Customer service is at a crossroads. The convergence between humans and machines means that while businesses are trying to automate, people are craving human contact to resolve their customer service issues. Bridging the gap between these opposing forces means finding a happy medium between high tech and human touch. This is where customer analytics comes into play.

But first – an answer to the million dollar question: what is customer analytics?

According to IT research firm Gartner:

“Customer analytics is the use of data to understand the composition, needs and satisfaction of the customer… [It includes] the enabling technology used to segment buyers into groupings based on behavior, to determine general trends, or to develop targeted marketing and sales activities.”

Customer analytics includes both the data that you collect from customers to gauge satisfaction and sentiment, as well as the software that helps you analyze and make use of it. This can include:

  • Demographic data like age, gender, and location
  • Web data such as usage patterns, time on site, and page visits
  • Historical data such as purchase history.

Collecting this data on an individual customer level and as an aggregate gives you the tools to individually target customers as well as drive the overall strategy of your business.

In this article, I’ll outline why you need to start using customer analytics, how it works, and the different types of customer analytics that could be useful for your company.

Do you need customer analytics?

According to the 2016 American Customer Satisfaction Index (ACSI), customer satisfaction in the retail sector is at an all-time high; eCommerce spend is growing steadily, while companies such as Amazon, eBay, and Netflix are showing increases in their ACSI scores. Despite the high level of customer satisfaction, however, the picture isn’t completely rosy.

A 2016 customer service study conducted in the UK by NewVoiceMedia shows that, despite improving since 2013, customers are still leaving companies due to inadequate service at the cost of £11 billion a year. The biggest issues for customers include feeling unappreciated, dealing with unhelpful or rude staff, and being passed off onto multiple people.

Where does the disparity between increased satisfaction and problematic service lie? Speaking with customer service expert Shep Hyken over Skype, he explains that as the bar for customer service increases, so too do customers’ expectations.

“Customers’ expectations are getting higher. There are companies that are setting the expectations higher with amazing levels of customer service. They’re the Apples and the Amazons – you’ve got all kinds of great companies that set the bar really high. When customers receive a great experience from these companies, they start to wonder why other companies, not even in the same industry, can’t provide that same level of service.”

“If I look at the American Customer Satisfaction Index, those companies that I mention are always at the top… but what about the ones at the bottom? Their scores, year over year, are creeping up, which tells me that they’re working harder to deliver a better customer experience. That said, they still aren’t meeting the expectation that’s been set by the higher customer service superstars,” says Shep.

Analytics is one area that can give a boost to companies lagging behind in customer service. Analytics provide the opportunity to dig deeper into customer behavior on both a large and granular scale, making it easier to target users and provide a seamless experience across channels.

“Every channel potentially delivers a different experience, however that experience needs to be at a level that is consistent with any other experience the customers have. Whether you’re dealing on Twitter, Facebook, or on the phone, your expectation of what good service is should be consistent from one channel to the next,” says Shep.

According to research conducted by Gartner, businesses are already catching onto the idea of analytics. In a 2016 report (research available to Gartner clients), the most crucial technology investment for customer experience improvement was customer analytics at 43 percent, up from 36 percent the previous year.

Similarly, more than a third of all inquiries to Gartner analysts in 2016 regarding analytics were related specifically to customer analytics.

Long story short: if you’re not already thinking about analytics, now might be a good time to start.

How do customer analytics work?

Can you imagine making strategic business decisions based on knowing what your customers will want and need? This is the essence of customer analytics. Using data collected from different points throughout the customer experience journey, customer analytics helps drive customer behaviour, enable advocacy, and avoid dissatisfaction, as outlined by Gartner.

Speaking with Bryan Clayton, CEO of GreenPal (think Uber for lawn care), he says that using the analytics in customer service solution Intercom has helped his company immensely.

“Our business revolves around Intercom for capturing our customer analytics and making them actionable. We have seen compounding improvements in customer activation by sending timely emails, and in-app messages when a customer has received custom quotes from our community of lawn service providers but have yet to pick one. We send that data to Intercom’s platform and then Intercom recognizes when the user needs the message.

