By Tom Swanson, Engagement Manager at Heinz Marketing
Last time we found out that ChatGPT struggles to make a visualized workflow. Today we are digging into whether or not ChatGPT can optimize a workflow based on qualitative data. Enjoy the video below!
Initial Findings:
- ChatGPT can create workflows from scratch but results may be suboptimal.
- Existing workflows ranged from acceptable to chaotic; aim is to optimize.
Challenges in Workflow Optimization:
- Workflow simplicity is key, but bespoke workflows tailored to teams are essential.
- Qualitative issues arise (e.g., MLT strategy, production constraints, sales discrepancies) affecting workflow efficacy.
Gathering and Analyzing Data:
- Qualitative data collection methods include surveys, post-mortems, and note logging.
- ChatGPT excels in analyzing qualitative data at scale, simplifying data cleaning processes.
Workflow Optimization Process:
- Data preparation involves context-setting and removal of extraneous details.
- ChatGPT queried for insights on issues in interviews, visualized results (e.g., word clouds, team-specific challenges).
Actionable Insights:
- Recommendations generated based on real team feedback, enabling prioritization and project sequencing.
- Notable recommendations include project management improvements and communication channel enhancements.
Conclusion and Next Steps:
- ChatGPT aids in identifying workflow optimizations but lacks execution capability.
- Additional applications include analyzing sales data trends for actionable insights.
Reach out for a free brainstorm call!
The post Can ChatGPT Optimize a Marketing Orchestration Workflow? appeared first on Heinz Marketing.
