Best Practices for Demand Forecasting in Contact Centers

What is call center forecasting?

Call center forecasting is the process of using data and analytical methods to predict future call volumes, customer inquiries, and staffing needs over time. By analyzing historical data, seasonal trends, marketing activities, and external factors, businesses can anticipate when and how customers will seek support so they can plan ahead of time to meet those needs.

When customers reach out to a contact center, they need help promptly. But when call centers are understaffed or have above-average call volumes, it becomes challenging to meet those demands — and unfortunately, 64% of consumers say they would never shop with a retailer again if they faced long wait times that made them abandon a customer service conversation. For contact centers and agents, this situation can contribute to burnout, lost profits, and reputational damage, and for customers, it’s simply a frustrating experience.

The purpose of call center volume forecasting is to optimize staffing levels, reduce wait times, and deliver exceptional customer experiences while managing costs. Forecasting is a foundational strategy for contact centers to balance customer satisfaction with operational efficiency.

Why demand forecasting in contact centers is crucial

At its core, the purpose of a contact center is to ensure customers’ happiness by resolving their issues promptly and effectively. Every interaction is a chance to build loyalty, trust, and a positive brand image. However, even the most well-intentioned teams can fall short of customer expectations without the right resources at the right time.

This is where contact center demand planning becomes a game-changer. By accurately forecasting call volumes and customer needs, contact centers can proactively align staffing, technology, and processes to deliver a seamless experience. Forecasting transforms the challenge of unpredictability into an opportunity for proactive support and makes managing customer happiness easier and far more successful.

Here are some immediate benefits of demand forecasting:

• Reduced wait times: Customers hate waiting for help, and long hold times can damage brand loyalty. Accurate forecasts help contact centers anticipate demand surges and assign the right number of agents at the right times to minimize delays and frustration.
• Improved customer experience: When you have the staff in place to keep up with demand, your contact center can meet customer needs more effectively and offer customized support, which can enhance satisfaction and trust.
• Better agent productivity: Predicting demand prevents agents from being overwhelmed and underutilized. When you don’t overburden your agents, they’ll have a better work-life balance and a healthier mindset to perform their best.
• Effective cost management: As a contact center, your staffing comprises around 70% of your total costs. Forecasting helps you allocate resources where needed most to reduce overstaffing and understaffing and control costs.

Key factors in call center demand forecasting

Effective demand forecasting in contact centers relies on several key elements that help businesses accurately predict call volumes and resource needs. Let’s look at some critical components and how they work together to optimize staffing and the customer experience.

Historical data analysis

Historical data is the foundation of effective call center demand forecasting. By analyzing past call volumes, interaction types, and resolution times, contact centers can identify patterns that reveal how demand fluctuates over time. These patterns often align with recurring factors such as time of day, day of the week, seasonal trends, or specific business activities.

For example, historical data may show a consistent surge in calls during the holiday shopping season or immediately following a new product launch. Recognizing these patterns can help business decision-makers anticipate and plan for similar demand spikes.

Seasonal variations

Seasonal factors like holidays, promotions, and trends significantly influence call volumes in contact centers. For instance, Black Friday and Christmas often lead to surges in customer inquiries about orders, returns, or support, while seasonal trends like back-to-school shopping or tax season drive predictable increases in activity for specific industries. Promotions and product launches also generate spikes in calls as customers seek information, troubleshoot issues, or capitalize on deals.

Accurate seasonal call volume forecasting enables contact centers to optimize staffing, ensure agents are equipped for specific inquiries, and maintain service levels during peak periods to enhance the customer experience.

Marketing and business initiatives

New product launches, marketing campaigns, and changes in business operations can all cause significant shifts in call center demand. When a company introduces a new product or service, customers often seek information, purchase assistance, or troubleshooting support. Marketing campaigns, especially those that include promotions or special offers, can generate heightened interest and drive more customers to reach out for clarifications, order status, or technical help.

Similarly, changes in business operations, such as introducing new policies, adjusting prices, or updating services, can create confusion or prompt customers to contact the support center for clarification or assistance. Understanding how these factors influence demand allows businesses to proactively plan for increased contact volumes and ensure their contact center is adequately staffed to handle the influx, improving efficiency and customer satisfaction.

External factors

External factors like economic changes or global events can greatly impact call center demand. Economic downturns or financial instability often increase customer inquiries as people seek assistance with billing, payment options, or financial products. On the other hand, when the economy is growing, customers might begin to have more questions about new opportunities, products, or services.

Natural disasters, pandemics, or geopolitical shifts can also create sudden spikes in call volumes. A global health crisis like COVID-19 may increase customer concerns regarding health-related services, changes in business operations, or safety measures. These external factors can cause unexpected demand surges, forcing businesses to adapt their forecasting models to account for these variables and maintain service levels during turbulent times.

