignores the rows where both want the same order placed. Behavioral trends are often explained by consumer psychology before the interface changes that coincide with them are checked. Some papers mention two-sided markets without saying which side bears which charge. Leaving the exit objection unanswered weakens the argument, since competition is the standard reason offered for why platform and user interests should converge over time.
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MKT-832 Topic 7 questions, answered
What is a two-sided market?
A market in which a platform serves two or more groups that value each other's presence, such as diners and restaurants, and sets charges for each side with the other in mind. Rochet and Tirole's work showed that how a platform divides its charges between sides can matter as much as their total. The example uses the idea to explain why a delivery platform can profit from actions that serve advertisers rather than diners.
Why does a platform's incentive matter to consumer research?
Because the platform decides what gets recorded, how options are ranked and which actions are easy, and each of those decisions follows its revenue. Behavior observed on the platform therefore reflects its design as well as its users. A researcher who reads a trend in platform data as a change in consumers, without checking the design changes that coincided with it, may be reporting the platform's strategy back to itself.
Are platform and user interests always opposed?
No, and the example is careful on this point. Both want the customer to find a meal and place an order, and most of the incentive map shows alignment. The divergences are specific: placements sold to advertisers, time spent scrolling past paid slots and offers timed to a moment of friction. Naming those rows precisely is more persuasive than a general claim that the platform exploits its users.