| Course | GB532 Marketing Research |
|---|---|
| Unit | Unit 9 |
| Paper type | Findings interpretation |
| Length | About 1,100 words, 6 pages double-spaced |
| Format | APA 7 student paper |
| School | Purdue University Global |
| Program | MBA |
| Updated | October 2026 |
Free sample paper for GB532 Unit 9
What One Customer in Four Means for the August Decision: A Unit 9 Findings Interpretation
[Student Name]
Purdue University Global
GB532: Marketing Research
Unit 9 Findings Interpretation
[Instructor Name]
[Date]
The propane distributor, the findings and every figure are composite and illustrative; the sources cited are real.
Objective 1: How Many Automatic Customers Have a Heat Pump
Finding: about 24 percent of automatic-delivery households have a heat pump in use, about 1,930 homes.
Confidence: high. The margin of error is about 3.4 points, inside the plan's 4.5-point target. The estimate applies only to automatic-delivery customers.
Implication: a quarter of the automatic base is large enough to justify a distinct plan. It is also large enough that delivery scheduling for these homes affects truck routes across the whole service area.
Objective 2: How Hybrid Homes Use Propane
Finding: most hybrid homes rely mainly on the heat pump in a typical month, but nearly two-thirds turn mainly to propane when temperatures are lowest.
Confidence: moderate to high. The finding rests on self-report, but it matches the secondary review's evidence that flagged accounts reduced propane most in the shoulder months and least in deep cold.
Implication: hybrid homes are not leaving propane; they are concentrating their demand into the hardest weeks to serve. The plan's value to these customers, and its cost to the company, centers on cold snaps.
The heat pump has not replaced propane in these homes; it has moved propane's job to the coldest nights of the year.
Objective 3: Interest in the Plan and Its Features
Finding: about 49 percent of hybrid households and 40 percent of other households are very or extremely interested. Guaranteed delivery during cold snaps is the most valued feature, followed by a lower fixed annual fee.
Confidence: moderate for the ranking of features; low for predicting uptake. Stated interest in a hypothetical offer typically overstates actual adoption.
Implication: the plan should lead with guaranteed cold-snap delivery and should be offered to all automatic customers, since interest among non-hybrid households is substantial. Whether it would keep hybrid customers is not answered by this survey. Malhotra (2019) distinguishes the information research can provide from the judgment managers must still make, and this objective is where that line falls.
Objective 4: What Delivery Scheduling Needs
Finding: hybrid households rate delivery timing lower than others, about 3.6 against 4.0, a moderate difference. Written comments complain of trucks arriving when tanks are still full and arriving late once a cold spell starts.
Confidence: moderate. The direction is clear and the effect is meaningful, but the survey cannot specify a new schedule.
Implication: the degree-day scheduling model treats a hybrid home as a smaller version of a propane-only home, which it is not. These homes need schedules triggered by forecast cold rather than by accumulated degree days, perhaps with tank monitors for the highest-risk accounts. The company's own delivery data, combined with the survey's identification of hybrid homes, can be used to build that model.
Objective 5: Heat Pump Services
Finding: about 9 percent of respondents would consider it and 24 percent might; interest is no higher among hybrid households.
Confidence: moderate, since a stated willingness to consider a service is a loose guide to purchase.
Implication: installation services are not a strong opportunity on this evidence, and pursuing them would draw attention away from the delivery problems customers actually report. Customers who already have heat pumps bought them elsewhere, and others show little interest in buying them from their propane supplier.
Alternative Readings
Two other readings of the results deserve consideration. First, broad interest in the plan might reflect general dissatisfaction with current fees rather than interest in backup heat as such. If so, a simpler fee reduction for all customers might win the same goodwill. The feature ranking argues against this reading, since guaranteed cold-snap delivery outranked the lower fee among hybrid households, but the two cannot be fully separated with these data.
Second, the moderate dissatisfaction with delivery timing among hybrid homes might stem partly from the novelty of their situation rather than a scheduling flaw. A household that installed a heat pump last year may simply not yet know how much propane it needs. The comments, which describe specific mistimed deliveries, suggest a real problem, but the company could check by comparing hybrid homes' delivery records with their tank levels at each fill.
Findings That Changed the Original Question
The original complaint was that heat pumps were taking the business. The findings show something different: heat pumps are changing when customers need propane, not whether they need it. That reframing matters for marketing as well as operations. A message to hybrid households that treats them as customers to win back would miss the point; a message that promises propane will be there on the coldest night speaks to why they kept the tank.
What Remains Unanswered
Will-call customers: the residential accounts that order fuel themselves were outside the frame. Their heat pump share and needs are unknown.
Former customers: households that left entirely were not surveyed.
Retention: whether a plan would keep hybrid customers can only be tested by offering it.
Price: the survey did not test price levels for the plan, so the fee must be set from cost analysis and tested.
Groves et al. (2009) note that coverage and measurement limits should travel with findings into decisions, not stay in a methods appendix. These limits shape the recommendation: a pilot rather than a full launch.
What the Findings Mean for the August Decision
Taken together, the findings support building a backup-heat plan, but as a pilot. The hybrid base is large, its propane demand is concentrated in cold snaps, and the most valued feature is reliable delivery when it matters most. Interest is broad but not proof of retention. Delivery schedules need to change regardless of the plan, because hybrid customers are already less satisfied with them. And installation services can wait until a future survey or a change in customers' interest suggests otherwise.
