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Reputation and Reviews (14:38)
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From the course by University of Pennsylvania
Wharton Business Foundations Capstone
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From the lesson
Marketing Plan for Review
In this Module, you'll write your Marketing Plan for your product or service that will be part of your final project. Because determining who the audience is for a product or service, and how to talk the audience about it is critical to the success of your capstone, you'll have the opportunity to get feedback on creativity and analytical strength of your marketing plan before you submit is as part of your final project. Once you submit your idea, please review the Marketing Plans of five of your peers.
Meet the Instructors
Christian TerwieschAndrew M. Heller Professor at the Wharton School, Senior Fellow Leonard Davis Institute for Health Economics Co-Director, Mack Institute of Innovation Management
The Wharton School
[MUSIC]
So welcome again everybody.
Today we're going to talk about something really cool and really interesting,
which is the whole idea of reviews and how they affect our behavior, both online and
offline, part of an omni-channel discussion.
So how are we going to do that?
Let me just give a quick overview of where we're going to go.
We're going to start with some motivation for
why review information is important and affects behavior in markets.
Then I'm going to give you a little bit of economic theory,
which I think is really fascinating based on some research
that was done by a colleague out in Los Angeles a few years ago.
I think you'll enjoy that.
And then finally I'll follow up some other examples of Amazon versus Barnes and
Noble on the internet and then Expedia versus TripAdvisor.
I'll explain those as we get through.
Here's the first motivation for reviews and use of reviews.
You'll notice there on the slide the statistic could even be higher.
I think I've been quite conservative here, but about 60% of us,
at least in the United States, but
I'm sure around the world, read reviews before we make purchase decisions.
And secondly positive reviews, whether they're for books, restaurants,
movies, jeans,
whatever it is that we're buying, are seeming to influence people's behavior.
So bringing this information into the market is very, very critical.
You might remember from one of our previous discussions that
one of the frictions that we often experience in the market is we don't
really know how good a restaurant is, how good a product is, how good a movie is.
And now that information is being made available much more easily and
much more efficiently.
Often by people who are complete strangers, but
the information's still useful for our purchase decisions.
Also, since we're here in Philadelphia,
at least I am, I wanted to put in a couple of quotes that I think speak
to the importance of reviews for merchants and probably even for individuals.
So Ben Franklin said, it takes many good deeds to build a reputation,
only one bad one to lose it.
So that might be interesting to think if you write a book and
you're selling it on Amazon and you're getting mainly five-star reviews and
suddenly a one-star review comes along, I wonder if that would affect your sales.
Well we'll answer that question as we go through the discussion a little further.
William Shakespeare, perhaps because of his British heritage,
I guess I'm partly from the area, coming from New Zealand.
He's a little more cynical, and
what he said in the quote there is that reputation is an idle and
most false imposition, often got without merit, and often without deserving.
So what he's saying is that sometimes people can build fake, or
phony reputations, and that's certainly true today in 2013.
In fact, many of the reviews, apparently, that we see on places like Amazon and
TripAdvisor and Yelp may, in fact, not be legitimate.
We'll get to that later on as well.
So just for your interest what I've done here is I've shown a bunch of links that
you can go and check out if you want to see how people review airlines.
People review recipes, people review doctors and so, and what you'll see here
is a flavor for how reviews are presented, whether visually with with stars,
whether they show the average, the deviation, whether there's content.
You may already be using some of these things, but just go and
take a look to get a sense of how this information is presented,
before I now give you some of the theory.
So before we get into the theory, I just want to share with you a very interesting
anecdote that I found on Chris Dixon's blog.
So this is a story about a startup that raised, as you can see on the slide,
about $4 million in venture funding, was eventually sold and
then roughly at the time of us preparing these videos in Philadelphia,
was a public traded company worth over $6 billion.
So who is this company?
This company actually is TripAdvisor, originally purchased by Expedia for
210 million and now has grown into a huge company
that's really a company primarily putting information into the market,
information that's contributed by people like you and I.
So for the budding entrepreneurs out there watching this, sometimes you can build
a great business just by bringing information into a market and
helping people make better decisions and better choices.
So lets begin with a little bit of theory.
Sometimes it's helpful to know just to ground what we're thinking about.
