A finished MKT-834 Topic 3 online experiment protocol example for a ticket marketplace's fee display, with event-level randomization, a power-based horizon, novelty and sample-ratio checks and a stopping result. Searches like "mkt 834 topic 3 assignment example", "mkt834 topic 3 sample" and "mkt-834 topic 3 example" land here.
What a finished MKT-834 Topic 3 online experiment protocol looks like
The finished protocol is a document the team signs before any traffic is split. It names one primary metric, completed purchases per visiting buyer, and two guardrails, refund requests and seller listing volume, with the decision each result would trigger. Randomization is by event rather than by buyer, because treated and control buyers bidding for the same limited seats would otherwise contaminate each other, a violation of the no-interference assumption in Rubin's framework. A power calculation sets the number of events and the fixed end date, with illustrative figures. Peeking is handled either by committing to that end date or by using sequential methods of the kind Johari and colleagues developed for continuous monitoring. A novelty check compares effects by weeks since first exposure. The sample-ratio check that Kohavi, Tang and Xu describe runs daily.
How an MKT-834 Topic 3 example is structured
Commitments precede design in this protocol, so the first section records the hypothesis, the primary metric and the result that would end the project. The randomization section follows, explaining why the unit is the event, what that costs in statistical power and how events are stratified by venue size and on-sale date. A power section states the minimum effect worth detecting, the variance assumed from past data and the resulting number of events. Monitoring rules come next, including who may view interim results and whether stopping early is permitted under a sequential method. A threats section treats novelty, interference among sellers who list across events and the sample-ratio check that detects broken assignment. Analysis rules are fixed, with the primary comparison, guardrails and any segment analyses labeled exploratory. The protocol ends with signatures and the date results will be read.
An ending result written first
The protocol states which outcome would stop the all-in display from launching, so an unwelcome answer has been accepted as possible before the test starts.
Events, not buyers, as the unit
Buyers in both arms competing for the same limited seats would contaminate the comparison, so whole events are assigned, at a stated cost in power.
A fixed horizon or a sequential rule
Repeated looks at a running test inflate false positives, so the team either commits to one reading date or adopts methods built for continuous monitoring.
Effects read by weeks since exposure
Buyers who noticed the new display may react to its novelty, so the effect is compared across exposure cohorts to see whether it fades or holds.
Sample ratios checked every day
A split drifting from its planned proportions signals broken assignment, and Kohavi, Tang and Xu treat that check as a gate before any result is read.
Segments labeled exploratory in advance
Cuts by device, venue size and price band may be reported, but the protocol marks them as hypotheses for later tests rather than as findings.
Where marks go in MKT-834 Topic 3
Protocols give up the most when they randomize individual buyers on a marketplace where treated and control buyers compete for identical seats, since the comparison then measures a reallocation between arms rather than an effect. Close behind is the plan with no fixed reading date and no sequential method, which invites stopping on the first favorable day. Many drafts list several success metrics without naming a primary one, leaving room to report whichever moved. Novelty is often ignored, although a changed display can draw attention simply by being new. Sample-ratio checks are commonly missing, and a broken split can produce a convincing but meaningless difference. Doctoral readers also expect the stopping result written down before any traffic is split, because a test that cannot disappoint anyone has not been designed to inform a decision.
Get an MKT-834 Topic 3 example written to your instructions
Send the MKT-834 Topic 3 instructions and your classroom's rubric, with the product change or scenario your section is testing. A custom example is written to them, with the stopping result stated first, the randomization unit chosen for interference, a power-based horizon, monitoring rules, novelty and ratio checks and exploratory cuts labeled, back in 24 to 48 hours. The first one is free.
MKT-834 Topic 3 questions, answered
What is peeking in an A/B test?
Checking a running test repeatedly and stopping when the result looks significant. Standard significance tests assume a single analysis at a planned sample size, so each extra look raises the chance of declaring an effect that is not there. Teams avoid the problem by fixing the reading date in advance or by using sequential methods designed for continuous monitoring, such as the always-valid approach Johari and colleagues described.
What is interference in a marketing experiment?
A situation in which one unit's treatment affects another unit's outcome, violating the assumption that each outcome depends only on its own assignment. Marketplaces are prone to it: if treated buyers purchase more of a limited supply, control buyers find less available, and the measured difference exaggerates the effect. Randomizing larger units, such as whole events or markets, is the usual remedy, which is why the example assigns whole events.
What is a novelty effect?
A temporary change in behavior caused by the fact that something is new rather than by what it does. Users may click a redesigned button more at first simply because they notice it, and the effect fades as it becomes familiar. The opposite, a primacy effect, occurs when users initially resist a change. The example checks for both by comparing results across groups exposed for different lengths of time.