Image Credit: Cortex
The
Low Down on AI-Powered Programmatic Advertising
When programmatic
advertising is powered by artificial intelligence (AI): “it brings
more efficiency to publishers and advertisers.” [1]. It can also be
said that: “AI is here to facilitate marketers’ lives for better
automation and decision-making, while being able to deliver
personalized end-user experiences” [1].
Right now, the worlds
of programmatic advertising and AI, are starting to integrate in a
big way. In a nutshell, programmatic advertising refers to: “the
automated process of buying and selling ad inventory through an
exchange, connecting advertisers to publishers” [1]. This strategy
employs real-time bidding and AI tech for inventory spanning a number
of fields including: TV, social and video channels, and mobile. AI
tech utilises algorithms to study users' behavior, thereby enabling
real-time campaign optimisations that are geared to a specific
audience that is more inclined to convert. Companies who specialise
in programmatic advertising have the means to collect this
information from their audience, so that they can target them with
far more precision, whether it is from their own data, or data from a
third-party provider [2].
Programmatic media
buying incorporates data management platforms (DMPs), demand side
platforms (DSPs), and side supply platforms (SSPs). DSPs
that facilitate buying advertisement inventory on the open market,
offer: “the ability to reach [a] target audience due to the
integration of DMPs [which] collect and analyze a substantial amount
of cookie data to allow the marketer to make more informed decisions
of whom their target audience may be” [2]. Search engine marketing
advertising on channels such as Twitter, Facebook and Google AdWords,
are prime examples of programmatic advertising [2].
The
Revolution of the Digital Advertising Market is Just Beginning
Right now, the digital
advertising market is being dominated by the protected few, who are
controlling the management of advertisers' ROIs, not to mention
publishers' revenues. To that end, AI is the preferred route for a
distributed programmatic ecosystem, as it can vie: “against the
duopoly, as it streamlines the demand targeting with supply
monetization, in a sustainable fashion” [1]. This will provide
better user classification, and thus lessen waste, which will result
in the monetisation of a supply which is far more relevant [1].
Unlike the duopoly that
mainly operates in a self-regulated environment such as moving on a
train track, the bid stream is like a busy motorway intersection with
a massive amount of traffic in perpetual movement. Analogous to
autonomous cars, when AI is applied to programmatic advertising, it
can navigate on its own within the environment, and is able to give
granular insights in order to find an economical path connecting
advertisers and publishers [1].
How
AI Ramps Up Audience Targeting For Advertisers & Publishers
“Programmatic
advertising already involves a good deal of AI, but that doesn’t
mean there isn’t room for improvement from the perspective of the
advertiser” [3]
Smart Interest
Discovery is the name of the game for audience creation. It offers
the means to evaluate different bidding strategies and traffic
sources so it is easy to evaluate the audiences' “intent behavior”
patterns for both long and short-term interests [1]. This level of
refinement is clearly set to become standard in the not too distant
future. The artificial intelligence layer enables the operator to
leverage this during real-time targeting. Further, in order to make
the advertising more pertinent and not as intrusive, the operator
must have the ability to respond on the premise of the users'
interests, and the demand requirements [1].
When artificial
intelligence meets programmatic advertising, just as with a human
brain: “advertising behaves like a central nervous system. It
consumes information for a large number of sensory organs, i.e.,
supervised and unsupervised machine learning algorithms” [1].
Further, for the purpose of taking strong real-time decisions, AI:
“takes optimal autonomous actions to adapt to changes in
significant factors governing demand and supply. It has the potential
to optimize towards a sustainable ecosystem [and] keeps up to speed
with dynamically evolving user behavior, constantly updating user
valuation” [1]. - So the high tech benefits are truly exciting!
So
What Are the Future Trends for AI-Powered Programmatic Advertising?
Let us
consider this scenario: “Just as a huge volume of stock market
transactions are handled by AI today, the further future of
programmatic advertising will likely involve competing AI systems,
altering bids and ads in real time” [3]. This will be supervised by
a team, yet nevertheless, act in an autonomous way to optimise an end
goal [3].
