How well do you know your customers? Insights from customer data are essential to understanding how to best serve your customers, so you can make strategic business decisions to boost customer loyalty and revenue. But, they’re only helpful if you know how to retrieve the data and use it to your advantage.
In this article, we’ll discuss the importance of Customer Intelligence, share insights on how to use Customer Intelligence data, and talk about platforms you may find helpful for data analysis. You’ll learn:
- What is Customer Intelligence?
- Using Customer Intelligence in your company
- How do you do Customer Intelligence?
- Examples of Customer Intelligence data collection tools
- Tools for measuring and analyzing customer sentiment
- Using AI in your Customer Intelligence strategy
- Getting quality insights from your Customer Intelligence software
- Customer Intelligence Tools FAQ
What is Customer Intelligence?
Customer Intelligence is the process of gathering and analyzing information about your customers and using it to inform business decisions. It can provide actionable insights to better understand your customers’ pain points, what they like vs. don’t like, their purchasing behavior, and what’s likely to drive their future engagement with your brand or organization. Based on these insights you can work to ensure your business is meeting their needs.
Customer data comes from many places, including:
- Demographic information
- Geographic data
- Purchase history
- Chat or help desk conversations
- Customer surveys (including net promoter score surveys)
- Feedback forms
- Social media interactions
- Campaign data
- Focus groups
- Email open/click information
What is a Customer Intelligence platform?
A Customer Intelligence platform is software that collects customer information in one place, making it easier to uncover a meaningful analysis using all available data. Having the information is great, but it only becomes helpful when you understand what the data means.
A Customer Intelligence platform can be as basic as a spreadsheet or file folder with customer data; however, for ease of analyzing, collecting, and storing this data, a robust Customer Intelligence platform that uses machine learning or AI analysis is the best way to go. AI platforms can help to analyze massive amounts of customer data quickly, so you get real-time actionable insights and information.
What is a Customer Intelligence database?
A Customer Intelligence database is the raw data used within your Customer Intelligence platform. This term is sometimes interchangeably used to refer to the analysis platform.
Here is a great illustration of how your data sources and Customer Intelligence platform work together.
Using Customer Intelligence in your company
It’s vitally important to have a Customer Intelligence strategy for your company. When your company actively gathers and analyzes customer information, you can understand customer satisfaction levels more easily. Customer intelligence data gives you a clear picture of where your customers feel you are meeting expectations and where you’re falling short. With this information, you can make business or product/service changes to better meet your customers’ needs.
It can also help you refine your customer journey by better understanding typical customer behavior. For example, your Customer Intelligence may indicate negative sentiments when people talk about your onboarding process for new customers. When you can better identify pain points, you can change the onboarding process, customer service, and resources and training given to new customers to make this process better meet their needs.
Customer intelligence can help inform changes for:
- Product and service features
- Marketing campaigns
- Better customer engagement
- New customer service approaches
- Overall customer experience improvements
How do you do Customer Intelligence?
Customer intelligence is a strategy businesses use to understand their customers better. Here are the five steps to start using data to improve the customer experience:
Step 1: Collect customer data
Look at your current systems and databases for where you have customer experience or demographic data. This may include account profiles, purchase and sales history, online interactions, and other direct or indirect feedback sources.
Step 2: Add missing data sources
Based on your already available data sources, look to see if there are any gaps in customer insights. For example, you may not have customer-supplied data from surveys or feedback forms. If you only have purchase history and basic demographic data, look for ways to add new feedback sources to your data. This will help you get more detailed insights into your customers.
Step 3: Choose a Customer Intelligence tool
Next, link all data sources to your chosen Customer Intelligence tool or platform. For real-time results, use an API or enable live data transfer from your data sources directly to your platform. This will help you get real-time insights and identify any problems early.
Step 4: Analyze your data
If your Customer Intelligence software includes machine learning algorithms, use them to analyze and summarize your data. If not, assign a team to review and summarize the data manually.
Your initial insights may uncover worrisome potential customer analytics but may not give you enough data to understand how to fix them. For example, you may determine that people are unsatisfied with their account settings menu. This insight is good but doesn’t tell you exactly what they don’t like about it. In this scenario, the problem could be any number of things, including:
- Non-intuitive user interface
- Missing features
- Hard to find in their account
- The settings page URL is broken in the main menu (so people can’t visit it).
