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Choosing reading books can be a serious undertaking. Even the choice of a novel or a detective book may not be taken lightly by readers. There are different ways in which consumers may get into choosing a book; some search and selection patterns in the decision process carried out by consumers can be observed in bookstores. It is possible to infer from observations, with some limitations, styles of shopping for books, involving certain tactics or rules utilised in the process. Book fairs especially offer an interesting and vibrant venue for book shopping with options not regularly available at stores. Such events may also provide an opportunity to detect new or distinctive patterns and styles of shopping that arise from the dynamic happening and busy environment.

The open-air Hebrew Book Fair has been taking place in a main central square in Tel-Aviv for over forty years in every June. Originally the book fair was held for a week but in recent years it has been extended by three more days due to its high popularity. It must immediately be noted that the book fair is an event reserved for publishers. It is a kind of ‘direct-sales’ event in which publishers meet face-to-face with readers to present their book collections to them for purchase on special discounts (the main bookstore chains run their own parallel competitive events with discounts in-store or near their stores). Visitors at the book fair can find Hebrew-native books and books translated to Hebrew from English and other languages; topical categories cover, for instance, prose, poetry  and novels; detective and thrillers; history, science, and other areas of knowledge; and last but not least children & youth books. Such an enormous selection of books is not available ordinarily at bookstores in the country. The larger publishing houses may occupy ten or more counters in-line.

The visitor traffic at the event, as in this year, suggests that print books are still highly desired by people. Nevertheless, to attract even more visitors, particularly families with children, the organisers added in the past few years food and drink stands and a sitting area with tables in the square’s centre. It may help to increase the convenience to visitors and festivity of the event though it could sacrifice a bit the respectability of this literary event. However, it may be a matter of necessity or priority to make the event more popular and vibrant so as to bring larger reader audiences back to books.

As suggested above, this book fair is a busy event with tens of thousands of books of numerous titles on display from different publishers and across a wide range of topics. It retains also a long tradition wherein Israeli authors attend to sign their books for visitors-buyers. Some book counters may become crowded with shoppers during certain hours through the afternoon and evening (i.e., after work and school hours) which can make it harder to access books and check them out more deeply. Hence it may require shoppers to apply tactics for choosing books of their interest and taste a little differently than they would while shopping in a bookstore. Yet visitors find their ways to browse books, sometimes more loosely, sometimes more meticulously; it seems to happen overall in an orderly manner, each visitor getting his or her place at a book counter or desk.

Visitors can be seen walking along counters of a given publisher, staying at a counter for a while to observe its books, then moving along. After selecting a few books from separate but adjacent counters of the same publisher, the visitor often returns to a previous counter to pay. However, visitors-buyers are also offered the option to keep books already selected behind the counter (a combination of convenience and security for both sellers and customers).

Three forms of browsing candidate books of interest can be primarily noticed: Firstly, eye-scanning the front covers of books from top. Secondly, lifting a book, turning it over and reading its back cover — an abstract, short review recommendations, or a brief biography of the author(s). A visitor may examine a few books from a counter this way, but being able to do so comfortably may truly depend on how many people are already at the counter. Hence, visitors who cannot find a free spot at a counter are often seen looking over a counter-top quickly, moving to the next counter, then coming back if perhaps there was a book that had caught their attention previously to check on the book more closely. But visitors generally do not have to wait too long to find a free spot at a counter. Thirdly, one gets to open a book and sample-read sections from its pages, or looking at photographs, charts or maps inside the book. Instances of reading inside books were observed much less frequently.

Examining a book’s content more deeply to form a better founded impression or opinion of it is more difficult and hence is less likely than would be seen at bookstores. Yet, if time and space at the counter allow, it is possible to find a visitor examining a book more meticulously. It appears to be particularly relevant and appropriate for ‘knowledge books’ such as in history, sciences and technology, the social sciences, economics and business. For example, a visitor in his ~70s was leaning over an open book on the history of WW2 by Max Hastings, appearing concentrated in reading and observing maps and photographs (‘Inferno/All Hell Let Loose’, translated). He seemed interested overall in history of the two world wars of the 20th century, judging from other books he browsed; after nearly ten minutes he handed three chosen books to keep, and continued searching [A].