Different methods for demand forecasting in contact centers

Companies may use various methods when forecasting call center demand. The best technique for your call center depends primarily on the data you have available as well as the level of accuracy you need to have.

Time-series analysis

Time-series analysis uses historical data and math to predict future call volumes. This method includes techniques like:

• Moving averages: Highlights overarching trends by smoothing fluctuations.
• Exponential smoothing: Weighs recent data more heavily for better accuracy.
• ARIMA models: Combines historical trends and seasonal patterns for robust predictions.

Regression models

Regression models identify relationships between call volume and other variables, such as marketing campaigns, seasonal events, or external factors. This approach helps businesses make data-driven staffing decisions.

Machine learning-based approaches

Machine learning improves the accuracy of forecasting by analyzing multiple variables simultaneously, including:

• Call volume
• Seasonality
• Promotions
• External factors like weather

Unlike traditional methods, machine learning continuously learns from data patterns over time and adapts to changes to improve predictions. This helps call centers anticipate demand more accurately and allocate resources most effectively to improve customer service.

Hybrid models

Hybrid models combine forecasting techniques, such as machine learning and time-series analysis. This model is particularly effective for larger call centers with diverse variables influencing demand.

Which method is right for your company?

Ultimately, the best forecasting method for your business comes down to these factors:

• Call volume variability: More variability may require machine learning or hybrid models.
• Company size: Smaller businesses may prefer simpler time-series methods, while large operations benefit from advanced tools.
• Available resources: Ensure your team has the expertise to leverage complex models or tools effectively.

The right technique is one that balances accuracy with practicality and aligns with your operational goals and resource capabilities.

Steps to forecasting demand in a contact center

Whether you’re just starting or refining your approach, following a structured process can lead to better outcomes for your business and customers. Here are a few simple steps to help you get started with contact center demand planning.

Step 1: Gather and analyze data

Reliable data is the foundation of any accurate forecast. Collecting data from key sources like your customer relationship management (CRM) system and workforce management software will provide valuable insights into past call volumes, peak periods, and customer behavior patterns. As you analyze historical data, you can start identifying trends that will inform your future staffing needs and prepare you for high-demand periods.

Step 2: Choose the right forecasting model

There are several forecasting models available, each suited to different types of contact centers. For example, you might use a simple time-series model for predicting call volume based on past data or a more complex machine-learning model that accounts for certain variables.

The key is to select a model that matches your contact center’s size, complexity, and business needs. Choosing the right model will help you accurately predict demand and avoid over- or understaffing.

Step 3: Implement forecasting tools

Once you’ve selected a forecasting model, it’s time to implement the right tools. NICE, Verint, and Calabrio, for example, are commonly used in contact centers to help with real-time forecasting and workforce management. These tools can integrate with your existing systems, provide insights into demand patterns, and help you make data-driven staffing decisions. Such tools can help you automate the process and update forecasts in real time.

Step 4: Test and adjust forecasts regularly

Forecasting isn’t a “once and done” type of task. Business needs and customer behavior can change constantly, so it’s important to regularly review and adjust your forecasts. You should test different models, measure their accuracy, and fine-tune them as necessary. As you adjust your approach based on new data, you’ll be better prepared to stay ahead of changes and keep your contact center operating smoothly despite demand fluctuations.

Customizing your forecasting approach

Every contact center has unique goals. Whether you aim to minimize wait times, optimize staffing costs, or improve service quality, your forecasting approach should be tailored to meet those goals.

For instance, if minimizing wait times is a top priority, you might forecast more conservatively to always keep enough agents on hand. On the other hand, if cost optimization is your focus, you might adjust your forecast to minimize staffing during low-demand periods.

Consulting with experts or using software

While forecasting tools and models are beneficial, there may be times when it’s worth consulting with experts or using specialized software to refine your forecasting strategy. If you’re dealing with complex demand patterns, seasonal fluctuations, or other challenges, a consultant or advanced forecasting software can provide additional insights and help you optimize your approach.

Common challenges in contact center demand forecasting

Accurate demand forecasting in a contact center can significantly improve service quality, customer satisfaction, and operational efficiency — but achieving precision is not without its challenges.

Data limitations and inaccuracy

One of the biggest hurdles in demand forecasting is relying on incomplete or inaccurate data. If your data sources don’t capture the full picture — such as seasonal trends, sudden shifts in customer behavior, or new product launches — your forecasts can quickly become unreliable. Outdated or poorly maintained data can also lead to overstaffing, understaffing, and missed service level agreements.

Dynamic customer behavior

Customer behavior is dynamic and hard to predict. A new marketing campaign, a product issue, or an unexpected external event can lead to sudden increases or decreases in call volumes. Traditional forecasting models often struggle to account for these unpredictable shifts, which makes it challenging to keep forecasts accurate.

