| Course | DBA-8050 Seminar in Marketing and Entrepreneurship |
|---|---|
| Module | Module 3 |
| Paper type | Briefing note: organizational interactions with customers |
| Length | About 824 words, 5 pages |
| Format | APA 7 student paper |
| School | Thomas Edison State University |
| Program | Doctor of Business Administration |
| Updated | October 2026 |
Free sample paper for DBA 8050 Module 3
Briefing Note: What Our Receipt Survey Can and Cannot Tell Us About Customers
Student Name
Doctor of Business Administration, Thomas Edison State University
DBA-8050: Seminar in Marketing and Entrepreneurship
Mentor Name
Month Day, Year
Briefing Note: What Our Receipt Survey Can and Cannot Tell Us About Customers
Purpose
This note appraises the customer survey we began in 2023 and asks whether it should keep guiding store decisions. The owners asked for a recommendation before next season's budget is set.
Background
Every receipt carries a code that invites the customer to answer an online survey. The first question asks how likely the customer is to recommend the store to a friend on a scale from 0 to 10, and the result is reported as a single score: the share of 9 and 10 answers minus the share of 0 to 6 answers. Two further questions ask what the customer bought and what could improve. In 2024 the five stores issued about 212,000 receipts and received about 8,500 responses, a response rate of 4 percent. Store managers' bonuses now include the score, and the Flemington store's fall from 61 to 48 in July triggered a staffing review.
What the Evidence Says About the Score
Reichheld (2003) introduced the would-recommend question and argued that it predicted growth better than longer satisfaction surveys in the industries he examined. The claim spread quickly because the measure is simple and easy to explain.
Later independent tests were less favorable. Keiningham et al. (2007) examined several years of customer data across industries, drawn largely from Norway, and found that the recommend score was no better a predictor of revenue growth than standard satisfaction measures such as the American Customer Satisfaction Index. Morgan and Rego (2006) compared several satisfaction and loyalty metrics across a large set of firms and found that average satisfaction and the share of very satisfied customers were useful predictors of business performance, while recommend-based measures added little. The research does not say the question is useless; it says that one number should not be trusted to carry decisions alone.
What the Method Says About Our Data
The score is only as good as the sample behind it. A 4 percent response rate does not by itself prove the data are biased. Groves (2006) showed that silence only distorts a survey when the reasons people answer are tied to what the survey asks about; the count of replies alone does not settle it. That is the risk here. Customers who had an unusually good or bad visit are more likely to use the code, and customers who buy one flat of annuals on a Saturday rush rarely do. Store differences also reflect who shops there: Flemington draws more first-time spring customers, who may answer differently from regulars elsewhere.
The July drop at Flemington illustrates the last two weaknesses. The store received 190 responses that month. With so few answers, a shift of thirteen points can arise from chance and from the mix of customers who chose to respond, so the staffing review may have reacted to noise.
| Feature of the survey | Strength | Weakness |
|---|---|---|
| Single recommend question | Simple, cheap, easy to track | Evidence that it predicts growth alone is mixed |
| Receipt code invitation | Reaches every buyer at no cost | Self-selected 4 percent may differ from the rest |
| Open comment question | Names specific problems | Comments cluster on extremes |
| Monthly store scores | Quick feedback to managers | Small monthly samples swing by chance |
| Bonus link | Draws attention to service | Rewards a noisy number and invites gaming |
Options
The first option is to keep the survey as it is. It costs nothing more, but decisions and bonuses would continue to rest on a number with mixed predictive evidence and an unknown bias.
The second option is to drop the survey. That would remove the noise but also the only regular channel for customer comment.
The third option is a mixed design. Keep the receipt survey for comments and add a short satisfaction question, since Morgan and Rego (2006) found satisfaction measures useful. Join the survey to loyalty card records, which show behavior for about 60 percent of sales: repeat visits, spending and the departments each customer uses. Add twelve short interviews with regular customers each July, when traffic is lower, to explain what the numbers cannot.
Recommendation
I recommend the third option for the 2025 season, at an estimated cost of 70 hours of staff time and a $3,000 interview budget. Store scores should be reported quarterly rather than monthly, with the number of responses shown beside each score, and they should leave the bonus formula until a full season shows whether they move with repeat visits. At the end of 2025 we would compare stores' survey results with their loyalty card behavior and keep the measures that track what customers actually do.
