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Want to unveil the secrets of your customer behavior? Let’s learn about customer intelligence (CI) and how you can implement it in your business.

For every business, learning about their customers and prospects inside out is the key to success. Only with the help of customer intelligence you will be able to learn about your customers better, including what they like and what they don’t.

Continue reading this explainer guide on customer intelligence to know all the crucial aspects of it in easy language.

What Is Customer Intelligence?

Customer intelligence (CI) refers to the data collection and analysis done by organizations to find out the best approaches for customer interactions. Using the collected insightful data, companies can make informed decisions about their products, services, business strategies, marketing campaigns, and more.

As customers share their valuable information while interacting with the business, it can be used by the companies to offer customized experiences to the customers. Customer intelligence is the process that makes it possible. 

It generates timely and relevant intelligence on the customers by analyzing customer data. With proper implementation of CI, organizations can build more meaningful business relationships with their customers and convert more prospects into customers.

Importance of Customer Intelligence

All companies store customer data in their system. However, the data is usually incomplete and siloed. As a result, the data fails to drive the superior customer experience that the companies want. 

Suppose an organization wants to achieve the highest impact and growth from the huge amount of customer data. Then, it needs to transform its knowledge into a true 360° customer view through customer intelligence.

Customer intelligence connects all the information companies have about a customer. With data science and data analytics, it provides you with a better idea about the customers and prospects so you know what they want from you. 

By generating personalized customer analytics data, it offers a unique perspective for service, marketing, and sales teams. As a result, these teams can visualize hierarchies, relationships, networks, etc., in the ways they want for their strategic needs.

Key Components of Customer Intelligence

#1. Data Collection and Analysis

This involves following a system to collect relevant data on customer interactions, behaviors, and preferences from various online and offline sources. The data is also analyzed through data mining and machine learning for meaningful insights and patterns.

#2. Data Integration

To get the intelligence of customers, the data collected from several sources is integrated into a centralized system. This can provide a holistic view of the customer by consolidating customer data gaṭhered from different channels and touchpoints.

#3. Data Storage and Management

The customer intelligence data is stored in a secure place for maintaining it without any risk. Companies need to use secure data storage systems or databases while following data governance policies to comply with data protection regulations.

#4. Customer Segmentation and Profiling

Another component of customer intelligence is categorizing the company’s customer base into different groups. The segmentation is usually done on common characteristics and behavior. At the same time, businesses perform customer profiling, which means creating individual profiles for each customer.

#5. Purchase Behavior Comprehension

CI also involves understanding the patterns and trends in customer purchasing behaviors. This is usually done by analyzing purchase frequency, purchased products, purchase timing, and average transaction value.

#6. Predictive Analytics

Companies also use historical and current data to predict the future behavior of their customers. Thus, they can get forecast data on customer churn, marketing campaign results, and purchase probability. 

Types of Customer Intelligence

#1. Behavioral Data

Behavioral data refers to the data about customer behavior within the company. This data lets you understand the customer behavior and modify the customer journey touchpoints. Website clicks, app navigation, social media engagement, and customer interaction with the support staff are considered behavioral data in customer intelligence. 

#2. Psychographic Data

Psychographic data includes personality characteristics and attitudes of the customer. This data is necessary for creating highly targeted marketing campaigns. 

#3. Transactional Data

Transactional data includes tracking customer purchasing behavior. This data lets companies identify their most popular products or services, customers’ buying patterns,  purchase frequency, and purchase timing.

#4. Demographic Data

Demographic data includes demographic information about the customer base, such as age, gender, geographic location, education, household member count, and income. When it comes to segmenting and targeting customer groups for marketing, this data is highly beneficial. 

#5. Attitudinal Data

Attitudinal data is customer intelligence data that enables businesses to understand the attitudes, sentiments, and beliefs of customers. With its help, organizations can learn about the customer’s feelings about a product, service, or certain interactions with a company. 

Key Objectives of Customer Intelligence

Reasons why a company wants to gather customer intelligence will vary. The common and major objectives of getting customer intelligence are:

  • Understand customer behavior and preference
  • Segment customer base for targeted marketing campaign
  • Provide bespoke customer experiences
  • Offer better products and services
  • Forecast customer behavior and product sales
  • Analyze customer feedback to improve business
  • Increase customer loyalty and reduce churn rate
  • Enhance marketing effectiveness
  • Get an edge over the market competitors
  • Reduce operational costs and get more revenue
  • Mitigate potential risks in the business
  • Build a company as a strong brand
  • Ensure data-driven decision-making

Data Collection Process of Customer Intelligence

In case you are wondering how to collect customer intelligence data for your organization to implement it, here are the steps you can follow:

#1. Get Reliable Customer Intelligence Software

It is almost impossible to manually collect customer intelligence data. Hence, companies need to use a customer intelligence platform for the automatic collection and analysis of customer data. There are a number of applications available in the market, but you need to find the most appropriate one according to your business and objective.

#2. Collect Quantitative and Qualitative Data

The first step to know your customers is to collect quantitative data. Since the data is measurable (being numeric or percentage-based), companies can use this to identify key trends on any topic and confirm whether they need additional information.

To find out additional context behind any trend, companies might need to take help from qualitative data. It consists of non-numerical data to offer details on individual preferences, attitudes, and motivations. Examples of qualitative data collection are conducting surveys, analyzing website and support data, etc.

#3. Aggregate Data From Multiple Sources

A company consists of multiple departments like marketing, sales, and support, and all of them collect customer data. For the benefit of the organization, data collected by all the departments should be stored in one place and made accessible to everyone. Thus, all employees can utilize the data to offer more personalized customer experiences.