Technology integration

Outdated systems or siloed data sources can severely limit your ability to create effective forecasts. If your contact center tools don’t communicate seamlessly — like workforce management software not integrating with CRM systems — you may lack a unified view of your data. This fragmentation makes it harder to spot trends and develop actionable insights for demand planning.

Best practices for accurate demand forecasting in contact centers

Overcoming the challenges of contact center demand forecasting requires a strategic approach. By applying the practices below, your contact center can refine its forecasting processes and improve accuracy, operations, and the customer experience.

Utilize predictive analytics

Modern forecasting tools powered by AI-driven predictive analytics can significantly improve accuracy. These tools analyze multiple data points — such as historical call patterns, customer demographics, and external factors like weather or economic conditions — to make more informed predictions. In the end, you’ll be empowered to anticipate demand effectively and reduce the risk of being caught off guard.

Collaborate across teams

Accurate forecasting requires input from various departments. Operations teams can provide insights on staffing and workflow, marketing can share campaign plans that may drive demand, and sales teams can alert you to product launches or promotions. When these groups work together, you’ll have a more thorough overall understanding of possible demand fluctuations.

Regularly update forecasts

Forecasting requires establishing a routine for reviewing and updating your forecasts with the latest data and feedback. Regular updates help you adapt to new trends, refine your models, and maintain accuracy as conditions change. Frequent reviews also make it easier to spot issues before they become problems.

Prepare for the unexpected

Flexibility is key to handling unforeseen demand spikes. Consider strategies like cross-training agents to handle different interactions or keeping a small pool of on-call staff to address unexpected surges and manage sudden changes without compromising service quality.

Demand forecasting tools and software for contact centers

According to a 2021 survey, approximately 50% of call centers still use manual forecasting methods, which accounts for reduced effectiveness and planning efficiency. Effective demand forecasting in contact centers requires the right automated tools to predict call volumes, optimize staffing, and improve customer experience.

Popular software solutions like these offer robust features tailored to workforce management and forecasting. Here’s an overview of common ones and what to consider when selecting the best one for your needs:

• Calabrio: Calabrio is known for its user-friendly interface, advanced analytics, and workforce optimization tools. It provides detailed insights into historical data and real-time operations that help contact centers create accurate forecasts while ensuring agent schedules align with anticipated demand.
• NICE: As a market leader in workforce management, NICE uses AI and machine learning to improve forecast precision. Its suite includes real-time forecasting, automated scheduling, and performance tracking, which makes it a top choice for large-scale operations.
• Genesys Cloud: This cloud-based platform integrates seamlessly with other contact center systems and offers tools for real-time analytics and AI-powered forecasting. Its scalability makes it ideal for businesses of all sizes, and its intuitive design reduces the learning curve for teams.

Key factors to consider when choosing a forecasting tool

The right contact center demand planning solution can boost accuracy while streamlining operations and improving overall customer satisfaction. Consider the following when choosing a forecasting tool:

• Scalability: Does the tool adapt to the size of your contact center and support future growth? Make sure the software can handle your current and projected call volumes without compromising performance.
• Ease of use: User-friendly tools reduce the time required for training and implementation. Search for easy-to-use interfaces and straightforward processes for generating reports or updating forecasts.
• Integration capabilities: Seamless integration with your existing CRM, workforce management, and analytics tools are critical. A well-integrated system ensures data flows smoothly to give you a complete view of operations.
• Customization: Each contact center has unique needs. Choose a tool that allows you to customize settings, reporting, and forecasting models to align with your goals, such as minimizing costs or improving service levels.
• Support and updates: Consider the vendor’s customer support quality and commitment to ongoing updates. Reliable support shortens the time to resolution, and regular updates keep your system equipped with the latest features.

How to get started with demand forecasting in contact centers

Getting started with accurate demand forecasting for your contact center may feel daunting, but with a few straightforward steps, you can lay the foundation for success. Here’s how you can get started.

• Collect reliable data: Start by gathering historical data from your CRM and workforce management systems. Complete, accurate data is essential for building solid forecasts.
• Choose a forecasting model: Begin with a basic model, such as time-series forecasting, to predict demand based on historical patterns. As you grow comfortable, explore more advanced techniques like AI-driven analytics.
• Utilize tools: Use software solutions like Calabrio or NICE to automate call center forecasting and scheduling. These tools simplify the process and provide actionable insights.
• Start small: Test your forecasting process on a specific period or campaign to gain confidence before scaling up.

Be sure to evaluate and update your models with new data regularly and seek agent feedback to pinpoint areas for improvement. Stay informed about new forecasting tools and methods, and adapt your approach as customer behavior and business needs evolve.

With a commitment to ongoing learning and refinement, your contact center can continuously improve forecast accuracy, optimize staffing, and enhance customer satisfaction.

Ready to take your demand forecasting to the next level? Get a quote today to explore the best tools and strategies for your business.