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1. When do reviews adequately
portray a product or service?
2. Seeing the world with the consumer ecosystem perspective.
Two Topics from Studying
Consumer Reviews
©Artistic Analytics, LLC
The Sufficiency ProblemGenerally the more
reviews you have, the
more they converge on
a consensus assessment
of the experience. That
suggests to the prospective
customer that the
experience is very
predictable and low risk.
Some experiences are polarizing: some people love them while
others hate them. Sometimes random chance will bring
these two sides
together in near
equal numbers,
with results
confusing to the
prospective
customer. How do
you know?
Was this review helpful?
Explaining “helpful:”
• The writer’s total “helpful” votes (85%)
• Length of review (5%)
• Mention of the word “excellent” (1%)
There is another dimension to
many review sites, where readers
assess the helpfulness of reviews.
However, it is not obvious what
the implications of this
information are.
A Business’ Helpful Peaks
After a certain point readers
consistently assess reviews
to be less helpful. This may
be the point were existing
reviews reach sufficiency.
The red line is a
locally-weighted
regression.
Jumps in total
helpfulness
signal important
reviews.
*Yelp review data from the area around Phoenix, AZ
Satisfaction Minimizes
At the approximate
point where “helpful”
peaks, customer
satisfaction seems to
minimize.
When the entity being
reviewed is sufficiently
portrayed, the proper
market begins to be
exclusively attracted
and satisfaction rises.
Matching Expectations with Outcomes
Since matching expectations with outcomes is the key to customer satisfaction,
consumers should be told when the available reviews might not yet allow them
to make an informed prediction of their outcome.
McPhee’s (1963) Theory of ExposureMcPhee’s Theory of Exposure:
• Natural monopoly. The most popular
products get the most users, and those
who use them least.
• Double jeopardy. Niche products have
a double disadvantage: (1) they are not
well-known; and, (2) when they
become known, it is by people who use
the popular products and prefer
them.
– But are they truly engaged by them?
Niche venues
Niche Proportion Clusters
Field 1 2 3 4
Consumers 16565 9682 6910 5319
Avg. stars 3.82 3.77 3.7 3.6
∑ Helpful -7168 12016 -2007 -2897
Niche Prop 2.7% 25.2% 48.6% 98.9%
Reviews 60090 124007 57599 11167
Rev/Cons 3.2 12.5 9.7 2.1
Check/Biz 5839.6 3576.8 1178.5 164.6
There are four (4) consumer clusters based
on the proportion of niche venues in their
reviews:
Hit venuesPatronizing a mix of 26% niche
businesses does not yield the
highest satisfaction, but it does
inspire the most participation
and engagement. This seems to
be the ideal point of
adventure.
Seeing the world with the
Consumer Ecosystem Perspective
A Typical Business Network
• This network was created by linking businesses that are categorized in the same way by Yelp.
• It depicts a map of the competitive landscape as these businesses likely perceive it.
• The competitive
perspective.
But there is another perspective:
Consumers link themselves to businesses in a hub-and-spoke network with their
patronage. The patronage of the same consumer connects the businesses
themselves into a network that in one way can be seen to compete for a share
of the consumer’s budget, and in another way sustain the consumer as an
ecosystem.
The Consumer
Ecosystem• The primary businesses
patronized by consumers
who also patronized Hotel
Tempe.
• Note that the Mission
Palms hotel here was not a
member of the competitive
map, and none of the
competitors in that map are
in the consumer ecosystem.
• The most important insight
though is that this provides
a rich multi-faceted portrait
of the consumption habits
of those who are patrons of
Hotel Tempe.
Applying the Ecosystem to Search AdsHypothesis: By shifting their repertoire of targeted searches beyond the obvious toward
those that are both relevant to their business and consumer needs, consumer-facing
businesses like Mission Palms can use search advertising more effectively.
A Nexus of Theory
• Market structure analysis (MSA) examines how products in the same market compete more strongly with each other than with those in different markets.
• The consumer ecosystem often depicts general brands and is appropriately described as brand mapping; brand mapping often uses consumer choice data similar to MSA.
• Many of the brands in consumers’ awareness compete for a share of their disposable income across product categories. The budget allocation research stream is often focused on how consumers prioritize planned purchases.
• Business ecosystem research sees consumers and producers as members of an economic community that coevolves in their capabilities and roles (e.g., the increase in economic activity that accrues to shopping centers that maximize heterogeneous retailer agglomeration).
Measuring the Ecosystem Perspective
Mutual Information
I(A; B) is the mutual information between an
advertiser and its consumers, B are all the consumers
who clicked A’s ads, p(a, b) is the joint probability of
the advertiser and consumers using the same query,
p(a) and p(b) are the probabilities of either using a
query.
To what
extent is an
advertiser
targeting the
full range of
queries
made by
consumers
that click its
ads?
Hierarchical Logistic Regression
Parameter Raw
Coefficient
Relative
Importance*
Query frequency -.207 .36Ecosystem MI .901 .33
Ad position -.432 .15Query freq.× rel. -.039 .07Past impressions -.371 .07
Relevance -.514 .02HHI -.048 <.01
Constant -1.304
Control variables from prior research:
• Prior ad exposures
• Prior ad clicks
• Ad display position
• Competitive interference
• General query frequency
• Ad-query relevance*Relative importance is the percentage of the
overall R2 that is attributed to a variable. Nagelkerke’s R2 of .262
Authenticity & Promise-Keeping
• Advertiser’s targeting of ecosystem queries must authenticallyempower the consumer to fulfill more needs.
• Landing page must match the ad.