  • Please be advised that the age estimates of visitors are based on observation alone in best judgement of the author.

Comparing books on a given topic can be an even more difficult task to perform at a counter. It is hardly practical to hold two books open simultaneously for comparison, but visitors may examine books sequentially in attempt to evaluate and choose which one is more suitable to their objectives. For instance, a visitor (male, ~60) looked into a book — its introduction, inner pages, and content — on the history of the state of Israel (by Michael Bar-Zohar), but he apparently did not find what he was looking for as he asked the seller if there were books on the period preceding the establishment of the state. The seller brought him two books (concerning the Arab-Israeli conflict): he opened one of them, went through its pages, and put it aside, then browsed at greater length pages in the other book and looked at photographs. Eventually he chose the first book on the state of Israel, after looking into it again, and the third book (total time 15 minutes, [B]).

The search and examination of books sometimes involves moments of deliberation. In some cases, as above [B], the visitor may ask for advice from a seller. Alternately, as in another case observed, a seller who noticed a visitor (female, 30-35) hesitating, offered her help with recommendations. The visitor-shopper was already holding two books and the seller brought her more books the latter thought may suit the shopper accordingly in prose or novels by Israeli authors. They continued talking about the books as the shopper browsed loosely inside some of the books or read from the back cover [C].

Deliberation can take some additional forms. For example, a female visitor (~45) was considering the purchase of a book on equity investments. She was checking in particular a book purporting to be adapted and designated for women. The visitor went through some book pages, being unsure it was a good choice, and seemed recoiled upon noticing the book was from 2011 (i.e., ‘Is it still valid and relevant?’). But eventually, following a short exchange with the (female) seller, the visitor-shopper decided to take it anyway [D]. A visitor (male, 25-30) at another publisher has shown an intriguing shopping process with deliberation to the last moment: He was already holding a book when moving to another counter to look over books of prose, selected one of them, then browsed some science and knowledge books (e.g., by an Israeli scholar, lecturer and prolific writer on sciences and philosophy, Haim Shapira), but collected none. Subsequently the shopper moved to a more remote counter where he picked-up instantly a book, came back to the previous counter of science and knowledge books to purchase three books. However, after he had already paid and the books were put in a bag by the seller and handed over to him, he took out one of the books and picked-up instead a different book in front of him on biblical philosophy (by Shapira, 10 minutes, [E]).

Shopping patterns can range from exploratory, looking for opportunities with little idea pre-conceived in mind, to being pre-minded, that is, having a goal to find a particular book. Moreover, visitors-shoppers may mix styles at different levels of search, examination and choice while shopping from the same publishing house. Mixed tactics could be seen above in the shopping of visitors [E] and [C]. Following are two more examples of this kind: (1) A young visitor (female, ~17-18) was browsing prose or fiction books, going through pages and reading inside some of the books or reading from the back covers of others, then passed to looking from top at books in adjacent counters of the publisher (a more haphazard quick scan), finally returning to the first counter to buy [F]; (2) A visitor (male, ~45, at a counter of books on history and politics) took a cursory look over a biography of one of Israel’s prominent leaders of the past, kept searching and shortly after found a book on the history of Sephardic Jews (‘Marranos’, Yirmiyahu Yovel) and looked into the book more dedicately; the visitor, who seemed overall interested in Israeli and Jewish history, picked up a book at the last moment by an Israeli historian on the commanders of the Nazi concentration camps (‘Soldiers of Evil’) and purchased it with the book on Marranos [G].

  • In a curious brief episode, demonstrating an apparent pre-determined choice of book, a visitor in his mid-40s approached a counter, stood pausing or looking over the books, then instantly extended his hand to pick-up three copies of a book on the Bitcoin, which he purchased; one of the sellers seemed so impressed that she asked to take a photo of him holding the books with her mobile phone to which he smilingly agreed [H].

