CONSUMER TRUST State of the Industry Report - 2019

An ExpertVoice eBook

An ExpertVoice eBook 2

“Americans have lost faith in institutions.”

Executive Summary1

This Washington Post headline 1 is one of roughly 449 million results that a reader can find when searching for the phrase “trust in institutions” using Google.

In recent years, think tanks, journalists, policymakers, marketers and pollsters have documented a decline in the trust that ordinary citizens place

in their governments, businesses and other institutions. Gallup, a pollster, created an online repository for year-over-year data on the receding levels of trust ordinary citizens place in groups such as banks and the military. 2 Faced with such a sustained decline, organizations as wide-ranging as retailers and advocacy groups must navigate the trust chasm armed with data and dexterity. We hope this research report will assist you in such efforts.

1 https://www.washingtonpost.com/posteverything/wp/2017/03/03/americans-have-lost-faith-in-institu-tions-thats-not-because-of-trump-or-fake-news/?noredirect=on&utm_term=.b731cdf2900b

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ExpertVoice, the world’s leading advocacy marketing platform, recently commissioned its annual State of Trust research in January 2019.

We conducted a panel with 500 Americans, a U.S.-census weighted audience, how they think about trust in the context of making high-consideration purchases. The results bolstered existing narratives and provided evidence of opportunities for retailers and brands alike.

For the second straight year, we found high confidence in friends, family, people who shared a respondent’s interests, and professional experts, the individuals whose ranks include coaches, guides and instructors. Nearly three in four respondents said they were likely or extremely likely to act upon a product recommendation coming from friends or family. On the other side of the spectrum, just one in five said they trust celebrities. Asked to elaborate on their opinions, 43 percent of respondents declared, unprompted, that they had concerns about athletes, celebrities and influencers being paid to make recommendations.

In an era where retailers have been saddled with high levels of debt 3, it is little wonder that years of declining investment in retail training has resulted in consumers discarding the recommendations of associates. The “retail apocalypse” (12.5 million search results) coincided with the rise of

e-commerce giants such as Amazon and Walmart. The search for advice on what to buy has shifted from in-person to online. Our panel indicated high levels of confidence in Amazon’s online reviewers, due to their preponderance and ease-of-access. At the same time, just 45 percent are confident they can spot a paid recommendation online.

How can brands and retailers tackle this challenging landscape? Our panel provided key insights: Brands should provide information and/or encourage reviews by individuals who have knowledge and firsthand experience with the products they’re promoting and are “ordinary” people who can be viewed as trustworthy i.e. there is no monetary gain for providing the recommendation. Brands that work to build and maintain credibility with their consumers through this approach are more likely to gain market share in the future.

For the second straight year, we found high confidence in friends, family, people who shared a respondent’s interests, and professional experts, the individuals whose ranks include coaches, guides and instructors.”

“2 https://news.gallup.com/poll/1597/confidence-institutions.aspx

3 https://www.bloomberg.com/graphics/2017-retail-debt/

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of respondents are familiar with influencer marketing.

Respondents continue to trust friends and family, people who share their interests and professional experts.

have acted on buying advice from friends and family in the previous year.

+ 12-point increase over the prior year.

+ 7-point increase over the prior year.

57% say they have acted on advice from online reviewers.

This, despite only 45% saying they were very or extremely confident that they could spot a paid recommendation online.

2

75%85%

57%Key Findings

Familiarity with influencer marketing may be tied to household income. Among our respondents, those earning greater than $50,000 indicated they were familiar with influencers 82% of the time, while those earning less indicated only 69% of the time.

Women are 5 percentage points more likely than men to be familiar with influencers and influencer marketing (77% to 72%)

say a good recommendation contains information about the reviewer’s personal experience with the product.

say they trust product reviews on Amazon.

say they have concerns about celebrities and/or influencers being paid.

52% of 18-29 year olds say they are confident they can spot a paid recommendation online, and just 29% of those age 45-60 say the same.

74%84%43%

18-29 45-60

52%

82% 69%

29%PAID?

77% 72%

2 Key Findings

6

Edelman, a market research firm, surveyed 33,000 individuals in 27 markets from Q4 in 2018 for their annual Trust Barometer report 4.

