Published on Admap as Big Data is a canvas for creativity by Yeong Yee, BBDO Singapore Commended in the Admap Prize 2015

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When you think big data, think bigger creatively
Yeong Yee
Admap
Judges Commended, The Admap Prize, June 2014

2.
When you think big data, think bigger creatively
Yeong Yee
BBDO Singapore
In driving innovation with Big Data, we should reconsider the notion that the big idea needs to be inspired by the
data. Truly impactful and world-changing ideas can arise when creativity is applied to Big Data, rather than the
other way round.
From programmatic buying to social listening to real-time marketing, Big Data and the advertising technology spawned from it
have played an increasing role in the creative process. From developing the big idea, to powering the small ideas, our
advertising communications are increasingly influenced and powered by Big Data. But that is only scratching the surface of the
power of Big Data to inspire real creative change. Trends towards more data openness and cloud-based analytical services
are changing the creative canvas on which we can now ideate.
At an Advertising Week 2014 panel called 'When Big Data Met Big Creativity', the speakers (distinguished creative leaders in
their respective networks) propounded a singular and specific view of the role of data. They posited that data serves as
insights, best used as inspiration for a creative professional to design campaigns to identify and reach a consumer. An oft-
cited example was BBH London's 'Keep Walking' campaign for Johnnie Walker, which was conceptualised from data that
found its drinkers were successful but striving. Another was 'The Dove campaign for real beauty', which was built on the data-
driven insight that 'only 4% of women consider themselves beautiful'.
Title: When you think big data, think bigger creatively
Author(s): Yeong Yee
Source: Admap
Issue: Judges Commended, The Admap Prize, June 2014
The Admap Prize 2015
This essay was Commended by The Admap Prize 2015 judges.
For more information visit the Prize page.
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3. The collection and usage of data in the advertising industry is not a new thing. Whether it is in researching our consumer or
measuring the effectiveness of our work, we have always gathered data, built analytical models using it, and employed it in the
creative process. In the classic Stephen King-Stanley Pollitt definition, data is what we use as a means to understand the
consumer so as to form insights for creative strategy, an analytical catalyst for the big idea.
In this traditional view, simple and crisp evidence-based data points are the basis of insights that inform the big idea. But this
view ignores the breadth and depth of what Big Data – and the advertising technology spawned from its adoption – brings to
the creative process. The difference now is what the 'Big' in Big Data actually implies in the usage and application of data to
advertising communications. How has the advent of Big Data actually changed the way we conceptualise the big idea?
Big data informs the big idea
First, we are learning more about the increasingly quantified world in which the consumer lives. The proliferation of
smartphones, internet-enabled devices, and other always-on geo-located technology has enabled us to learn more about our
consumers and their behaviour. Behavioural insights derived from modelling such Big Data fuel creative thinking into how the
consumer lives, communicates and interacts with their device and with other people. The creative work that is inspired by
insights into the quantified self is often perceived as being contextually relevant. For example, the Weather Company analyses
the behaviour patterns of its digital and mobile users across three million locations worldwide and correlates it with the climate
in their users' locale. The Weather Company is able to predict how shoppers' habits change with fluctuations in the weather,
and has used that predictive capability to serve relevant messages from advertisers on its platform.
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4. Second, Big Data has empowered the discovery of patterns that were hitherto never suspected or even hypothesised about.
These patterns are often surprising, even downright weird, but they make for very compelling insights and inspiring creative
fuel.
The Big Data startup Evolv uncovered one such pattern. Evolv sifted through three million pieces of HR data from its clients to
hone in on the levers of employee productivity. Strikingly, it was discovered that the web browser a job applicant uses to apply
for their job has a strong correlation to whether he or she is going to be a star employee or not. Another even more surprising
example Evolv uncovered was that criminals actually make better call centre employees: they are found to be 1-1.5% more
productive than employees without criminal records.
Predictive modelling and pattern spotting at scale are where Big Data has an edge in informing the big idea. But it goes
further: with available social listening tools (which are powered by Big Data), brands are also able to extract, trawl and
comprehend ever-shifting consumer sentiment in real-time. They can adapt marketing communications online (particularly in
social channels) and offline (to a limited extent). The practice of creative work tapping upon social listening has even spawned
an entire creative category of work: that of real-time marketing.