The main publishing houses presenting at the book fair offered deals of ‘3 for 100’, that is, three books for 100 shekels (~$28 in June). One publisher even offered five books for 150 shekels. These deal offers were displayed on signage boards above counters. A fourth book could be purchased for 50% of its list price, but this offer was not displayed. Visitors-shoppers who had already selected three books enquired whether there would be a discount for additional books, and were replied with the 50% offer. For instance, visitor [A] so enquired before continuing his search. Another visitor (male, ~30) who was holding four books by Ken Follett seemed unable to make up his mind which three to buy, posed the question about a fourth book discount, deliberated a little longer while shuffling the books in his hand, and finally passed all four to the seller to purchase [I]. In some cases, however, it was the seller who initiated the offer of discount on a fourth book in hope to increase the sale. Visitor [C], for example, accepted an offer as such and bought four books, probably in appreciation of, and perhaps feeling obliged to reciprocate, the advice she received from the seller. Conversely, another visitor (~30), who selected three books in history and politics on his own refused the offer by the seller when submitting his books to purchase [J].

Visitors were induced by these deals to buy more books from any single publisher. A single book could usually be bought with a 20% discount but this offer was not made public, proposed by a seller only on request of the visitor. This policy makes it simply unworthy economically for visitors to cherry-pick the books they most require or desire from different publishers (consider that many of the books cost 80-120 shekels each!). The greater problem, however, is that it may drive consumers to buy books they do not care for or do not have time to read soon. Henceforth, visitors could end up buying a pack of books, collected from several publishers, for the whole year to read. It puts quantity before quality in buying books. The ones standing to suffer from this policy are of course the book retailers who will likely see fewer shoppers at their stores in the coming months. From a publisher’s viewpoint, they may see it as only a reprisal to similar deals offered at bookstores throughout the year.

Visitors-shoppers at the book fair appear to use composite decision strategies for choosing books at the counters of a publisher: a different type of rule or method may be fitted to choose among different books (e.g., picking-up a book planned ahead to purchase, using book titles or author names as memory cues for books they have considered recently, examining inside books with greater scrutiny to evaluate them). Furthermore, the book shoppers are searching for informational cues, starting from the front cover of a book, going to the back cover, then getting inside the book. They could be extending the search for cues about a book as they feel is needed (e.g., cut the search short if sufficient information has been retrieved) or are stimulated to learn more about the book (e.g., intrigued by information on the back cover to look inside).

The difference in shopping for books at the book fair compared with bookstores seems to be not so much in the types of rules or tactics used as in the extent and frequency they are used. Book shoppers may feel at greater ease to search for a book at a store with a print of a book review cut from a newspaper (as observed in a store) than they would in the book fair (surely the same applies if one seeks guidance from his or her smartphone). One may also feel more comfortable and free to browse inside a book at a bookstore, at a quiet corner to stand or perhaps on a couch or sofa to sit and read, than at the book fair. Yet, visitors of the book fair seemed to adapt quite well to the conditions at the counters; they appear to use rules or methods similar to those that can be seen at bookstores, only adjusting them to search and choose more efficiently, particularly by restricting deeper examinations to situations where a book demands it.

  • Additional research methods can aid in identifying and verifying more accurately the book images and information viewed by visitors and the decision rules they use. Those methods include particularly eye-tracking and a real-time protocol of the shopping decision process (‘think aloud’). But executions of such methods may be inconveniently intrusive and interfere with the natural course of the shopping trip for visitors. Another method to consider with less intervention is an interview with a visitor-shopper after concluding a shopping episode.

Gaining greater insight into shopping for books and understanding the decision processes visitors-shoppers follow at a book fair can help in devising new designs of book displays (e.g., better organise books by topics or themes, easier-to-find) and improved practices to accommodate the visitors at the event. The organisers and publishing houses may also come up with a new co-operative scheme that would allow visitors to accomplish more effectively their objective in selecting and buying the books that interest them most or they desire to read.

