“Those who fail to learn from history are doomed to repeat it.” Winston Churchill might have had a different meaning in mind when he uttered this famous sentence. Still, you’d be shocked how much this sentiment can apply to customer care operations—especially when considering how best to use call center data.

Naturally, customer care starts with engaging your customers. However, data analysis can help you understand how your business is perceived and performing and where you can improve. The correct data will tell you the following:

  • Where customers are most comfortable reaching out to you.
  • What communication channels your customers tend to avoid.
  • Where customers are converting to repeats or where prospects are converting to customers.
  • Where and how customers are upgrading their services and making purchases.
  • Why customers are unhappy, and what they’re doing about it.

Once you know how to find and collect it, data can become more valuable than gold. Since raw data is free of bias, it can provide objective insights when it’s organized. And when you mine that data for actionable intelligence, you can save time and money and propel your business forward, providing better care, services, and operations.

The Data Benefits of Omnichannel Support

The Data Benefits

Omnichannel support is a customer care strategy designed to engage with your customers on a variety of mediums. One invaluable benefit of implementing such a strategy is that the data you’ll collect can be a tool to foster memorable and seamless customer experiences, regardless of the channel it occurs on.

Capture the correct data, and you can improve your entire operation. Here are just a few examples:

  • Data from inbound phone support can tell you about common problems, questions, and concerns your customers might have that should be addressed. It can also provide unique information about the times people engage with you. 
  • Data from outbound phone support can provide insights into what types of messaging might be most effective for engaging prospective and current customers.
  • Data from SMS text messaging support can be used to determine customer response rates. This is especially true for businesses whose target audience skews younger, as they are far more likely to engage with brands via text.
  • Data from social media support can add a communal component to customer care, allowing you to crowdsource answers to potential concerns and issues. It can also be a way to mitigate problems that frustrated customers are trying to vocalize publicly.
  • Data from email support allows you to detect patterns that can be indicative of bigger product issues. It also allows you to test out different messaging styles and identify which is best for engaging with your audience for use in other parts of the business. 

Call center data pulled from a variety of channels can be beneficial in channel-agnostic ways. With the right data strategy, you can improve your customer care holistically and inevitably elevate your business.

From KPIs to Analytics in Driving Data-Based Customer Care Decision-Making

Working with call center data means understanding how to use quantitative information to set goals and measure progress toward those goals. Key Performance Indicators (KPIs) and data analytics provide the fundamentals for such efforts if it’s holistically collected and well organized.

Just the Basics: Key Performance Indicators (KPIs)

In call center marketing and communications, KPIs measure your organization’s performance. These indicators might include:

  • Customer Satisfaction Score.
  • Net Promoter Score.
  • First-Call Resolution Rate.
  • Total Ticket Resolution Rate.
  • Call Abandonment Rate.
  • Average Ticket Handle Time.
  • Customer Churn Rate.
  • Retention Data
  • And more.

Using KPIs, you can set call center goals and connect those goals to more significant organizational performance. Find the right metrics to track, and you can evaluate every aspect of your call center operations.

Just the Basics: Call Center Analytics

Call center analytics are how you collect and interpret the data that feeds into your KPIs. The four types of analytics you can use to track your metrics include:

  • Descriptive analytics refers to historical data that can identify trends and customer preferences—for example, gaining insights by looking at the last three months of call center operations data.
  • Diagnostic analytics, which digs deeper into descriptive analytics to drive new conclusions. For example, by combining First-Call Resolution and Net Promoter Score data, you can gain insights into overall customer satisfaction, even if you don’t track customer satisfaction as a separate metric.
  • Predictive analytics uses historical data and trends to predict future results. Algorithms, statistical models, and machine learning can play a crucial role in helping to predict future customer preferences and behaviors.
  • Prescriptive analytics leads to a specific recommended outcome based on predictive analytics. For example, anticipation of future customer preferences may lead to a recommendation to invest more heavily in one of your customer care channels in the future.

Each of these types of analytics can make the data from your call center operations more meaningful. Connect them to your metrics, and you’ll be on your way toward leveraging that data for meaningful operational insights, change, and improvements.

Millennial Services can help your business with this process by determining which metrics to focus on and how to interpret the data. 

How to Capture Call Center Data Across Channels

How to Capture Call Center Data Across Channels
Leveraging your contact center data can only work if you have reliable inputs that feed into your analytics dashboards, models, and processes. Some of the most common ways to collect customer data related to your call center include event tracking, customer surveys, and speech and text analytics while not overlooking general agent feedback, which is invaluable.

Setting Up Events to Track Behavior

Your analytics suite should have events that indicate the type of engagement you see, especially for digital interactions. Examples of these types of events include:

  • Digital product usage analytics.
  • Engagement with your website’s knowledge and help section.
  • Clicks on relevant contact information for your support channels.

