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SmartData Collective > Big Data > Data Mining > Do Customer Reviews Help or Hurt?
Data Mining

Do Customer Reviews Help or Hurt?

AkinArikan
AkinArikan
4 Min Read
Do Customer Reviews Help or Hurt?
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As the previous post explored the question whether Freshdirect would see increased revenues from user generated content, one of my most resourceful colleagues, Jay Henderson, pointed out an interesting study by Bazaarvoice.

Bazaarvoice, if you didn’t know this already, is a solutions vendor that facilitates customer reviews for retailers and other eCommerce companies. In their own words, they bring “the power of social commerce to the world’s best brands.”

This study was done for Bazaarvoice’s client Bath and Body Works in 2007. The client and/or Bazaarvoice measured whether an email containing customer ratings and reviews would be more successful than ‘the average email” that includes the company’s typical marketing messaging.

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And what did the study find?

The email with peer reviews led to increased average order values by 10 percent! Wow. In addition to this monetary success indicator, session length was higher and bounce rates were lower when peer reviews were included in the email.

Now, admittedly, the study isn’t saying that they sent the same email content twice, once with reviews and once without. So it isn’t quite apples & apples that are getting compared I have the feeling.

But still, there is a great indicator here that customer generated reviews do seem to bring  great, tangible business value. And best of all, it is relatively easy for Bazaarvoice customers to run similar tests, measure outcomes, and convince themselves.

Incidentally, I was speaking with John Grech at Bazaarvoice competitor PowerReviews just this week. PowerReviews uses a “tag-based” approach to capturing customer reviews. That is to say that reviewers can enter social tags describing products they review.

For example if you  are reviewing a sneaker you might tag it as “Great for running”.

Merchandisers can obtain a data feed from PowerReviews that correlate tags vs. merchandise. Merchandisers can then offer navigation based on these tags, e.g. “Which shoes are great for running?”

Interestingly, there is also a promise for extensible web analytics solution to make use of the same tag data feed. Web analytics can then roll up web visitor activity, e.g. by “shoes that are great for running.” The web analytics solution would then be enabled to correlate that to keywords or referrers that attract visitors which end up looking at shoes that are great for running.

And let’s not forget about the offline marketers too.

Marketers can use the user generated tag content as a type of focus group. So if you designed a direct mail catalog about shoes that are great for running you could tap into this peer advice.

PowerReviews too have their case studies available online.

More power to these vendors. And many thanks to Jay for pointing it out.

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