What is customer intelligence (CI)? Benefits, types, + examples

Customers crave personalization, often more than businesses realize. In fact, 62 percent of customers say they wish businesses would do more personalization, according to the Zendesk Customer Experience Trends Report 2023.

Thankfully, creating those personalized experiences has become easier and more impactful in recent years due to the power of customer intelligence (CI).

By using CI to gain a deeper understanding of customers, support agents can communicate with buyers to make them feel understood and appreciated, leading to increased customer engagement, retention, and loyalty.

• What is customer intelligence (CI)?
• What are the benefits of customer intelligence?
• 5 types of customer intelligence
• What powers customer intelligence?
• How to collect customer intelligence data in 3 steps
• How to use customer intelligence analytics
• 5 customer intelligence best practices
• Customer data intelligence examples

What is customer intelligence (CI)?

Customer intelligence (CI) is the process of collecting customer data and pulling insights from it. CI allows companies to determine their customers’ needs, pain points, purchasing behaviors, favorite products, demographic details, and more.

The goal of collecting CI data is to use the information to personalize each customer’s experience. This also enables agents to anticipate and respond to customer needs in a more empathetic, conversational way.

What is the difference between business intelligence and customer intelligence?

Customer intelligence tells businesses more about customers, while business intelligence tells companies more about themselves.

• Customer intelligence (CI) includes data that illuminates customer needs, identities, behaviors, and preferences. This data helps businesses refine sales, marketing, and support strategies.
• Business intelligence (BI) is a collection of data about a company’s operations, including sales, finance, marketing, and customer service. Business leaders typically formulate insights using this information to make decisions, streamline workflows, and monitor performance.

What are the benefits of customer intelligence?

Gathering customer intelligence and storing it in a location where all team members can access it can contribute to better customer experiences and more revenue.

Here are some of the top benefits businesses see when employees have access to CI:

• Increase sales: Organizations that put effort into understanding customers tend to see better conversion rates and a higher return on investment (ROI) on marketing and customer experience (CX) investments.
• Improve customer loyalty and retention: CI data allows businesses to personalize customer experiences and predict customer expectations, encouraging higher customer retention and loyalty rates.
• Identify conversion opportunities: Sales teams can use customer intelligence to proactively anticipate customer needs and capitalize on conversion opportunities early, increasing customer lifetime value (LTV).

5 types of customer intelligence and tips for each

Excellent support teams don’t settle for whatever customer data comes their way. Instead, they find the right information and explore additional avenues to account for all variables, even if not all information is available in their customer relationship management (CRM) tool.

If you can’t find the data you need internally via a CRM or customer service platform, rely on external, third-party sources instead. External CI typically includes data from surveys, user feedback, digital interactions, and focus groups.

Regardless of how you choose to obtain customer intelligence, these are the five types you should focus on analyzing:

• Transactional data

• Behavioral data

• Psychographic data

• Demographic data

• Attitudinal data

1. Transactional data

As the name suggests, transactional data refers to the customer information a business collects when a shopper completes a transaction.

Transactional CI data typically includes:

• Time of transaction

• Amount spent

• Prices of purchased items

• Promotional offers and used discounts

• Payment method

• Purchase history

Tip: Use transactional data to understand customer preferences, purchasing hesitations, and top-selling products.

2. Behavioral data

Behavioral data measures customer behavior and engagement levels with employees, promotional offers, and your website.

Behavioral CI data typically includes:

• Website visits and page views

• Content downloads

• Web form submissions

• Purchasing behaviors

Tip: Use behavioral data to understand a buyer’s journey to making a purchase and which factors are most influential.

3. Psychographic data

Psychographic data includes information about a buyer’s attitudes, interests, personality, and values.

Psychographic CI data typically includes:

• Religious or political beliefs

• Hobbies

• Daily activities

• Media consumption habits

• Motivators and detractors

• Decision-making and communication styles

Tip: Use psychographic data to understand what events or offers are likely to encourage a customer to take action.

4. Demographic data

Demographic CI data is information about the characteristics of a buyer or customer segment.

These characteristics typically include:

• Occupation

• Income level

• Education

• Location

• Age

• Gender

• Marital status

Tip: Use demographic CI to identify recurring trends associated with specific characteristics and anticipate consumer behavior and needs.

5. Attitudinal data

Attitudinal data provides insights into how users feel about specific products, services, or experiences.

Some examples of attitudinal CI include:

• Customer satisfaction

• Pain points

• Purchase criteria

• Customer sentiment

• Product and branding desirability

Tip: Attitudinal data is often a strong supplement to demographic CI, as businesses can use it to explain why specific customer segments make the decisions they do.

What powers customer intelligence?

There are several options available to businesses that need to gather, analyze, and leverage customer data, but the key to success is utilizing technologies that power intelligent CX.

Here are a few of the top capabilities to look for when choosing a customer data solution:

• Customer context panels give agents the key context they need to provide seamless, conversational experiences. The primary benefit of customer context panels is that they improve agent efficiency and customer satisfaction.
• Advanced data and analytics drive more meaningful, trusted interactions. Agents can also use this data to anticipate customer needs and communicate proactively.
• Suggested articles provide agents with talking points to use when discussing a product or resolving a support request. This should encourage more personalized, empathetic, effortless, and responsive customer experiences.