These analytics will allow you to better understand your users in terms of how they use your product and its features and where they reach out for help. Improving your understanding of customers, in turn, will allow you to create a better support system that meets your customers where and when they’re most likely to need assistance.

Sending Customer Surveys to Collect User Feedback

Listening to your customers also involves ensuring they can voice their opinions about the products you sell and the level of support you offer. 

The most common example of this method is the Net Promoter Survey. This Survey asks a straightforward question: on a scale of 1 to 10, how likely are your customers to recommend your product? Some businesses also include a follow-up qualitative question asking the customer to explain their response. Analyzing the data elicited through this type of process helps you understand customer loyalty, improvement opportunities, and upsell possibilities. If your customers take the time to provide feedback, you have a duty to assess it. 

Of course, this is one of many survey types you could send to your customers. Follow-up satisfaction surveys, sent after a customer care engagement event, can provide valuable feedback about your call center operations and approach. With the right tool, it’s simple to implement a CSAT or similar followup process. 

Tracking Speech and Text Analytics for Support Calls

Finally, technology has increasingly allowed call centers to draw quantitative insights from written and spoken customer interactions.

Speech analytics, for example, leverages machine learning to analyze the words used in spoken conversations with your agents. You can analyze key phrases and words your customers use to understand sentiments and common issues without manual effort. The same method works for written texts, emails, or social media interactions.

Leveraging CCaaS to Capture Call Center Data Across Channels

There are numerous ways to gather analytics for your call center. Using your Contact Center as a Service (CCaaS) software capability set is the best place to start.

CCaaS solutions have a unique advantage thanks to their comprehensive integration across customer care channels, which enables them to track data effectively across multiple methods of communication. Using a CCaaS solution, you can see areas where customer behaviors mirror patterns or are diverse across various channels, leading to an analysis of influential trends.

CCaaS-based analytics save valuable time, consolidate management support, and offer a consistent channel experience. They also grant decision-makers the necessary traction to glean deeper insights by harmonizing data across call center operations.

Disclaimer: Millennial Services is certified through Zendesk for CCaS capabilities. However, our partnerships are software-agnostic, and plenty of other CCaaS solutions also offer robust analytics capabilities. Rather than switching, start this process by looking into your existing tool’s analytics capabilities for effective data tracking and determining where the gaps are.  

You have the Data. It’s Time to Leverage It.

Regardless of how it’s collected, the effectiveness of your data depends entirely on how you choose to use it.

Anytime you have large data sets, you must do a few things to maximize its benefits. If you work with a call center provider, ask them if they can partner with you or take these steps on your behalf.

  1. Define your objectives. Any data-based effort must begin with knowing what information you seek. You should start by defining what KPIs you want to track and how those KPIs connect to your larger business goals.
  2. Elevate relevant questions. What answers does your data need to provide? Are you looking to track customer satisfaction, speed, efficiency in call resolution, or something else? The sooner you prioritize relevant answers for your call center, the better.
  3. Clean your data. Raw data is nearly always cumbersome, partly because of its volume and because it can lead to inconsistencies. Keep your data focused and clean enough to ensure its accuracy and relevance. An experienced call center provider will have plenty of experience with this process and can save you valuable time.
  4. Interpret your data. This is where data turns into analytics. Again, an experienced call center provider who knows the areas you want to optimize based on your business model can help you get the insights you need.
  5. Visualize your findings. You’ll often need to put data in front of people who may not understand it in its raw form. Effective data visualization and communication can help you convey your findings and insights to all stakeholders.
  6. Develop an action plan. Finally, your insights and visualization should include an action plan for improving KPIs. That plan should consist of not just action steps but also regular intervals at which analytics should measure whether or not these steps are beginning to make an impact.

From there, it’s time to start executing your action plan. Over time, this can lead to an iterative approach prioritizing continuous improvement as you leverage quantitative call center information to optimize your operations.

Getting Started on Call Center Data With Millennial Services

If you use it correctly, call center analytics can transform operations. Every channel you use to interact with customers has the potential to bring data insights that can drive your KPIs and feed your analytics.

Data-driven improvements in customer care are well worth the effort and disruption they might require. Used correctly, they can be the driving force behind making your business more attractive to your current customers and target audience.

But you have to get it right. That means finding effective and efficient ways to capture the correct data and then leveraging that data in the right way to drive meaningful action across your call center and business.

To get there, you’ll need to identify which business goals the data being analyzed will drive. You’ll also need to build consensus, both within your team and with all relevant stakeholders, on how to attack data collection and explore it in ways that benefit the entire business.

Thankfully, you don’t have to walk this road alone. You should have a partner who’s equally well-versed in call center analytics and industry trends. Contact Millennial Services and learn how a partnership with us can help you reach your goals and leverage analytics and KPIs for lasting, meaningful change and improvement across your call center.