Written by: Victoria Yu
Victoria Yu is a Business Writer with expertise in Business Organization, Marketing, and Sales, holding a Bachelor’s Degree in Business Administration from the University of California, Irvine’s Paul Merage School of Business.
Edited by: Sallie Middlebrook
Sallie, holding a Ph.D. from Walden University, is an experienced writing coach and editor with a background in marketing. She has served roles in corporate communications and taught at institutions like the University of Florida.
Updated on February 27, 2024
Customers are the backbone of your business. Without customers, you have no business. Since we know this is true, any business owner would be wise to learn everything he or she can about their customers in order to appeal to them more effectively and drive sales.
One way to learn more about customers is by using something called customer intelligence. While this might sound like something out of a spy movie, customer intelligence is actually a common strategy businesses employ to help improve customer-facing operations and, as a result, make more sales.
Key Takeaways
Businesses use customer intelligence (CI) to collect, analyze, and leverage large amounts of customer information to improve customer interactions.
Customer intelligence is used by all customer-facing roles: marketing, sales, and customer service. Post-sale, the data is then collated and analyzed to guide larger strategies.
There are four main types of customer data collected in CI: transactional, behavioral, psychographic, and demographic data. This data is usually collected from a CRM or designated CI software system.
By leveraging CI, a business can improve customer personalization, drive profits, monitor brand sentiment, segment customers, and optimize pricing.
Customer intelligence (CI) is the goal when a business collects large amounts of data and information about its customers and analyzes it in order to derive insights into the customer’s behaviors, needs, and wants.
Using this customer data and information, a business can improve and personalize its interactions with each individual customer in real time and drive high-level analytics to attract more customers, and more customers, ultimately, translate into more sales, more revenue, and a more profitable business.
Additionally, CI enables marketing personalization, which is good for everyone involved: Accenture reports that 91% of consumers are likely to shop with brands who recognize, remember, and provide relevant offers and recommendations, while McKinsey reports that fast-growing companies attribute at least 40% of their revenue to their marketing personalization efforts. Therefore, it is clear that customer intelligence, for business and for customers, is a win-win investment!
It’s easy to say that CI leverages customer data to improve business insights. But what exactly does customer intelligence entail, and how does a business do it? To answer those questions, let’s look at the who, what, when, where, why, and how of customer intelligence.
Customer intelligence efforts are used to collect and leverage data throughout the customer journey, meaning it’s used by all customer-facing roles, including marketing, sales, and customer service. CI aims to break down data silos between these departments, with the goal of connecting every customer touchpoint to provide a seamless customer experience.
First, marketers might use customer intelligence to hone in on which communication channels a customer is most responsive to and ensure that the customer sees a different promotion on each channel. This creates a richer, omni-channel, and an efficient marketing experience.
Then, salespeople might use intelligence on a customer to determine what sort of value propositions and sales appeals would be most effective, based on the customer’s demographics, psychographics, and behaviors. This becomes especially important when selling to existing customers, as it enables cross-selling or upselling products or services to a customer based on what they purchased previously.
Finally, customer support centers can leverage intelligence to hone in on the communication channels that are the most effective for solving customer queries and issues. These efforts will help to enhance customer satisfaction and customer loyalty, while also reducing the cost of customer support.
“Customer data” is a fairly broad term. There are actually four main types of data collected and leveraged from customers. In the following paragraphs, we will go through each data type, one by one, to provide an explanation and an understanding of how a business can leverage each type.
As we mentioned earlier, customer intelligence is used by marketers, salespeople, and support agents alike. In other words, CI is used from the beginning to the end of the sales process.
Once a customer has made a purchase, the company is able to use the data it has collected on existing and previous customers to mine opportunities for upselling or cross-selling. By leveraging a customer’s transactional data, a business can use the intelligence it has gained to drive growth at a fraction of the marketing cost.
Additionally, managers and analysts are able to perform customer analytics using the information in the database to derive insights on specific customer segments, or even the business’s customers as a whole. With these customer insights, the company can tweak its marketing and sales strategies on a day-by-day basis to manage and maintain alignment with customers’ shifting expectations.
Since customer intelligence is used throughout the customer journey, it naturally follows that the data is sourced from the entire customer journey. This could be behavioral data from how the consumer acts, transactional data from their final purchase, and demographic and psychographic data from surveys and analyses.
A small- or medium-sized business might simply use a customer relationship management (CRM) software system to collect customer data from its own sales pipeline and derive insights using reports, analytics, AI, or machine learning. However, the main failing of traditional CRM analytics is that it tends to focus primarily on transactional data.
On the other hand, an enterprise-sized business might use a designated customer intelligence software platform, which integrates the data from a CRM with other third-party data sources such as speech analytics from call centers, mouse movements from the customer’s visit to the business website, research surveys, click-through rates from your marketing emails, online reviews, social media, and chat logs.