Ron Ventura, Ph.D. (Marketing)

 

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During a shopping journey in a store where a consumer intends to buy multiple products, he or she is required to make a sequeqnce of choice decisions. Each decision is about to be made in a category with different product attributes, but beyond that there could also be differences in the settings of the choice situations, such as the size of the choice set, the structure of information display for product items, and information format. The transition between choice problems that differ in their characteristics should require shoppers to make some adjustments in preparation to reach a decision, each time in somewhat different settings. This is in fact true when filling a basket either in a physical store or on a website of an online store — shoppers have to shift between decision problems, and on the way they may need to replace or correct their choice strategy.

Researchers have been studying the paths that shoppers frequently follow, moving between sections of a store during their shopping trip. This type of research usually focuses on identifying and depicting the sequence in which store sections and product categories are visited, and the frequency in which category displays are stopped-by. However, the transitions from a choice decision in one category to another may also have  consequences for the decision process in any single category visited (e.g., as in adjusting for every new choice problem). Moreover, the sequence or order in which choice problems are resolved may have an effect on particular decisions.

  • Different techniques are applied for tracking the pathways of shoppers in brick-and-mortar stores (e.g., RFID, mobile-based GPS, video recording through surveillance cameras). Studies in supermarkets have shown what areas of a store shoppers approach first, and how they start by walking to the back of the store and then make incursions into each aisle (without leaving the aisle on the other end but returning to their point-of-entry). Hui, Bradlow and Fader reveal that as shoppers spend more time at the store, the checkout looms more attractive — the shoppers who feel a stronger time pressure become more likely to go through an aisle and approach a checkout counter. As perceived time pressure increases shoppers also tend to cut-off exploration and concentrate on visiting product displays from which they are most likely to purchase. (1)

Consumers have been described as adaptive decision-makers who adjust their decision strategies according to characteristics of the problem structure or context — for example, the amount of information available (given the number of alternatives or attributes), the type of information (e.g., scale, units), or the order in which information elements are displayed. In the outset, consumers may be guided by top-down goals — maximizing accuracy (relative to a maximum-utility ‘rational’ rule) and minimizing cognitive effort; a decision strategy (i.e., a rule like Equal-Weights or Lexicographic) can be selected in advance with respect to the accuracy-effort trade-off assessment of rules in a given choice situation, this according to Payne, Bettman and Johnson. However, they argue that this approach may not be sufficient on various occasions. When the characteristics of a choice problem are not familiar to the consumer, he or she will construct a strategy step-by-step as the structure and detail of information on alternatives is observed and learned. Even in cases the choice situation and context are familiar, the consumer may face unexpected changes or updates in information (e.g., inter-attribute relations) that may require her or him to modify the strategy. Hence, a consumer who started with a specific rule may replace it with another on-the-fly in response to data encountered, and often elements from different rules may be combined into an adaptive new choice strategy (as opposed to a ‘pure’ strategy)(2).

The construction of a decision strategy is therefore frequently the product of a delicate balance between top-down (goal driven) and bottom-up (data driven) processing. When in particular preferences also are not well-established by the consumer, preferences (e.g., importance weights of attributes) also are formed or constructed as one proceeds in the decision process. In such a case the preferences formed would be more contingent on the particular process followed and the strategy constructed thereby. Bettman, Luce and Payne extended the constructive choice model and added to the goals of maximizing accuracy and minimizing effort two more goals (directed by a perceptual framework): minimizing negative emotions (e.g., perceived losses, difficult trade-offs) and maximizing the ease of justifying decisions (to others or to oneself). (3)

However, the adaptation of consumers may not be complete, and thus a shopper may not fully “reset” or fit his decision strategy to features of the next choice problem, which may differ from features of the previous choice setting. Levav, Reinholtz and Lin investigated specifically the impact of one characteristic of decision problems on a decision process: the number of alternatives (4). They tested how many alternatives consumers would inspect more closely from each choice set, if the total number of alternatives available increases from the first to the last decision problem (e.g., 5, 10, 15 and so on until 50), versus a decrease in the number of alternatives available from the first to the last decision (e.g., 50, 45, 40 and so on until 5 — participants were allowed to sample songs to listen to before choosing a song for each track on a disc).

