Most business leaders would agree that customer experience data is a valuable source of information. The insights from it can be used to drive positive business outcomes like repeat purchases and increased brand loyalty. And yet, understanding which actions to take to realize those potential gains isn’t so straightforward.
Thankfully, you don’t have to guess when it comes to what will drive the biggest impact; the answer lies in the data. Combining your CX data with technology and best practices will allow you to narrow your focus on the CX improvements that will deliver the most effective results.
Gathering CX data
You can’t conduct an effective CX data analysis unless you actually have a reliable pool of data to pull from.
The first source of CX data should be your customers themselves via feedback surveys. According to a study by the global business research firm Gartner, customer feedback can increase the success rate of upselling and cross-selling efforts by 15 to 20% while decreasing customer retention costs by as much as 25%. Net promoter score (NPS) and customer satisfaction (CSAT) score are two useful types of customer feedback to actively gather and analyze.
Direct customer feedback is invaluable, but reviewing survey results is a time- and labor-intensive process. So, the next source of CX data you should be gathering is an automated one via speech analytics. With intelligent voice recognition and natural language processing, you can analyze 100% of your agent-customer interactions and score them for content and outcomes. Flag the most commonly used terms as well as your customers’ sentiment to get an aggregate picture of how your service stacks up.
Speech analytics is also useful for analyzing customers based on different criteria–their lifetime value, which products they own, and so forth. Analyzing customers in this way is important because it often provides more nuanced insights than looking at your customer base as a whole. The things that are important to high-ticket or repeat customers, for example, may be different than the things that matter to one-off buyers.
Finally, gather CX data from your owned channels, like your website. Record buyer behavior like clicks, time on site, support inquiries, and satisfaction ratings at key touchpoints in the customer journey. Some of these touchpoints include new inquiries, first-time website visitors, the point of sale, during onboarding, during service calls, and at the point of returns, cancellations, and renewals.
Analyzing CX data
To analyze CX data effectively, you need a platform that makes it easy to do so. An all-in-one contact center platform serves as a user-friendly CRM while providing robust reporting that’s easy to compile and understand.
Some of the most important CX metrics to consider when pulling reports are:
- Net promoter score
- CSAT score
- First response time
- First call resolution
- Average speed of answer
- Average handle time
- Average wait time
- Call abandonment rate
- Customer retention rate
- Customer lifetime value
There are countless more CX metrics you can measure and analyze; the ones that matter most to you will depend on your industry and your service goals. We dive deeper into our top 8 metrics for inbound contact centers here.
6 ways CX data analysis can deliver the biggest impact
If you’ve followed the above steps, you should be left with a hefty stockpile of CX data that’s ready to put to good use. Here are six ways to leverage it to make a speedy, measurable impact on service quality.
Use call volume data for more effective scheduling
From fluctuations in volume to agent availability to seasonality, the contact center industry has some of the most complex staffing considerations of any field. Put your vast reserve of CX data to use to schedule agents in the most effective way possible.
Use intelligent scheduling to incorporate call metrics, like average handle time and wait time, into your calculations along with call volume for highly precise staffing that alleviates long wait queues. Reducing wait times is a surefire way to make a meaningful positive impact on customer satisfaction.
Create self-service solutions for your most frequent issues
Earlier we touched on gleaning CX data with intelligent speech analytics. One important data point you can pull with this method is the nature of your customers’ calls.
Take a look at the top five to ten reasons customers contact you–chances are you’ll see a clear delineation between the most frequent and less frequent call topics. Then, assess whether you offer options that allow customers to self-resolve your top needs. If such options don’t yet exist, adding self-service channels like chatbots, virtual agents, IVR systems and an online resource library to address these topics can make an immediate impact in terms of service times and first-call resolutions.
Anticipate customer needs in advance
CX data analysis can shed light on the points in the buyer’s journey where customers are most likely to contact you, like immediately before and after making a purchase or at the one-year mark for subscription products.
Leverage this information to anticipate these calls before they occur and take proactive steps to address them. Some examples include an onboarding series that helps new customers get up and running smoothly, informational blog posts that explain new features and one-click renewal emails for subscription accounts that are almost ready to expire.
Pinpoint underperforming channels
Having a blended omnichannel approach means service interactions can take place seamlessly across multiple channels. If any of these channels aren’t up to par, however, it can contribute to call abandonment. Your customer experience analytics can tell you where these drop-offs are happening and why.
Your CX data analysis, for example, may reveal that SMS conversations have an unusually low customer satisfaction rate. Focusing your CX strategy to improve this channel–especially if it’s a popular one–can make a big difference in terms of both satisfaction and first call resolutions.
Identify top performers
CX data isn’t only for gaining insights on your customers. It’s a valuable source of information about your agents, too. Use it to identify top performers who are consistently getting high customer feedback scores or reaching great call benchmarks.
These are the agents who should be on the schedule during your busiest periods, but your data analysis might reveal that you have an all-star who’s stuck on the overnight shift. Use the insights to ensure that your most effective agents are front and center when customers need help most.
Create coaching materials
Use CX data analysis to zero in on customer interactions that were particularly effective. These types of interactions shouldn’t end when the agent hangs up the phone. Instead, they should live on as a training resource for other agents.
Use call recording to capture 100% of interactions in real-time, then revisit the best ones at a later date for coaching purposes. Screen recording allows you to get a full understanding of how your best performers resolve issues, which can provide invaluable direction to optimize your workflows for all agents.
Your CX strategy shouldn’t be left to chance. A data-driven approach will help you discover the greatest opportunities to make meaningful changes that will lead to more efficient service, shorter wait times, and ultimately, more satisfied customers.