Event Essentials Strategic Marketing Plan: : Marketing Options for Event Management Services & Software Providers in the COVID Digital Age
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Our objective was to detect feasible and effective strategic marketing options for our community partner Event Essentials (EE), an event management software provider operating out of California, U.S.A. These strategic marketing options were chosen based on market research, internal and external analyses, and the client’s needs that were presented to us. Along with the implementation of the strategic options, our team curated targeting, positioning, and communications strategies that would fit within the strategic marketing plan for optimal results. The market research we conducted initially consisted of both secondary and primary data sources. After our initial proposal, our team decided to weigh the value of our primary data more heavily when evaluating the proposed strategic options. This data was richer and better suited the client’s issue(s). We obtained the primary data in interviews with a convenience sample of potential clients in the target industries. We believe that with the successful implementation of our strategic marketing plan and recommendations, Event Essentials will increase their brand awareness, reach, brand recognition, and new business development; Resulting in the sustained growth and success of their business throughout the COVID-19 era and beyond. Department: Business Faculty Mentor: Dr. Fernando Angulo-Ruiz
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it