“We also use Intercom to improve our customer retention by tracking what we call ‘red flag metrics’. This is when a customer has gone longer than 14 days without a mowing service and we can set them up for a series of touchpoints which include follow up emails and mobile app push notifications prompting them to come back and schedule more visits… Intercom has been an integral part of enhancing our customer lifecycle touchpoints and improving the effectiveness of our customer journey.”

By making the most of customer data, GreenPal is able to micro target its customers and create a better experience for the customer while generating more business for itself.

Customer analytics use cases

According to Gartner, there are six styles of customer analysis to take advantage of, each one useful for a different type of business:

1. Employees

Using a history of customer preferences, communication styles, and employee behavior, employees are the ones that drive a positive experience for customers.

Example: Having employees that can change styles and cater to individual customers is key, but being able to match styles is even better. CVS Health used Mattersight, a behavioral routing solution for call centers, to better match call center agents with customers. CVS segmented its customers into six behavioral groups based on subtle cues in speech patterns; then, it analyzed and scored its agents for similar patterns, matching customers and agents with similar patterns. The results were reduced call times and improved call performance, providing a better overall experience for both the call center agents and CVS customers.

2. Deep listening

Listening to what customers are saying via social media or interpreting their usage data can help identify needs or product gaps.

Example: A social media monitoring tool like Brandwatch or Brand24 can monitor online conversations to help strategize and target the right users. The Guardian used Brandwatch Analytics to isolate and target an 18 to 24 year old demographic in the run-up to the 2015 UK general election. Using these insights and targeting content at this demographic, the Guardian was able to increase mobile usage among this group by 18 percent, as well as gaining a 645 percent increase in mentions during this period.

3. Data sharing

Sharing data collected by the company with customers helps build trust and strengthen relationships.

Example: Sharing usage stats such as average number of products purchased or average checkout time can incentivize users to take action by making a purchase or subscribing to an upgrade. Netflix shares data with users about speed and performance based on internet service providers (ISP) in different regions. Users can then use this information to decide if they want to switch ISPs. Although a change in provider isn’t exactly linked to Netflix, it can have a ripple effect for customers who want a better experience using the streaming service, as well as build trust between Netflix and its customer base.

4. Back to basics

Analyzing what’s most important to customers (ie. speed, product quality) lets you deliver an experience that caters to that.

Example: If you advertise yourself as “the best in town” but are getting complaints about the quality of your product or service, analyze what’s causing the problem and make adjustments accordingly. Find your strength, and run with it. PUMA, for example, isn’t known for having the most affordable shoes or the quickest delivery times like Amazon, but it stands out from its online competitors with more detailed product information, a better display, and a better user experience to drive online sales.

5. Mass customization

Delivering a personalized product or service depending on the individual consumer gives the customer more of what they want, and less of what they don’t.

Example: Delivering products tailored to consumer preferences based on previous purchase history, activity, or browsing patterns increases the probability of conversion. Amazon’s recommendation engine is an example of using previous purchasing and browsing patterns to suggest products that are tailored to a person’s individual tastes, while Spotify’s Discover Weekly curates weekly playlists for each user based on their previous week’s listening patterns.

6. Changing behavior

It’s less about predicting a customer’s behavior than it is about understanding and changing it.

Example: You can offer free trials to users for a subscription or service and encourage them to continue paying on a monthly basis. ChargeBee is an online subscription and billing software that uses customer behavior data in order to identify which trial users are more likely to convert by looking at how – and how often – they use the product’s free trial. It separates the casual users from those who are more likely to purchase a subscription by comparing usage data to those people who are already subscribed. From there, they’re able to tailor more or less aggressive marketing campaigns to users that are more or less likely to sign-up.

Get started with customer analytics

Regardless of whether you’re in the retail, publishing, streaming, software, or eCommerce sector, there are ways that you can collect data about your customers and users to help make informed business decisions and provide exception levels of customer service.

If you’re using a CRM or customer service software, the chances are that you’re already collecting data that’ll help you delve deeper into your customers’ profiles. Whether you’re just getting started with analytics, or want to dive deeper into the psyches of your customers, there are different levels of analytics that any business, big or small, can use.

 

Check out software to help you start your customer analytics journey: