INSIGHT
for patterns in both big and small data,
because every consumer leaves invisible
and visible digital data fingerprints of their
behaviour. The objective of machine-based
learning programs is to use data to improve
the program’s understanding and adjust
the program’s outputs — in real time. A
good example of this is Facebook’s News
Feed, which changes according to a user’s
personal interactions with other users. If
a user frequently tags a friend in photos,
writes on his wall or “likes” his links, the
News Feed will show more of that friend’s
activity in the user’s News Feed, because of
the algorithmic criteria.
end up with an unviable product, because
there would be far fewer in-play markets
available to bet on.
User journey mapping
In user journeys and user experience
— or the actual digital sales funnel —
programmatic advertising and real-time
buying based on hard data (or data science)
are using more and more machine-
based algorithms to increase new-player
acquisition programs. In a different
medium, the digital behemoths Amazon
and Netflix lead the way in this, targeting
audience cohorts with relevant and
personalised advertising.
AI for fraud prevention
There have been many announcements
recently from well-known gaming brands
deploying AI-based innovations. Betsson
said that its big-data team in Malta had
developed various AI algorithms to
solve different business requirements.
Some were improving customer
experience or the ability to detect fraud
or to automate payment processes
and customer segmentation.
Margin optimisation
Other areas impacted include in-play or live
betting, which has enjoyed hugely increased
interest from both operators and players.
This usage makes absolute sense when you
think about the thousands of computations
involved in delivering in-play betting
markets, never mind the cash-out and
partial cash-out offers now so prevalent.
These igaming businesses need to adopt a
lean approach and reduce operational costs
regarding headcount within the trading
and risk teams, and improve both top-level
GGR (gross gaming revenue) and bottom
line margins. If they didn’t use machine-
based AI, they would have to hire teams
in their hundreds to monitor the flow of
betting transactions and it’s likely they’d
the QA engineer. AI is more objective
and less prone to external, emotional or
environmental factors, which could affect
decision-based testing routines.
Digital design for conversion
enhancement
Advances in AI to help design and
optimise websites, based on users’
real-time interaction data (and their device),
are already happening. Wave goodbye to
front-end developers for desktop, tablet
and mobile!
And the future? Everyone shall
become a digital number
Indeed, everything and everyone shall
be distilled down to a machine-based
algorithm, just in the same way that
childless couples can determine the sex and
genetic disposition of a child, and so shall
igaming and affiliate businesses determine
the selection and hiring processes of people
within the operational igaming teams.
Personally, I believe this to be the
elephant in the room. Why? Well,
machine-based learning is only as good as
the creator — the human who programmes
the initial algorithms — and its code needs
to be continually checked, by a human who
needs to make a reasoned judgment on its
validity. Or is it the case that another AI
code will check the other system, and so
forth, ad infinitum?
“Because around 80% of software testing is repetitive
and because manual testing doesn’t scale efficiently,
AI is now transforming this process”
Software testing
Furthermore, with the growth of AI
applications, perhaps one of the most
significant constraints for both igaming
operators and affiliates is software testing
and the deployment of digital innovation
to stay one step ahead of the competition.
Because around 80% of testing is
repetitive and because manual testing
doesn’t scale efficiently (it requires
manpower, itself a considerable cost for
any business), AI is now transforming
this process. It could also be argued that
the software test cycle can be influenced
by the subjective human behaviour of
The future of AI application is within
your hands as the creator. Choose it wisely,
for the success of both your business and
the people it employs and the customers it
serves depends on it.
MARK MCGUINNESS has
more than 22 years’ experience
in digital marketing director
roles with both private and
public igaming operators. He is
currently the CMO of BetOlimp and
the founder of esportsbet.com,
a resource for gamers and sports bettors
who wish to start betting on esports.
iGB Affiliate Issue 66 DEC 2017/JAN 2018
47