The Fortexx Group

Historically, the concept of a ‘consideration set’ has been considered as a constant, stable group of competitive brands that a consumer might consider along their buyers journey. Essentially, this is the group of brands they may weigh as options before making their decisive purchase. In a traditional marketing funnel, this is a very useful concept, as it explains that awareness is followed by consideration, which is then followed by conversions. The more brand exposure, the more awareness is created and, in turn, the more prospective consumers.

A linear model for a linear age.

This can be a useful concept for an age governed by algorithms. However, we are now entering a new age of technology-driven marketing platforms. AI is quickly changing the game and we’ve updated this article to include some information from a more recent article regarding LLMs. As AI technology is adapted and adopted, it is quite possible that we will soon be able to make more connections within a smaller, more targeted group of people.

Some ways in which the consideration set is not constant:

Human decision-making is not linear. It doesn’t take place in a controlled environment, in a vacuum. Instead, it is constantly changing as the root of our decision changes. Humans are constantly adapting to new information, which then influence our decision-making patterns. Ah yes, patterns. Try as we might, not all people follow the same patterns of decision-making. Many may follow similar patterns, but as the information at hand may change at any time, so may the trends of our decision-making.

At times, search engines and predictive softwares can be nearly exact in populating what we are looking for, sometimes they can be frustratingly off by miles. How many times have you found yourself searching with different terms again and again until you finally gave up because you could not find what you were looking for? Or maybe you found similar options to what you needed, but nothing close to the quality or price point you wanted?

Contextual & Inefficient Decision-Making

Context also plays a large role in our decision-making whereas the consideration set is not constant. For example, our preference changes when we look for a casual or romantic dinner. For a casual outing, you may consider more affordable, widely available brands and restaurants that you would never consider for a romantic evening that would require something more upscale and refined. Our preferences may also change as we are shopping for either a party favor or a get-well gift.

These contexts radically reshape which brands we gravitate towards. For this reason, there is no static, universal, linear consideration set. In fact, a constant consideration set would ignore the dynamic nature of human choices.

Another way in which the consideration set proves to be a moving target is when we understand that human decision-making can be, at times, extremely inefficient. Preference and memory – recollection in general – are biased and imperfect. This creates an unpredictable quality to how we make decisions. Not just this, but there is no way to be thorough and efficient at the same time. In today’s age, there is a seemingly endless stream of competition for every product and service out there. How can one person comb through every option and make an efficient and thorough analysis in order to find the best one?

Thinking briefly back to our last point, how can a search engine perfectly comb through each and every one of these options for you while perfectly understanding the context of why you are searching in the first place? We recommend reading up on LLMs and how they may revolutionize this process in the near future.

Surveys & Focus Groups

Many sample sizes, focus groups and survey-based metrics are flawed, as well. While they assume the static consideration set, they are further supporting a linear model that does not exist. The larger the sample size, the bigger the consideration set, proving that it is not constant to begin with. The larger the sample size is, the more accurate the consideration set may be, but it will never be perfectly representative of the actual thing. Survey-based metrics also poorly represent the consideration set in question because the consumer is removed from the buyer’s journey, and so the answers are not a natural reflection of their thought process at the time they make purchases.

Consumer responses are highly situational. They are also influenced by external stimulation, meaning that survey prompts would innately manipulate the results. A consumer might, for example, report considering more luxurious brands because they are aspirational, but when they make purchases, they may actually be a more practical or economical buyer.

What are CEPs?

Category Entry Points, or CEPs, are cues that stimulate the buyer’s journey. They can be internal or external. Examples of internal cues are moods, emotions, memories and motives. External cues can include location, time of day and availability.

CEPs can help businesses understand which brands are most likely to be considered when a buyer is making a decision. They can help build associations between their brand and the category’s core buying situations. They help businesses align their marketing efforts with the situations that are most likely to lead to a sale.

CEPs recognize that each consumer has a buyer’s journey: a beginning, middle and an end. It always starts somewhere. The middle is the search and the end is the purchase. So of course, if we just jump into the middle of the journey, our outcome prediction may be off by a long shot. When we understand what initiated the journey in the first place, we can more accurately predict what the consumer actually is looking for and what they need.

What’s next?

While we rethink brand metrics, it’s important to measure relevance across different contexts, to identify gaps where your brand isn’t currently evoked and to build campaigns tailored to situational needs, rather than static demographics. Moving away from one-dimensional marketing is going to be critical in the new age of technology. The idea of the ‘perfect consideration set for every scenario’ and ‘singular consumer type’ are borderline archaic concepts. By using CEPs, we can get closer to understanding each individual consideration set per consumer and the complex buyer’s journey on which they travel.