After decades of diminishing faith in key institutions 5, Edelman found a 4-point increase in their trust index. This masks a critical issue that companies have struggled with in recent years: a trust gap between two groups, who Edelman terms the informed public and the general population, the latter representing 84 percent of the world.

The portrait of trust in institutions gives brands a reason to be uneasy. Commerce is increasingly digital and if consumers don’t have confidence in the accuracy of online information regarding a brand or its products, they’re less likely to purchase. With somewhere north of 80 percent of Americans reading online reviews prior to purchase 6, both brands and consumers have concentrated their time and financial resources on online recommendations.

According to the Stanford Network Analysis Project, Amazon had over 34 million product reviews through 2013 7. Cue two-plus years of headlines like “Here’s why Amazon Can’t Fix Review Spam” 8 and companies such as Fakespot being developed to ferret out “dishonest and unreliable reviews.” 9

Manufacturers that earn an F rating from such algorithms may rue the day they decided to prioritize review quantity over quality.

Or maybe not. Companies have an incentive to ensure that their products have more reviews, faster. A 2013 study from researchers at the University of Las Palmas de Gran Canaria in Spain analyzed reviews of over 16,000 hotels.10 The authors documented a clear positive trend between review quantity and rating: More reviews lead to better reviews, from the brand’s point of view. Companies that fall behind their competitors may be allured to produce fraudulent reviews, either in favor of themselves or against their rivals. Luca and Zervais (2016) discovered that increased competition among restaurants led to establishments becoming “more likely to receive unfavorable reviews.” 11

Background3

4 https://www.edelman.com/trust-barometer

5 https://news.gallup.com/poll/1597/confidence-institutions.aspx

6 http://www.pewinternet.org/2016/12/19/online-reviews/

7 https://snap.stanford.edu/data/web-Amazon.html

8 https://lifehacker.com/heres-why-amazon-cant-fix-review-spam-1825955852

9 https://www.fakespot.com/

10 https://journals.sagepub.com/doi/abs/10.1177/1938965513481498

11 https://pubsonline.informs.org/doi/10.1287/mnsc.2015.2304

Commerce is increasingly digital and if consumers don’t have confidence in the accuracy of online information regarding a brand or its products, they’re less likely to purchase.

“

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Cutthroat competition leads to cutthroat methods, particularly for independent firms fighting an uphill battle in an increasingly monopolistic economy. 12

Eric Anderson at the Kellogg School and Duncan Simester at MIT Sloan conducted perhaps the most robust investigation into the accuracy of online reviews. The duo partnered with a private label retailer to match reviews to purchase history. Their findings shed light on the characteristics of potentially fraudulent reviews. Reviews are written by a tiny portion of all purchasers, just 1.5 percent in their data set. Of these reviewers, 6 percent had unconfirmed purchases. Such reviews had an average rating of 4.07 out of 5, compared to 4.33 among verified buyers. The score differential was mirrored on an Amazon data set the pair examined. In addition, Anderson and Simester discovered that “the word count for the reviews without confirmed transactions” was “approximately 40 percent higher than in the reviews with confirmed transactions”. Such comments also contained details unrelated to the product and often featured multiple exclamation points.

Our work adds to the existing literature by assessing which groups people trust when researching high-consideration products, such as outdoor gear. We also look at the connection between age, gender, household income and confidence in sussing out problematic product reviews. Finally, we examine specifically what information individuals want in reviews: personal experience and product details.

12 https://www.economist.com/special-report/2018/11/17/which-american-industries-are-most-in-dan-ger-of-monopoly

13 http://web.mit.edu/simester/Public/Papers/Deceptive_Reviews.pdf

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Respondents are generally familiar with influencers and influencer marketing.

This is to be expected, given the online medium for the poll. We found a 12 percentage-point increase in familiarity compared to the 2018 results.

Brands and manufacturers are concerned not just with trust but with how trust correlates to purchase. As in 2018, we found a high likelihood to act on buying advice from groups that respondents can relate to: family, friends, people like them and a group we term the professional expert, which includes individuals such as coaches, trainers and outdoor guides.

