Tag Archives: eWOM

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Making the most out of your marketing efforts in the context of eWOM

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Think about it, who is your favourite advisor when it comes to finding your next, undiscovered restaurant? Your mum or perhaps your best friend? Sometimes they might not give the best advice, luckily you have kind strangers who write reviews online, which you can consult. Review platforms such as Yelp.com, enable people to write and read reviews on products and/or services. But how do businesses handle marketing efforts in the context of electronic word-of-mouth (eWOM)? This is an important question for managers since the rise of the Internet has changed how they allocate marketing expenditure, turning more to online advertising (Lu et al. 2013), but is this effective? To answer this question Lu et al. research the influence of promotional marketing on third-party review platforms.

What was their approach?
Lu et al. examined the impact of online coupons, keyword sponsored search and eWOM on weekly restaurants’ sales using a three-year panel study. They focused on restaurants since going out to dinner is a high-involvement service and eWOM is particularly important for high-involvement products and/or services (Gu et al. 2012). With high-involvement products customers spend considerable time searching for information before purchasing. Lu et al. collected their data from one of the largest restaurant review websites in China. Online coupons are displayed on this platform and the keyword sponsored search works as follows: restaurants buy keywords and when users search for restaurants using that keyword, the restaurants will be displayed at the top of the platform’s search results.

Key insights
One of the key insights Lu et al. found is that both promotional marketing and eWOM have a significant impact on sales. Keyword sponsored search and eWOM have a positive impact on sales. Likewise, offering online coupons has a positive impact on sales, however this relationship is not present for coupon value, indicating that the presence of online coupons is more important than their value since it increases awareness among users (Leone and Srinivasan 1996). Another key insight is that interaction between eWOM and promotional marketing is significant. The interaction between eWOM and coupon offerings is negative, indicating that they substitute one another and thus only one is needed to attract sales. On the other hand, the interaction between eWOM and keyword sponsored search is positive, indicating that they complement one another and together increase sales. Furthermore, if you would use both promotional marketing tools simultaneously, this would negatively impact sales since too many marketing tools  at the same time is experienced as too intrusive by customers. Altogether, these insights highlight different sources of information, with different levels of credibility, while still both sharing the power to inform and attract customers.

Looking to promote your business?
The study’s strength is that it presents some very useful advices when it comes to using promotional marketing in the context of eWOM. First of all, it is good to know that allowing promotional marketing activities on third-party platforms does not hurt the platform’s credibility and thus indicates some interesting marketing possibilities. According to Lu et al., you should stimulate users to generate more positive eWOM since this increases sales. Businesses could use online coupons to get customers’ attention, but if the volume of eWOM is high, this tool becomes less effective. In the case of high eWOM volume, businesses should rather buy keywords to increase sales. However, businesses should not use these two promotional marketing tools simultaneously since this decreases sales, rather they should focus on the tool that is most suitable for them.

Although these insights are useful, managers should note the study’s weaknesses. One of these weaknesses is the study’s generalisability. Firstly, the study only included restaurants from Shanghai, while other academics indicate the presence of cross-cultural differences (King et al. 2014). Secondly, the study focused on high-involvement products, while many studies examine low-involvement products, e.g. books and films, and find that eWOM has a significant impact on sales (Chevalier and Mayzlin 2006; Duan et al. 2008). Thirdly, the study focused on one platform, while other studies indicate that eWOM across platforms can impact sales (Gu et al. 2012). Therefore, future research could focus on whether the study’s results also apply cross-culturally, across different product and across different platforms. Another weakness of this study is the limited dimensions of eWOM and promotional marketing captured. For instance, Chavelier and Maryzlin (2006) indicate that the length of reviews also influences customers’ purchasing behaviour. Besides, the measurement of promotional marketing is two-fold, while other options such as banners or pop-up ads also exist. Future research could therefore investigate whether results differ for other promotional marketing tools and if adding more dimensions for eWOM might indicate different results. To conclude, although the paper has some weaknesses, it does not overturn the practical implications, managers should however be cautious and decide whether the study applies to their specific situation or if their situation deviates from the study’s setting.

References
Chevalier, J.A. and D. Mayzlin (2006) ‘The Effect of Word of Mouth on Sales: Online Book Reviews’, Journal of Marketing Research 43(3): 345-354.

Duan, W., B. Gu and A.B. Whinston (2008) ‘The dynamics of online word-of-mouth and product sales – An empirical investigation of the movie industry’, Journal of Retailing 84(2): 233-242.

Gu, B., J. Park and P. Konana (2012) ‘Research Note – The Impact of External Word-of-Mouth Sources on Retailer Sales of High-Involvement Products’, Information Systems Research 23(1): 182-196.

King, R.A., P. Racherla and V.D. Bush (2014) ‘What We Know and Don’t Know About Online Word-of-Mouth: A Review and Synthesis of the Literature’, Journal of Interactive Marketing 28(3): 167-183.

Leone, R.P. and S.S. Srinivasan (1996) ‘Coupon face value: Its impact on coupon redemptions, brand sales, and brand profitability’, Journal of Retailing 72(3): 273-289.

Lu, X., S. Ba, L. Huang and Y. Feng (2013) ‘Promotional Marketing or Word-of-Mouth? Evidence from Online Restaurant Reviews’, Information Systems Research 24(3): 596-612.

 

Articles

“THIS POST IS SPONSORED”

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Effects of Sponsorship Disclosure on Persuasion Knowledge and Electronic Word of Mouth in the Context of Facebook

facebook-logo-100035675-mediumThey are everywhere. We all have seen one: a post on Facebook, Instagram or any other social media platform with a little sign saying that the post is sponsored. We see a celebrity enjoying a certain product and recommending it to the audience. We think to ourselves if the person in question is genuine in his or her motives of sharing it, whether they are actually using the product or whether we should follow their recommendation to purchase it ourselves and possibly share our newly found trophy with our family and friends. This simple everyday ritual we have with ourselves, sometimes multiple times a day, has prominent psychological mechanisms coming into play, guiding us through the journey starting from the recognition of the post as sponsored to eventually activating us to share it with our loved ones.

These psychological mechanisms lay the foundation of the research conducted by Boerman, Willemsen and Van der Aa (2017). The researchers identify the source of the sponsored post(brand or celebrity) as the initial step to recognizing it as carrying persuasive, or in other words, advertising value by consumers. This is defined as the activation of the conceptual persuasion knowledge, which in turn, activates the attitudinal persuasion knowledge. Attitudinal PK gets activated when consumers start developing critical and distrusting feelings towards the advertisement (Boerman, Van Reijmersdal and Neijens 2012).  All these are used as determinants to find out whether the consumers eventually engage in electronic word of mouth (eWOM; cf., Berger 2014).

Designing the experiment

Building on the theoretical foundations mentioned above, researchers conduct an online experiment with 409 participants. A post with David Beckham drinking an Illy branded cup of coffee with the text ‘Starting the day with a nice cup of coffee!’ (posted by David Beckham) and ‘David Beckham starts his day with a nice cup of coffee!’ (posted by the brand) is shown to participants to test the following hypotheses by having participants answer a series of questions:

H1. A Facebook ad that is accompanied by a sponsorship disclosure (‘Sponsored’) will be more likely to activate consumers’ conceptual persuasion knowledge, than a Facebook ad without a sponsorship disclosure.

H2. A Facebook ad that is posted by a celebrity will be less likely to activate conceptual persuasion knowledge, than a Facebook ad that is posted by a brand.

H3. The effects of a sponsorship disclosure on the use of conceptual persuasion knowledge are stronger when a Facebook ad is posted by a celebrity compared to when a Facebook ad is posted by a brand.

H4. Source moderates the effect of the sponsorship disclosure on attitudinal persuasion knowledge through the activation of conceptual persuasion knowledge: The mediated relationship of the disclosure on attitudinal persuasion knowledge will be stronger when the Facebook ad is posted by a celebrity (vs. a brand).

H5. When a Facebook ad is posted by a celebrity, a sponsorship disclosure activates conceptual persuasion knowledge, which results in the use of attitudinal persuasion knowledge and ultimately lowers eWOM. When a Facebook ad is posted by a brand, such serial mediation is less likely to occur.

The figure below clearly outlines the experiment design and the source of the Facebook post as the initial stimulus.

Screen Shot 2018-02-14 at 18.06.39

Anticipated results

In line with the expectations, researchers found evidence to support all five hypotheses. They found that the conceptual and attitudinal PK activation was significantly different when the source of the post was a celebrity in the presence of a sponsorship disclosure. This was not the case when the ad was posted on Facebook by the brand. Activation of the attitudinal PK after recognizing the post as an ad resulted in consumers engaging less in eWOM as a result of the distrusting feelings they developed by recognizing the post as advertising. An interesting finding of the study, however, indicates that little attention is paid to the sponsorship disclosures. The study shows that 59% of the participants did not recognize the sponsorship disclosure which is also in line with previous studies conducted (e.g., Boerman, Van Reijmersdal, and Neijens 2012; Campbell, Mohr, and Verlegh 2013; Wojdynski and Evans 2016). Intuitively, this has an impact on the interpretation of the results. Even though the activation of the conceptual and attitudinal persuasion knowledge of the consumers will result in less engagement, lowering the perceived success of the ad, this does not directly condemn sponsored celebrity Facebook posts to failure since the majority of the people won’t recognize the post as an ad.

 

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 Leveling the playing field

Although the study comes with its limitations due to its single product, brand (Illy coffee), celebrity (David Beckham) and geographical (conducted in the Netherlands) focus, it provides invaluable insights into the effect of sponsorship disclosures on Facebook posts. It seems the regulators’, such as FTC’s, disclosure requirements are not sufficient enough to level the playing field for consumers when it comes to social media advertising. Further research might reveal, however, how this could be overcome as well as consumers moving along the learning curve might become more aware themselves. Until then, better to think twice before you share that post by your favorite celebrity you saw on your newsfeed.

References

Berger, Jonah (2014), “Word of Mouth and Interpersonal Communication: A Review and Directions for Future Research,” Journal of Consumer Psychology, 24, 4, 586–607.

Boerman, Sophie C., Eva A. Van Reijmersdal, and Peter C. Neijens (2012),“Sponsorship Disclosure: Effects of Duration on Persuasion Knowledge and Brand Responses,” Journal of Communication, 62, 6, 1047–64.

Boerman, S., Willemsen, L. and Van Der Aa, E. (2017). “This Post Is Sponsored” Effects of Sponsorship Disclosure on Persuasion Knowledge and Electronic Word of Mouth in the Context of Facebook. Journal of Interactive Marketing, 38, 82-92.

Campbell, M., Mohr, G. and Verlegh, P. (2013). Can disclosures lead consumers to resist covert persuasion? The important roles of disclosure timing and type of response. Journal of Consumer Psychology, 23(4), pp.483-495.

Wojdynski, Bartosz W. and Nathaniel J. Evans (2016), “Going Native: Effects of Disclosure Position and Language on the Recognition and Evaluation of Online Native Advertising,” Journal of Advertising, 45, 2, 157–68.

Articles

Know Yourself And Know Your Enemy

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‘If you know yourself and know your enemy, you need not fear the result of a hundred battles’ (Sun Tzu, Art of War)

Online retailers currently implement and leverage a variety of sales support tools. This article provides insight in consumer (users) behaviour on those e-commerce websites (Adomavicius and Tuzhilin 2005). It looks at different factors that might affect consumer behaviour (specifically consumers’ decisions whether or not to buy a product) (Hennig-Thurau et al. 2012). In this research the effect of two things on sales of a product is examined. One is recommendation systems (generated by the firm) and the other is online review systems (generated by customers). Previous literature has primarily focused on both loose effects; this study particularly looks at how these two factors might combine together to affect consumers’ behaviour.

Recommendation systems are where each product will give you recommendations to other (similar) products (Oestreicher-Singer and Sundararajan 2012). This study argues that we should see recommendations systems as networks with a number of different products linked to each other. This study seeks to analyse the whole network of related product referrals. The author predicts that the position of all the different products within a network might affect the sales of a product. Any product near to the centre of the recommendation network will get more attention. So, if the Product A is near to the centre of the network it will get more sales. If the competing product (or normally products) is near to the centre these will get more attention, taking attention away from the Product A, and so Product A will get less sales.
Online review systems (eWOM: electronic word-of-mouth) are where users of this site write a review of a product. This study observes when the consumers is shopping on the site, they can see both reviews of the product they are considering and also all reviews of other recommended products. The author predicts that the fact that they can see these other reviews creates competition, which makes the customer less likely to buy the particularly product.

The empirical analysis are performed with collected data from Amazon.com on 1.740 randomly selected books within four categories (programming, business, health and guide books) over a period from two years. This empirical analysis yields three major findings. The research has shown that recommendation systems intensify the competition between products. The authors state that the products which are linked to recommendation systems generate more sales if they have a central place in the referral recommendation network. There have been extensive findings that these sales gains are impeded by improvements in the reviews (eWOM) of competing products. This indicates that a positive eWOM received by a competing book worsen the rank of the focal book.

The main limitation of this study is that they used data at aggregate level, and not at individual consumer level. Therefore, the collected data does not track the actual activity of reviews/recommendations. This is a missing link for virtually all eWOM studies. The solution to this limitation could may be collecting click-stream data to better connect behavior and action.

 

 

References
Adomavicius, G., and Tuzhilin, A. 2005. “Towards the Next Generation of Recommender Systems: A Survey of the State-of- the-Art and Possible Extensions,” IEEE Transactions on Knowl- edge and Data Engineering (17:6), pp. 734-749.

Hennig-Thurau, T., Marchand, A., and Marx, P. 2012. “Can Auto- mated Group Recommender Systems Help Consumers Make Better Choices?,” Journal of Marketing (76:5), pp. 89-109.

Oestreicher-Singer, G., and Sundararajan, A. 2012. “Recommen- dation Networks and the Long Tail of Electronic Commerce,” MIS Quarterly (36:1), pp. 65-83