Customer experience management (CXM) enables companies to deliver experiences that delight people. Because exceptional customer experiences are highly personalized to the individual, data analytics plays a vital role in CXM. When used effectively, data can help companies better understand customers' needs and preferences so they can craft the kinds of personalized experiences that retain loyalty.
What is customer experience management?
Customer experience management is a cross-functional collection of strategies and tactics designed to improve customer happiness and loyalty. It hinges on providing highly customized communications, offers and service tailored to each customer. Modern organizations are leveraging customer data from various touch points supplemented by demographic information and data from third-party sources.
Customer experience management is often confused with customer relationship management (CRM). Although they share some commonalities, their purposes are distinct. The emphasis of CRM is on making a company more profitable by improving the efficiency of maintaining customer relationships, while CXM seeks to boost profitability by improving customer engagement and increasing desired buying behaviors.
These differing priorities are also reflected in how customer data is used for each. With CRM, data is analyzed to identify trends, KPIs and statistics that provide insights related to the big picture of sales and service. In the case of CXM, data is analyzed at the individual customer level and used to improve a customer’s experience across the engagement life cycle—spanning acquisition, retention and loyalty.
The role of customer experience analytics in CXM
Customer experience surveys remain a mainstay of many businesses' efforts to better understand consumers’ needs and desires. While survey-based measurements are valuable, these methods paint an incomplete picture. Customer experience analytics help create a more comprehensive view. Here are five business benefits customer experience analytics help companies achieve by accurately gauging the needs of their customers and assessing how they view their products and services.
Deepen customer insights
Customer experience analytics coalesce all relevant customer data, including activity on websites, apps and social pages; purchase and return history; and messages sent via contact forms and online chats. When analyzed together, this data enables brands to uncover important insights such as buying trends, unvoiced pain points and communication preferences.
Provide highly personalized experiences
All marketers make assumptions about their target audiences. While these assumptions are sometimes correct, they often are not. Customer experience analytics allow a company to uncover what’s really going on with customer needs and preferences. For example, a vitamin and supplement brand may learn that its line of electrolyte powders is favored by avid hikers. This insight can then be used to create personalized marketing campaigns launched at the beginning of the spring hiking season, personalized to the customer segment identified as hiking enthusiasts.
Strengthen customer loyalty and increase customer lifetime value
Highly engaged customers produce more value over a longer period of time. Companies that use data to provide truly customized experiences earn the loyalty of customers who appreciate the attention to their needs and preferences. In addition to inspiring personalized product recommendations and offers tailored to specific customers, data analytics can provide front-line personnel with helpful information about individual customers and ideas on how to best engage with them.
Reduce customer churn
Building customer loyalty also entails providing world-class support when things go wrong. Customer experience analytics can help companies proactively engage customers at a high risk of attrition. For example, customer service teams can receive automated alerts when an order takes longer than normal to fulfill so a representative can proactively offer the customer a discount on a future order to strengthen their trust.
Monitor the success of customer engagement efforts
Accurate measurement of the effectiveness of customer engagement efforts helps decision-makers determine which programs are most useful and which ones need to be retooled or scrapped. With the insights gleaned from customer data, business leaders can make more customer-focused business decisions and better allocate resources.
Barriers to exceptional customer experience management
Data is the driving force behind all successful customer experience management programs. Armed with the insights that customer data uncovers, businesses can create customer experiences that build brand loyalty and increase revenue. But for many organizations, legacy data infrastructure stands in the way of integrating this holistic, customer-focused approach across all areas of the business. Here are four barriers CXM helps organizations overcome.
Siloed data
When customer data is stored across multiple departments or locked away in disparate systems, it’s impossible to see a complete picture of each customer. Cloud data platforms create a single source of truth, providing a secure yet accessible location to house and work with all relevant customer data.
Poor data diversity
In-house data plays a crucial role in improving the customer experience. But companies benefit most when they can also access external data, including information from social media sites, partner organizations and third-party data marketplaces.
Insufficient data storage and compute resources
The sheer volume of data available today requires substantial storage and compute resources. Legacy systems struggle to meet the resource requirements of modern customer experience management. To take advantage of all the value data can offer, companies need a cloud data platform that provides the significant storage and compute power required to handle intensive data analytics tasks.
Inability to scale
As businesses grow, their data needs grow along with them. Legacy systems rely on on-premise hardware and software, making them difficult to scale. In contrast, cloud systems are flexible and can scale up and down as needed to ensure available storage and compute resources meet the needs of the business.
Poor data security and governance
Storing and analyzing customer data requires robust data security and governance standards. By nature, on-premise systems are difficult and costly to secure. Cloud data platforms, however, are purpose-built to comply with industry standards for data security, and offer powerful governance controls.
Empowering customer experience management with the Snowflake Data Cloud
With the Snowflake Data Cloud, companies can arrive at insights faster, improve customer experience management and ultimately increase customer lifetime value. In addition to enabling deep customer insights by unifying fragmented data, Snowflake makes it easy for companies to access and activate data to power segmentation models, recommendation engines, and other artificial intelligence and machine learning investments.
See Snowflake’s capabilities for marketing and customer experience. To give it a test drive, sign up for a free trial.