The results are intriguing when one considers the lay of the buying landscape. Purchases are increasingly shifting online, yet just 48 percent of respondents say they are likely to act on the advice of an online reviewer. All the same, if they are purchasing online, they have little choice but to take into account online reviews, which generally appear front-and-center prior to adding an item to your digital cart.

What makes respondents likely to act upon a recommendation? A few of our panelists shared their thoughts. In general, they indicated a preference for those they personally know, although they were willing to make exceptions for online reviewers in certain cases. Selected quotes are highlighted below.

Results4

86+80+75+46+33+33

Fig. 1: Are you familiar with social in�uencers and in�uencer marketing?

25%

50%

75%

100%

2019 2018

75%63%

Fig. 2 - How likely are you to act upon a product recommendation from each of the following groups? (Percent answering likely or extremely likely)

Family and Friends

People who share the same interests as me

A professional expert (coach, guide, or instructor)

People you meet participating in your favorite activity

Online reviewers

Coworkers

Professional athletes

Retail sales associates

Social in­uencers on Facebook, Instagram, etc.

Celebrities

74%

63%

54%

51%

48%

46%

23%

22%

22%

17%

9

Compared to 2018, we document upticks in taking buying advice from the less trusted groups, such as celebrities. This is shown below.

“I’m more likely to trust those I know personally rather than someone I don’t know about products. I think the only exception is online reviews.”

“When someone is getting paid to sell something, I don’t trust it. Groups of people online are brutally honest, so I trust their reviews the most.”

“People that have more knowledge about the product and are familiar to me make me feel more comfortable with spending my money on something rather than someone who’s paid to sell the item.”

When asked which group’s recommendations led to actual purchases in the prior year, the answers were similar to the previous question on trust.78+57+44+42+29+28+25+22+12+9

Fig. 3 - Which of the following groups have you taken buying advice from in the previous year?

Family and Friends

Online reviewers

People who share the same interests as me

Coworkers

A professional expert (coach, guide, or instructor)

People you meet participating in your favorite activity

Social in­uencers on Facebook, Instagram, YouTube, etc.

Retail sales associates

Celebrities

Professional athletes

78%

57%

44%

42%

29%

28%

25%

22%

12%

9%

Fig. 4 - Year-over-Year Comparison Respondents likeliness to act on a recommendation from:2+12Celebrities 2%

12.20%6+24Social in�uencers on Facebook, Instagram, YouTube, etc.

6%24.60%6+9Professional athlete 6%

9%32+22Retail sales associates 32%22%50+57Online reviewers 50%

57%30+28People you meet participatingin your favorite activity

30%27.80%45+42Coworkers 45%

41.60%85+78Friends and Family 85%77.80%

2018 2019

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Of particular note is that while 48 percent said they were likely to act on a recommendation from an online reviewer, nearly ten percent more said they actually had acted. 54 percent said they would be likely to act on an expert recommendation, while a 29 percent actually had.

This indicates a competitive opportunity for firms to connect such experts with consumers. Furthermore, we found double digit differences for people you meet participating in your favorite activity and people who share the same interests as me. The differentials are noted below.

Table 1 - Buying Advice versus Likelihood to Purchase

Group Took Buying Advice Likely to Act Difference

Friends and family 78% 74% 4%

Online reviewers 57% 48% 10%

People who share the same interests as me 44% 63% -19%

Coworkers 42% 46% -4%

A professional expert (such as a coach, guide, or instructor) 29% 54% -25%

People you meet participating in your favorite activity 28% 51% -23%

Social influencers on Facebook, Instagram, YouTube, etc. 25% 22% 2%

Retail sales associates 22% 22% -0%

Celebrities 12% 17% -5%

Professional athletes 9% 23% -14%

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Consumers have been inundated by advertisements in recent years. Through the first half of 2018, the Interactive Advertising Bureau estimated $49.5 billion in digital ad spend, a “dramatic 23 percent year-over-year increase.”14 In response to the above bombardment and developments such as ad blockers, firms have shifted their spend toward influencers on YouTube and Instagram, or to compensating online individuals for leaving favorable reviews for them and negative reviewers for competitors.

Our respondents appeared aware of such tactics and unsure of how well they could detect them. We specifically prompted them to think about paid recommendations that are not explicitly labeled as an advertisement.