A Note on Statistical and Practical Significance
Several differences in the data are statistically significant and small. Sullivan and Feinn (2012) recommend judging results by their size as well as their p-values, and the interpretation has done so: the plan interest difference between hybrid and other households is real but small, while the delivery timing difference is both real and meaningful. The decision should give more weight to the second, since it describes a problem customers already have rather than a preference for a plan they have not yet seen.
References
Groves, R. M., Fowler, F. J., Jr., Couper, M. P., Lepkowski, J. M., Singer, E., & Tourangeau, R. (2009). Survey methodology (2nd ed.). Wiley.
Malhotra, N. K. (2019). Marketing research: An applied orientation (7th ed.). Pearson.
Sullivan, G. M., & Feinn, R. (2012). Using effect size, or why the p value is not enough. Journal of Graduate Medical Education, 4(3), 279-282. https://doi.org/10.4300/JGME-D-12-00156.1
Reading the GB 532 Unit 9 instructions
In GB532 Unit 9 you interpret your findings for the decision they were meant to inform. Organize the interpretation by research objective rather than by table. For each objective, give the finding, a statement of how confident you are and why, and what it implies for the decision. Mark any objective the data could not answer, and say what would answer it. Consider alternative explanations for key results, note any finding that changes the original question, and keep to associational wording wherever the design cannot show cause. Close with what the findings, taken together, mean for the decision and how practical and statistical significance should be weighed. Expect about five pages, citing research methods sources in APA 7.
Inside the GB532 Unit 9 example
The interpretation takes five objectives in turn. The heat pump share is answered with high confidence. Use patterns are answered with moderate to high confidence, and the highlighted sentence restates the central finding that propane's job has moved to the coldest nights. Plan interest is answered for features but not for retention, citing Malhotra on the line between research and judgment. Delivery scheduling and services follow. A section weighs two alternative readings, another shows how the findings reframed the original complaint and a list of unanswered questions cites Groves and colleagues. The implication for August is a pilot, and Sullivan and Feinn support weighting the moderate delivery gap above the small interest gap.
Reading the GB532 Unit 9 grading rubric
GB532 interpretation work earns marks for turning results into implications while staying within what the design supports. Organizing by objective earns early credit. A finding, a confidence statement and an implication for each objective carry significant weight. Marking what remains unanswered, and saying how to answer it, shows honesty. Weighing alternative explanations shows critical thinking. Noticing how findings reframe the original problem shows insight. Avoiding causal language a survey cannot support shows methodological care. A conclusion for the decision that weighs effect sizes completes it. Malhotra, Groves and colleagues and Sullivan and Feinn supply the interpretation's APA 7 sources.
GB532 Unit 9 help from the desk
Many GB532 Unit 9 interpretations walk through tables in order and restate each number, leaving the manager to work out its consequence. Others claim that a survey shows a plan will keep customers. A common gap is confidence: each finding deserves a statement of how sure the reader can be and why. Some writers ignore objectives the data could not answer. Organize by objective, give each a finding, confidence and implication, mark gaps, weigh alternative readings, note how the question has changed, avoid causal claims and state what the findings mean together. Explaining that heat pumps changed when customers need propane, not whether, shows interpretation at its most useful, because it gives the manager a different problem to solve.
Get a GB532 Unit 9 example written to your instructions
Which research questions did your GB532 project begin with, and what did the Unit 8 output show? Send both, along with the interpretation prompt and rubric for Unit 9. Written around those original questions, the custom paper assigns each a verdict and a stated confidence, and a first one arrives free in 24-48h. The paper above is an original model document written by our desk, not a submitted student paper and not an official Purdue University Global document.
More GB532 papers and MBA samples
- GB532 Unit 1: Discussion Board Post
- GB532 Unit 2: Problem Definition Memo
- GB532 Unit 3: Secondary Data Review
- GB532 Unit 4: Research Proposal
- GB532 Unit 5: Sampling Plan
- GB532 Unit 6: Questionnaire Draft
- GB532 Unit 7: Seminar Reflection
- GB532 Unit 8: Data Analysis Report
- GB532 Unit 10: Research Report
- GB531 Unit 9: Campaign Measurement Plan
- GB530 Unit 9: Integrated Promotion Plan
- GB528 Unit 9: Implementation Plan
- GB527 Unit 9: Demand Forecast
GB532 Unit 9 questions, answered
How is interpretation different from the analysis unit?
Analysis produces results; interpretation says what they mean for the decision. In Unit 8 the question is whether a test was run correctly. In Unit 9 it is whether the finding answers the research question, how confident anyone should be, and what else could explain it. Many GB532 sections grade the two on separate rubrics for that reason.
What should I do if the data do not answer one of my research questions?
Say so directly and explain why, whether the item failed, the sample was too small, or the design could not reach the answer. Then state what would answer it. Graders generally reward honest gaps over stretched conclusions, and an unanswered question can become a recommendation for further research in the final report.
Can I use causal language when interpreting survey results?
Rarely. A survey shows that two things occur together, not that one produces the other, unless the design controlled for alternatives. Words such as associated with, more common among, or consistent with are safer. If your analysis tempts you toward a causal claim, name the rival explanation and what study would settle it.
Where can I find a free GB532 Unit 9 sample paper?
This page carries a full GB532 Unit 9 findings interpretation for a propane distributor, organized by objective with findings, confidence statements, implications, alternative readings, unanswered questions and APA 7 references.
Why recommend a pilot rather than a full launch?
The survey shows broad interest in the plan but cannot show whether it keeps customers. A pilot in a few towns, compared with similar towns, would measure retention directly before the company commits.