In other words, the customer data leveraged for customer intelligence can be collected from a myriad of different sources. The sky’s the limit, so it’s up to every business to determine how much data they want to collect, and if they have the infrastructure to collect and to process it.
What is the bottom-line point of going through all the hard work involved in meticulously collecting and piecing together pieces of customer data throughout the customer journey?
Think about it like this: if a stranger from out of town asked you to give them a grand tour of your home city, you might show them the most famous and photogenic tourist locations. While this tour might be satisfactory, the tourist has only seen the “highlights,” but has not seen many things the city might have to offer that makes people enjoy living there.
However, if a close friend asked you to give them a tour of your city, since you know them well, you would have a better understanding of what they enjoy and could direct them to restaurants they’d like, pieces of history they’d be interested in, or local stores they might like to visit to purchase things related to a hobby. Likewise, the ultimate goal of CI is to turn strangers into friends, enabling a better understanding of the sales lead’s individual wants and needs to turn their customer journey into a more personalized experience.
By personalizing each customer’s sales journey, a business can streamline its sales process, tailor its offerings, and develop a strong rapport between customer and business.
According to a study by Adobe, organizations with extensive personalization saw a 54% increase in customer loyalty, 49% increase in revenue, 43% increase in customer retention, and an average return of $3 to $5 per dollar spent per customer. Financially, customer intelligence provides an amazing return on investment in all categories!
Now that we know and understand the ultimate goal of CI, let’s take a look at some actionable ways companies can leverage the data they collect.
By keeping an ear to the ground and analyzing customer data from social media and other channels, a business can gain a clear sense of its reputation in the market, as well as how individual consumers perceive it.
This tells the business what customers are and aren’t satisfied with, helping them adapt their brand image moving forward.
Using demographic, psychographic, behavioral, and transactional data, companies can group their customers into different categories and segments to enact tailored marketing campaigns for each group.
Grouping and segmenting customers improves the chances of generating sales in each category, and it also enhances opportunities to generate, overall, more customer loyalty.
Based on psychographic and behavioral data, a company can identify a customer or market segment’s price elasticity. In other words, the data can be used to help determine how sensitive customers are to fluctuations in price.
With this information, a company can hone in on the most appealing price for each customer and increase the chance of closing a deal for a higher margin.
Using transactional data and previous customer trends, a business can upsell or cross-sell a customer by recommending products they might be interested in based on what they’ve purchased.
This preemptively satisfies the customer’s unvoiced needs and preferences, while increasing the value of the customer’s transactions. This is especially important for businesses that offer hundreds of different products, such as retail stores or entertainment companies.
Now that you have a good understanding of CI, you might be eager to develop your customer intelligence processes. Although this guide provides a wealth of information, there’s no need to feel overwhelmed. Understand that you can start small by collecting customer data in a database that you can use to analyze simple trends, such as identifying lead sources, or segmenting customer groups.
In no time at all, you’ll be leveraging CI to make detailed forecasts and customer journeys, turning sales from a guessing game into strategic business plans and operations.
While both CRM and CI use data to improve customer experiences, it’s better to say that CRM is a tool used to facilitate CI strategies.
CRM software systems help a business collect data from customers, true, but its main purpose is to use that data to help manage individual leads in the sales process. On the other hand, CI takes the aggregation of all that customer information and uses it to derive deeper insights into the business’s customer base. With those insights, the company can adjust its strategy going forward to appeal to more consumers as a whole.
Though more data is generally better for deriving customer insights, the caveat is that customers are only comfortable with companies leveraging information they’ve willingly given to you. Twilio Segment reports that personalization is appreciated by 69% of customers as long as it is based on data they have explicitly shared with a business, rather than data purchased from a third party.
In other words, we’d recommend investing in your own data collection tools such as a CRM, rather than attempting to purchase data from a third party. Not only is this a breach of customer privacy, but the data may be outdated, rendering it useless.
Our biggest tip for leveraging customer intelligence is to have a water-tight and efficient database storage system for your data. You might collect a thousand data points on the customer, but without a clear system for organizing, processing, and leveraging those data points, your customer intelligence will never yield any useful analytics. For the same reason, you should also be sure that your database and processing systems have the capacity to grow as your business does.
Once you have the infrastructure to process massive amounts of consumer data, all that’s left is to collect as much data as possible, and create actionable insights and plans based on your analyses. This means your marketing, sales, and customer service departments should be constantly tapped into your CI system to enact the most up-to-date recommendations.
At this scale, it’s unfortunately impossible to process all of your consumer data by hand. That’s why most businesses purchase designated customer intelligence platforms such as SAS Customer Intelligence 360, Microsoft Power BI, Qualtrics XM, and NGDATA.
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