‘Loyalty’ is a soft word in business – similar to ‘culture’ and ‘leadership.’
Yet we intuitively know it matters but have difficulty quantifying how much it matters.
A new era of metrics, modeling, and accounting is ahead of us as we head into the era of ‘consumer capitalism’ where a customer base becomes a company’s primary long-term asset.
Why Loyalty Metrics Matter
100 years ago, loyalty was the only thing holding businesses back from bankruptcy. In an era where telephones were in their infancy and the passenger car was a novel innovation, businesses built trust with local customers by sourcing high-quality products and delivering on a high standard of service.
In turn, they were rewarded with customer loyalty and word-of-mouth marketing. As the Baby Boom began, many of these businesses hit their stride and began decades of expansion in their local and national markets.
It wasn’t until we began to enter the era of LBOs (leveraged buyouts) and Wall Street’s tricks that we began to see the beginnings of the ‘global brand.’ Propelled by large amounts of liquidity and ruthless standards, the goalposts suddenly shifted from customer-centric to shareholder-centric.
It wasn’t until we began to enter the era of LBOs (leveraged buyouts) and Wall Street’s tricks that we began to see the beginnings of the ‘global brand.’ Propelled by large amounts of liquidity and ruthless standards, the goalposts suddenly shifted from customer-centric to shareholder-centric.
HBR – The Loyalty Economy
Without getting into a philosophical debate about the purpose of business, it became clear that dumping loads of capital behind business leaders whose unilateral focus was to ‘maximize shareholder value’ shifted executive incentives away from customers and towards shareholders. Cost-cutting, outsourcing, and everything else linked to the globalization business model soon became the ‘trends.’
Price became the ultimate variable, and as a result, accountants and finance departments began working towards shifting the bulk of its work towards maximizing short-term, quarterly earnings.
A Shift Back to Brand Loyalty
Now in the digital age where you can measure and track everything in business, we are starting to see a shift back to loyalty. Not in a hokey advertising way, but in a way that customer loyalty itself becomes an asset, one that informs the expected future cash flows and ultimately the value of the business in the future.
“Customer value” has several definitions. I use the term to mean the total lifetime value of a company’s customer base. Companies can increase this value by acquiring more customers, earning more business from existing ones, retaining them longer, making their experience simpler (and often less expensive to deliver) through digital improvements, and so on.
HBR – The Loyalty Economy
NPS (Net Promoter Score)
Performance can be tracked in a number of ways. For example, Net Promoter Score (NPS) is standard way for marketing teams to measure customer satisfaction with a given product or service. You will often see this type of NPS survey delivered by email or in-app when they ask you ‘how likely are you to recommend this product/service to a friend?’
There will be different benchmarks for NPS depending on the industry, but generally, it can be assumed that a business with many Promoters (ie. loyal, enthusiastic customers) will see strong growth and financial performance. Naturally, NPS is not a perfect metric and has many flaws; however, it is a starting point and certainly an indicator for expected future performance.
My research shows that loyalty leaders—companies at the top of their industries in Net Promoter Scores or satisfaction rankings for three or more years—grow revenues roughly 2.5 times as fast as their industry peers and deliver two to five times the shareholder returns over the next 10 years.
HBR – The Loyalty Economy
A lot of research is now focusing on how such metrics (NPS, etc.) correlates to financial performance.
Given that several avant-garde public companies have begun to disclose certain loyalty metrics (obviously the ones they deem to be favourable), there is a new body of academic and capital market’s research being conducted to better understand behavioral and transactional metrics about a given company’s customer base.
But most companies neglect such an obvious benefit because they haven’t acquired the capabilities to manage customer satisfaction, and it’s difficult to promote such an ideal over short-term shareholder value.
Nomad Group
In theory, this data can then be modeled and essentially become predictive of future performance. Questions abound, however, as to what that data will look like and how it will be standardized. To start, we highlight below a simple benchmark that could be applied to almost every business (product or service), before diving into more advanced analytical models.
Likewise, disclosing the volume of purchases and retention rates among the top 20% of customers relative to the remaining 80% would materially improve investors’ ability to value a company’s customer base.
Customer-Based Corporate Valuation (CBCV)
The work by Peter Fader – who sold Zodiac to Nike and is now running Theta Equity partners – focuses on using transactional logs in non-subscription businesses to model future cashflows using certain assumptions.