The solution you use for customer intelligence must balance emotional intelligence (EQ) and IQ. Consider using Zendesk AI as a trusted partner in customer service problem-solving and a tool for rapid business growth.

How to collect customer intelligence data in 3 steps

Consumers today interact with brands via various touchpoints—social media, chat, phone, in-store, and so on. Manually tracking all these interactions can lead to inaccuracies and inaccessibility between teams.

Here, we share the types of CI to collect, how to collect it, and tips for disseminating the information for company-wide benefits.

1. Invest in good customer intelligence software

Support teams should use a customer data platform to automatically collect, store, and analyze customer data. CRM software is a type of CI platform. It allows users to:

• Monitor customer interactions: Look for a customer relationship management tool that tracks customer interactions at every touchpoint, whether that’s a social media message or a one-hour phone call with the support team.
• Access advanced reports: A good CRM tracks metrics on a single dashboard and generates valuable data-driven reports, such as quarterly sales cycle and profitability reports.
• Install integrations with other tools in your tech stack: Customer data can be challenging to manage when it lives on multiple disconnected platforms. Instead, integrate your CI software with other tools in your tech stack for better efficiency and productivity.
• Automate support processes: Find a CRM with AI (artificial intelligence) and workflow automations. This enables customer self-service and improves the agent experience by automating routine tasks, providing customer insights, and surfacing relevant content recommendations.

CRMs are essential customer intelligence tools that store invaluable data and keep cross-functional teams in sync.

2. Compile quantitative and qualitative data

Quantitative data is often the first step to understanding customers. This data is measurable and either numeric or percentage-based. Businesses can use quantitative data to identify key trends and determine if they need additional information.

If businesses find a trend they don’t understand the reasoning behind, they can use qualitative data for more context. Qualitative data consists of non-numerical data that provide details about individual beliefs, attitudes, preferences, and motivations.

Conduct surveys, hold focus groups, and analyze website, sales, and support data to find this information. This should give you a full picture of customer needs and expectations.

3. Unify data from different sources

Just because the marketing, sales, or support department discovers an insight doesn’t mean they should be the only ones who know about it. Once you obtain consumer data and insights, make them accessible team-wide to ensure all employees can use them to create better, more personalized customer experiences.

Use a tool with a unified customer view to ensure that the information is documented and available to anyone who may benefit from it.

Here are some common ways teams use data from other departments:

• Marketing teams often use sales and support data to perfect messaging, advertise promotions, and target relevant customer segments with the right products.
• Sales teams often use marketing and support data to follow up with a customer about a product and close the deal.
• Support teams often use marketing and sales data to keep track of past purchases and proactively predict customers’ needs.

How to use customer intelligence analytics

We briefly touched on the broad ways various departments can use CI from other teams. Now, let’s go deeper to understand more about the specific ways businesses can use customer analytics for successful outcomes.

• Cross-selling: Keep track of customer order histories and identify opportunities to sell products related to past purchases.
• Price optimization: Use CI analytics to understand what features are most important to each customer segment and how much they’re willing to pay so you can maximize sales and revenue.
• Knowledge base materials: By monitoring the top-selling products and the knowledge base resources customers use most often, you can determine which articles to update or find existing resource gaps.

5 customer intelligence best practices

Now that you know more about using CI to your advantage, let’s dive into some best practices you should follow for business and customer success. Here are five essential customer intelligence best practices that businesses across industries can utilize.

1. 
   Leverage customer sentiment: Use customer sentiment to understand how customers feel about your brand and develop ideas to win over unhappy customers. According to our CX Trends Report, 58 percent of customer service agents say that lack of CI affects their ability to provide outstanding care, and it often causes negative experiences.
   Build a customer-first organization: Putting the customer first often results in happier customers, better customer retention, and higher profits. That’s why businesses need to analyze CI before making decisions that can impact CX.
   Assess real-time and historical data: Use historical CI to understand trend fluctuations and long-term customer behavior patterns, but don’t forget to account for real-time data. This ensures you’ll be aware of emerging trends and issues early on.
   Improve agent efficiency: Agents can use CI to anticipate customer needs, redirect users to topical knowledge base resources, gather context about individual customers, and more.
   Protect customer privacy: Only collect sensitive customer data with consent, and always adhere to privacy regulations so CI remains safe where you store it and is only accessible to authorized parties.

Customer data intelligence examples

Here are some examples from our latest CX Trends Report of the type of CI data businesses may receive, the most important takeaways, and how different teams can turn that data into actionable tasks.

Apply this process to internal predictive analysis efforts at your organization and use data to make impactful decisions.

1. Use CI to understand business and customer needs

Noom is a subscription-based health app that helps users track their daily food intake and exercise. In 2021, the business released Noom Mood, a cognitive behavioral therapy (CBT) app that helps users manage and cope with daily stressors and mental health conditions like anxiety.

2. Share CI to enhance cross-functional collaboration

Polaris is a Minnesota-based retailer that sells boats, motorcycles, off-road vehicles, and snowmobiles. In 2017, the vehicle manufacturer decided to deepen connections with customers and launch Polaris Adventures as a way to increase accessibility to powersports.

Use consumer intelligence to connect with your customers the right way

Customer intelligence can tell you a lot about the people who shop with your business and provide the necessary insights needed to provide the best products and support.

Invest in a powerful, trusted customer intelligence platform like Zendesk to get started.