Identify Unused Features & Send Education Ai Agent Workflow Blueprint

Retention Stage Customer Success Agent
Identifies valuable but unused product features, determines relevance to specific customers, and sends targeted educational content to drive adoption.

Who this Ai Workfow Is For

Go-To-Market Pros

You care about improving the entire lifecycle of buyer and customer journeys. And you want inspiration for areas where Ai may help.

Ai Builders

You want inspiration for real-world ways to help people as you're building your Ai product.

Pros Focused on the Retention Stage

You're focused on the Retention stage in your daily job and want to find ways for Ai to help you do more with less.

How this Ai Workflow Helps

This workflow is designed for product and customer success teams who want to increase feature adoption across their customer base. By identifying underutilized features that could provide value to specific customers, teams can deliver targeted educational outreach that highlights relevant benefits and increases product stickiness.

The process begins by analyzing each customer's product usage data to identify which significant features they haven't adopted yet. An AI then evaluates whether these unused features align with the customer's goals, industry, or use case to ensure relevance before any outreach occurs. This intelligent filtering prevents customers from receiving irrelevant feature suggestions that might feel like generic upselling.

When a valuable, unused feature is identified for a customer, the workflow uses AI to craft a personalized educational message. This message explains the feature's specific benefits for their situation, provides clear instructions or a tutorial link, and encourages adoption. After sending the message via the appropriate channel (email or in-app), usage is tracked to measure effectiveness and potentially trigger follow-up communication if needed.

Ai Workflow Example as Inspiration for More

Does this AI agent workflow rely too much on AI and not enough on human know-how? Or the reverse? Is it missing steps or tools?

Note that this Ai workflow is presented as inspiration for what's possible. Adjust the amount, type and quality of the data inputs. Adjust how much or how little your human team mates (or you), AI and fully autonomous agents contribute.

And test it! Learn what works and what doesn't.

Don't forget! In the end, it's not just about efficiency. It's about delivering great experiences for your customers and customers-to-be.

1. Trigger: Schedule Feature Adoption Scan
Trigger. Initiate the feature adoption scan on a regular schedule (monthly or quarterly) to identify opportunities across the customer base.
2. Review Feature Usage
Tool Call. Review each customer's usage to see which major features they are not using that could benefit them.
Data
Analytics Google Analytics Mixpanel Custom API
3. Assess Feature Relevance
LLM Call. Have an AI assess if the unused feature is relevant to the customer's profile.
Report
LLM OpenAI Anthropic Google Gemini
4. Compose Educational Message
LLM Call. Use GPT-4 to compose a personalized message explaining the value of that feature and include a short guide or video link.
Email
LLM OpenAI Anthropic Google Gemini
5. Dispatch Feature Message
Tool Call. Send the message via email or in-app notification and track if the feature starts being used.
Email
Email Automation SendGrid Mailchimp HubSpot

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