If there is one superpower we would love to pick for every support manager, it would be the ability to tell the future.
Seeing even four months ahead would definitely help predict every team’s hiring and scheduling needs. We’d all go from having a saturation of tickets with nobody to handle them to having everything solved smoothly.
Getting a crystal ball ain’t easy — but here’s what customer service forecasting can help you with.
What is customer service forecasting?
Customer service forecasting is the practice of predicting future customer service demand using historical data, trends, and statistical analysis.
Instead of vague answers like “Ask again later” or “Outlook not so good,” we’re talking actionable forecasts and insights about future call volumes, staffing needs, and more.
Why is it important?
With accurately forecasted volumes, you can guess when you’ll be busy and make sure you have enough staff to keep wait times short. It helps you plan your team, use your resources wisely, and make sure your customer service folks are always ready to give great service.
Forecasting can also help with budgeting. If you think you’ll have a lot of demand, you might need to put more money into your customer service department to handle it.
But here’s the kicker: without accurate forecasting, you’re basically sailing in the dark. You might have too few staff during a rush (cue the disgruntled customers) or too many during a quiet period (hello, wasted resources). Accurate forecasting keeps you right on course and helps you predict the number of agents needed at all times — even during stormy business weather.
4 metrics to forecast your future support needs
Though we don’t have any magic way to uncover the future for you, we have collected 4 customer service metrics that can help you predict your future support needs both in hiring and tooling.
These are the 4 metrics that you can use to take a glimpse into what your team’s future might hold:
- Contact Ratio;
- Net Promoter Score (NPS);
- Customer Effort Score;
- Churn (and its partner, Retention).
Let us bring you closer to the crystal ball.
Contact Ratio is the number of conversations that you receive divided by the number of active/paid users that you have at that time.
Contact Ratio = Number of conversations / Number of active users
It’s a great indicator of whether your product is growing in complexity, and, thus, prompting more tickets, or becoming easier and more straightforward to use. It’s also a great indicator of the effectiveness of your self-service, ticket volume trends, and your team’s proactive support.
This is a whole company metric because the product, product marketing, and support teams all have an impact on how many tickets your team has to handle in the end.
How does Contact Ratio help predict the future?
As you grow larger, your Contact Ratio should get lower or remain the same. If your contact ratio starts to increase, it shows that your support conversations are growing faster than your user base. This is not good for a company’s growth.
Pay attention to your Contact Ratio, and use it as a guiding light across teams to see what could be changed. For example, solving a simple issue in the product could decrease the number of tickets in your inbox.
Net Promoter Score (NPS)
While Customer Satisfaction Score (CSAT) is a transactional metric asked after a specific interaction, NPS is a more holistic metric designed to measure the overall customer experience with your company.
NPS, or Net Promoter Score, revolves around the question: On a scale of 0-10, how likely are you to recommend our product/service to a friend or colleague?
Based on the responses, customers are categorized into three groups: Promoters (9-10), Passives (7-8), and Detractors (0-6). The Net Promoter Score is then calculated by subtracting the percentage of Detractors from the percentage of Promoters.
The resulting number ranges from -100 to 100, with a higher score indicating a higher likelihood of customer recommendation.
NPS % = ([Number of Promoters – Number of Detractors] / Number of total responses) x 100
Even though NPS is traditionally used as a metric for Product or Marketing teams, support has an impact on this number, as well. It’s a great way to align teams towards a common goal: the customer.
However, NPS only tells half of the story. Keep in mind that customers see things from their perspective. They don’t have inside information on what the expected or designed experience is from the company’s perspective.
How does NPS help predict the future?
As your company grows, you will find various ways how to target your NPS and experiment with different audiences. Pay attention to how your NPS reacts when you make product changes, introduce new features, or change the way you handle support.
As you find patterns in customer behavior, you can predict what you should (or shouldn’t) do with your support team and product.
For example, if you notice that people really love it when you improve your product or add new features, then your product team could put additional effort there. If your NPS sky-rocketed when you enabled chat support for paying customers, you should think about introducing it to all customers.
Customer Effort Score (CES)
Your company’s customer effort score indicates how much work your customers have to put in to get a resolution to their support inquiry.
Much like customer satisfaction, customer effort is measured by sending a survey after a conversation has finished.
By measuring how much effort customers need to put in to get their issues resolved, you can find out if your support is hitting the mark.
CES % = (Total sum of responses / Number of responses) x 100
Customers should not have to feel like they’re pulling teeth to get their problems resolved. If they do, it probably indicates a larger issue with your product, tooling, or the way you support them.
How does CES help predict the future?
You can use your indicators of high or low effort as a means to predict customer behavior, loyalty, and churn. Start by segmenting your customer base or questions to see which parts of your product or user experience are consistently ranked as high effort.
Once you’ve identified the bottlenecks, shift your focus to those areas. Provide a better user experience to increase customer loyalty, and decrease the number of tickets that you get as you grow.
Churn & retention
Customer churn rate is the percentage of your customers or subscribers who cancel or don’t renew their subscriptions during any given time period.
According to Hubspot, the best way to calculate churn is to designate a time period and tally up the total number of customers you acquired and the number of customers who churned during that time period. Then, divide the number of customers who churned by the total number of customers acquired, and multiply it by 100.
Churn Rate % = (Churned customers/Acquired customers) x 100
You can also calculate the Retention Rate — the number of customers who continue to engage with your company and remain loyal over a specific period:
Retention Rate % = ([Customers at the end of the period – New customers]/Customers at the beginning of the period) x 100
How do Churn & Retention help predict the future?
As you grow larger, both churn and retention become key indicators of the activities that had an impact on your customer base and, subsequently, on support.
For example, if you remove a feature, or change pricing, you might notice an increase in churn. More unhappy customers mean more tickets in the inbox.
Just like with NPS, you can use churn and retention patterns to understand when your volume may spike or dip. This way you’ll know to organize staffing accordingly.
If you make a product change or build something that people have been asking for, this will boost retention. You’ll have more customers to support and you should forecast future staffing based on that growth.
How to build a customer service forecast, then?
Have you been tracking the above-mentioned metrics for a while? Building a customer service forecast might seem daunting, but with these steps, you’ll have your forecast up and running in no time:
- Collect historical data: Start with gathering data from past months or years. This step is all about collecting as much information as possible to be able to identify trends and patterns.
- Identify patterns and trends: Look for peaks and valleys in your data. Do you see more calls during the holiday season? Is there a spike in email, live chat, or call support requests after launching a new product? Identifying these patterns helps you anticipate future needs.
- Consider business changes: Are you launching a new product soon? Planning a big marketing push? These business changes can impact customer service demand. Incorporate them into your forecast.
- Monitor and adjust: Your forecast isn’t set in stone. Regularly check how your predictions stack up against actual demand, and adjust your forecast as needed. This isn’t a “one-and-done” process; it’s a continuous loop of learning and improving!
Go forth and prosper!
Once you’ve built a forecast for your team, keep an eye on it as you move forward. This data serves as the heartbeat for your growth. When your numbers start to change, you will know how many agents or customer service tools you have to add to the mix.
Not every support team is built the same way, and growth will look different for everyone. Pay attention to the support metrics that make the most sense for your team. This way, your team will be ready for whatever comes at it, even without a crystal ball.
Originally published in January 2019, last updated in July 2023.