In one of the decision contexts tested, most relevant here, the researchers simulated an online shopping trip: participants in the experiment were asked to choose in sequence from eight different product categories (e.g., body lotions, energy bars, notebooks, shampoo). For some of the participants the number of alternatives increased between categories (i.e., 5, 8, 13, 17, 20, 23, 26, 30) whereas for the others the number of alternatives in a choice set changed in a reverse order (product categories were also presented in two opposite sequences of alphabetical order). Participants could examine more closely each option in a choice set by mouse-hovering on a thumbnail photo of the product item to see its enlarged photo image, its price, and a short product description.

  • Note: In a physical store the equivalent would be picking a product package from a shelf, inspecting it from different angles, reading the label etc. Advanced 3-D graphic simulators let a user-shopper in a like fashion to virtually “pick” a product item from a shelf display image, rotate it, “zoom-in” to read more clearly its label, etc.

Levav and his colleagues found that the direction in which the size of the choice set changes matters, and that particularly a low or high number of options in the first decision problem induces consumers to examine more or less information on options through the shopping trip. If a shopper starts with a small choice-set, he or she is more strongly inclined to inspect every option or acquire more information on each option available. This tendency endures in the next choice problems as the number of options increases, though it may level-off at some point.

In the online shopping experiment, the “shoppers” in the increasing condition examine on average the description for each option more times than “shoppers” in the decreasing condition for smaller choice sets. The former gradually adjust downward the amount of information acquired on each option but the amount of information “gathered” overall does not decrease; for relatively small choice sets (up to 13 options) they would still examine more information on options than “shoppers” who started their journey with the largest choice set. A “shopper” who starts with a large choice set constrains himself from the beginning to inspect options less closely; even as the choice set may become more “manageable” in size, the average “shopper” does not intensify the examination of information on single options considerably, clearly not to the level as “shoppers” whose first decision is from the smallest choice set.

  • For choice sets larger than 17-20 options, where the task for “shoppers” in the increasing condition may become too time-and-effort consuming and “shoppers” in the decreasing condition may still feel too pressed, the level of information acquisition is more similar.

The researchers refer to this form of behaviour as “bounded adaptivity“; they explicate: “Our results indicate that people are actually “sticky adapters” whose strategies are adapted to new contexts — such as the initial choice set — but persist to a significant degree even in the face of changes in the decision environment” (p. 596). The authors suggest, based on results from one of their experiments, that an increasing condition, where consumers’ first choice decision is made from a small choice set, may activate in  consumer a ‘maximizing’ mind-set, searching deeper into information on alternatives (as opposed to a probable ‘satisficing’ mind-set of a consumer in a condition of decreasing size of choice set). Levav et al. note that while ‘maximizing’ has often been regarded in literature as a chronic trait of personality, they see the possibility that this mind-set can be triggered by a decision situation.

If decisions during the shopping trip are not made independently, since adaptation where necessary is not complete or “sticky”, studying in isolation the decision process a shopper goes through in front of a particular product display could be misleading. For instance, the shopper’s decision strategy may be influenced by a choice strategy used previously.  An “imperfect” or “sticky” adaptivity does not have to reflect a deficiency of the consumer-shopper. It may simply designate the sensible level of adaptivity needed in a given decision situation.

(1) Shoppers may not have to hurry to modify their strategy if the perceived change in conditions of the choice problem is small enough to allow them to act similar as before. Shoppers can often adjust their decision tactic gradually and slowly until they get to a situation when a more significant modification is required. (“Shoppers” in the decreasing condition above seem to be more “in fault” of remaining “sticky”.)

