What is customer intelligence?
Customer intelligence (CI) is the collection and analysis of large amounts of data that organizations use to determine the best, most effective ways to interface and interact with their customers. Details and activities that are gathered about customers are analyzed to gain deeper understanding and build more meaningful business relationships.
What are the business benefits of customer intelligence?
CI continually builds loyalty and return business by preemptively engaging and proactively guiding and optimizing offers across all customer touch points. It also increases retention by offering the most relevant information and seamless experiences. Additionally, it delights users by offering dynamic customer context via relevant, personalized and targeted interactions. CI maximizes return on investment by targeting the most valuable customers.
Why is customer intelligence important?
A comprehensive view of customers requires integrating multiple sources of data to generate deep insights into behavior. Enter customer intelligence, a sophisticated customer analytics ecosystem that helps businesses deliver superior customer experiences across all channels. A robust CI solution provides actionable recommendations for managing relationships. By integrating multiple data sources and systems, it generates a profile for each individual, understanding what drives their choices and guides them to their next best action.
What are some specific facets of business performance that CI can improve?
Customer Intelligence can create flexible technology platforms that enable organizations to apply data analytics and machine learning opportunities and:
- Expand cross-selling and upselling. By analyzing customers’ propensity for new offerings, companies can forecast campaign effectiveness and fine-tune channel marketing. This work is performed autonomously, relying on machine learning model improvement. Benefits include better campaign sales rates, lower marketing costs and greater visibility into marketing ROI.
- Apply agent/channel analytics. Applying analytics to customer behavior by channel and by salesperson or agent, businesses can optimize how they serve customers and measure ROI. This helps increase revenues, adapt and enhance services, increase satisfaction and improve agent effectiveness.
- Optimize contact center operations. Analytics that gauge the effectiveness of call centers identify ways to reduce costs, optimize customer experiences through their preferred channels and identify causes of leakage.
- Qualify leads from third parties. Improving how to qualify leads from campaigns and third-party data can increase marketing resource effectiveness and increase customer satisfaction.
- Mitigate customer attrition. Identifying at-risk customers and the drivers of attrition. Automated monitoring of at-risk customers provides insights that suggest preemptive actions.
- Re-imagine brand loyalty. With comprehensive data on consumer behavior, organizations can personally acknowledge and reward each customer at all touchpoints of consumption to build connection and brand love.
What are some real-world examples of how companies have used customer intelligence to boost performance?
Here are a few…
A national specialty retailer enriched more than 80% of its consumer records and established affiliations, linking transaction data with master data to improve campaign effectiveness, leading to a 14% improvement in response rate.
A national insurance company improved qualified prospect identification by 45% by creating a single customer view to identify qualified prospects for customized offers from a universe of over 120 million members.
To enhance customer experience and increase conversion rates, a national financial services firm performed seamless, automated data integration among various data capture, analytics and targeting tools, enabling them to personalize targeting for 97% of known customers and achieve an ROI of 25%.
To fine-tune its existing loyalty management programs, a leading beauty products and services company created personas for 6 million customers by demographic profile, purchase behavior and unmet needs.
An intelligence and analytics solution enabled a global automaker to better understand customer behavior patterns. The solution increased cross-selling and upselling opportunities by analyzing 13.5 million sales and service survey response records.