Lior
Tasman
Lior
Tasman, the CEO of PredictiveBid, Predictive Bidding Platform, is a
leader in the industry, and has worked alongside a number of the
biggest advertising companies in his 10-plus years with innovative
start-ups. While giving an interview for Techemergence, he looked at
where artificial intelligence can help to ameliorate some of
programmatic advertising's biggest issues [3].
Tasman stated that: “AI
is solving the problem of crunching big sets of data and then making
a lot of relatively fast, complex calculations… it is also a system
that improves itself over time based on its predictions” [3]. It is
not difficult to construct a rule-based algorithm, however, if one
requires “a machine that really reacts to specific events in the
market; that’s better at predicting how likely the market is to
behave; and you need to make that decision really fast, you really
need a system that is more” [3]. Step forward artificial
intelligence – a phenomenon that has the capacity to carry out
these calculations, and then assist by automating manual and complex
computing issues [3]. Tasman also remarked that his team is becoming
more effective through AI. There has to be a unison between human and
humanoid, as the latter only serves to make the process of decision
making quicker or easier, and help the team work more efficiently
[3].
Moti Tal
Another great candidate
to answer this question of future trends for Techemergence, was Moti
Tal, the Co-Founder of Simplaex. Tal boasts 18 years in high tech,
and heads the company's research and development department. He
believes that with the ascent of AI, it will be common: “to see
more products that streamline the interactions of the different
actors across the programmatic advertising value chain” [1]. To
that end, with the addition of artificial intelligence, “advertising
will be more personalized, and as a consequence more relevant and
less intrusive, which is a step forward towards a positive browsing
experience, making the freemium content model sustainable” [1].
Tim Sims
Further, tech expert,
Ross Benes, recently conducted an interview on behalf of eMarketers,
with Tim Sims, the SVP of Inventory Partnerships, The Trade Desk.
This involved an interesting discussion on various aspects of
automated ad buying.
On the question as to
why Sims chose to incorporate artificial intelligence tools within
his company's system, Sims noted that it was down to the massive size
of programmatic bidding, stating: “we look at 9 million queries per
second... [and] you put that in the context of other mature
marketplaces like Nasdaq or the New York Stock Exchange, it’s
astronomical” [4]. There are opportunities from this colossal size
of bidding. Sims said that the company utilise all the data for
forecasting, and are able to use the information to generate more
artificial intelligence decisions, whereby: “the platform takes
control to find the best execution path for a particular campaign”
[4].
While acknowledging
that one component of this strategy is supply path optimization tech
(advanced algorithms which can decide what the the most effective
result for a specific advertiser will be at that very second by
appraising the maximum number of data points), Sims notes that with
AI, there are other components such as performance and price [4].
First-Price Auctions
The move to first-price auctions (where the highest bidder determines
how much an impression gets sold for) [5], which were introduced to
offer more transparency to auction dynamics [5], means that it is now
more essential than even for the purchaser's side to transact in an
competent marketplace. To that end, discovering the market rate for
such an impression can be instigated via artificial intelligence.
When asked whether ad rates have been impacted by moving to
first-price auctions, Sims stated that it likely that over the
previous six months or so, throughout the entire ecosystem there have
been signs of a rise in the CPM (cost per thousand) [4].
What
Does OONA Offer?
“OONA
- Always Striving to Offer Superior Ad Options to Channel Owners &
Content Holders”
OONA – the cool interactive Entertainment & Messaging platform which offers more than TV & OTT, is currently set to provide AVOD (advertising-based video on demand) and premium options to 185 million Indonesians, and is on course with its goal for delivering its revolutionary service to other regions including other parts of Asia, Africa, South America, the Middle East, the US and Europe.
OONA is the brainchild
of leading digital strategist and CEO, Christophe Hochart, who
focuses on user experience for competitive advantage. To that end,
the platform is naturally geared towards programmatic advertising.
