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The way people make decisions with their “Lizard Brain” and only afterwards give quantifiable justification to themselves based on logical reasoning is a much discussed topic in conversion optimization techniques of online marketers. Consumers make decisions based on their emotions, after which they look at the real value of the attributes of the product or service later.
If this is true, could customer satisfaction and retention be influenced by focusing more on the rational side of the brain in the after sales process? Or would satisfaction with a choice be more closely related to even more stimulation of the emotional side of decision-making? As we use data science to increasingly tailor the online experience to each individual customer in order to influence each individual conversion, we also need to look at the impact this breach in the decision-making process may have on customer satisfaction.
Here we explore the emotional decision-making framework and identify potential knowledge gaps that open up opportunities for additional research.
Most of the major sites use some form of id=”urn:enhancement-4056a0e6-227e-44d7-b7f3-ca840a93e0e8″ class=”textannotation disambiguated wl-thing”>conversion optimization, either by using big data to tailor the online experience to the individual user or by using A/B testing (here are my favorite tools) to determine the optimal word choice and color scheme to create a visitor to perform the desired action and become a customer. Emotional targeting is the latest trend in this kind of optimization. Marketers recognize the power of the emotional side of decision making and use it to move a visitor to a purchase they might not have made otherwise. However, few studies look at how this form of persuasion affects customer satisfaction.
The ultimate profit that can be achieved for marketing and conversion optimization is not limited to the initial sales, but lies more in the combination of conversion ratio x customer lifetime value. If increasing conversion also affects customer satisfaction and, as a result, retention and customer value, both processes need to be analyzed together to get a full picture of the results of the impact of on-site optimization on the bottom line.
Combining the two in follow-up studies could prove very useful in discovering new ways companies can increase their return on investment (ROI). Here we will look at the theory behind the correlation, offering insights into ways in which this theory supports the existence of the correlation between influencing online sales and after sales.
Impact of Emotions on Decision Making
Emotions have traditionally been viewed as a completely separate process of rational thinking. Although decision-making has historically been seen primarily as a rational process, over the past two decades more and more studies have emerged that show a more intertwined picture between reason and emotion.
Emotions are essentially unconscious evaluations that inform, modify, and receive feedback from various sources, such as our higher cognitive processes. In decision-making, emotions function as attributes that we can access through our own working memory, through a more conscious cognitive process, or through emotional mechanisms. Combined with domain knowledge of the subject on which a decision has to be made, one can form logical reasoning and a decision-making strategy (Chown, Jones & Henninger, 2002). Schwarz (2000) found that this is in line with much of the information-processing approach theory. He had already seen the contradictions in studies that undermined “rational choice” theory, since most studies related to rational choice had been conducted in a situation where the test taker could be expected to know the consequences of different sets of choices, allowing them to use attributes from their perspective. could retrieve working memory. In reality, an average decision-making process is much more complicated than “just” a rational cognitive process where emotions and domain knowledge overlap.
Rational choice theory might still apply in a situation where a person has domain knowledge and previous experience of the choice he has to make (Bettman, Luce & Payne, 1998) but Schwarz goes further by stating that choice makers have a limited capacity. to process information and not be able to retrieve every bit of important information needed to make the decision entirely from working memory. In addition, people have limited computing power to process all available information to arrive at a perfectly weighted outcome.
We do not base our decisions on ratio, but we also include emotional factors. We then assign attributes to these emotions so that we can factor them into our decision. The most influential emotions are two of our most basic: regret and disappointment. The possible feelings of regret or disappointment we might experience in the future can influence our decisions today as we try to avoid these feelings. We make decisions that minimize the chance of these emotions. This is a utility model where possible future feelings of regret or disappointment are included as an attribute in the overall weighting of choices (Zeelenberg, Van Dijk, Van der Pligt, Manstead, Van Empelen & Reinderman, 1998).
Chown, Jones & Henninger describe this same utility model where emotions are not seen as disruptive to rational decision-making, but as additives as separate attributes. Especially in time-sensitive situations, emotions can help to quickly come to a good decision.
Yet the above theory is mainly built on the fact that people are mainly rational beings who do include their most basic emotions in their decision-making. These emotions are an attribute, in addition to rational attributes and actual features of the various options, and each is then assigned its own value.