- Changes don’t save when selected
You may need to expand your customer analytics sources to get more detailed information. This means going back to step 2 and creating or adding new quantitative or qualitative data sources to help determine exactly what is causing the negative customer sentiment.
When you use an AI platform like Idiomatic, all information is passed to the system in real time, helping to uncover these negative insights automatically and in real time. It decreases the likelihood of missing an important issue that needs immediate correcting before it affects too many customers.
Step 5: Use data to inform business decisions
Once you get the detailed analysis and results, use this information to make the required changes to increase customer satisfaction. After making these changes, look at the data again and you’re likely to see customer satisfaction increase. If not, look into the insights again, add more data sources if needed, and see what else may contribute to this negative customer sentiment.
Examples of Customer Intelligence data collection tools
Many helpful tools and software help you gather Customer Intelligence. Here are a few examples:
Mixpanel
Mixpanel helps you answer questions like, “How is my product used?”, “Why and where do users drop off?” and “Which users retain best?” It helps you analyze your customer data to learn the customer behavior characteristics tied to customer retention.
Heap
Heap uses data science to remove your customer insight blindspots to impact business results. It focuses its data collection on how users interact with your product or website.
Segment
Segment collects your customer data through APIs and helps you “activate” its insights. Get a complete customer view across all your digital platforms and channels. It also enables you to streamline the sharing of data across your systems.
Zendesk
Zendesk helps you offer conversational support to your customers efficiently and effectively. It pulls customer data from multiple data sources so you get a unified view of your customer, so you can personalize their customer journey to boost customer satisfaction and retention.
Sprout Social
Sprout Social’s listening tools scan the web to see what others say about your brand, even if they’re not customers. This provides valuable insights into your potential and current customer base to learn more about how people feel about your brand.
Tools for measuring and analyzing customer sentiment
Using the data you gather through the above tools and other data sources, use a more robust AI-based platform to look for trends in your customer analytics data. Here are four examples of customer and consumer intelligence platforms:
Idiomatic
Idiomatic helps you accelerate customer growth by unlocking insights across the customer journey. This platform helps you unlock the “why” behind customer feedback with world-class AI customized to your business. You can upload unlimited custom data sources, do keyword searches of data, view customer sentiment analysis models, create and track different user segments, and view visualizations of your data trends.
Request a demo
Hubspot
Hubspot’s customer service software best analyzes data sources from within its own software family and products. It’s part of their integrated CRM platform that features conversational tools, a shared inbox, help desk automation, knowledge base functionality, customer feedback and surveys, reporting, a customer portal, and playbooks.
Signal
Signal’s Customer Intelligence software takes your customer data points (aka “signals”) and helps you organize this data. It provides robust tag management and data services to help you map your customer journey. It also features API-enabled data collection, a rules engine, and data distribution.
XM Discover (Formerly Clarabridge)
XM Discover uses natural language processing (NLP) to measure your audience’s characteristics. It helps you determine why customers are reaching out to your brand and what they plan to do next by interpreting the meaning behind their words. It includes 100+ pre-built connectors to popular data sources.
Using AI in your Customer Intelligence strategy
Of course, you can always analyze your gathered customer data manually. This introduces a higher likelihood of human error and misinterpretation, however. A Customer Intelligence platform helps collect and analyze mountains of data in seconds. When you use machine learning to analyze your customer feedback and sentiment data, you get quicker results that only get better and more accurate over time as the AI “learns” about your customers and business trends.
Getting quality insights from your Customer Intelligence software
Idiomatic is an AI-driven Customer Intelligence platform and predictive analytics software that provides real-time customer insights. You can link your various customer feedback and data sources to the platform, and the AI will look for correlations and trends and summarize the data so you can take action to enhance customer loyalty and address pain points right away. This will help you increase customer lifetime value, reduce acquisition costs, and boost NPS and customer satisfaction scores.
Learn more about how Idiomatic’s Customer Intelligence software can be the missing link to analyzing customer data to better understand your customer’s pain points and needs.