So economic theory would suggest that more information to consumers is
almost always better.
The more light that's brought to bear on a market, it's usually better for,
certainly, the end users, people like you and I.
In addition, an economist might tell us that if information is
provided into a market, it may change the behavior, not only of the buyers and
who they decide to buy from, but also the behavior of the sellers.
Maybe they'll be more motivated to provide better quality products and services.
So to examine this, there was a very interesting study done by two coauthors,
Jenn and Leslie, I've provided the reference for
the paper in the notes if you want to read the original paper,
who looked at what happened to the market for food, restaurant food,
in Los Angeles after inspections were done of the restaurants there.
So what I’ve shown on the slide are the actual photographs
of ratings of restaurants that appear in the windows of restaurants in Los Angeles.
In the United States, you also see them now in New York and
probably other places, too.
Perhaps in your home country you have something similar.
So the way this works is a health inspector visits a restaurant.
The health inspector goes through many,
many things in terms of the hygiene of the restaurant, gives it a score out of 100.
If the score is more than 90, then that restaurant places a sign in the window
that says that this is an A hygiene grade, B is a lower grade, and
C of course is a lower grade down still.
And so the co-authors, Jen and Leslie, wanted to figure out whether or
not providing this information into the market
would change the behavior of the consumers that were there.
And what did they find?
Well, what they found was the demand at restaurants that got
an A went up quite substantially, about 5 to 6%.
Demand at restaurants that got a B actually went up hardly perceptibly,
less than 1%, and demand at restaurants that got a C, of course, went down.
So once the information was in the market people, as you might imagine,
wanted to go to restaurants that had better hygiene and better quality food.
So that was a buyer explanational, that was an effect on demand.
But there's also an effect of information on supply,
which I think is at least as interesting, perhaps even more so.
So what did the provision of that information in the market
do to the sellers?
Well, it caused them actually to increase the quality of what they’re offering
because now there’s more of a benefit to be known as an A restaurant.
So to check this out, what the researchers did was something very clever.
They looked at the number of people that got sent to hospital for
food related illnesses, and what they found was in markets where
the signs were in place, that went down substantially, about 13%.
Whereas in other parts of California that didn't have the system, the number
of people going to the hospital for food borne illness was actually going up.
So again, that’s a pretty clever test that shows this was also affecting
the behavior of the sellers, as well as the behavior of the buyers.
So what do we learn from this?
Here’s the key principle, is that reviews and
review systems definitely change behavior, both of buyers and also of sellers.
But the most important thing,
knowing that, is that reviews ideally should be objective and verifiable.
This is not always the case.
Let's look at a couple of research examples.
The first one was a very clever study that was done two professors at Yale
that examined whether or not reviews for books help ramp up sales.
They looked at two different websites, amazon.com and barnesandnoble.com.
And what they found is,
most of the people who write reviews are in fact fairly generous.
There are five possible stars that you could give for a book at Amazon, and
the average rating at the time of the study was about 4.1.
On Barnes and Noble, for whatever reason, people are even more generous,
the average rating was about 4.5.
One star reviews are pretty rare, that's the lowest review.
So one star reviews would show up about 7% of the time on Amazon and
about 3% of the time on Barnes and Noble.
So did all of this reviewing have any impact on sales?
Yeah, you bet it did.
So what the authors found is if you got more positive reviews
sales of your book went up.
And they also found that if you got more negative reviews, one star reviews,
then sales of your book went down.
In addition, there was kind of a subtle effect of this negative information such
that if I got a negative review on a book that I had written, a one star review,
that seemed, in some, sense to also slow down the rate of positive
reviews that were coming along subsequently.
So, again, a very, very interesting study showing that reviews are affecting sales.
Now, of course, this might motivate people who are selling books
to review their own books if they know that it's going to have a positive effect.
So what I'm showing here, and you can read the articles and the links, is a picture
of a very interesting lady, Harriet, who has reviewed over 25,000 books on Amazon.
So I'm not suggesting that she hasn't, but
it's just interesting to notice that one person can generate so many reviews.
Now, in addition to our friend, Harriet, there was another fellow who was doing
something perhaps a little more devious but in some ways quite clever.
So there's a fellow called Mr. Rutherford.
You can read the article I provided a link for.
