Your Practical Guide to Succeeding with Customer Intelligence
How much do you know about your customers? Who are they? What makes them leave and what makes them loyal? What are their biggest pain points?
Modern consumers expect a lot out of customer service, and it doesn’t take much to make them abandon a brand. 72% say that they would do so after just one bad customer service experience.1
That means you can’t afford to guess at what makes your customers happy. You have to create experiences that take their preferences into account from the start.
The way to understand who your customers are and what they want is customer intelligence. In this resource, you’ll learn what customer intelligence is and how you can use it to build better relationships with your customers.
What is customer intelligence?
Customer intelligence is the collection and analysis of large amounts of customer data. It gives you insight into your customers that helps you understand them and provide them with a better experience.
You’re probably already collecting data on your customers. Most companies at least have basic information in a CRM system or a history of the customer’s support tickets. Maybe you’ve dug a little deeper into your customers’ psyche with website heat maps or customer surveys.
Any and all information you have on your customers is valuable — if you put it to use.
Customer intelligence isn’t just about gathering data, it’s about how you analyze it and use it for data-backed decision making.
Data is hard to manage and understand when it’s collected and stored using disparate tools. For it to be actionable, it’s important to integrate your data into a single platform.
Why is customer intelligence important?
When you have a deep understanding of your customers, you can deliver a better customer experience.
58% of business leaders say their companies have seen a significant increase in customer retention and loyalty as a result of using customer analytics. 44% report that using customer analytics has resulted in significant revenue growth.2
Customer intelligence helps you take customer service to the next level. Here are just a few things you can do once you start collecting large amounts of customer data.
#1 Personalize the customer experience
Customer intelligence allows you to go beyond polite but impersonal customer service and provide an experience tailored to the individual. Customers are happier when you personalize your offerings — and they’re getting used to it.
Today’s consumers are accustomed to a Netflix homepage that knows they prefer suspenseful detective TV shows to feel-good romantic movies and “suggested for you” Facebook posts that understand their love of exotic fish.
Companies that implement a personalization strategy see a 33% improvement in customer loyalty and engagement. Customer intelligence is key to that personalization.3
For customer service teams, personalization means that you understand the likely customer journey and pain points of different groups of customers. You can anticipate their needs and interests and tailor solutions accordingly.
Personalization leads to higher customer satisfaction as measured by increased NPS scores, better customer retention, and a lower customer service call volume.
#2 Measure your success
Customer intelligence lets you gauge the effectiveness of your customer service. As your support strategy evolves, you can judge the reaction of your customers based on their behavior.
First, you use the insights you’ve collected to make an educated decision about how to change the customer experience. Then, you analyze the data to see what changes have occurred due to your updated strategy.
For instance, your customers frequently message your brand on Facebook Messenger for customer support. With this information, you decide to extend your support to Facebook Messenger, and dedicate a few support agents to offer support on this channel. What you’ll soon notice is that customers tend to offer higher CSAT scores on Facebook Messenger owing to 1-1 real-time conversations, and you’ve also recorded a dip in your average handle time.
#3 Be proactive
What’s better than responding to customer issues quickly? Anticipating issues before they arise.
Analyzing data from support tickets, customer feedback, website and knowledge base usage, and other sources let you identify common pain points at each step in the customer journey and be ready for them.
#4 Strengthen customer relationships
A strong customer relationship is based on mutual understanding.
You understand your customers’ needs and expectations. Your customers trust that you will use the information they offer wisely, they know that you get them and that they can expect a consistently high level of service.
Customer intelligence gets you the insights you need to strengthen your understanding of your customer base.
What types of data can you use for customer intelligence?
The more data sources you have, the clearer your understanding of your customers will be. Customer intelligence combines data sources to answer questions like:
What support ticket types do your NPS detractors have in common?
Or
What knowledge base articles do customers search for in their first week of owning your product?
Let’s take a look at the various data sources that you can use for customer intelligence and frame your own questions like the ones given above.
#1 Data from customer support interactions
Make use of your customer service software to collect data on the customer support experience. For example, you might look at the most common customer inquiries or track what time of day you receive the highest volume of tickets.
AI chatbots can do their own data analysis, using machine learning to anticipate customer needs. You can use chatbot data to build bots with more helpful conversation flows.
When customers have an issue with your product or company, they don’t always turn to you directly. Monitoring social media lets you listen in on what customers are saying and turn it into actionable data.
#2 Data from customer behavior
Gather data on how customers use your website and your product.
For example, website heatmaps and other web analytics let you know what customers are searching for and what they care about most. They can also alert you if customers seem to be looking for something that isn’t there, like a particular support topic or channel to reach you.
If you have a knowledge base, you can track which articles are referenced most often. You could even give customers the opportunity to rate each article on its usefulness.
Cross-reference your knowledge base content with your other data. If there’s a topic that customers regularly ask your chatbot about, for example, consider adding articles on that topic to your self-service portal.
#3 Data from talking to customers
Many support teams send customer satisfaction (CSAT) surveys to evaluate their performance and measure customer sentiment. For example, the survey might be sent in an automatic email after a ticket is closed.
Combining CSAT information with other customer data helps you understand which factors affect customer satisfaction and how happy customers behave compared to unhappy ones.