Conclusion
The receipt survey gives us a voice from customers, but the evidence on its single score and the self-selected sample behind it do not support using it alone for staffing or pay. A mixed design keeps the comments, adds behavior and conversation, and lets next year's data show which measures deserve the owners' trust.
References
Groves, R. M. (2006). Nonresponse rates and nonresponse bias in household surveys. Public Opinion Quarterly, 70(5), 646-675. https://doi.org/10.1093/poq/nfl033
Keiningham, T. L., Cooil, B., Andreassen, T. W., & Aksoy, L. (2007). A longitudinal examination of net promoter and firm revenue growth. Journal of Marketing, 71(3), 39-51. https://doi.org/10.1509/jmkg.71.3.039
Morgan, N. A., & Rego, L. L. (2006). The value of different customer satisfaction and loyalty metrics in predicting business performance. Marketing Science, 25(5), 426-439. https://doi.org/10.1287/mksc.1050.0180
Reichheld, F. F. (2003). The one number you need to grow. Harvard Business Review, 81(12), 46-54.
Reading the DBA 8050 Module 3 assignment instructions
Briefing notes are three of the graded pieces in DBA-8050, and the public syllabus leaves their timing to the course calendar, so this sample sits with the module on how firms deal with their customers. A briefing note is short and practical. It should tell senior readers what the issue is, what they need to know, what the research says, which options exist and what you recommend. In this module, the subject is a consumer-facing research or marketing practice, and the course objective asks you to appraise the techniques behind it, not only describe them. Choose a practice your organization really uses, explain how it collects data, judge it against peer-reviewed evidence and end with a decision the readers can make.
How the DBA 8050 Module 3 example is put together
The note follows the order owners expect: purpose, background, evidence, options and a recommendation. The background gives the survey's mechanics, its 4 percent response rate and the bonus link that raises the stakes. One section sets Reichheld's original claim against two independent tests of the score; another uses Groves to explain why a low rate matters only when response is tied to the experience being measured. A table weighs five features of the survey, and the July drop at one store, built on 190 answers, shows the cost of reading noise as fact. Three options lead to a costed mixed design, with quarterly reporting and the score kept out of pay for a season.
Reading the DBA 8050 Module 3 grading rubric
Mentors look for briefing notes that a busy executive could act on: a clear issue, enough background to follow the argument, evidence drawn from academic research, a fair comparison of options and a specific recommendation with cost and timing. In Module 3 the appraisal of method matters most, so notes that judge the sample, the measure and the way results are used score higher than notes that only report findings. Balanced treatment of a popular metric, giving its claim and its tests, shows critical reading. Concise writing earns marks in this format, so plain headings, short paragraphs and one table do more than long discussion. APA citations stay in place even in a brief.
DBA 8050 Module 3 help: mistakes that cost marks
The most frequent problem is a briefing note that reads like a short essay, with no options and no recommendation. Another is praising or condemning a metric on reputation rather than on evidence. A thin response rate is neither proof of bias nor safe to ignore; what matters is whether the customers who answer look different from the ones who stay silent. Include the numbers that matter, such as responses per store, and show what decisions currently rest on the data. Price your recommendation and say how you will know whether it worked. Send your DBA-8050 briefing note topic and a free first sample is drafted around your organization's own research practice.
Write yours, or have the desk draft it
This paper is an original model document written by our desk, not a submitted student paper and not an official Thomas Edison State University document. Read it for the moves, then write your own to the instructions in your classroom. If you want one built to your exact prompt and rubric, the first custom sample is free and arrives in 24 to 48 hours.
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DBA 8050 Module 3 questions, answered
Where can I find a free DBA 8050 Module 3 sample paper?
The briefing note above appraises a garden center chain's receipt survey and its would-recommend score for the owners.
How do you write a doctoral briefing note?
State the issue and purpose, give background, summarize the evidence, compare options and close with a recommendation readers can approve.
Does Net Promoter Score predict growth?
Reichheld argued it did, but independent tests by Keiningham and colleagues and by Morgan and Rego found it no better than satisfaction measures.
Does a low survey response rate mean the results are biased?
Not necessarily; Groves showed bias depends on whether the reasons for responding relate to what the survey measures.
How is DBA-8050 graded?
The briefing notes carry the largest share after the final paper, 25 percent, ahead of the article analyses at 20 and the forums at 15; live sessions add 10 and the final paper 30.