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How Online Reviews Have Redefined Word of Mouth Marketing

Having word of mouth is no longer enough to grow your business. These days, customers actively express their opinions online and drive an entire economy. This is an opportunity for small business owners to take note and get directly involved with their customers. One such tool is Kenect, a technology platform that generates positive reviews. If you are a small business owner, using this tool will help you tap into the power of the online review economy.

 

Customer reviews

In today’s market, customer reviews are more important than ever. In fact, most consumers would instead read reviews than hear a promotional message from the company. Therefore, businesses need to provide their customers easy access to positive customer feedback and promptly respond to negative reviews. As the saying goes, you are only as good as the people who represent you. This means that customer reviews have a profound impact on your business.

Consumers are increasingly turning to the internet to search for information, and the online world is no exception. If people find a positive review online, they are more likely to visit the business in person or make a phone call. In 2016, 54% of consumers contacted companies after reading a review, compared with only 3% in 2017. Another interesting fact is that 64% of U.S. consumers cite recommendations from friends and family as their primary sources of brand awareness. In fact, 55% of people share their purchases via social media, including Facebook and Twitter. Further, 74% of consumers identify word-of-mouth as a significant factor in their purchasing decisions.

 

Influence of price on review helpfulness

Consumers rely on reviews to help make purchase decisions, and the popularity of online consumer reviews can cause information overload. Price cues may help consumers make informed decisions, although they aren’t the only factor. In fact, research suggests that the price of a product has different effects on review helpfulness than its other characteristics. Here are a few of them:

Price: Considering the price of a product, consumers are more likely to give it a high rating than a low one. Therefore, this variable is an essential predictor of review helpfulness. However, some consumers do not view price as a significant factor in rating. Therefore, a higher price is not always associated with a higher helpfulness rating. Hence, the price of a product does not necessarily influence review helpfulness.

Information quality (IQ): Researchers have attempted to explain reviews’ helpfulness using the concept of information quality. Chen and Tseng have shown that people need information about other parties to make an informed decision. The idea of IQ captures various aspects of the information a consumer receives. The first dimension is the price. The second relates to the price. The final dimension relates to the asymmetry in information.

Several factors may influence review helpfulness. While review effectiveness affects the likelihood of purchasing a product, price affects the relationship between eWOM and a movie’s box office performance. Moreover, the price may also have a profound effect on review helpfulness. The latter is significant in movies because reviews tend to differ widely in quality and predictive power. The study will be helpful in other industries as well.

Review usefulness can help consumers make better purchase decisions when users know the price of a product. Moreover, helpful reviews provide consumers with a diagnostic function. Therefore, online retailers that offer more helpful reviews have more value for consumers. However, the majority of websites do not include a useful voting function. As a result, many studies receive only a few helpfulness votes. This is due to the lack of a rationale for the voting function.

 

Influence of UGC on conversions

Studies show that customer reviews can impact conversion rates by increasing or decreasing sales. These reviews are more persuasive when they are from verified buyers, who are more likely to give a positive review than anonymous ones. Verified reviews are also more credible since they come from verified buyers and not from companies who have paid them to provide them. The first ten customer reviews that appear on a page can have the most impact, determining the conversion rate of a product.

It is estimated that ninety-nine percent of online shoppers read product reviews before making a purchase decision. Businesses need to respond to these reviews; the more consumers see positive reviews, the higher the likelihood they will purchase. Whether positive or negative, it’s essential to know that one or two reviews can boost your conversion rate by as much as 10%. Studies have shown that the higher your reviews, the higher the conversion rate. However, this doesn’t mean that negative reviews shouldn’t be posted.

Consumers spend four times longer on a site when they can read reviews and compare different items. They also spend more on things that include assessments, and higher-priced items often convert better than cheaper ones. Further, consumers trust consumer reviews more than manufacturer descriptions, and online reviews influence 67 percent of purchase decisions. Additionally, 81% of consumers are willing to wait for a product with a good review and would pay more for it.

In one study, the Spiegel Research Center studied the data of a high-end retailer and found that products with reviews tended to boost conversion rates by 190% and 380%. However, the same study also found that a product’s average star rating is no indication of whether it is a bad or a good purchase. Consumers spend 4x more time on a website when interacting with a negative review than with a positive one, according to Collinger.

 

Effect of sensory reviews on review helpfulness

The Effect of Sensory Reviews on Review Helpfulness

The effects of sensory reviews on review usefulness are controversial. This study challenges previous literature that has found a relationship between review extremity and helpfulness. While this isn’t surprising, it is also a challenge to the “average” review concept. Consumers often judge a product’s “utilitarian” or “hedonistic” traits. This may explain the relationship between extreme reviews and review helpfulness, but more study is needed to determine what this relationship is.

The effects of sensory reviews on review helpfulness are examined across product types. We found that reviews of products with high-quality labels are more helpful than those that aren’t. Moreover, reviews posted later received less helpful votes than those published earlier. Overall, coefficients of review timing showed negative signs in all models. Nevertheless, the results suggest that the effect of review length and depth on review helpfulness is robust to review timing and content.

Similarly, the effect of sensory reviews on review helpfulness is also influenced by content. Reviews with high helpfulness receive more votes than those with low ratings. It is not clear how to overcome this negativity bias. The authors note that this result may be related to people’s difficulty reasoning about expected behavior. However, a more complex explanation is the effect of positive emotion on review helpfulness. The study also suggests that reviewers’ perception of a product’s performance is influenced by subjective factors.

In contrast, the effect of language styles on review helpfulness is less relevant. Reviewers who use a language style that conveys clout and authenticity are more helpful than those with high ratings. The Effects of language styles on review helpfulness are less apparent when positive emotion is included. However, when a review contains many personal details, such as the name of a friend or the type of skin the reviewer has, its helpfulness is not increased.

The effect of sensory reviews on review helpfulness is further supported by experiments conducted on consumer behavior and online review sites. In Model 2, the impact of skin type and trouble on review helpfulness is insignificant. However, the effect of skin type and a high score on review helpfulness becomes more meaningful when these factors are combined. In Model 3, high-rated reviews with the reviewer’s skin type receive additional helpfulness votes.

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