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Client Relations Team metrics and KPIs

What are Client Relations Team metrics?

Identifying the optimal Client Relations Team metrics can be challenging, especially when everyday tasks consume your time. To help you, we've assembled a list of examples to ignite your creativity.

Feel free to copy these examples into your favorite application, or leverage Tability to maintain accountability.

Find Client Relations Team metrics with AI

While we have some examples available, it's likely that you'll have specific scenarios that aren't covered here. You can use our free AI metrics generator below to generate your own strategies.

Examples of Client Relations Team metrics and KPIs

Metrics for Improving matching for counselling

  • 1. Match Success Rate

    The percentage of successful matches between clients and counsellors based on gender, strengths, and client challenges.

    What good looks like for this metric: 70% - 80%

    Ideas to improve this metric
    • Conduct regular surveys to collect feedback on match success
    • Analyse client profiles to better understand their needs
    • Evaluate counsellor performance to identify strong areas
    • Use data analytics to build predictive match models
    • Implement continuous training for counsellors

  • 2. Client Satisfaction Score

    Measures the average satisfaction of clients post-session using a standardised satisfaction survey.

    What good looks like for this metric: 80% satisfaction score

    Ideas to improve this metric
    • Regularly update the satisfaction survey based on feedback
    • Ensure timely follow-ups with clients post-session
    • Adapt counselling sessions based on client feedback
    • Develop a robust grievance redressal mechanism
    • Provide incentives for high client satisfaction

  • 3. Counsellor Specialisation Match

    The percentage of matches where counsellor's specialisation aligns with the client's primary challenges.

    What good looks like for this metric: 60% - 75%

    Ideas to improve this metric
    • Regular updates of counsellor specialisation areas
    • Conduct in-depth client assessments pre-assignment
    • Invest in counsellor continuing education programs
    • Offer counsellor-specific challenge training
    • Use AI to match based on specific skill sets

  • 4. Gender Match Compatibility

    Evaluates how often client's gender preferences match the counsellor's gender.

    What good looks like for this metric: 75% match success

    Ideas to improve this metric
    • Collect more detailed data on gender preferences
    • Ensure diversity in counsellor hiring practices
    • Implement flexible scheduling for increased availability
    • Match using gender preference as a priority factor
    • Regularly review and fine-tune matching algorithms

  • 5. Prevalent Challenge Resolution Rate

    Defines the resolution rate of the most frequent challenges clients face during counselling sessions.

    What good looks like for this metric: 65% - 80%

    Ideas to improve this metric
    • Implement targeted training for counsellors on prevalent challenges
    • Regularly review practice strategies for most common challenges
    • Offer workshops focusing on prevalent client issues
    • Monitor and improve knowledge database specific to frequent challenges
    • Seek client input on challenge resolution strategies
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Implement these metrics

Tracking your Client Relations Team metrics

Having a plan is one thing, sticking to it is another.

Don't fall into the set-and-forget trap. It is important to adopt a weekly check-in process to keep your strategy agile – otherwise this is nothing more than a reporting exercise.

A tool like Tability can also help you by combining AI and goal-setting to keep you on track.

Tability Insights DashboardTability's check-ins will save you hours and increase transparency

More metrics recently published

We have more examples to help you below.

Planning resources

OKRs are a great way to translate strategies into measurable goals. Here are a list of resources to help you adopt the OKR framework:

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