The document highlights the significance of including a 'voice of the customer' metric in marketing measurement, specifically through the Social Engagement Index (SEI), which quantifies customer experiences by analyzing social media commentary. The SEI has demonstrated a strong correlation to sales, with evidence showing it as a major driver of brand performance in marketing mix models. Michael Wolfe argues that understanding customer experiences offers valuable insights into brand performance and opens new opportunities for marketers.

1. The Missing Element from
Marketing Measurement

2. Overview
• Marketing-mix models have been a critical tool for
helping marketers understand and quantify marketing
effectiveness.
• Nevertheless, something significant has been missing
from these equations. That missing element has been
the “voice of the customer” or a metric reflecting
customers’ every-day experience with individual brands.

3. Overview
• Michael Wolfe, of Bottom-Line Analytics, illustrates the
importance of this issue and omission here.
• This approach derives a customer-experience metric for
various brands by converting textual experiential
comments from social media into a metric. Called the
Social Engagement Index or SEI, this metric converts
these text into a time based metric using a set of
linguistics and language rules, scoring emotions and
personalization while accounting for special subject-
matter context

4. Overview
• The SEI as a metric has proven to be a strong
predictor. In its application over a dozen categories
and 18 brands, it has shown an average statistical
correlation to sales of 75 percent!
• When employed within comprehensive marketing mix
models, the SEI has shown to be the largest single
driver of brand sales. Within the context that this
metric truly is a measure of the customers’ brand
experiences, this should be no surprise. Providing a
positive day-to-day experience at every usage touch
point is, indeed, a most important driver of brand
performance and sales!

5. The correlation* to sales over time shows the SEI™ has Predictive Power
5
SEI validation: four categories. Strong
linkages and correlations of SEI to sales
Correlation = 86%
Correlation = 84%
Correlation = 81%
Correlation = 83%
Correlation = 83%
*Lead lag analysis has confirmed that causation is only one way – the SEI™ to a large degree is able to
drive hard commercial metrics.

6. Recent Marketing-Mix Model cases show the customer
experience (SEI earned media) as the largest sales driver
44.9%
9.1%4.0%2.2%1.8%2.3%
5.9%
29.8%
Brand Gamma Decomposition of Sales
Baseline
TV
Print
Radio
Owned Digital SEO
Paid Digital Mobile
Paid Digital Search
Customer Experience Earned
Digital Social SEI
54.1%
5.5%1.5%
4.4%
2.1%
2.8%
5.9%
23.7%
Brand Beta Decomposition of Sales
Baseline
TV
Print
Radio
Owned Digital SEO
Paid Digital Mobile
Paid Digital Search
Customer Experience Earned
Digital Social SEI
60.4%
4.5%
2.1%
3.3%
1.1%2.1%
5.3%
21.2%
Brand Alpha Decomposition of Sales
Baseline
TV
Print
Radio
Owned Digital SEO
Paid Digital Mobile
Paid Digital Search
Customer Experience Earned
Digital Social SEI
64.8%1.5%0.2%0.3%3.6%0.1%1.8%
27.8%
Brand Omega Decomposition of Sales
Baseline
TV
Print
Radio
Owned Digital SEO
Paid Digital Mobile
Paid Digital Search
Customer Experience Earned
Digital Social SEI

7. Summary & Conclusion
• This document makes a case that there is an important and
critical missing factor from today’s marketing measurement
and that is a measure of the customer experience. This is a
day-to-day measurement of a customer’s brand usage and
experience.
• By leveraging a highly linked social media metric representing
this customer experience, Michael Wolfe illustrates the size
and important role that the voice of the customer plays in
driving brand performance. By measuring and monetizing
this via a classical marketing mix model, it illustrates a whole
new path of insights possible from this recurring exercise and
also opens an opportunity to better understand the “whys”
behind brand performance directly from the “voice of the
customer”.