#4. Generate Actionable Customer Insights

After the collection of customer data, you need to analyze it to generate actionable insights. These are useful for any business that wants to develop a customer-focused business strategy. If you think that customer intelligence only offers clarity about customer interaction, you are wrong. It also makes you aware of the customer’s expectations so that you can work accordingly.

How To Implement Customer Intelligence in Your Business

#1. Objective Identification

Before you opt for customer intelligence, you need to be certain about what you want to achieve with customer intelligence. After learning about the goals, companies can start to identify the data types they have to collect.

#2. Actionable Data Collection

As discussed above, several types of customer data can be collected for customer intelligence. Companies need to start collecting data that can meet their specific goals.

#3. Data Analysis

After the data collection phase, businesses have to perform data analysis to determine the trends and patterns of customer behavior. A number of tools are available for data analysis, such as CRM software, ML algorithms, and analytics software.

#4. Implement Actionable Insights

From the analysis, companies will get insights into their customers based on which they have to take action. The actions could be developing new products, targeting customers more effectively, or offering better experiences to the customers.

Benefits of Appropriately Implementing Customer Intelligence

#1. Offer Personalized Experiences

Customer wants organizations to know their preferences, and this can be done through customer intelligence. With it, organizations can know about the choice of individual customers and offer them suitable products. 

#2. Identify Conversion Opportunities

Customer intelligence data allows sales teams to proactively cash on conversion opportunities, leading to increased customer lifetime value (LTV).

#3. Lower Customer Churn Rates

When companies know what causes customers to leave, they can take necessary steps to stop them from doing that. It helps them reduce customer churn rates by offering them lucrative offers.

#4. Increased Customer Loyalty

Another closely related aspect to churn is customer loyalty. When the churn rate is less, customers feel more valued, and they tend to stay with a business for a longer time.

#5. Data-Driven Decision Making

With customer intelligence, companies can make more data-driven decisions. If they want to know how satisfied the customers are with the support team, collecting CSAT scores will work better than guessing. 

#6. More Sales

Organizations that understand their customers with CI tend to bag more sales and ROI on marketing and customer experience (CX) investments.

#7. Improvised Customer Segmentation

When businesses have the right customer intelligence, they can segment their customer base based on common traits. Thus, they can target specific customer groups and approach them with personalized marketing campaigns.

Prominent Customer Intelligence Platforms

#1. Frame AI

You know that support tickets are expensive, but how much do they cost for your business? Frame AI lets you learn the real impact and cost of each support query.

Top Features

  • Shows the monetary impact of each ticket against the overall cost of service
  • Uses a unique approach to label and score the tickets
  • It helps you make data-driven investment decisions on roles and tools 
  • AI cost reporting to share the cost impact of decisions 

This tool also reveals more than just the ticket counts — you get to learn about scheduled calls and log reviews that need more time and manpower to resolve.

#2. Informatica

Informatica is a complete customer intelligence data platform that enables you to offer AI-powered experiences for smooth customer interaction. 

Top Features

  • ML technology to automatically identify known and unknown accounts
  • Segment the customers to run highly personalized marketing campaigns 
  • Graph data store to visualize B2B hierarchies, relationships, social networks, and more
  • Multiple customer views using key attributes
  • Actionable insights and best recommendations for users 
  • Uncover insights about customer preferences, intentions, and sentiment

With its help, companies get a better understanding of their existing customers and prospects coming from all touchpoints across all channels.

#3. Dialpad

With Dialpad, you get AI in action for quick resolution of customer requests. It comes with AI tools for live agent coaching and sentiment analysis.

Top Features

  • Omnichannel workspace to support customers through calls, messages, and video calls
  • Get in touch with customers across channels from Dialpad
  • Features like call transcription and CSAT prediction to boost team productivity
  • Integration support for popular apps like Salesforce, Zendesk, and Google Workspace
  • Real-time visibility into usage and adoption across global offices

This software is also suitable for business communications as it allows hybrid teams to stay connected and scale up globally.

#4. Intercom

Intercom helps you make online business personal and grab more CSATs by sharing insights into customer behavior.

Top Features

  • Seamless integration of customer data for instant access to customer history
  • Offers behavioral data to target customers according to their actions
  • Custom tracking of unique data as per business requirements 
  • Prioritizing important customers by routing their issues on top of the support queue
  • Quickly find out the context from previous chats and billing
  • Customer segmentation for targeting based on location, action, etc.

Moreover, this platform lets you get the whole picture of a customer, including location, expenditure, business type, etc.

Wrapping Up

A well-planned customer intelligence strategy is a must-have for both B2B and B2C businesses. It helps you understand the customers, reduce their churn rate, and segment them for personalized marketing campaigns.

Following the steps mentioned here, you can effortlessly collect customer intelligence data and implement them. Also, I have added some CI tools that you can use for your organization to get customer intelligence data with ease.

Next, check out the best audience intelligence platforms useful for marketers like you.

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  • Tamal Das
    Author
    Tamal is a freelance writer at Geekflare. He has an MS in Science and has worked at reputable IT consultancy companies to gain hands-on experience with IT technologies and business management. Now, he writes content on popular B2B and B2C IT…
  • Rashmi Sharma
    Editor

    Rashmi is a highly experienced content manager, SEO specialist, and data analyst with over 7 years of expertise. She has a solid academic background in computer applications and a keen interest in data analysis.


    Rashmi is…

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