What is repeat contact rate and how do you rethink it in the age of AI?

Natalie Smithson
AI enthusiast | Tea addict | Focused on using AI assistants to win the working week

What is repeat contact rate?

Repeat contact rate measures the number of customers who contact you more than once about the same issue. This metric is crucial for understanding customer satisfaction levels and how effective your support services are. A high repeat contact rate can highlight issues with solving queries promptly on the first attempt.

How do you calculate repeat contact rate?

To calculate repeat contact rate, divide the number of customers who reach out multiple times for the same issue by the total number of unique customers who initiated inquiries initially:

(Number of customers with repeat contacts / Total unique customers) x 100

By tracking and analysing the repeat contact rate, you can identify patterns in customer behaviour and service quality. You can then make informed decisions about how to improve your team’s performance and the overall customer experience.

What is a good repeat contact rate benchmark?

A typical benchmark for the repeat contact rate is between 10% to 20%. This implies that about 80% to 90% of customer queries are successfully resolved on the first contact (first contact resolution). Maintaining a low repeat contact rate can lead to a higher customer satisfaction score and retention rate.

Rethinking repeat contact rate strategies to suit the age of AI

With human agents it can be difficult to work out where a problem lies if your repeat contact rate is high.

Is it that agents aren’t being trained appropriately to be able to help customers first time? Is information they have access to out of date? Or do customers first try to contact you at times you’re offline?

Bring an AI assistant into the mix and it’s far easier to work out where the problem lies. You’ll be able to consistently gather data from chat based conversation to transform your insights and find out why customers are having to get in touch with you more than once:

  • Find out straight away why customers are having to contact you a second time and use combined data across all channels to spot trends, say customers contact you to sign up for membership, but have to contact you again because your system is down and their confirmation doesn’t come through. You’re instantly alerted to the problem, so you can fix it.
  • If customers want to be transferred to a human agent, you can do this seamlessly using live chat. The best part is, your agent can see the chat based conversation so far, so will already know what the problem is. Not only will the customer not have to repeat themselves, you can also be sure to put them straight through to the right person or department.
  • Using API integration, you can link up your AI assistant with your go-to business system, so you can automatically log support tickets using a tool like Jira at any time of the day or night, ready for your teams to pick them up and start working on a resolution straight away.

Naturally, if your repeat contact rate is high, you’ll want to put a stop to customers having to get back in touch altogether. Using an AI assistant will help with this, since your support service gets faster and more accurate, plus runs 24 hours a day:

  • Instant answers to routine enquiries and continuous training to answer new ones
  • 24 hour service; your AI assistant never needs time off!
  • Once you’ve trained your AI assistant to give a response to a query, it will always send out the same reply (so long as you implement large language model (LLM) capability safely), unless you decide to change it.
  • One central store for all your customer data across all channels means you have a constant finger on the pulse of customer communications, so can nip any issues in the bud.

“The ability to take information directly from our site and present that to customers has delivered major change. I believe out of the huge range of customer digital transformation I have delivered that our AI assistant has been one of the best projects and has delivered consistently since being installed. Honestly, we couldn’t have chosen a better company or solution for our AI based chat system.” ~ John Branigan, Director of IT and Transformation for Mytime Active

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How can proactive communication strategies help reduce repeat contact rates?

Implementing proactive communication strategies such as automated follow-ups, status updates, and resolution notifications can help address customer issues promptly and prevent the need for repeat contacts. By keeping customers informed throughout your support process, you can improve transparency, manage expectations, and lower the likelihood of multiple interactions on the same issue.

What role does customer empowerment play in decreasing repeat contact rates?

Empowering customers with self-service tools like AI assistants, knowledge bases, and easy-to-access resources can significantly reduce repeat contact rates. By providing customers with the means to resolve common enquiries independently, you not only improve customer satisfaction but also decrease the need for repeated interactions, ultimately leading to more efficient and effective support experiences.

How can sentiment analysis enhance efforts to minimise repeat contact rates?

Using sentiment analysis tools to evaluate customer emotions and feedback can provide valuable insights into the underlying causes of repeat contacts. By understanding customer sentiment during interactions, you can identify areas of dissatisfaction, address issues promptly, and tailor responses to improve your overall satisfaction score (CSAT). Analysing sentiment data can help you proactively mitigate potential repeat contact triggers and enhance the quality of customer support interactions.

In what ways can data-driven strategies optimise the reduction of repeat contact rates?

Data-driven strategies offer you valuable insights to optimise processes and effectively reduce repeat contact rates. By analysing customer behaviour, and chatbot interactions data, you can see patterns, root causes of repeat contacts, and areas for improvement. Using data analytics means you can make informed decisions, tailor your support services, and implement targeted solutions that address customer needs efficiently, leading to a decrease in repeat contact rates.