De Martino, Kumaran, Seymour & Dolan (2006) found that human choice is very receptive to the way choices are presented, which they called the “framing effect”. It seems that the further we go into the 21st century, the more evidence is found that emotions influence a large part of our choices. While Tversky & Kahneman (1981) had already discussed the effect of framing on choice preferences two decades earlier, brain activity is now also included in the studies to gain a better understanding of the processes that play in our brains when we make these decisions. De Martino, Kumaran, Seymour & Dolan found that the framing effect was specifically associated with activity in the amygdala, suggesting that an emotional system plays a key role in averaging choice bias. The actual attributes on which to base our decision remain unchanged, only the emotional attributes change from frame to frame. And yet our choice outcome changes very drastically.
A year later, Seo & Barrett (2007) found that the more intense the emotions experienced during the decision-making process, the higher the performance on the task. In addition, being more in touch with your feelings and the ability to identify the feelings is an even stronger factor in achieving a higher performance on decision-making due to the ability to estimate the possible biases that arise from these feelings. This indicates that our feelings are not always counterproductive to making optimal choices, but they can be misleading if you cannot map them properly. Intense feelings are an involuntary process that can be helpful but must be understood in order to counteract possible prejudices they could cause.
In decision-making research, rationality is usually described as formal consistency, i.e. conforming to the laws of probability and the axiom of utility theory (Pfister & Böhm, 2008). Rational choices are choices that lead to the best possible outcome, based on all the attributes available to make the choice. The statement that Pfister & Böhm make afterwards, that emotions can only have a negative impact on optimal decision-making, could be incorrect because emotions can also be seen as attributes in the entire process. Fortunately, they have also found research that contradicts the theory of emotions as only a negative factor, and indicates that a complete separation between emotion and cognition is unlikely to last.
Pfister & Böhm even go a step further than Seo & Barrett did in 2007 and point out that our emotions might even be called rational. If they can be included as rational attributes, they can therefore also form part of utility theory, a theory that up to this point was based on the irrationality of feelings. The extent to which emotions can be called rational is based on our ability to evaluate our feelings.
In an ideal world, controlling our feelings could lead to an optimal way to make the best possible choices, but the aforementioned framing research indicates that emotions can be misled quite easily and we may not always be aware of the effects. of these involuntary attributes that control our choices.
that the outcomes of our decisions can influence our emotions (Schwarz, 2000). We may not realize it in every situation and we may not have discovered every aspect of this in our many studies in this area. But if we assume that Schwarz’s statement is true, we must also assume that changing the outcome of the consumer’s choice also changes the emotions he has about that choice. Are we also working on lowering customer satisfaction and loyalty?
Choice satisfaction can be negatively influenced by two emotions: regret and disappointment. We become disappointed when our chosen option is not what we expected. We feel regret when it is as we expected, but we think we could have made a better choice (Zeelenberg, Van Dijk, Van der Pligt, Manstead, Van Empelen & Reinderman, 1998). If we know exactly which choice will ultimately make us most happy and thereby maximize our expected satisfaction, we would rarely experience disappointment or regret afterwards. We’re just not very good at determining what will ultimately make us happiest (Pfister & Böhm, 2008).
When you influence one or all four of the goals a consumer has when making a choice, we change their expected outcome. For example, when an e-commerce site sets up peer reviews together with other UGC to manipulate the expected reactions of the customer’s social environment about his purchase, the actual reactions can be very different. The actual outcome does not match the expected outcome in this case and therefore leads to disappointment and a dissatisfied customer. Justification, trust, expected regret, evaluation costs and ultimate negative emotion are the five drivers of consumer satisfaction and they also determine loyalty, product recommendations and the amount and size of word-of-mouth (Zeelenberg, Van Dijk, Van der Pligt, Manstead). , Van Empelen & Reinderman, 1998).
In the example of using user reviews and UGC, positively charged cues lead to a more positive assessment of the customer whether this is the right product for him. Reading a text with positive content can already be enough to influence decision-making and this works even better when it connects to the linguistic style of the target group (Ludwig, De Ruyter, Friedman, Brüggen, Wetzel & Pfann 2013). If afterwards the purchase turns out to be considerably less in line with the personal style of the consumer, he could experience a feeling of disappointment.
