I ran Writer through a 30-day trial, focusing exclusively on generating B2B case study drafts. The goal was to evaluate its output quality and structure against a standardized brief. I used the same brief for all tests, only varying the hypothetical client company and industry.
The prompt structure was consistent:
```
Generate a B2B case study draft for [Client Company], a [Industry] company.
Use the following structure:
- Client Background
- The Challenge
- The Solution (implementing our product, [Product Name])
- Quantifiable Results
- Client Quote
Tone: Professional, data-driven. Avoid marketing fluff.
```
**Output Analysis:**
* **Structure Adherence:** Excellent. Writer followed the requested format precisely in every generation.
* **Tone Consistency:** Consistently professional. It rarely strayed into overly promotional language.
* **Content Depth:** Variable. The "Challenge" and "Solution" sections were logically sound but often generic. Output required significant fact-specific editing to feel authentic.
* **Quantifiable Results:** A notable weakness. While it included a "Quantifiable Results" section, the metrics were often vague or used placeholder text (e.g., "increased efficiency by a significant margin," "reduced costs substantially"). This required the most manual intervention.
**Example of a generated "Results" section needing edit:**
```
Quantifiable Results:
* Achieved improved operational workflow.
* Reduced time spent on manual processes.
* Enhanced team productivity and collaboration.
```
**Required edits to make it usable:**
* Replaced all vague metrics with specific, credible percentages and time frames.
* Added concrete before/after scenarios.
* Inserted real-world constraints mentioned in the brief that the AI had glossed over.
**Conclusion:** Writer functions as a strong structural template engine. It saves time on initial formatting and drafting a coherent narrative flow. However, for a convincing B2B case study, it cannot generate the specific, hard data points that are critical for credibility. The editor's role shifts from restructuring content to deep, detail-oriented fact injection and metric specification. It's a useful first-draft tool, but the "heavy lifting" of making the case study authoritative remains manual.
Numbers don't lie