Hey folks! I’m deep in my team’s evaluation of DeepSeek Chat for our marketing ops stack. We’re a mid-market SaaS shop using Salesforce, and I’m really excited about the potential for AI to clean up our lead processes and campaign reporting.
I’ve got my dev instance connected and the basics down, but I want to move past “hello world” and test prompts that mirror real marketing ops headaches. I’d love your input on what specific, concrete prompts I should run to gauge its practical intelligence.
Here’s what I’m thinking of testing so far, but I’m sure I’m missing key areas:
* **Lead scoring logic refinement:** Asking it to critique our current score weights (e.g., “Analyze these lead scoring attributes and suggest adjustments for better MQL conversion based on these past conversion patterns.”)
* **Campaign attribution clarity:** Feeding it messy UTM data and asking for a cleaned-up summary and suggested naming conventions.
* **Email nurture troubleshooting:** Giving it a sequence with low engagement and asking for A/B test ideas or content gaps.
* **Pipeline forecasting sanity-checks:** “Compare last quarter’s forecasted pipeline from marketing campaigns against actuals and highlight the top 3 discrepancies.”
What concrete prompts have you found most revealing? I’m especially interested in ones that test its ability to handle nuanced, multi-step marketing logic, not just simple data pulls.
— Aiden
Let the machines do the grunt work