Referring to another example, that of adding an insignificant attribute, Sela, Berger & Liu (2008) point out that large choice sets results in the decision maker having to reject more options, since normally a consumer will only have one or perhaps a few products. choose from an e-commerce assortment, which again increases the expected disappointment (Schwartz, 2002). In addition, confusion in nature is a sign of danger and is therefore something to be avoided, while clarity is an indication of the safety of a good decision (Chown, Jones & Henninger, 2002). Given that a much larger set of options and attributes could potentially cause confusion, using an advanced recommender system to narrow down options or using a large number of difficult options framing could increase conversion. But Sela, Berger & Liu (2008) point out that the size of the assortment not only influences the fact that consumers make a choice, but can also push the decision maker towards a choice that is easy to justify. Utilitarian requirements are often easier to defend than indulgence in a purchase. Conversion optimization is often made to get consumers to make impulse purchases and to do so will reduce the number of (observed) choices or will add a small utilitarian attribute to otherwise luxury goods resulting in over-evaluation and reduction of guilt about purchases that are wasteful. and seem frivolous. What a consumer will most likely experience afterwards when he has spent money on impractical luxury goods. But giving consumers a “functional alibi” can give them a push toward purchasing a product they probably wouldn’t have done otherwise. The little utilitarian attribute that was added may not be as visible when they receive the order at home as it was presented on the website, which could lead to post purchase regret if they look more rationally at their choice.
Consumers judge the choice of product or service based on disappointment and regret. But another side of purchase satisfaction is the assessment of the selection process itself (
Directing the decision-making process through Emotional targeting
Emotions are a product of evolution and were a necessity in our everyday, primitive life. We had to make quick decisions to survive and had to develop a mechanism of emotions to make our decision-making a little smoother. In this regard, emotions can be seen as primarily contributing positively to the process (Bettman, Luce & Payne, 1998) (Chown, Jones & Henninger, 2002). But it is clear that not all emotional reactions always contribute positively. And marketing strategists are now looking for ways to use these evolutionary and automatic responses to their advantage. Wouldn’t consumers eventually feel like they’ve made a choice they wouldn’t normally make when convinced in this way?
Our biological preference for using emotions in decision-making was created as a way to survive dire circumstances. In this regard, the level of excitement is an indicator of the seriousness of the situation. What is commonly referred to as arousal is actually a collection of related responses including increased heart rate and respiration and changes in levels of dopamine, norepenephrine and other brain chemicals (Chown, Jones & Henninger, 2002). These chemicals in our brains lead us to fall back on our memory and patterns (or our super-fast decision-making strategy some would say). This means more emotional decisions, even when conflicting attributes are available. A lot of persuasion-to-purchase methods rely on stimulating excitement to encourage impulse purchases (i.e., buying decisions that don’t weight all the attributes in a way that someone would normally choose). “Sex sells” is a commonly used term in marketing where evoking excitement is perhaps most evident.
The most important decisions consumers can make are often made up of very difficult choices, such as a preference for speed of a car over suitability for a family, and the more complex the problem facing you, the more a person’s preferences and preferences are. goals play a role in the process.
Bettman, Luce & Payne characterize four separate goals that a decision maker may have: (1) to minimize the effort required to arrive at a decision, (2) to optimize the accuracy or satisfaction of the decision, (3) to negative emotions during minimize decision-making and (4) maximize the ability to justify the decision retrospectively. Depending on the situation, consumers may try to maximize one or more of these goals. According to their research, more complex problems are often solved with less complex attribute weighting methods, often choosing the strongest options on the most preferred attributes, regardless of their score on many of the other attributes.
Marketers are already using these goals by making their choices easier for the consumer by presenting it in easy to understand tables and even showing what he should choose based on his personal situation or what the majority of other customers have chosen. They tell a clear story about what the consumer can expect as a result and they offer simple justifications (why YOU deserve this product, “beacause YOU deserve it!”) But what they actually do is tap into the underlying source of these preferences, which is all comes down to the emotional motivations behind it.