What he decided to do was to offer himself as a review-writing service for authors.
So if you'd just written a book, he might be willing to write 20 reviews for you for
some sum of money, let's say $100 or $500, completely, of course, fake reviews.
And what was interesting about this was Mr. Rutherford
was making about $28,000 not a year, but a month by doing these fake reviews.
So what does this tell us?
It tells us that information's powerful and it also tells us that sellers might
want to manipulate the information that's offered.
So, you might be sitting there scratching your head as I was when I first read
that story.
Boy, somebody making almost $30,000 a month providing fake reviews.
So clearly, this is a bit of a problem, and it's come to the attention of
many other writers and kind of experts, and so, how might one address this problem
of fake information being out there affecting people's behavior?
Well on the next slide,
I'm showing a story, you can read the full story in the New York Times,
about a gentleman who's an expert on something called data mining.
So what he would do is he would go through all of the text of reviews and try and
figure out what reviews are real and what reviews are fake and so on.
Now, even though that's a pretty sophisticated technique, it turns out that
it's actually difficult for a computer to figure out what's really true and
what's not under certain kinds of circumstances.
So it would be difficult, for example, for a data mining
algorithm to figure out if I was saying something sarcastically, for example.
So those nuances of language might be quite difficult.
So to look at this question from a different perspective, Dina Mayzlin,
who's a professor now at USC, she was one of the original authors on the other study
I mentioned about looking at the effect of reviews on Barnes & Noble and
Amazon, decided to tackle this problem in a very, very interesting way.
So let me illustrate that for you.
What she did is she wanted to compare ratings on TripAdvisor
versus ratings on Expedia for the same property.
So let's choose a property so we can all be clear about what we're talking about.
So it turns out there's a Sheraton Hotel on the corner of 36th and
Chestnut Street here in Philadelphia.
So Dina and her co-authors were curious as to whether the reviews of that property
were the same on TripAdvisor as they were on Expedia.
So most of you have probably been to those websites,
and you'll notice again it's a five star review system, and
you get a histogram of reviews, so some number of one star reviews,
two star reviews, three star reviews, four star reviews, and five star reviews.
Now if both of those sites are providing the same objective
information those histograms should be identically matched, right?
So that was the test that she wanted to see.
Were the histograms different for the same property?
And what she found was on TripAdvisor there were slightly more one star reviews
for certain properties and also slightly more five star reviews.
And when she dug in a little bit more what she found was if you were operating that
hotel, the Sheraton Hotel at 36th and Chestnut Street and located quite close
to you was a competitor, a competitor who perhaps just owned their own little hotel.
Let's call it Chris' hotel, Chris Heffron, the videographer.
And Chris's hotel is competing with the Sheraton, and because he's a one man shop,
not really accountable to a big organization as I would be if I were
a manager at the Sheraton, he would be more likely to write a one star review and
try and knock his competitor, the Sheraton at 36th, and he would be more likely to
write a five star review and to praise his own property.
That's what Dina and her colleagues found.
So again, it's very, very interesting to think about whether review information is
valid, because certainly people are acting on the basis of review information.
So this is a good point for me to now summarize the key idea,
if you were to introduce reviews into a market,
what you'd want to do is make sure those reviews are objective and verifiable.
And so what Dina did in her study is she made an assumption that reviews
on Expedia are more objective than reviews on TripAdvisor.
So I'll let you think about that for
a moment as to what the reason might be if you've looked at both of those sites.
I use both myself when myself when I'm deciding where to stay.
TripAdvisor was less objective than Expedia for the following reason.
In order to be able to post a review on Expedia you have
to have stayed at that property within the last six months.
So Expedia will send you an email and they'll know
from your credit card receipt that you actually booked and you stayed there.
Where as at TripAdvisor, you are supposed to have stayed there, but
that need not be the case.
I can go and write a review for a property that I had not stayed at.
So again, I think this is a fascinating area of online offline competition, and
again, I'd like to challenge and
encourage those of you out there who are thinking about starting your own business.
If you can start a business that brings information into a market,
that can be something very, very powerful.
If you think about the story of how TripAdvisor has grown into a multi billion
dollar company, that's essentially just gathering and
processing and providing review information that's generated by all of us.
[MUSIC]
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