I read this awesome post on HBR that prompted me to write this blog post here. Before I start discussing further, most part of this post is from that post.
Competitive position. In domains where customers depend mainly on O, branding takes on less importance, and newcomers find relatively low barriers to entry as a result. This is also apparent in the restaurant business: Research by Michael Luca, of Harvard Business School, suggests that in cities where large numbers of diners rely on Yelp reviews, independent restaurants tend to benefit, while chains and franchises often see their revenues decline.
Companies in O-dependent markets can also diversify more easily than others, because new peer-to-peer information can overcome long-held conceptions about what a company is (and isn’t) good at. LG and Samsung have taken full advantage of this capacity, moving beyond their original core products (electronics) into a broad array of tech goods and home appliances.
In general, we see greater market-share volatility in domains where customers depend mainly on O. (Witness the swift declines of Nokia and BlackBerry.) Conversely, brand equity and loyalty can protect established players in O-independent domains; brands such as Clorox and Bud Light, influenced primarily by P and M, enjoy relative stability. O is also not of great concern to the likes of Grey Goose vodka and Hermès—brands for which prestige and emotional ties play an important role and quality is a given.
Communication. Let’s consider what happens in this arena for products suited to O-dependent purchase decisions. In recent years many camera buyers have turned to ratings and user reviews as their main source of information. This means that celebrity endorsements are less effective than they once were. Banner ads intended to create or reinforce brand awareness are not very successful either, because when it comes time to buy, the weight of trusted reviews usually overrides any residual effect of fleeting exposure to an ad. Instead, companies such as Nikon and Canon should focus on generating user interest in particular products and promoting an ongoing flow of authentic (and positive) content from O on internet retail sites.
Consumers are less likely to consult O about purchases that are not very important to them—most people don’t go on Facebook or Twitter to ask “What kind of paper towels should I buy?” or “What brand of detergent do you like best?” So marketers trying to reach O-independent consumers can be guided by some of the old rules, including many traditional M activities. P&G, for instance, can still benefit from persuasive advertising and eye-catching store displays for Bounty and Tide.
With the growing availability of opinions from experts and users, the importance of a brand name had diminished. In the past, buyers typically made relative
comparisons (“Is Brand A better than Brand B?”) or went by the maxim
“You get what you pay for.” They were largely dependent on information
provided by manufacturers in the form of marketing. Today, thanks
primarily to user-generated reviews and people’s tendency to consult
social media friends about purchases, buyers have other options. The
wealth of peer-to-peer information and the unprecedented availability of
expert opinions give them access to what’s known as absolute value—a
rich, specific sense of what it’s like to own or use the goods they’re
considering.
Every marketer is aware of the rise of online
reviews and other sources of peer-to-peer information, but many neglect
this trend and market products much as they did a decade ago. We believe
that many companies need to dramatically shift their marketing
strategies to account for the rising power exerted on future customers
by the opinions of existing customers. The experts at HBR have created two tools to help
managers do that: the influence mix and the O continuum.
The Influence Mix
Customers’ purchase decisions are typically affected by a combination of three things: Their prior preferences, beliefs, and experiences (which we refer to as P), information from marketers (M), and input from other people and from information services (O). This is the influence mix.
Think of it as a zero-sum game: The greater the
reliance on one source, the lower the need for the others. If the impact
of O on a purchase decision about a food processor goes up, the
influence of M or P, or both, goes down.
In recent years O has taken on increasing weight
in many categories, but plenty of exceptions remain. For example,
habitual purchases (such as milk) tend to be dominated by P, while
someone shopping for a toothbrush is most likely to be swayed by
packaging, brand, pricing, and point-of-purchase messages—all components
of M.
Companies need to ask: To what extent do
consumers depend on O when making decisions about their products? We
present the answers as points along the O continuum. The closer your
product is to the O-dependent end, the greater the shift in how
consumers gather and evaluate information about it.
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The O Continuum
Once firms understand where a product falls on the O continuum, they can consider the strategic implications in four realms:Competitive position. In domains where customers depend mainly on O, branding takes on less importance, and newcomers find relatively low barriers to entry as a result. This is also apparent in the restaurant business: Research by Michael Luca, of Harvard Business School, suggests that in cities where large numbers of diners rely on Yelp reviews, independent restaurants tend to benefit, while chains and franchises often see their revenues decline.
Companies in O-dependent markets can also diversify more easily than others, because new peer-to-peer information can overcome long-held conceptions about what a company is (and isn’t) good at. LG and Samsung have taken full advantage of this capacity, moving beyond their original core products (electronics) into a broad array of tech goods and home appliances.