Real-time marketing came to the fore when Samsung used real-time social listening software to understand the reactions of
consumers to the iPhone 5's launch in 2012. Samsung collected live commentary of consumers in social channels in the hours
during and after Apple revealed the iPhone 5. It aggregated consumer reactions to understand the new features of the
product, as well as what the fanboys were gushing about. Based on the insights, Samsung was able to create a new print,
digital and TV ad campaign that mocked Apple customers and poked fun at the product's features when the iPhone 5
launched.
Big data needs small ideas
Clearly, our ability to collect, analyse and scale Big Data can enable deep insights and new perspectives into consumers'
behaviour and even their aspirations. But that is only one end of the creative process. Advertising technology in the form of
programmatic buying enables targeted communications in real-time, affording the advertiser the ability to optimise its creative
work in the digital realm to the most relevant consumer context.
To subvert an earlier turn of phrase, this is perhaps best described as CRM at scale: the creation and delivery of
personalised, micro-targeted messages, in real-time, which are informed by deep data insights into consumer behaviour and
patterns.
From the creative professional's perspective, we are now presented with more avenues than ever to personalise the
consumer's brand experience: the creative professional has a far larger canvas for creative expression. He or she is
theoretically less confined by the restraints of delivering a one-size-fits-all message (while still keeping it on brand). As per the
aforementioned Weather Channel case, the contextual data it gleans on its online and digital consumers can present many
opportunities for targeted and relevant messages; for example, FMCGs can target users of the Weather Channel with a new
shampoo brand's anti-frizz product when the local climate becomes more humid.
The same ability to power many small ideas also affords the creative agency the ability to take more creative risks. Advertising
technology empowers the agency to monitor and measure the performance of creative assets in real-time and lets us test the
effectiveness of our work in connecting with our consumers or between subsections of that audience. A process of creative
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5. evolution – be that simple A/B testing or a more complex process of content Darwinism (content decisions driven by efficacy of
content) – can then lead us to work that is better attuned to consumer needs and desires.
It is thus somewhat ironic that Big Data can now afford more creative free rein by providing the means to test and learn with
intuitively inspired creative work (rather than relying on the evidence-inspired work born of data).
Big data and the dearth of new ideas
Herein also lies the quandary that Big Data presents to the creative process: owning the technology that helps us optimise our
creative work also leads the Math Man inside us to want to measure the effectiveness of our creative output.
Driven by the need to make advertising communications effective, the typical client will tend towards a well-intentioned but
reductive approach in terms of evaluating and approving creative work. For instance, the typical client will want to rigorously
test all the creative work the agency delivers before, during and after any campaign. Resultant 'learnings' (always in the form
of quantitative and qualitative market research) will be distilled to inform creative briefs for the next series of campaigns. A
veritable gallery of 'What Works, What Doesn't' supported with metrics and KPIs tends to pepper the typical campaign report.
While there is nothing inherently wrong with learning from the performance of past work, the dilemma is that our reliance on
past data to measure good creative work might actually discourage the creative professional from experimenting or originating
work in the long term. We are compelled to deliver against a benchmark of previously effective work, rather than being truly
inspired to attempt creative and original thinking. It is an advertising vicious cycle that – even if seemingly unlikely – needs to
be at the back of our minds whenever we view the usage of data from the perspective of effectiveness and performance.
Similarly, when we use Big Data in a predictive manner, we can come to over-rely on the derived correlations to cement our
understanding of aggregated consumer behaviour, often with unintended individual consequences. For example, in 2002, TiVo
built a profiling algorithm to deliver movie content based on analysis of what its customers record on the DVR. Although the
algorithm took into account many variables (favourite actor, genre, etc.), it delivered content that perplexed its customers,
famously resulting in hilarious consumer stories such as My TiVo Thinks I'm Gay.