In addition, the way you make a choice or the way you represent the options relative to other options plays a major role in which choice a consumer will ultimately make (Bettman, Luce & Payne, 1998). Often a product or service that is very similar to another option in the set is added to increase the perceived value of the best choice (to the seller, not the consumer) and a marketer may also present the gain of one choice as a loss of the other in order to increase the impact of the attribute of one of the choices. Research indicates that changes in presentation and loss/gain inversions activate the amygdala in different ways, supporting the theory that in these situations a consumer changes their preference based on emotion (De Martino, Kumaran, Seymour & Dolan, 2006).
Pfister & Böhm (2008) mainly present the same four goals, although they describe them slightly differently: information, speed, relevance and commitment. In particular, their interpretation of commitment (or the ability to justify) gives a marketer a new way to influence decision-making on an emotional level. The expected reactions of a purchase from the social circle of the consumer is easy to manipulate with a well-known tactic: peer reviews, user generated content (UGC) and discussion boards. The best results can be obtained when reviews and discussions are not only written in a positive way, but when the overall style of writing is also in line with the preferred way of communication of the consumer (Ludwig, De Ruyter, Friedman, Brüggen, Wetzel & Pfann 2013). Not only are reviews now prominently placed on e-commerce sites, but they are also curated for mostly the most positive and style consistent texts to ensure an emotional connection with the consumer. Instructions can be drawn up to ensure that all reviewers use this preferred language and their own editorial reviews can be style-matched for optimal impact.
Another way to influence the outcome of a decision is by adding an insignificant attribute to luxury goods. Sela, Berger & Liu (2008) describe that this works especially well in situations with a large number of options to choose from, as this choice overload encourages the use of utilitarian attributes. Someone would spoil themselves buying a luxury good that they wouldn’t normally buy based on an apparently small and unimportant attribute. This does not mean that the consumer puts his feelings aside when making his choice, but rather that he increases the value of the emotional factor for justification of his choice.
Finally, since people regret action rather than in-action, people are more likely to choose the path of action when pursuing their goal of minimizing regret (Schwarz, 2000). In this last example I would like to point out the “fear of missing out” principle, in which this mechanism is clearly used. Who has never seen the expression “only two left” or “only fifteen minutes left for this deal”.
Choice satisfaction and customer satisfaction
Choice outcomes elicit emotional responses. An individual is satisfied or dissatisfied with the utility of the chosen option. But this satisfaction comes not only from the attributes of the product or service received, but also from the comparison of these attributes with what was expected beforehand and the reasons for not choosing the alternatives (counterfactual thinking). ) (Zeelenberg, Van Dijk, Van der Pligt, Manstead, Van Empelen & Reinderman, 1998).
Particularly in choices where there are a lot of attributes to consider, a consumer will base their decision on a subset of attributes that were most important to achieve their goals without causing information overload. The same thing happens with emotional versus non-emotional attributes. The decision-making process in which subsets of attributes are used will not reduce accuracy when the attribute selection is based on the consumer’s real goals (Bettman, Luce & Payne, 1998). When we modify the way we arrive at this selection by framing it differently or by presenting attribute advantages as disadvantages or any other way of influencing our customers, how can these chosen attributes still reflect our true goals?
Choice and customer satisfaction are two separate constructions in which choice satisfaction can lead to customer satisfaction. There is considerable evidence that satisfaction positively influences loyalty, readiness and tone of online recommendations and word of mouth. There are also several studies where it is evident that interference in this process can lead to reduced satisfaction. For example, reducing the effort to make a decision ultimately lowers customer satisfaction. Since choice and consumption satisfaction are positively related to each other, there is a direct, positive effect and an indirect, negative effect to the evaluation. The overall effect remains positive. So a strategy that promotes ease of decision making (or increases conversions) by reducing the effort someone has to make to make a decision may not be optimal for customer lifetime value (Heitmann, Lehmann & Herrmann, 2007).