In general, we see greater market-share volatility in domains where customers depend mainly on O. (Witness the swift declines of Nokia and BlackBerry.) Conversely, brand equity and loyalty can protect established players in O-independent domains; brands such as Clorox and Bud Light, influenced primarily by P and M, enjoy relative stability. O is also not of great concern to the likes of Grey Goose vodka and Hermès—brands for which prestige and emotional ties play an important role and quality is a given.
Communication. Let’s consider what happens in this arena for products suited to O-dependent purchase decisions. In recent years many camera buyers have turned to ratings and user reviews as their main source of information. This means that celebrity endorsements are less effective than they once were. Banner ads intended to create or reinforce brand awareness are not very successful either, because when it comes time to buy, the weight of trusted reviews usually overrides any residual effect of fleeting exposure to an ad. Instead, companies such as Nikon and Canon should focus on generating user interest in particular products and promoting an ongoing flow of authentic (and positive) content from O on internet retail sites.
Consumers are less likely to consult O about purchases that are not very important to them—most people don’t go on Facebook or Twitter to ask “What kind of paper towels should I buy?” or “What brand of detergent do you like best?” So marketers trying to reach O-independent consumers can be guided by some of the old rules, including many traditional M activities. P&G, for instance, can still benefit from persuasive advertising and eye-catching store displays for Bounty and Tide.
Market research.
Companies in domains that are not susceptible to O can continue to draw
on conventional market-research approaches, but those in O-dependent
areas need to think differently. Market research usually aims to measure
P—it tries to predict the kinds of products consumers will like by
assessing their preferences in the past. But as purchase decisions
become more reliant on O, rooting around in consumers’ psyches to
understand P yields lower returns. For example, a market research study
conducted in early 2007—before the release of the first iPhone—concluded
that U.S. consumers would not be interested in a “convergent” device
that combined the functionality of a cell phone, an MP3 player, and a
camera. (Whoops.) What went wrong? The study had measured P, but as soon
as the iPhone hit the market and early adopters began gushing over it,
people became influenced by O. Instead of measuring individual
consumers’ preferences, satisfaction, and loyalty, marketers should
redirect resources to the systematic tracking, coding, and quantifying
of information from review sites, user forums, and other social media.
Product segmentation.
A product’s location on the O continuum often varies across customer
segments and from country to country. One group of consumers might rely
primarily on O, while another might be more attuned to M. And some
distribution channels are less conducive than others to O. (Shoppers in
brick-and-mortar stores are often more susceptible to M than online
shoppers are, for instance.) Companies should analyze different consumer
segments and tailor their marketing strategies accordingly. When
communicating with segments that rely on M, a company can use
advertising to build top-of-mind awareness, persuade customers, and
position its offerings—but those strategies probably won’t work for
segments that rely on O. Marketers should also bear in mind that the
degree to which a particular customer relies on O might vary with
situational factors. For example, some of the people who take full
advantage of O while shopping for electronics online may come under M’s
influence on Black Friday, when ads touting deep one-day-only discounts
abound. With not much time to decide or to consult reviews, they may
pick up products impulsively, in the belief that “if it’s on sale on
Black Friday, it must be a good deal.”
Biggest Challenge In Online Reviews
When we talk with companies about shifting their
marketing mix in recognition of the rising power of O, we hear one
consistent objection: Growing suspicion (and in some cases, proof) that
online reviews are subject to manipulation and fraud. Some marketers
believe that consumer reliance on O will decline as more shoppers become
wary of deceptive reviews. We disagree. Yelp, TripAdvisor, and others
are becoming increasingly sophisticated at weeding out fake reviews, and
consumers are developing a better sense of which sites (and which
individual reviewers) they can trust.
Consumers used to the richness of online reviews
will ever return to relying on traditional M. Consider two data points.
First, 30% of U.S. consumers say they begin their online purchase
research by going to Amazon for product information and reviews; second,
studies commissioned by Google have found that shoppers consult 10.4
sources of information, on average, before making a purchase. Voracious
information-seeking has become deeply ingrained in many consumers, and
we can envision no scenario in which they will see traditional marketing
as a better provider of product information.
The sources of O change rapidly. New review
sites and game-changing technologies can suddenly appear. For instance,
consumers who use smartphone apps such as ShopSavvy to compare prices
can minimize the weight of M on their decisions even on Black Friday.
The idea that a new website or app can undercut years of careful
messaging may be deeply frustrating to marketers—but it is a reality
they must face. As the influence mix evolves, success will come to
companies that can closely track the sources of information their
customers turn to and find the combination of marketing channels and
tools best suited to the ways those consumers decide.
This awesome post can be found on this link.
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