(2) Shoppers-consumers look for regularities in the environment in which they have to decide and act (i.e., arrangement of products, structure and format of information) that can save them time and effort in their decision process. Regularities are exhibited in the ways many stores are organised (e.g., repetitive features in display of products) that shoppers can gain from in decision efficiencies. Regularities are likely to reduce the level of ongoing adpativity shoppers may need to exercise.

(3) On some shopping trips, ordinary or periodic (e.g., at the supermarket), shoppers frequently do not have the time, patience or motivation to prepare and deliberate on their choice in every category candidate for purchase. They tend to rely more on routine and habit. Prior knowledge of the store (e.g., one’s regular neighbourhood store) is beneficial. Shoppers would want to adapt more quickly, perhaps less carefully or diligently, and they may be more susceptible to “sticky” adaptivity.

It can be difficult to influence when and how shoppers attend to various sections or displays for performing their decision in differing choice settings. But it is possible to identify what zones shoppers are more likely to visit in early stages of their shopping trip. If a store owner or manager wants to induce shoppers thereafter to search product selections at greater depth, he or she may arrange in those locations displays with a small number of options for a product type. It should be even easier to track movements and direct shoppers to planned sections in an online store website. On the other hand, the retailer may stage a display with some surprising or unexpected information features for disrupting the ordinary search, and induce shoppers to work-out their decision strategy more diligently, thus devoting more attention to the products. However, this tactic should be used more carefully and restrictively so as not to turn-away frustrated or agitated customers.

Displays in the store (physical or virtual) and information conveyed on product packaging (including graphic design) together influence the course of consecutive decision processes shoppers apply or construct.

Ron Ventura, Ph.D. (Marketing)

Notes:

(1) Testing Behavioral Hypotheses Using an Integrated Model of Grocery Store Shopping Path and Purchase Behavior; Sam K. Hui, Eric T. Bradlow, & Peter S. Fader, 2009; Journal of Consumer Research, 36 (Oct.), pp. 478-493.

(2) The Adaptive Decision Maker; John W. Payne, James R. Bettman, & Eric J. Johnson, 1993; Cambridge University Press.

(3) Constructive Consumer Choice Processes; James R. Bettman, Mary Frances Luce, & John W. Payne, 1998; Journal of Consumer Research, 25 (Dec.), pp. 187-217.

(4) The Effect of Ordering Decisions by Choice Set Size on Consumer Search; Jonathan Levav, Nicholas Reinholtz, & Claire Lin, 2012; Journal of Consumer Research, 39 (Oct.), pp. 585-599.

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Models of consumer preferences and choice most often follow a rational paradigm of decision-making — the consumer weights the values of attributes of each alternative considered  to derive its total utility value, then compares those utilities and chooses the alternative achieving maximum utility. Assuming this well-defined and straightforward process, it is relatively easy to construct predictions of preference shares or market shares. Yet the decision rule hereby described  is not so trivial or easy for consumers to apply; it requires a relatively large amount of information and a non-negligible computation effort. In order to simplify the decision process, consumers may use any of a selection of short-cut rules or heuristics (alternative-based and attribute-based rules) that demand less information and less cognitive effort to make a choice. On many occasions the process may not even include the rational-optimizing weighted additive (WADD) rule. Hence, decision processes tend to be more diversified than normally assumed in marketing research.

When consumers apply rules other than the WADD rule, predicted preference shares based on a maximum utility criterion for choice may off-shoot consumer actual choices. Indeed, there are other factors that may be implicated in biasing predicted preference shares when measuring preferences in consumer surveys — factors such as product availability and the visual display of products in stores, accessibility of brand and product information in the real world, and time constraints. Preference shares may further deviate from actual market shares when quantity is a key factor (e.g., a consumer buys 1, 2 or 4 cups ofyoghurt on any single purchase occasion and when purchase frequency varies). However, I will focus in this post-article on the factor that resides within the consumers, that is, the decision rules they use. In fact, decision rules are elected by consumers in adaptation to situational and environmental conditions as noted above.

