Assessing opportunities for AI in support

Identify areas in your support operations where AI can drive improvements.

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Develop an AI strategy for customer support

Welcome to the second tutorial in this course. Having introduced the basics of using AI in customer support, we'll now focus on identifying where AI can make a significant impact within your support operations.

Points we’ll cover:

  • Analyzing your entire customer support workflow
  • Spotting bottlenecks and inefficiencies
  • Identifying tasks most suitable to be done by AI
  • Exercise: Identify opportunities for AI in your own operations
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Understanding your current processes

Before integrating any AI, it's crucial to have a thorough understanding of your existing customer support processes. This involves analyzing each step from initial customer contact to issue resolution.

Map out your entire customer support workflow, making sure you evaluate these areas:

  1. Customer inquiry handling: How do you receive and process customer inquiries?
  2. Response generation: What methods do you use to provide solutions to customer queries?
  3. Issue escalation: How do you escalate and handle complex issues?
  4. Feedback collection: How do you collect and use customer feedback?

Identifying inefficiencies

Diving a little deeper, now look for bottlenecks and repetitive tasks in your current processes. These are prime candidates for AI integration.

Try and identify areas that have:

  • High volumes of routine inquiries: If your team spends a significant amount of time answering basic questions, AI can automate these to free up human resources.
  • Inconsistent response quality: AI can standardize responses to maintain a high quality of support.
  • Delayed response times: AI can reduce wait times by providing instant responses to common questions.

Evaluating tasks suitable for AI

Not every task in customer support is right for AI. You specifically want to identify tasks that are repetitive, rule-based, and high-volume.

This includes tasks like:

  • FAQ automation: Automating responses to frequently asked questions.
  • Ticket routing: Using AI to categorize and route support tickets to the appropriate departments.
  • Data analysis: Employing AI to analyze customer data and generate insights for improving services.

✍️ Exercise: Identify opportunities for AI in your operations

Now that you've learned about assessing opportunities for AI in customer support, it's time to apply these concepts to your own support operations. Follow the steps below to create a visual map of your current workflow and identify potential areas for AI integration.

Steps:

  1. On a piece of paper or using a digital tool like a flowchart maker, create a diagram that outlines your current customer support workflow from start to finish. Include steps such as:
    • Receiving customer inquiries
    • Categorizing and prioritizing issues
    • Generating responses
    • Escalating complex problems
    • Collecting customer feedback
  2. Once you have your workflow mapped out, use a different color or symbol to mark any areas that you think could benefit from AI integration. Consider:
    • Steps that involve high volumes of routine inquiries
    • Tasks that are repetitive and rule-based
    • Areas where response quality or consistency could be improved
    • Bottlenecks or delays in the process
  3. For each potential AI opportunity you've identified, write down the specific task or problem AI could help with, and how you think AI could be applied (e.g., chatbots for FAQs, sentiment analysis for prioritizing issues).
  4. Finally, prioritize the AI opportunities you've identified based on their potential impact and feasibility. Consider factors such as the complexity of implementation, available resources, and alignment with your overall support goals.

Doing this activity should help you translate the theoretical concepts from this tutorial into practical applications tailored to your unique support environment. By visually mapping your workflow and identifying specific AI opportunities, you'll be better equipped to develop a targeted AI strategy in the next tutorial.

In the next tutorial, we will discuss how to build a comprehensive AI strategy that aligns with the opportunities you’ve identified in this lesson.

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