Experience data and operational data

Definition

When talking about customer experience data, it is often described as there being two primary types: operational data and experience data. It’s essential to understand the difference between the two to use them effectively.

Operational Data

Operational data refers to the data that pertains to the functioning and performance of a product or service. This type of data is collected automatically by an organization’s systems, and it helps in analyzing performance levels, identifying errors, and overall operation of the organization. This data is usually structured, collected in a centralized database and is decision-oriented. Examples of operational data include sales data, inventory levels, website traffic, and customer churn rates. This type of data is useful in identifying areas that need improvement and also in studying past trends to improve future performances.

Experience Data

Unlike operational data, experience data is subjective and usually based on customer interaction and feedback. It refers to the data collected from customer feedback, reviews, surveys, behavioral data, and social media interactions. Experience data helps marketers to gain insights into how customers feel, their thoughts, and opinions about a brand, product, or service. Experience data is primarily collected through qualitative research and is unstructured, context-dependent, and subjective. Examples of experience data include reviews, social media comments, and customer service feedback.

Why Both are Important

Both operational and experience data are crucial to enhance customer experience and boost the bottom line of any business. Operational data helps businesses understand how the company is performing, identify bottlenecks, and streamline operations to optimize performance. On the other hand, experience data enables businesses to gain insights into customer sentiment, understanding what drives customer loyalty, and areas for improvement. By combining both operational and experience data, marketers can tailor their campaigns to the needs of their customers, improving their experience.

How to Leverage Both

One effective way to leverage operational and experience data is to integrate them into a centralized system. For instance, by integrating data from customer service queries with operational data such as sales data, businesses can identify correlations between a particular product or feature and customer dissatisfaction. This means that leveraging both types of data is essential in building a strategy that leads to customer satisfaction, enhanced customer experience, and ultimately increased revenue.

Data is a crucial part of the marketing world, and understanding the difference between operational and experience data is essential to unlocking actionable insights. Operational data focuses on the performance of an organization, such as revenue, whereas experience data provides marketers with customer sentiment insights that strategic decisions towards customer satisfaction. By combining both data types, businesses can tailor campaigns towards their customers uniquely, leading to improved customer experience, increased brand loyalty, and ultimately greater revenue.

Related

Resources

House of the Customer (2023) by Greg Kihlström

The Agile Brand Guide: Marketing Measurement & Analytics by Greg Kihlström is available in print and digital.