It can be easy to think of customer experience programs as one homogenous aspiration for organisations, but with a little probing, what often emerges are two discrete types of programs: analytical, and operational CX.

In both cases, CX professionals will use operational data (such as customer attributes, financial data, product data) along with customer interactions, feedback, and social conversations, plus agent and employee feedback, to understand and improve the Customer Experience. Programs are designed to help understand and improve experiences and drive financial or market advantages to the company. But there are significant differences between the two approaches.

Analytical CX

Analytical CX programs are often outgrowths of traditional customer insights, market research, or even agency-led initiatives designed to look for specific answers to specific questions about the customer. Analytical CX programs typically display these attributes:

1. Analytical CX is project based

A project has a discrete objective, desired outcome, and deliverable designed to answer a specific type of question about a product, a service, a marketing campaign, or a customer service initiative. Often the project is timed to a strategic initiative about to be taken or underway.

2. Analytical CX is driven by hypothesis-testing, scientific method approaches

A customer insights analyst might want to test assumptions about customer affinity to a new product. Or hypothesise on the reasons a website is or isn’t meeting customer needs. Using customer feedback, surveys, social content, or conversations, that analyst will test his hypothesis, adapt it if it fails, and iterate until proving or disproving the theory.

3. Analytical CX is performed by analysts or data scientists

This is typically done in a dedicated customer experience function, or by marketing, operations research, or even IT personnel whose day job is to live in the data and analyse it. These are people fluent in many types of research, comfortable with advanced tools, and with wrangling data from diverse sets, often on a whim, to answer the pressing question of the day.

There is a home for Analytical CX in most large organisations. As businesses become more complex, data becomes more diverse, dynamic and increasingly more unstructured, analytical CX professionals provide the technology, tools, and process skills to answer the strategic questions of the day.

Operational CX

Operational CX programs, by contrast, are designed to help organisations manage their own performance to achieve operational goals, business improvement goals or successful transformation goals. Operational CX programs typically display these characteristics:

1. Operational CX programs are ‘always on’ because businesses are always on

They are visible to employees for whom analysing data isn’t a full-time job, but for whom receiving insights to drive continuous improvement and performance to goals is valuable and useful both personally and organisationally.

2. Operational CX programs go through long-term evolution

Just as performance objectives evolve and as business practices and customer interaction channels evolve, Operational CX programs evolve but it is measured in quarters and years, not days and weeks.

3. Operational CX programs aren’t projects with a start and end

They’re initiatives that persist until goals are achieved, and then often persist further to ensure goals are maintained.

Typical CX goals that are aligned to operational CX programs would include:

    • Increasing customer satisfaction, or NPS scores
    • Reducing churn
    • Achieving and/or maintaining product quality, and competitive differentiation
    • Streamlining support procedures to improve first call resolution, increase contact centre deflection from high cost to low cost channels, or to maximise utility and capability of newer support channels such as self-service, mobile apps, or online chat, chatbot, and messaging clients
    • Driving increases in marketing outcomes like brand equity, loyalty, or market awareness
    • Driving increases in sales outcomes like rep sales achievement, or improving sales organisational performance
    • Reducing product safety, financial or regulatory risk

 In an Operational CX paradigm – regardless of the type of outcome an organisation is aiming to achieve – the program is structured using a programmatic approach:

  1. Outcome measures are established (NPS, call centre performance metrics, sales goals)
  2. Input drivers are collected from operational, feedback, and conversational sources. Typically input drivers would include cost information, performance characteristics of agents, sales reps, calls, and most importantly, conversational attributes and feedback attributes extracted from call transcripts, surveys, social conversations, chats, chatbots, and more.
  3. Where needed – input drivers, if contained within unstructured sources such as calls, transcripts, text, etc, are extracted and tagged using text analytics solutions designed for such purposes.
  4. Lastly – reports, and dashboards, based on performance management best practices and templates, are created and disseminated across the organisation to provide performance feedback to staff, management, and executives. These dashboards provide a feedback mechanism so that staff can identify ways to improve to achieve outcomes, and provide management tools to help management and executives manage their teams to achieve their goals.

 To drive CX maturity in an organisation, it’s often easier to start with an analytical approach, but sustainable cultural alignment to CX best practices, and more importantly financial return on CX initiatives (through saving money, improving loyalty, or reducing risk) is most likely to come from an Operational CX approach.

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