The most profitable customer is not the one who makes a purchase just once and then never comes back. In some cases, a customer only becomes profitable after one or possibly even a few orders. Yet there is little research that highlights the effects of conversion optimization on customer satisfaction and customer lifetime value. Looking at separate studies from different studies, it becomes clear that there is indeed a strong correlation. We see every day that our emotions can influence our decision-making. we see too Heitmann, Lehmann & Herrmann, 2007). A consumer experiences satisfaction in the choice process when he can justify product choice with a match between the available and the optimal choices. But even if the outcome is ultimately positive, one could still experience regret because there was no way to justify the choice at the time it was made. Maybe, because you’ve been influenced by emotional targeting and you should have known better. Connolly & Zeelenberg (2002) give this fairly extreme example: Suppose you leave a party while you are a bit tipsy and you decide to drive home instead of calling a taxi. You arrive home safely, but the next morning you still regret looking back at your decision. You knew the moment you made your choice that you had had too much to drink and that there were options that you could have chosen. You have no excuse: Your decision to get in the car was completely irresponsible and could easily have led to catastrophic outcomes.”
But doubt in the choice process can also lead to regret when the decision maker is unsure which alternative best suits their preferences. Guiding them to a choice by intervening in the choice process could also increase customer satisfaction. But what can a marketer do best to limit post-decision regret?
This is where it makes sense to incorporate the same tactics used for conversion optimization into the after sales process as well, where personalization is even easier as the online business now knows more about their customer than if it were just a visitor on the web. web site. It should be much easier to match brand messages to the customer’s linguistic style in the after sales emails and maybe even the shipping box and product content than it was on the website during the initial visit. The same data science techniques to determine the behavior of the website visitor can also be used to analyze the customer’s preferences in communication style.
Combining on-site behavior and an assessment of how consumers made their purchase decision can help analyze the individual information needs a customer needs to be optimally satisfied, highlighting UGC they can relate to , the framing of the selected “deal” over other options, the small utility of their “functional alibi” or any other button the marketer had turned to move the visitor to become a valued customer.
Chown E., Jones R.M. & Henninger A.E. (2002). An Architecture for Emotional Decision-Making Agents. Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Seo M.G., Barrett L.F. (2007). Being emotional during decision making—good or bad? An empirical investigation. Academy of Management Journal
Heitmann M., Lehmann D.R. & Herrmann A. (2007). Choice Goal Attainment and Decision and Consumption Satisfaction. Journal of Marketing Research, May 2007, Vol. 44, no. 2 (pp. 234-250)
Bettman J.R., Luce M.F. & Payne J.W. (1998). Constructive Consumer Choice Processes. J Consum Res (pp. 187–217)
Schwarz N. (2000). Emotion, cognition, and decision making. COGNITION AND EMOTION, 2000, 14 (4) (pp. 433-440)
Zeelenberg M., Van Dijk W.W., Van der Pligt J., Manstead A.S.R., Van Empelen P. & Reinderman D. (1998). Emotional Reactions to the Outcomes of Decisions: The Role of Counterfactual Thought in the Experience of Regret and Disappointment. Organizational Behavior and Human Decision Processes. Volume 75, Issue 2, August 1998 (pp. 187–217)
De Martino B., Kumaran D., Seymour B. & Dolan R.J. (2006). Frames, Biases, and Rational Decision-Making in the Human Brain. Science 04 Aug 2006:
Full. 313, Issue 5787 (pp. 684-687)
Ludwig S., De Ruyter K., Friedman M., Brüggen E.C., Wetzels M. & Pfann G. (2013). More Than Words: The Influence of Affective Content and Linguistic Style Matches in Online Reviews on Conversion Rates. Journal of Marketing Volume 77, Issue 1, January 2013 (pp. 87-103)
Connolly T., Zeelenberg M. (2002). Regret in Decision Current Directions in Psychological Science 11 (6), December 2002 (pp. 212-216)
Tversky A., Kahneman D. (2002). The framing of Decisions and the Psychology of choice. Science, New series, Volume 211, Issue 4481 (Jan 30, 1981) (pp. 453-458)
Pfister H.R., Boehm G. (2002). The multiplicity of emotions: A framework of emotional functions
in decision making. Judgment and Decision Making, Vol. 3, no. 1, January 2008 (pp. 5-17)
Sela A., Berger J. & Liu W. (2008). Variety, Vice, and Virtue: How Assortment Size Influences Option Choice. Journal of Consumer Research, Volume 35, Issue 6, April 1, 2009 (pp. 941-951)
Joost Nusselder is The Content Decoder, a content marketer, dad and loves trying out new tools en tactics. He's been working on a portfolio of niche sites since 2010. Now since 2016 he creates in-depth blog articles together with his team to help loyal readers earn from their own succesful sites.