The best measure of business success on the market today might be one that’s been hiding in plain sight for 30 years. Customer Value (CV) is a primary KPI that can keep you relevant through even the most volatile markets, and most companies still overlook it in favor of quick and easy conformity checks.
In this article, we’ll look at how and why it handily beats its most popular contemporaries, Customer Recommendation and Customer Satisfaction.
Customer Value has over 30 years of research behind it and is considered one of the foundations of modern business measurement. It is the most comprehensive and predictive measure of future customer behaviors and loyalty.
However, one of the reasons Satisfaction and Recommendation are still in use is that the market has yet to offer a service that can effectively operationalize Customer Value.
One reason for this is that CV has historically been difficult to measure. A concrete measure of Customer Value that is actionable couldn’t be produced fast enough to be timely and relevant.
As a result, companies have often looked for compromises, such as speed over accuracy, or short-term ROI over longevity.
This has led to Customer Recommendation and Customer Satisfaction becoming the most widely prevalent measurements due to their simplicity and ease of use.
However, two recent and major changes have made it possible to apply Customer Value on a larger scale:
- Technology has advanced to the point where tracking CV is fast and cost-efficient enough to be viable at the enterprise level, thanks to the development of AI and Natural Language Processing tools. The main drawbacks of using CV are quickly disappearing.
- The risks of overreliance on either Satisfaction or Recommendation have become more widely known, as multiple companies who were once household names have seen their Sat./Rec. scores climb while at the same time losing market share.
For the first time, it is possible to consider Customer Value as a primary measurement. Therefore, it is crucial for businesses to understand the practical distinctions between Customer Value, Satisfaction, and Recommendation.
Satisfaction and Recommendation are useful measurements when applied correctly, but they are both contained within Customer Value.
A Customer Value-based strategy can achieve all the benefits of both Satisfaction and Recommendation and more, but the reverse is simply not true.
Customer Value is a measure of the trade-off between benefits and costs perceived by the customer when considering a supplier’s offering and market alternatives. It is the ultimate factor behind customers’ decisions of expenditure and loyalty to any business.
Different customer profiles value different things, such as relative costs (including dollars, emotional/physical effort), benefits (product/service quality), market alternatives (direct and indirect competitors), and external influences (market conditions, geography, weather, etc.).
CV also accounts for external factors that companies have little to no control over, such as climate, socio-economic issues, politics, pandemics, or market innovation and disruption.
While these factors cannot be controlled, tracking their influence on CV can create opportunities to innovate and provide a more complete picture of the environment in which customers make decisions.
• Holistic measurement: Customer Value accounts for all the trade-offs that a customer makes before deciding to purchase a product or remain loyal, including relative costs (dollars, emotional/physical effort), benefits (product/service quality), market alternatives (direct and indirect competitors), and external influences (market conditions, geography, weather, etc.).
• Strategic overview: Customer Value provides a complete strategic view of customers, reaping the benefits of both Satisfaction and Recommendation while covering their weaknesses.
• Outside-in customer perspective: Basing insights directly on the customers’ perspective removes the potential for internal biases. The customer can express their needs, wants, and expectations directly to the company without interference.
• Qualitative insights at a quantitative scale: By using AI and Natural Language Processing tools, it is possible to gather and analyze large amounts of customer feedback in a timely and cost-effective manner.
• *Difficult to measure: Traditionally, it has been difficult to produce a concrete and actionable measure of Customer Value that is timely. *However, this weakness is removed with the right technology and implementation.
- Easy to measure: Customer Satisfaction is relatively easy to measure, as it can be assessed through surveys or other simple channels.
- Useful as a conformity check: Able to verify if your processes are being executed correctly.
- Narrow focus: Customer Satisfaction only measures how happy customers are with a specific product or service, rather than considering all the trade-offs they make before making a purchase or remaining loyal.
- Subjective: Customer Satisfaction can be subjective and influenced by personal biases, making it less reliable as a measure of long-term customer behavior.
- Time to relevance: The survey questions often take time to prepare, and by the time it’s created and approved, the questions may no longer be relevant to customers.
• Low cost: Gathering Customer Recommendation data is generally low cost, as it can be done through social media or other online platforms without much effort.
• Provides insights into customer loyalty: Customer Recommendation can provide insights into how loyal customers are to a company and how likely they are to recommend it to others.
• Narrow focus: Similar to Customer Satisfaction, Customer Recommendation only measures willingness to recommend rather than considering all the trade-offs they make before making a purchase or remaining loyal.
• Subjective: Customer Recommendation, like Satisfaction, is subjective and influenced by personal biases for the same reasons.
• Non-strategic: Because of its subjectivity, Recommendation can vary highly from one specific interaction to another, making it unreliable for determining long-term strategy.
• Not 100% representative of personal preference: Customers may recommend products or services that do not necessarily align with their own personal needs or values, leading to inaccuracies.
• Not a lasting indicator of overall success: High levels of customer recommendation do not guarantee company success, as customer needs and preferences can change quickly. Companies often deploy Recommendation surveys as a conformity check to make sure operations are working as expected, but it is only a surface-level indicator of health. Much like a thermometer, it’s useful but cannot substitute for a doctor’s evaluation.
Verdict: What’s the best measurement?
With the right tools, Customer Value provides a holistic view of the trade-offs that customers make before deciding to purchase a product or remain loyal.
It takes into account all the factors that influence a customer’s decision, including relative costs, benefits, market alternatives, and external influences.
By gathering and analyzing customer feedback through AI and Natural Language Processing tools, it is possible to gather and analyze large amounts of data in a timely and cost-effective manner.
On the other hand, Customer Satisfaction and Customer Recommendation are relatively easy to measure but have a narrow focus, only considering a specific aspect of the customer experience.
They are also subjective and influenced by personal biases, making them less reliable as measures of long-term customer behavior.
In order to make the most informed decisions, it is important for businesses to consider all three measurements. While Customer Satisfaction and Customer Recommendation can provide valuable feedback, a Customer Value-based strategy can achieve all the benefits of both measurements while also covering their weaknesses.