Different techniques have been developed since the 1950s for identifying and tracking the rules people utilise to reach a choice decision between alternatives (e.g., travel destinations, car brand and model). Not less important than identifying single rules is the task of mapping the sequence in which these are used in a complete decision process, and this is where the study of decision-making can become complex.

  • At the foundation of research in this field we find the “think-aloud” verbal protocol method for recording and mapping decision processes initiated by Simon and Newell. In this method, a consumer is given a choice problem and is requested to talk aloud  whatever thoughts come to his/her mind while (or right after) performing the task and reaching a decision (note: verbalising the thoughts aloud, not explaining them!) The content of protocols is later coded into procedures or mental operations that make up generic rules, and decision processes are mapped.
  • A related technique uses information display boards of brands and their associated product attributes. By tracking the sequences in which consumers retrieve information items (i.e., cells in a brand-attribute matrix) the researcher can infer what rules are likely to have been applied and map decision processes.  This approach is implemented in a software known as MouseLab for computer-aided data collection and analysis of the decision processes (now also available as an Internet-based application MouselabWEB). Researchers Payne, Bettmann and Johnson who developed the original software applied it for their ground-breaking work on the behaviour of the adaptive decision maker in selecting rules and constructing decision strategies.
  • Another interesting approach (Active Information Search [Brucks]) that allows decision makers to pose their own queries for product information (e.g., physical attributes, usage situations, price) may be seen as a semi-structured level between the protocol approach (least structured) and the approach of MouseLab (most structured).

More recently researchers in the area of decision-making have shown increased interest in the methodology of eye tracking for investigating search patterns for information. By measuring eye movements with specialised optical equipment, researchers capture locations where the eye fixates in a stimulus display (i.e., takes-in information) in-between rapid movements (saccades). This approach is already adopted often in studies of advertising effectiveness and shopper behaviour in retail scenes.

Researchers Reisen, Hoffrage, and Mast took the challenge of evaluating different techniques for tracking consumer decision processes (2008*). Primarily, they developed a multi-method framework approach called InterActive Process Tracing (IAPT). The investigative procedure has three stages:

  1. Active Information Search (selecting relevant attributes);
  2. Seeking specific attribute values of product alternatives (information acquisition) and choosing a preferred alternative;
  3. Verbal reporting of decision processes (i.e., retrospective but with assistance from a moderator in formalising descriptions of the decision rules applied).

Firstly, the IAPT approach allows to integrate three methods, one at each stage, and compare their contributions to our understanding of decision processes and predicting choices. Secondly, the researchers provide new methodological insights by comparing two alternative methods for the second stage: the more veteran method of MouseLab and the new method of eye tracking for recording search patterns.

  • In the second stage of information acquisition and choice, participants were shown several choice sets. Each choice set comprised a different selection of four alternative mobile phones (brands and their models) randomly drawn from a pool of phones available in the market. The form in which information on alternatives in a choice set is displayed is contingent on the method used for registering information acquisition: by mouse clicks or by eye fixations.

Let us consider first some key findings and insights obtained in the first study of Reisen and his colleagues, using MouseLab in the second stage for recording information acquisition:

  • Two major types of strategies were identified: additive strategies (alternative-based) with equal or varied weights assigned to attributes or elimination (by-attribute) simplifying strategies — the elimination strategies were used more frequently (30 out of 31 respondents) than additive strategies (23 out of 31) though most participants (71%) combined strategies of both types.
  • The difference in predictive ability of choices between additive (optimizing) strategies and elimination (simplifying) strategies is less dramatic as many might expect (55%-57% versus 47%-51%, respectively). Notably, predictive ability when using rules as described by participants in their individual protocols was much higher (73%) than in case of applying rules pre-defined according to literature as done for the comparison of strategies above.
  • When using an elimination strategy, logic suggests that one would not seek more information on an alternative after it had been eliminated. Interestingly, however, acquisition of specific attribute values was traced for an alternative that was supposedly already eliminated by respondents using an elimination-by-attribute type of strategy (67%). This  makes sense, according to the researchers, if consumers initially acquired information as they explored the alternatives available for choice and only in a second phase committed to a decision strategy (i.e., the strategy eventually described in the verbal protocol).

