How can you really “guarantee” results to your customers?

Many actions in our daily lives guarantee results. We apply heat to raw ingredients, knowing they will cook. We press a button for coffee or tea, trusting it will yield a rejuvenating cup. We watch keys slip through the fingers in a predictable pirouette toward the ground, not the sky. These actions are based on cause and effect, and the promise of predictability makes them welcome at best or tolerable at worst, such as the descent of the dropped keys.

"I knew it" is one of the brain's most favorite phrases. And if you're married, "I told you so" is just as satisfying.

Yet, not every cause and effect is so transparent or reliable. Consider the commonly held belief that drinking milk causes mucus production and makes your cold symptoms worse. This belief, widely accepted and often the reason for avoiding dairy during a cold, has been debunked by scientific studies showing no such causal link.

How do we get better at spotting and establishing causal relationships to improve how we make decisions in everyday life and business, too? If only there were a checklist…

Decades ago, Dr. Austin Bradford Hill (1897-1991), a pioneering figure in epidemiology, developed criteria to systematically assess whether a relationship between two variables is indeed causal. He is best known for the "Bradford Hill criteria," a set of nine principles that can be used to establish evidence of a causal relationship between a presumed cause and an observed effect. These criteria are:

1. Strength of association: The stronger the association between the cause and effect, the more likely the relationship is causal.
2. Consistency: The association is observed repeatedly in different studies and under various circumstances.
3. Specificity: The association is specific to a particular disease and particular exposure.
4. Temporality: The cause must precede the effect.
5. Biological gradient: There is a dose-response curve, meaning the greater the exposure, the greater the risk.
6. Plausibility: The association is biologically plausible or makes sense according to current biological knowledge.
7. Coherence: The association does not seriously conflict with the generally known facts of the natural history and biology of the disease.
8. Experiment: Causal evidence can be obtained from randomized experiments.
9. Analogy: The effect of similar factors may be considered.

You can adjust these criteria in a persuasive presentation and a sales context. Here is how:

1. Strength of association: Use stats and stories to show evidence of how your products/services impact customer outcomes. Show how the results are above normal levels (so make sure you have a benchmark of what "normal" is in your industry).
2. Consistency: Demonstrate how the results you promise happen every time without fail (and how you have a plan if something should fail).
3. Specificity: Link specific features of your product to specific customer benefits and clarify that the cause (your product) always and only produces the effect. As a side note, our data show that the inability to link solutions to customer needs is one of the biggest mistakes customers identify when sellers lose deals.
4. Precedence: Establish that using your product precedes observed improvements in customers. Clarify to your audience how this sequence never changes.
5. Dose-response: Show that increased use or integration of your product correlates with greater customer benefits. In other words, if they use your product a little bit, they can expect a little effect, and if they use your products a lot, they can expect a big effect.
6. Plausibility: Ensure the benefits of your product align with industry knowledge and customer expectations. Evaluate your presentations to make sure they obey the laws of nature and logic.
7. Coherence: Your product's benefits should be coherent and align with how your customer's business operates. Usually, the most persuasive presentations are not the ones filled with novelty on every slide but also with other things people find familiar.
8. Evidence from trials: Use data from pilot studies or trials to show that others are getting the same effect when they implement what you're suggesting.
9. Analogy: Draw parallels to similar products or solutions that have shown to be effective in similar situations. If you translate this into a formula, it would be like, "Other things like [x] work like this, too." A strong metaphor can impact how convincing an argument is.

Let's see how some business scenarios reflect items from this checklist. Netflix once believed that increasing its library size would linearly increase user engagement. However, with additional research, they found that while content volume is important, engagement on the platform is more than just adding more titles. Engagement is a complex metric influenced by varied content that resonates with viewers, not merely the quantity of content. This point illustrates the dose-response item in the checklist above.

Here is another nuanced example of cause and effect in action: Tesla's introduction of the Autopilot feature, which sparked debate about its safety. Back in 2021, Tesla's safety reports, which contrasted using Autopilot vs. not using it, indicated fewer crashes per mile when the Autopilot feature was on. The report mentioned one crash for every 4.31 million miles with Autopilot versus 1.59 million miles without. The data was criticized for not accounting for the fact that accidents were more common on city roads and undivided roads than on highways, where Autopilot was mostly used. The Autopilot feature has made improvements since then, but this case illustrates the complexities in establishing causality, highlighting the importance of factors like context (Specificity), the strength of the relationship (how significantly Autopilot influences safety), and consistency (year-over-year improvement).

In general, it's helpful to understand and interpret causal relationships accurately in business and everyday life because you will not accept "truth" without question. This is how you know that cracking knuckles will not cause arthritis, reading in dim light will not cause poor eyesight, shaving your hair will not make it grow thicker, and swallowed gum will not stay in your stomach for seven years.

When you use a structured approach to appraising content and evaluating causality, you become a better decision-maker for yourself and a more credible partner for your customers because you can demonstrate the value of your products in a convincing way.

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Carmen Simon, Ph.D., is the Chief Science Officer at Corporate Visions. She uses neuroscience tools to research how the business brain processes business messages, remembers them, and decides to act (or not). Her research (available at Corporate Visions and Emblaze) is translated into practical guidelines, which sellers and marketers use to create memorable and actionable customer engagement.