OONA offers a strong flexible business model to channels and content
holders via its OTT monetization methods, and this has become very
popular with both mega and smaller studios and content holders alike.
OONA's advertising
options include: 1. A programmatic advertising video (30 seconds),
CMP and CPC revenue. 2. Programmatic display advertising (30
seconds), CMP and CPC revenue. 3. Programmatic advertising
short-video (pre-roll 6 seconds). and 4. Pay per view
micro-transactions.
The bottom line is that
programmatic advertising increases efficiency and saves money - two
very valuable advantages. By opting for automation, it puts human
beings out of the equation, and buying ads becomes less expensive and
more dependable. Also, very importantly, program channels and content
holders are able to optimize their KPIs (key performance indicators),
and attain a deeper insight into the behavior of consumers [6].
The
Rock and Roll Future of Programmatic Advertising
There are a number of
exciting predictions: 1. Purchases of programmatic advertising will
skyrocket, and ultimately, purchasing will surpass conventional,
manual ad purchasing. Furthermore, industry experts predict that
leading up to 2020: “programmatic advertising will drive 100% of
advertising purchases. Organizations not championing automation will
fall behind those that do"[5]. 2. Traction will be gained in the
field of DCO (dynamic creative optimization), the cutting-edge
display advertising which delivers automatic multi-variate testing,
namely, algorithms which interpret results and ascertain how to
deliver advertisements for the most optimal performance. 3. There
will be more header bidding [6] such as that offered by the OONA
platform. This empowers channels and content owners with a high tech
method so they are able to offer inventory to multiple advertising
exchanges at the same time. 4. Personalisation will become more
intelligent. When channels and content owners are able to laser focus
their programmatic ads to individual viewers, then they can leverage
strategies including explicit demographics and geo-location [6].
Now, along with other
like minded leaders in the industry, Hochart believes that although a
substantial amount of artificial intelligence is already integrated
into programmatic advertising, more high tech AI marketing
applications have the potential to produce even better results, and
for OONA, this can mean a win-win situation
for everyone involved.
In summary, although
the intersection of AI and marketing is relatively new, it is clear
that AI offers the potential for being the best
route to a distributed programmatic ecosystem. It is a truly
exciting breakthrough, and the odds are that those who pursue it,
will gain rich rewards...
References
[1].
Adotas (2018). “Q&A: What You Need to Know About AI-Powered
Programmatic Advertising.” Accessed 28 Jun.
2018.http://www.adotas.com/2018/03/qa-need-know-ai-powered-programmatic-advertising/
Accessed 28 Jun. 2018.
[2].
Faggella, Daniel (2018). “Artificial Intelligence in Marketing and
Advertising – 5 Examples of Real Traction”
Techemergence.https://www.techemergence.com/artificial-intelligence-in-marketing-and-advertising-5-examples-of-real-traction/
Accessed 28 Jun. 2018.
[3].
Fagella, Daniel (2017). “Artificial Intelligence and the Future of
Programmatic Advertising.”
Techemergence.
https://www.techemergence.com/ai-future-programmatic-advertising/
Accessed 28 Jun. 2018.
[4].
Benes, Ross (2018). “Why DSPs Are Applying AI to Programmatic
Bidding.” eMarketer.
https://www.emarketer.com/content/why-dsps-are-applying-ai-to-programmatic-bidding
Accessed 28 Jun. 2018.
[5].
Chen, Yuyu (2018). “Programmatic advertising is preparing
for the first-price auction era.”
https://digiday.com/marketing/programmatic-advertising-readying-first-price-auction-era/
Accessed 28 Jun. 2018.
[6]. Kloefkorn, Sheila
(2017). “Trends In Programmatic Advertising To Watch This Year.”
Forbes. Retrieved
from:https://www.forbes.com/sites/forbesagencycouncil/2017/05/16/trends-in-programmatic-advertising-to-watch-this-year/#781cb7cf7f11
Accessed 28 Jun. 2018.
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