Every CEO has a ready answer for what makes the company different. Great service. Good people. Strong relationships. The trouble starts when you ask how they know. Do customers say so? Does anyone check?
Jaynie Smith has been poking at that gap for a long time. She runs Smart Advantage, a consultancy based in Fort Lauderdale, and by her own count she has looked at 250 companies over 25 years, backed by more than 30,000 customer interviews. What kept turning up was the same thing. Firms sound sure of their edge, but there’s rarely proof that buyers agree.
Strength versus advantage
Smith keeps her definition short: a competitive advantage is the reason people do business with you. Notice whose opinion counts there. Not management’s. You might be proud of your engineering or how fast you answer the phone, and that makes it a strength. It turns into an advantage only when buyers weigh it heavily when they buy, you beat the alternatives on it, and your own performance numbers back that up. She calls those numbers Customer Relevant Indicators™, or CRIs™.
This shows up in everyday work. A website opens with “best quality,” and so does every competitor’s. A sales rep burns twenty minutes on the company’s 50 years in business, which the prospect never asked about. When a company can’t say what it does better in terms a buyer cares about, the talk slides to price. Smith makes this case in her book Creating Competitive Advantage (Doubleday, 2006), and it’s still in print twenty years later.
Vague language doesn’t help. Take “great customer service.” One executive hears fast callbacks, another hears free shipping. If people can’t agree on what it means, nobody can measure it, and a claim without a measurement falls apart the moment a skeptical buyer pushes on it.
What customers know that insiders don’t
Nobody inside the building sees all of it. The CEO sees strategy, sales hears the objections, and the warehouse crew knows what a delivery really takes.
Customers use their own checklist: how fast the vendor responds, whether the order arrives right, how much the supplier knows, how much risk lands on the buyer. Decent customer research asks everyone the same questions and reaches enough people to matter. It also works better when the interviewer has no stake in the answers, which is the idea behind double-blind research. Then the results can be compared, and you can finally see which attributes rank highest and where you stand on each.
A small caution. Smith’s numbers come from her own client work across many industries and company sizes. They show a pattern. They aren’t one controlled study.
Four blind spots
Leaders guess wrong. Smith reports that 95 percent of the businesses she surveyed didn’t know their customers’ top buying criteria. That’s her result from her own projects, where what customers valued was set against what internal teams had assumed.
The metrics miss the point. Say the leadership team did know the criteria. Many would still have nothing to measure them with. Companies count what’s easy to count: call volume, throughput, sales by region. You can follow a dozen internal numbers and not one of them touches why customers actually buy.
Executives disagree. According to Smith, agreement inside most companies on their own advantages is little to none. Test it yourself. Ask the CEO, the head of sales, the marketing lead and an operations manager separately, then compare. If the answers differ, the market gets mixed messages. Marketing promises speed, sales hands out discounts, and operations are told to cut costs.
Nobody audits the numbers. Smith says most companies she’s seen are sitting on landmines or goldmines. A landmine is a hidden hazard: one term defined three ways by three departments, a spreadsheet no one has touched in years, an average covering up a steady decline. A goldmine is the opposite, a real strength sitting in a report nobody reads.
And these feed each other. Leaders who don’t know the buying criteria choose the wrong metrics. With no shared evidence they argue. With no agreement on what matters, nobody checks the data.
Picture this
A regional equipment distributor thinks fast delivery is its edge. Then someone looks closer. Three departments report three different on-time rates: one counts from the order date, one from the ship date, one against the date the customer asked for. The company has been promising a figure it can’t reproduce.
Now add customer research showing buyers care more about technical advice while choosing equipment than about speed. And the distributor’s field engineers happen to solve those questions on the first contact more often than anyone ever tracked. So the company has been advertising a shaky strength while sitting on a real one. Once both facts are out, the website, the sales pitch and the dashboard all have to change.
From findings to decisions
Evidence like this can shape most parts of a business, though nobody should count on a guaranteed financial return. The website can lead with attributes buyers rank highest and the company can document. Sales presentations can open with proof instead of adjectives. Marketing money can follow the criteria that really drive choice. Product and service teams get a simple test: does this improve something customers value? Operations can add dashboard measures tied to those priorities, and leaders can brief the whole company from one set of facts. It helps with spending choices too, since money going into a supposed strength can be weighed against how much buyers care about it.
A seven-step approach
Write down what leadership believes about why customers choose the company. Each department answers separately.
Find out which buying attributes matter most to real customers and prospects, using solid double-blind research.
Compare your beliefs with the research and mark where they differ.
Audit the definitions, reliability and usefulness of the metrics tied to those attributes.
Line departments up behind the differentiators the evidence supports.
Turn the findings into specific sales, marketing and operations actions, each with an owner.
Go back to the evidence regularly. Customer priorities change.
Where AI fits
Plenty of companies are now pouring their data into AI tools, and those tools work with whatever they’re given. If definitions are inconsistent or records have gaps, the output can read nicely and still rest on shaky numbers. Smith’s view is that AI inherits the discipline a company’s systems already have. Practically, that means agreeing on definitions and checking the data before automating any decision, and keeping people in charge of questioning what comes out.
The advantage you can prove
Anyone can claim an advantage. Proving one is work: learning what customers value, measuring performance against it with data that holds up, and getting the leadership team to act on what the evidence says. Some companies will learn that a favorite strength barely registers with buyers. Others will find strengths they’d overlooked. Either result beats the assumption that came first. If you want to follow more of Smith’s thinking, you can find her on LinkedIn.
