In behavioral economics terms, we all operate under what is called “bounded rationality.” We almost never have 100% of the information on any given topic, circumstances habitually change, and new data are discovered regularly. So what are we to do? If we wait until all of the information is known, then we’d never make any decisions. Marketers would never implement their strategies, data would never be ready for activation, and new products would never be released. We would be stuck in a perpetual state of information gathering.
This is where heuristics and biases come in. Think of heuristics simply as cognitive shortcuts that simplify our decision-making. They allow us to make judgments quickly and efficiently, often without conscious awareness. Biases, on the other hand, are preferences that rely on subjective or externally influenced information; these preferences can lead to systematic errors. Together, heuristics and biases shape our perceptions, preferences, and ultimately, our decisions.
Without these shortcuts, our lives would be crippled with inaction due to a constant overload of information, inputs, and analysis paralysis. With our bounded rationality, we operate within the confines of cognitive load, or our mental processing bandwidth. The more shortcuts we take, the less our resources are wasted on small, ineffective choices thus freeing up our bandwidth for more important tasks and decisions. This is widely claimed to be why Steve Jobs wore the same type of black mock turtleneck and jeans every day; if we have a finite amount of decisions we can make every day, then eliminating the trivial choices and minutia frees our cognitive load to be used for higher-level and more strategic thinking.
Understanding Heuristics and Biases
There are hundreds of variations of established heuristics and biases. Let’s explore some of the most common examples you may have heard about and how they apply to the Salesforce ecosystem:
1. Availability Heuristic:
This heuristic leads us to overestimate the importance of information readily available to us. Humans tend to correlate their exposure to something with a presumed commonality of that stimuli. In other words,the more we hear about something the more likely we are to assume it’s normal, show a preference for it, or have it top of mind.
Here’s an example: when enjoying a tropical beach vacation, would you be more concerned with shark attacks or falling coconuts?
You probably said shark attacks; And why wouldn’t you? Maybe you heard about an incident or a recent shark sighting at that very beach. And it’s tough to forget a news story where a vicious attack leaves a salient imprint on our memories. Plus, who doesn’t love Shark Week?? And while stories, media coverage, conversations, and common fears make shark attacks much more available to us, the reality is that falling coconuts kill 15 times more people than sharks every year. But since we’re not exposed to stories about these types of incidents, we will hone in on what’s more available to us: being devoured by Jaws.
Marketers leverage this with concepts like ad retargeting. By consistently keeping their brand names, products, or services available to consumers in the form of ads, when the consumer is finally at the point of the purchase lifecycle to make a conversion, who do you think is top of mind? By providing steady availability of vivid, memorable messaging, marketers can increase their odds of conversion, especially when applying propensity models (via Calculated Insights) in Data Cloud to gain insight into timely activation of targeted advertising audience segments.
2. Anchoring Effect:
When making decisions, we often rely heavily on the first piece of information encountered (the anchor). This initial anchor then biases our subsequent judgments, even if it’s irrelevant or arbitrary. This would be like me asking you to estimate the population of Thailand and sharing with you the size of neighboring countries like Cambodia (17MM) and Laos (7.5MM). Most people would guess somewhere in the ballpark of those population sizes. But the size of nearby countries may have no impact on the size of Thailand (which is about triple the population of both those countries combined).
Consumers experience this all the time when they see price markdowns. Virtually everyone will place more value (and reason to buy) when they see an item that was originally priced at $200 on sale for $50. But when consumers see that same item originally priced at the $50 price point, it is not perceived with nearly as much value nor urgency to purchase. This is precisely why so many Salesforce marketers will dynamically populate catalog fields using AMPscript that display both original / suggested pricing as well as actual / sale pricing in order to anchor that original value against the new offer.
This is a huge tactic in negotiation strategy. Many schools of thought on negotiation will claim that setting the anchor for your desired price, salary, or terms is a significant advantage and provides control to the party setting the anchor by allowing them to establish the baseline for the rest of the negotiation (provided it is a reasonable anchor).
3. Confirmation Bias:
People tend to favor information that confirms their existing beliefs or hypotheses. Whenever we discuss topics with family or friends that agree with us, watch news sources that align to our political beliefs, or search Google with leading questions (e.g., why are dogs better than cats?) we are engaging in confirmation bias.
This is exhibited in consumers who attempt to fend off buyer’s remorse by sharing with their friends all the features and benefits of their recent purchase. They may provide a positive CSAT score for their experience, cease all exploration of competing products, and even go as far as to criticize their former options. The product may not be superior at all, but the consumer goes through all this effort in order to convince themselves that they were right in their purchase.
Organizations do this as well. We send out marketing surveys with leading questions (e.g., “how much did you enjoy your experience?”), we justify our spend on tech or campaigns by over attributing revenue to them (e.g., are your abandonment campaigns truly bringing in as much revenue as they appear, or would some of that revenue have converted regardless? We cannot possibly know without control and experiment groups being set up in our attribution, but this is rarely the case for most marketing or analytics teams). We seek out evidence that supports our preconceived notions. Even AI is susceptible to this bias. If left to its own devices, AI models can commit to biases and find unrepresentative patterns. This can lead to hallucinations including generating content to support its own biases. This is one of the reasons Salesforce puts so much emphasis on their Einstein Trust layer in AI and applies practices such as dynamic grounding and prompt defense to eliminate these biases.
4. Loss Aversion:
This concept refers to our tendency to prefer avoiding losses over acquiring equivalent gains. The fear of loss is a much more salient motivator to our behavior than the prospect of gaining (of equal value). There are even fMRI studies that suggest that losses are experienced at approximately twice the neural impact compared to gains (although there is a lot of variability in attempting to quantify these neural activations… one could even accuse some of these studies of confirmation bias :).
This powerful and innate fear of losing drives much of our behavior. Cable companies know this all too well when they offer consumers free trials of certain sports or movie packages; you get to try it (and subsequently get addicted to it) for 90 days or so, then they take it away unless you pay more for it. But losing this newfound comfort is unbearable for us, so we just fork over the additional funds. Hook, line, and sinker. Free trials, freemium models, product samples and temporary upgrades are very influential tools that prey on our loss aversion as consumers.
But again, companies experience this same issue. We’re hesitant to sunset old technologies and migrate to new platforms. Losing data is an unbearable thought, even when the data is dirty, unusable, or slowing other systems / processes down. Even culling the herd on audience segments can be painful. We assume more is better, but virtually every audience or campaign performs better (and costs less) when it is smaller and more targeted.
There are many more heuristics, biases, and behavioral economics concepts that shed light on how and why we make the decisions we do. By recognizing these cognitive shortcuts and innate preferences, consumers can make more informed decisions, marketers can craft more effective strategies that resonate with their audiences, and companies can better navigate their data, organizational changes, and operate more efficiently.
