Customer Intelligence Examples: How to Gain Better Customer Insights
What do 91 percent of consumers have in common? The fact that they say they are more likely to make purchases from brands that personalize offers and tailor recommendations to potential customers than from those that do not. To reach those consumers in ways that are motivating to them, brands need clear insight into customer analytics.
Enter customer intelligence: the process of customer data collecting and analytics to facilitate decision-making that improves the customer experience and enhances a brand’s success. Customer intelligence data may include purchase history, interactions with brand representatives such as sales team members or customer service employees, and social media or website engagement. The better a brand’s customer analytics and customer intelligence strategy, the better they can serve consumers.
How to Build a Customer Intelligence Strategy
Most companies, including small businesses, collect customer data in some form. However, collecting the right information and analyzing it to create actionable insights is another story. Studies show that 60 to 73 percent of enterprise data is never analyzed, which leaves a wealth of information unexplored and unable to be acted upon.
A clear customer intelligence strategy can help brands understand the information at their fingertips and make the most of it. Here are five steps to building an effective customer intelligence strategy:
- Determine your objectives
- Audit current data collection sources
- Select a data analysis platform
- Act on insights
- Monitor and hone the process
Consider each of these steps a bit more in-depth.
Determine Your Objectives
Leaders need to know what questions they are asking and what the use of the answers will be. Customer intelligence can help brands answer questions like:
- Why are a high number of shoppers leaving items in their carts?
- Which promotions are driving customers to the company website?
- How are customers reaching out for support?
By setting the parameters for data collecting and analysis according to a specific question or challenge, brands can increase their chances of gaining actionable insights that address their specific situations.
Audit Current Data Collection Sources
The next step in building a customer intelligence strategy is analyzing the data collection sources a brand already has in place. These may be existing software platforms, website and social analytics, or spreadsheets. Identifying all data collection sources can help companies determine if they have gaps in their data. Perhaps a corporation has a large amount of demographic information but little record of interactions with customers. Maybe customer service conversations are only in unsearchable transcript form.
A clear view of the data collection sources a company already has—as well as how effective they are—will help business leaders determine the right changes to make.
Select a Data Analysis Platform
With objectives and existing collection sources in mind, it’s time to select a data analysis platform. While some companies may choose to employ a full data science team for the sake of a more manual process, most organizations will find that a software solution providing customer insights management and analysis will be more efficient and cost-effective.
Such software leverages data analysis, business intelligence, and machine learning to reveal patterns and insights. These solutions accessibly present trends, patterns, and insights for data-driven decision-making and greater business agility.
Act on Insights
Perhaps data revealed that customers are leaving items in their carts due to slow page-loading during the checkout process. Maybe a personalized offer succeeded in March, while the October attempt went poorly.
Insights like these can empower company leaders to focus on the right challenges, systems, and goals. By revealing patterns, trends, and meaningful perspectives on customer behaviors, customer intelligence tools illuminate the right next steps to take. The insights may reveal that a brand voice is succeeding in email while flopping on social media, that certain days of the week have the highest marketing campaign response rates, or that there’s a gap in the customer service workflow. With this knowledge in hand, company leaders can focus on making the right changes.
Monitor and Hone the Process
Implementing a customer intelligence strategy and platform is a critical task for modern organizations, but it isn’t something to set in motion then leave alone. Scheduling regular reviews of the strategy and gathering feedback from various company departments will help companies refine and improve their customer intelligence collecting and analytics system. Treating customer intelligence as an iterative, evolving process is key for organizations that want to engage in digital transformation holistically and thoroughly.
Customer Intelligence in the Real World
From the banking sector to amusement parks and the automotive industry to high-end cosmetics, customer profiles, transactional data, and other forms of customer intelligence are sparking success throughout the marketplace. Consider four examples of customer analytics put to use in the real world.
Make New Friends but Keep the Old: Increasing Customer Retention and Recruitment in Banking
NCBA Bank wanted to serve its 32 million customers with excellence, but its marketing and CRM processes were hurting rather than helping. In an attempt to reduce silos and better support their customers, the bank’s leaders turned to tools from Oracle for campaign management, behavioral intelligence, and data management.
Oracle’s applications helped the bank track and influence customer activity, tailor messages to address customer needs and keep customers engaged. As a result, NCBA has seen a 200 percent improvement in email open rates, a 20 percent decrease in customer churn, and a doubling of qualified leads.
Data-Driven Drives for Detail-Driven Drivers: Enhancing Personalization in Vehicle Sales
Bentley Motors is known for producing cars that are designed and built to customer desires so specifically that no two vehicles are the same. In an effort to achieve effective digital transformation and self-service data analytics that expand this personalized approach, Bentley leveraged Salesforce and Tableau software that connects customer data sources and then visualizes them.
As a result, Bentley’s chief data officer, Andy Moore, says that the company now has “a true understanding of every customer touch point…We’re no longer meeting [a customer] for the first time every time. Moore says that the customer intelligence tools have drastically reduced data processing time for tasks like reporting. The software has also generated better communication between departments, as employees across marketing, technology, and the shop floor can view, discuss, and take action based on shared insights.
Simply the Best: Matching Luxury Products with an Exceptional Experience
When Japan’s Kao Corporation wanted to grow Molton Brown Limited, one of the leading brands in the company’s global luxury cosmetics portfolio, company leaders knew they should focus on customer experience. The Molton Brown brand is centered on creating peaceful, long-lasting products made of the best bath and body ingredients. The company’s legacy e-commerce system, however, was anything but calming. The system could not handle high web traffic, quickly share customer data with supply chain, or provide key functionality consumers expect.
Kao turned to SAP to harmonize the brand, its online storefront, and the backend data management. With a new cloud solution and customer engagement platform, Molton Brown enhanced personalization, site speed, and traffic management. These improvements, paired with better delivery options, loyalty program functionality, and an enhanced checkout process, led to a conversion rate lift of over 30 percent. The company also surpassed its Black Friday and Cyber Monday goals in addition to creating significant technology investment savings as SAP products require less hardware, software, and maintenance than prior systems.
Up to Par: Improving Customer Service for a Growing Golf Club
The United Kingdom’s Junkyard Golf Club started out as a local popup offering a one-of-a-kind indoor golf experience in a club-like environment. The company grew quickly as demand soared, but Junkyard Golf Club struggled to keep up with the rising customer service demand.
They implemented Zendesk tools. Customer satisfaction rates soared as the solution empowered communication and captured customer service needs to be analyzed, acted upon, and used as material for self-service articles that empower customers with the information they need. With Zendesk, the company went from handling 3000 tickets per month with an average first response time of 48 hours to 9000 a month with dramatically reduced response time—eight hours on email, 30 minutes on social, and less than one minute on chat.
Become a Customer Intelligence Leader with an online Doctorate of Business Administration from Marymount University
Organizations that leverage customer behavioral data into meaningful insights outperform their peers by more than 25 percent in gross margin and 85 percent in sales growth. The online Doctor of Business Administration (DBA) in Business Intelligence program at Marymount University equips data-savvy professionals to leverage customer intelligence as change agents in an ever-changing marketplace.
In a course titled Maximizing Digital Transformation, for example, students learn to improve operations using technology solutions, including customer intelligence tools. The curriculum covers managing organizational shifts that occur when companies “go digital” and equips students to develop effective digital strategies.
The fully online, cost-effective DBA in BI from Marymount University Online can be completed in as few as three years. Become a BI expert with a DBA in Business Intelligence from Marymount University Online.