14 https://www.iab.com/news/digital-ad-spend-hits-record-breaking-49-5-billion-in-first-half-of-2018/

���������Fig. 5 - How con�dent are you that you can spot a paid recommendation online

(excluding an advertisement)?

4%

Extremely condent

Very condent

Somewhat condentNot so condent

Not at all condent

15%30%

41%10%

The results are telling. Just 45 percent are confident they can spot paid recommendations. Although the results are similar across gender and household incomes, this confidence is concentrated among younger individuals.

But even among the extremely online generation, barely over half are confident they can detect paid endorsements that are not labeled as ads. These numbers are highly concerning in the context of the academic literature cited earlier. Everyday purchasers depend on e-commerce retailers to indicate whether a reviewer has purchased the product. Brands that double as retailers have strong motivations to forge such information.

Age Not confident Somewhat confident Confident

18-29 16% 33% 52%30-44 8% 51% 41%45-60 19% 52% 29%

Table 2 - Younger individuals are more confident they can spot a paid recommendation online chase

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Respondents to the survey freely indicated that they want information from someone who purchased the product, used it and understands it. 43 percent are worried about celebrities or influencers being paid to recommend products. As one person put it, they want “REAL, AUTHENTIC reviews by someone who was not paid or given free product in exchange for promoting or reviewing said product.” Another admitted to leaving deceitful 4- and 5-star reviews to boost a family member’s business.

When Anderson and Simester analyzed online reviews, they discovered that reviews left by non-purchasers were more likely to contain irrelevant information15 and omit the product details. Correspondingly, panelists yearned for reviewers that left information indicating product knowledge and experience.

Fig. 6 - What characteristics make up a trustworthy recommendation?

4%

36%

52%

57%

61%

74%

Other (please specify)

The reviewer’s knowledge of the brand

The reviewer includes a comparison to a like product

The reviewer’s knowledge of the product category/activity

The reviewer’s knowledge of the product details and speci�cations

The reviewer’s personal experience with the product

Perhaps the most provocative result of our survey is the high level of trust that respondents placed in Amazon reviews.

What do we make of the above results, given the low levels of trust in institutions and a plethora of media stories covering fake reviews on Amazon? Several factors could be at work. Our poll was conducted online, to an audience that may be more favorable toward online retailers. In addition, Amazon allows photos, videos and purchase verification information to be present in their reviews, enhancing credibility even amid the proliferation of paid reviews.

Fig. 7 - For each of the following websites, please indicate if you trust product reviews on that website?

13%

22%

26%

34%

41%

85%

Other ecommerce websites (e.x. Backcountry.com)

Brand websites (e.x.Skullcandy.com)

eBay

Retailer websites (e.x. Best Buy)

Walmart.com

Amazon

14 http://web.mit.edu/simester/Public/Papers/Deceptive_Reviews.pdf

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Respondents to our survey were young, slightly more female than male, and concentrated in low-to-middle income ranges, due to controlled weighting.

This is shown below in Figures 8 to 10. Not represented is the geographic distribution, which matches official U.S. Census regions.16

Demographics5

Fig. 8 - Age

�����45-60

30-44

18-29

53%32%

15%

Fig. 9 - Gender

���MaleFemale 47%53%

Fig. 10 - Household Income

$0-$9,999

$10,000-$

24,999

$25,000-$49,999

$50,000-$74,999

$75,000-$99,999

$100,000-…

11%

14%

27%

22%

16%

9%

16 https://www2.census.gov/geo/pdfs/maps-data/maps/reference/us_regdiv.pdf

Respondents were likely to act upon product recommendations from family, friends, people like them and experts. They are less likely to trust celebrities, athletes and online influencers. Each of these groups are associated with paid endorsements and/or a lack of quality information. Despite only 45 percent of survey respondents exhibiting confidence in spotting paid recommendations, they uniformly congregate to Amazon when researching high-consideration purchases. Critically, the survey found massive gaps

in likelihood to purchase and indicated purchases among groups such as professional experts and people with similar interests to the individual.

Brands and marketers that can connect those groups to consumers will thrive in today’s consumer-centric economy.

Conclusion5

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