What do we need to implement CBCV?
The model consists of 4 interlocking submodels governing how each customer of a firm will behave:
• the customer acquisition model, which forecasts the inflow of new customers
HBR – The Loyalty Economy
• the customer retention model, which forecasts how long customers will remain active
• the purchase model, which forecasts how frequently customers will transact with a firm
• the basket-size model, which forecasts how much customers spend per purchase
Certain elements like customer acquisition and basket-size model will be easier to predict than others such as customer retention and how frequently customers will transact with a firm. We broke down the CBCV paper written by Fader et al. in some depth in an earlier post, which uses advanced statistical modeling and analytics to calculate CBCV for publicly traded firms.
Accounting for Loyal Customers?
This assumes that companies have both the data available and the finance and accounting teams in place to break that data out into their quarterly reports.
While the more rigorous calculations are really only feasible for medium and large-size firms, the basic premises can be applied to even small firms who are collecting customer data using CRM (customer relationship manager) software and transactional logs.
Using the CBCV approach, revenue numbers no longer exist in a vacuum. Instead, they are a direct function of a small set of behavioral drivers—in this example, total customers acquired, retention dynamics, and average revenue per user (ARPU). This framework makes revenue forecasting easier and serves as a diagnostic, helping managers and investors understand where the value creation is coming from
HBR – The Loyalty Economy
From a capital market’s perspective, this type of data can be broken out to help find the future stars and diagnose deficiencies in the current portfolio.
Overall, the CBCV is a new and novel approach to calculating the value of a customer base (and thus a firm) using advanced statistical and analytical techniques. Finance departments of the future may begin playing around with their own customer models, but for now most of this data is held in the marketing and executive branches. This creates its own set of challenges that will need to be addressed in creative ways going forward.
Customer Capitalism – Accounting
We won’t truly enter the age of customer capitalism until financial-accounting standards bodies enact rules that require reliable, auditable disclosure of customer-relationship health.
HBR – The Loyalty Economy
It is always impossible to predict when these types of ‘loyalty metrics’ will become standard in financial disclosures of publicly-traded companies.
Not only do financial standards boards have to determine what metrics are required, they then have to determine how those metrics will be integrated into current standards and enforced (ie. make them auditable).
Furthermore, some jurisdictions will decide to implement them before others and then the typical problems in accounting (ie. non-GAAP vs. GAAP) will emerge.
For now, it is enough to start thinking about how to storify this data in a concise way. Different industries have their own unique types of customer bases, and within those industries, each company has its own style and strategy for acquiring and retaining customers.
If you’re an executive and you aren’t currently disclosing your customer metrics, start thinking about the story they would tell if disclosure were required
HBR – The Loyalty Economy
Customer Acquisition and Retention
Ultimately, painting a story about customer acquisition and retention can be done with a specific set of fairly simple metrics (ie. new customers, repeat purchases). However, as was discussed above, looking at your top 20% of customers and their purchasing behaviors can sometimes lead to the most insightful data points.
80/20 Rule and Loyalty
This type of Power Law (typically the top 20% drive 80% of the volume) is visible in some businesses more than others, but analyzing the top subset of a customer base (ie. based on volume or goods purchased) almost always leads to actionable insights for the executive team.
Whether those insights will be required (or strongly recommended) to be disclosed public investors or to private investors is TBD (to be determined).
I don’t think you’ll see standardized, fine-tuned Net Promoter Scores as part of corporate financial statements any time soon, but some information about customers will probably be required in the not-too-distant future in the management disclosure and analysis (MD&A) section of the annual report or in the footnotes.
HBR – The Loyalty Economy
Loyalty as a Future Performance Indicator
Nonetheless, we have seen in this post that customer loyalty is a future performance indicator, and understanding it in greater detail can have benefits for the business in the short, medium, and long-term.
The 1st step is to analyze it, the 2nd step is to put one or two metrics around it that can be tracked, and the 3rd step is to shape those metrics into the narrative that gets discussed among executives, investors, and potentially even public markets.
Overall, we are seeing loyalty metrics becoming more sophisticated as businesses and investors alike seek to better understand how this data can inform strategy and predict future performance. Much work is to be done, but this field may help us unlock insights and reshape frameworks around the pursuit for profit in the global economy.