Through no fault of its own, Big Data thinking is inherently linked with thinking in the short term. Creative optimisation and
predictive modelling are inherently short term in nature as these processes are informed by recent data. The accuracy of an
analysis decreases with time and unaccountable shifts in consumer trends derail efforts at long-term prediction.
In the long term, we need to be mindful not to allow the energy of Big Data adoption to erode the brand equity. UK
supermarket retail chain Tesco is often held up as the quintessential example of the success of analytics-driven CRM. Its
consumer-level marketing, analytics, and the sophistication in using its customer data made it one of the most oft-cited Big
Data case studies. But as the Harvard Business Review article 'Tesco's downfall is a warning to data-driven retailers'
highlights, Tesco in 2014 had fallen to an 11-year low in terms of market valuation and had lost customers to discount chains
in the UK. One of the reasons cited for its failure is Tesco's programme being 'out of touch' with its shoppers.
Big data has big implications for the creative process
Brands such as Tesco need to continually leverage Big Data for innovation rather than for endlessly applying it to optimise the
effectiveness of its messages. In driving innovation with Big Data, we should reconsider the notion that the big idea needs to
be inspired by the data. Why shouldn't creativity inspire the usage of Big Data instead? Truly impactful and world-changing
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6. ideas can arise when creativity is applied to Big Data, rather than the other way round.
In fact, the need for creativity in the Big Data profession is emerging. A recent Smart Data Collective article by Big Data expert
Bernard Marr highlights how Big Data professionals are often asked to solve problems that companies do not even know they
have. Since the application of Big Data requires the Math Man to work with unstructured data (data in the form of human
speech, free text, and even images and video), Marr highlights creativity as a key and valuable skill to massaging and
interpreting the variety of such data.
Making Big Data sets publicly available is also another way to accelerate the pace at which creative Big Data innovations
emerge. The public sector has been the most forthcoming in making Big Data sets available for just such a purpose. In 2013,
New York city started its Open Data project and progressively made its data publicly available. Through an annual citywide
app development competition, NYC encouraged the development of numerous apps and visualisations for data sets generated
in the process of providing municipal services. These ranged in data from city government services and public safety to social
services and transportation. Participants made interactive maps of different tree types, and designed functional apps that
make the typical New Yorker's life a little easier.
One other Big Data innovation is also worth noting. In 2011, IBM introduced a supercomputer called Watson – a Big Data
powered machine which combines artificial intelligence and analytical software to operate as a 'Question Answering Machine'.
It debuted Watson by pitting it in a Jeopardy! quiz competition against the game's reigning human champions and Watson beat
both handsomely in the trivia competition. It was a seminal moment for Big Data as it showcased machine learning at its finest.
Since that time, IBM has extended the application of Watson into computational creativity, which is akin to pattern spotting at
scale, and used it famously in medical diagnoses and in creating new food recipes. The application of Watson to creating food
recipes is (so far) the most compelling example of using Big Data in creating something totally new out of hitherto
undiscovered combinations.
Watson was also made available as a cloud service in December 2014. The implication of this is momentous. We have access
to Big Data sets that are increasingly made public by enterprises and public services such as New York City's, and we also
have the means to crunch that data with cloud-based services like Watson's. The creative canvas is not that of deriving
insights to power advertising communications: it is to apply creativity to uncover the insights that can truly change the world for
the better.
That confluence of available technology and openness is where Big Data truly inspires creativity. It is time for the creative
professional to consider that Big Data technology creates a canvas for a far wider variety of creative work, and it is more than
just the insight-informing tool that our Advertising Week 2014 panellists perceive it to be.
Read more winning essays
Gold
Embrace the outliers: Abandoning
certainty will unlock the creative qualities
of big data
Ben Essen, IRIS
Silver
Commended
Reducing (not removing) risk: Why data
can never supplant taste
Gareth Price, The Social Partners
A period of punctuated equilibrium
inspired by big data
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7. About the Author
Yeong Yee is digital planning director at BBDO Singapore, and previously led digital planning for Grey Digital SEA. Before
switching to advertising in 2012, he was an analytics, IT and management consultant with IBM, Accenture and RedPill.
yeong.yee@proximity.com.sg
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