You can also dig deeper into customer sentiment by conducting customer interviews.
#4 Other customer data
The data in your CRM, like purchase histories or demographic data, can be very valuable for customer intelligence. You might find that customers have different expectations based on their age or region of the world.
How do you gather customer intelligence?
Instead of using separate tools and databases to collect data from each source, you can use a customer intelligence platform, a tool that can manage customer analytics from many sources.
Freshdesk
Freshdesk, a customer service software, also plays the role of being a customer intelligence platform. Freshdesk enables you to create customer profiles and store in-depth, useful information about your customers. Additionally, Freshdesk also shows a timeline of historic conversations with customers. All information reading a customer can be easily accessed while engaging with them and used to personalize conversations.
Using Freshdesk, you can collect extensive data on support issues and segregate the data collected using support ticket tags and types. You can then run reports based on the tags and different types of tickets to learn what your customers need the most help with. You can also collect data on customer sentiment with CSAT surveys. Customizable surveys can be created, sent, and analyzed from within Freshdesk.
If you use Freshdesk to build your knowledge base, analytics can tell you which articles are the most popular with customers and which ones your AI chatbot suggests most frequently.
There are several other types of tools you can use to build an efficient customer intelligence process.
Customer Data Platform (CDP)
A CDP is a unified database of customer information from all of your channels.
The data is generally gathered directly from your customers, and because it’s personal information, it’s subject to strict data security standards.
Your CDP can share its customer data with the other tools in your tech stack.
Data Management Platform (DMP)
DMPs are also databases of customer information, but they store third-party, anonymous data, like cookie and IP address information.
This sort of data is useful for analyzing broad trends in the market and helping to create customer segments.
Which technology solutions you should use depends on the data management needs of your organization. Some companies only have one customer intelligence solution while others have complementary technologies.
How do you use customer intelligence?
You’ve collected and stored your data and you’re ready to convert it into actionable customer insights.
So how do you get started?
To get the most out of customer intelligence, start by sharing your information with relevant people across the business. Everyone from your product team, your marketing and sales teams, your support team, and the management team should have access to aggregated customer intelligence. Organizational silos are the enemy of customer intelligence — for effective analytics, data from all sources should be combined and the insights shared widely.
You can do this by using dashboards, reports, and customer journey visualizations.
Customer service agents who interact with a customer should have all the available information you’ve collected on that person. It gives them a deeper understanding of the customer and helps them provide a smooth customer support experience.
#1 Customer journey maps
The customer journey is the path that customers follow through the stages of their relationship with your company. It starts whenever they first become aware of you — maybe they saw an ad or read a review — and continues through their purchase decision and interactions with your support team.
Visualizations, or maps, of the typical customer journey, are useful for predicting customer behavior and anticipating customer needs.
Customer intelligence lets you analyze every step along the customer journey to perfect your map.
You can look into what types of customers drop off after each touchpoint or when various support issues tend to arise. You might find out that customers have a higher CSAT if their first interaction with you is over the phone rather than email.
These insights show you opportunities to provide an improved customer experience at every touchpoint.
#2 Customer segmentation
Your customers are all unique. They have different preferences and frustrations and they all take their own customer journey.
While you can’t always predict the needs of specific customers, you can come closer by grouping them into segments of like individuals. These segments can be used to deliver experiences customized to each group.
Some customer service agents will be better than others at responding to a particular type of customer. You can route customers from those segments to the agents best equipped to help them.
There are a number of ways you can segment customers.
You can base it on their stage in the customer journey. Someone who just learned about your products has different needs than a long-time user.
You could divide customers by sentiment, such as whether they typically give low or high CSAT ratings. If they usually feel negative about support interactions, you might choose to offer proactive support, faster service, or a different channel.
You can also use sentiment-based segments to analyze what other characteristics these groups have in common. Maybe your customer service is resonating more with people who work in some industries than others.
Customer segments are often based on demographics, and geographies as well. See if you can identify how these groups interact differently with your company at various touchpoints.
#3 Better customer service
You’ve collected data, examined each step of the customer journey, and taken a deep dive into who your customers really are.
Now you use it to build something great.
Start small. Use your customer intelligence to identify an area of concern. Maybe a lot of your European customers have low satisfaction with your customer service when they use the chat feature.
Develop a hypothesis. Maybe they’d be happier if the chatbots were multilingual. Implement this change, and analyze your new data to see if the problem is solved or if you should try something else.
Over time, applying your customer intelligence across touchpoints and segments will lead to drastic improvements in the customer experience.
Continuous improvement
Customer intelligence is a never-ending process. Keep looking for new sources of data and new ways to analyze it.
Only 32% of customer experience professionals feel they have enough information to understand customer needs and apply it to improving customer experience.4
It’s a challenge, but not an insurmountable one.
Collecting, aggregating, and analyzing that information is very possible — you just need the right tools. Freshdesk makes it easy to develop actionable insights into your customer service.
Source:
1 – https://www.acquia.com/resources/ebooks/deliver-cx-they-expect-customer-experience-trends-report
2 – https://hbr.org/sponsored/2018/06/real-time-analytics
3 – https://www.ibm.com/account/reg/us-en/signup?formid=urx-43366
4 – https://smartercx.com/straight-cx-leaders-latest-insights-2018/
