Your team sees opportunities you don't. Here's the full picture.
Multiple support tickets and sales calls mention the need for real-time webhooks for order status updates. This is blocking enterprise deals and causing workarounds.
Field workers at logistics companies can't access our platform on mobile browsers effectively. Native mobile app repeatedly mentioned as requirement.
Current dashboards don't meet compliance and audit requirements for enterprise customers. They're building their own reporting on top of our API.
Engineering analyzed past tickets - ML model could accurately categorize and route tickets, reducing manual triage time significantly.
Main competitor just launched native Slack integration with 2-click setup. Sales team reports it's coming up in 60% of competitive deals.
New competitor entered market with aggressive pricing. Sales seeing this in 8 recent deals. Quality is lower but price is attractive to SMBs.
Customer Success sees 40% drop-off in week 1 of trial. They have specific UX improvements based on customer calls that could help.
Small business customers are getting stuck during onboarding. Support is spending 3-4 hours per customer on setup calls that should be self-serve.
Teams want notifications and quick actions directly in Slack and Microsoft Teams. Current email notifications are being missed.
Deploy pipeline currently requires manual approval for all changes. ML model could auto-approve low-risk deployments based on test coverage and blast radius.
Chatbot could guide new customers through setup, answer common questions, and escalate only when needed. Reduce CS load significantly.
Competitor added AI insights to their dashboards - automatically surfaces trends and anomalies. Sales says enterprise customers are impressed.
Trade show feedback: customers want to build custom workflows. Competitors highlighting their API ecosystems. We need better developer experience.
Marketing team has interactive demo idea for blog posts - could boost trial signups. Needs engineering support to build embeddable widget.
ML model could analyze usage patterns to predict churn 30-60 days in advance, giving CS team time to intervene proactively.
Current demo environment doesn't showcase enterprise features well. Sales team wants realistic sample data for different industries.
Finance team manually reconciling revenue across systems. Integration with accounting system could save hours of work.
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