Don’t They Mean The Same Thing?

Have you ever received an estimate of how long it would take for an order to arrive, or how long it would take for your car undergo repair? Did you know that the units or granularity the speaker chooses to use in their estimate effects your interpretation of the expected time of completion? According to Y. Charles Zhang and Norbert Schwarz, the level of precision the information is communicated with influences your perception on your own estimated time frames.  Zhang and Schwarz base their research on Paul Grice’s four maxims of communication. According to Grice, speakers adhere to the four following principles of communication: truthfulness, relevance, clarity and quantity of information.  Whenever someone tells us something, we assume that they’re telling us the truth. We also assume that they’re providing details relevant to the message, avoiding ambiguity, and providing us with just enough information to relay the message. Based on these Gricean principles, Zhang and Schwarz discovered that estimates provided with higher precision resulted in smaller time estimate windows. Wider time estimate windows occurred when the information provided to the listener was broader.

Zhang and Schwarz employ four different studies to discover the effects of granularity on consumer behaviour. The first study is separated into two parts, study 1a and 1b. In study 1a, 267 students were approached on campus and asked to evaluate the best and worst case scenarios for a repair situation. The students were told that their car was in for repairs, and they received one of three estimates for their repair: 30 days, 31 days or 1 month. Upon receiving this information, the students were then asked to provide the worst and best case scenarios as dates on a calendar. This displayed the student’s time frame estimate. Students given the 30 and 31 day estimates provided a narrower time frame estimate as compared to students that were given the 1 month estimate, demonstrating that students provided with more precise information had a more opportunistic expectation for their repair. Study 1b employed 90 students. The participants were told that a construction project would finish either in 1 year, 12 months or 52 weeks, giving three levels of granularity. Afterwards, the students were asked to provide the earliest and latest date of completion based on the information they received. Students that received the 52 week estimate provided the narrowest time interval. Students shown the 12 month interval had a wider time interval than those shown the 52 week estimate, and students shown the 1 year estimate had the widest time frame estimate.

Studies two and three explore “the role of communicator cooperativeness” (Zhang, and Schwarz 9). Zhang and Schwarz manipulate the expertise (Study two) and trustworthiness (Study three) and examine the effects of time frame estimates provided by participants. In study two, participants were provided with articles that explained the launch of a new car in either 2 years, or 104 weeks. The source of the article was either identified as the chief research officer (CRO) of the company, or an auto fan site that reportedly started the rumor. After reading the article, participants were asked to evaluate the likelihood of the car launching on time. Secondly, participants were asked “[i]f the launch of the new car took longer than planned, how many months do you think it would likely be delayed?” (Zhang, and Schwarz 10). Consistent with the findings of study one, participants provided a narrower time frame estimate if they were presented with the article where the CRO stated 104 weeks. Participants given the article that credited the auto fan site as the source of information did not replicate this result, regardless of granularity of information provided.

Study three examined the interaction between communicator trustworthiness and granularity of information provided. Participants were told that there was a power outage and that restoration of service would either occur in 4 days or 96 hours. Half the participants would also learn that “the company has been on Forbes’ list of ‘The 100 Most Trustworthy Companies’ for the last 11 years…whereas the other half learned that the company ‘has repeatedly been found to falsify financial reports over the last 11 years’” (Zhang, and Schwarz 12). After reading the articles, participants were asked to provide the likelihood that 1) power would be restored on Day 3 and 2) power would be restored on Day 4. Zhang and Schwarz found that participants given the article with the claim of company trustworthiness thought it was more likely for restoration to occur on day 3 if they were provided the 4 day estimate. Other participants given the 96 hour estimate were more likely to believe that restoration would occur on day 4 – “presumably, the company used the precise “96 hours” estimate for a reason” (Zhang, and Schwarz 13). Results of the study showed that 68% of participants believed that the trustworthy company was more likely to restore power by the 4 day deadline, whereas 54% of participants believed that the untrustworthy company would restore power by the given deadline. Thus the communicator’s trustworthiness plays a role in the optimism of the listener’s perception.

In Zhang and Schwarz’s final study, they examine the relationship between granularity and consumer choice. Like study one, study four is separated into two components: 4a and 4b. Study 4a provided participants with the product description of two different GPS devices. The first device was described to last up to 2 hours, or up to 120 minutes. The second device was described to have 3 hours or 180 minutes of battery life. Subjects were asked to provide their estimates of how long the battery on the devices lasted. Participants perceived the products given finer grain information lasted closer to the product description estimate, estimating that the devices would last 106 minutes and 160 minutes, for the GPS devices listing 120 minutes and 180 minutes of service time respectively. In contrast, participants given product descriptions of 2 and 3 hours of battery life estimated that the devices would last 1.49 hours (89 minutes) and 2.4 hours (144 minutes) respectively. In study 4b, participants were told that they preparing for a 90 minute hiking a trip, and that a GPS device was “very important [to complete] the trip safely” (Zhang, and Schwarz 14). Participants were then presented with two GPS devices as rental options. The first device lasted up to 2 hours (or 120 minutes) and the second device lasted up to 3 hours (180 minutes). Participants were given their choices in minutes or hours. Results of the study showed that participants were more likely to choose a device that lasted up to 120 minutes for the hiking trip, and more likely to choose a device that lasted up to 3 hours when presented with hours as the denomination of units. Again, the overarching theme of granularity influencing participant perception comes up.

Based on Zhang and Schwarz’s findings, it becomes apparent that quantity of information, in accordance to Grice’s conversational maxims plays a role in persuasion. Companies can strategically place different denominations of units to relay different information in the favour of the company. For instance, a company unsure of the completion time of a project can give an estimate with coarser units (using months instead of days for completion). On the other hand, a company looking to launch a product in a new market can use finer grain units in their product description to influence the purchasing decision of new consumers. The implications of this study can carry forward in a vast array of business functions from marketing to sales to public relations so it is important to understand the effects of granularity on perception.


Zhang, Y. Charles, and Norbert Schwarz. “How and Why One Year Differs From 365 Days.” Journal of Consumer Research. (2011): 1-28.


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