Affiliate marketing is stagnant and ripe for innovation. In-content
“affiliate” or “performance” marketing — driving traffic through product
links embedded in original content — is one of the oldest business
models on the web and it has barely changed in a decade. This year,
2014, change is emerging.
A new affiliate exchange, bringing merchants and publishers together
to buy and sell clicks in real time, launched in the summer of 2013.
This new content-driven commerce exchange is picking up steam. As a
result of this exchange and others like it, publishers will unlock
billions of dollars in revenues in the next five years. Merchants will
be able to reliably and predictably buy product specific content-driven
commerce clicks on demand and at scale.
Affiliate marketing is plagued by a reputation for fraud. It is also
dominated by coupon sites that often do little more for merchants than
create margin pressure. Equally problematic, affiliate marketing suffers
from mind boggling fragmentation and complexity. Tens of thousands of
merchant programs are spread across dozens of affiliate networks in the
US alone. Much of the work required of publishers for earning from
clicks they drive to merchants remains manual and error prone. Until
recently, real- time bidding for contextually-relevant product
placements within original content hasn’t been possible.
Sites like the New York Times don’t monetize through affiliate
marketing not out of high-minded editorial integrity but because old
school affiliate marketing isn’t worth the trouble. For these reasons,
affiliate marketing has never achieved the economies of scale of either
search or display advertising.
In 2014, this has all started to change. A combination of big data,
Natural Language Processing, and powerful predictive analytics has
automated away the complexity. These technologies sound complex. In
fact, they simplify all of the messy pieces that comprise creating,
pricing, and filling affiliate inventory in a rational two-sided
marketplace. Both the buyers (online merchants) and the sellers (online
publishers) of affiliate clicks are benefiting.
This has allowed for the emergence of the first ever content-driven
commerce exchange. In this exchange publishers auction clicks on product
links embedded in their content to the highest bidder that sells the
product (A Nikon D5300 camera is the same camera if you buy it at
BestBuy or on Amazon). By bidding to buy these in-content shopping
clicks, merchants are winning more sales. At scale, this shift will
boost publishers’ commerce-based revenues by double-digit to
triple-digit percentages. Online merchants finally gain reliable,
predictable access to commerce driven by trusted content and the
aggregated audience of in market shoppers.
The drivers for this change are self-evident to every online
publisher. Today, publishers sell clicks on product mentions embedded in
their original content with no idea how much the average click yields
in revenue. They cannot keep track of changes in commission structures
across dozens of affiliate networks or direct performance marketing
relationships with merchants. They cannot predict in advance whether
traffic to one online merchant will convert at a higher rate than
traffic to another.
Publishers should not be expected to build sophisticated models to
predict which merchant will pay the most for, let’s say, a German
visitor on a mobile phone clicking on a deep link to a pair of dress
shoes. The results are woeful inefficiency. A publisher trying to
manage affiliate marketing manually is lucky to monetize a third of
their commerce clicks, and at rates that drastically undervalue their
worth. This is a classic yield management problem, long ago solved for
both search and display.
Merchants also suffer. There is no unified marketplace, no NASDAQ or
DoubleClick or AdWords for clicks from content. Today, merchants must
navigate the existing universe of sophisticated click traffickers. These
include the classic affiliate networks, comparison shopping engines and
countless other niche players. Successful integration into an affiliate
network is neither easy nor fast. As a result, switching costs are
high. In the end, merchants that need to buy extra shopping clicks
struggle to find them.
The solution for affiliate clicks is a platform where big data trains
ever-smarter models that drive advertising automation. What humans see
as chaos — a pool of content and clicks fragmented across a giant mass
of affiliate networks — computers see as data — normalized, structured,
relational data.
This allows software to create linkages between content sites and
commerce sites and to price those linkages efficiently. This efficiency
will place the best merchant offers on clicks delivered by the
publishers with the best audience. Today, the best models can
automatically identify product mentions with high precision. Predictive
pricing models select the most economically rational link based on
factors such as commission fee structure and merchant conversion rates.
Software automatically embeds that link, routing traffic to the most
competitive retailer.
The first content-driven commerce exchange opened for business in
June. Every day, it auctions off thousands of clicks on product mentions
to eager merchants. Publishers see earnings per click that were 200% to
300% higher, on average, as compared to clicks not flowing through the
exchange. A number of merchants eagerly jumped in to gain access to one
of the largest aggregated pools of content-driven shoppers on the Web
today. Most importantly, the whole process was orderly and painless on
both sides. It’s the future of content-driven commerce and it’s
inevitable.
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