In the second study, Reisen, Hoffrage, and Mast tested two methods for tracking search and information acquisition in the second stage: MouseLab and eye tracking, the more recent entry into this field of research. The information acquisition of each participant in this study was measured using both techniques sequentially (i.e., first series of choice tasks with MouseLab, and the second series with eye tracking [or vice versa]; half of the choice sets overlapped between series of choice tasks).  The following are noteworthy findings and insights:

  • Frequencies of usage of additive and elimination strategies were similar in relative terms to those found in the first study.
  • Predictive ability in choice tasks applying MouseLab was a little higher (69%) than in choice tasks with eye tracking (63%), but not statistically significant. More importantly, in repeated choice tasks (i.e., the same choice set), when respondents remained consistent in their choice under both conditions, predictive ability of the choice of that same alternative was considerably higher (78%) than in inconsistent tasks (40%).
  • Respondents took more time overall to acquire information by mouse-click (MouseLab: 37 seconds) than by just eye gazing at the display (Eye Tracking: 20 seconds).
  • However, eye gazing appears as more time-efficient from a respondent’s perspective: when eye tracking respondents accessed items in cells about 42 times on average compared with 22 cell-accesses while employing MouseLab. It is noted that the number of different cells accessed was similar between conditions (15-17 cells). Put differently, eye tracking allows for a higher rate of re-acquiring or double-checking information items rather than inspecting more of the information available on alternatives.
  • In this study again it was observed that “regardless of the condition [MouseLab or Eye Tracking], participants accessed about 50% more information than prescribed by their strategy.” Yet, it is also reported that considering the information that is needed by a strategy, the greater part of it (82%) was accessed as expected. That is, the excessive information acquisition does not come necessarily at the expense of required information.
  • Note: Findings from the second study suggest enlightening clues as to how respondents tackle choice tasks in choice-based conjoint studies. In particular, it points at the selective manner in which respondents consider information on alternatives included in a choice task, looking at only some of the attribute values shown, and yet they may re-access those same values several times until making their choice. Apparently this process may take less than 30 seconds to complete.

Following their assessment of findings in the second study, Reisen and his colleagues seem unconvinced that using eye tracking in IAPT is advantageous over MouseLab. With eye tracking respondents can finish each a choice task more quickly and yet access more information. However, they tend to repeatedly access the same information for a purpose the researchers describe as “validating a tentative choice.” Further difficulties in using the eye tracking methodology for tracing decision processes are suspected inaccuracies in capturing information acquisition (i.e., a respondent accidentally fixates on a cell while thinking; when respondents voluntarily mouse-click cells, the search paths seem more systematic) and failed calibration of equipment that leads to loss of unusable data.   The researchers conclude (p. 655):

It appears that this methodology improves neither the exactness of the description of the cognitive processes nor the quality of the results concerning the information search. Although this method allows for a more natural way of searching for information, it does not provide more informative data than does Mouselab.

Eye tracking can teach us a lot about how consumers look at and attend to different portions of ads such as bodies of pictures, text and brand logos, their  appreciation of package designs, or how shoppers inspect product displays on supermarket shelves. It can be helpful also in studying the decision processes consumers follow, but it is not more appropriate and accurate than former methods known for a similar purpose like MouseLab. More importantly, each of the four methods considered for IAPT specialises in capturing different aspects of the decision process (e.g., characterising patterns of information acquisitions vis-a-vis identifying the decision rule applied). A primary lesson to be taken from this research is that using multiple complementary methods with different scopes of specialisations can contribute considerably to obtaining a better mapping of decision processes and building models with higher predictive ability.

Ron Ventura, Ph.D. (Marketing)

Reference:

Identifying Decision Strategies in a Consumer Choice Situation, Nils Reisen, Ulrich Offrage, and Fred W. Mast, 2008, Judgment and Decision Making, 3 (8), pp. 641-658.

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