Getting data-fit requires selecting and consuming the right kinds of data, applying it where it matters most by linking it to creative workstreams, and recognizing organizational barriers. Brands need to collect smart, clean, and purposeful data that is properly vetted and linked to objectives. Data should inform what brands communicate and the experiences they design by feeding into expectations and experience management. However, most attempts to leverage data fail due to organizational barriers like legacy systems, data silos, lack of skills, and not celebrating successes. Overcoming these barriers requires investment, building cross-functional relationships, internal training, focusing on easy wins, and learning from others.

1. “Getting Data-Fit”
Scott Thomson, Global Head of Analytics, Naked Communications
Darren Drew, Database Marketing & CRM Manager, Virgin Atlantic
(From a presentation at iCOM Seville 2014, Global Forum For Marketing Data & Measurement)
The data diet
STRUCTURED
DATA GOODNESS
UNSTRUCTURED
DATA
WILD&FREEDATA
ORGANIC
AGGREGATED
LOCALLYSOURCED
Data is not going away. It is here for good.
I am sure we have all heard about how many Terabytes and Zettabytes and Yottabytes worth of data there is
out there. We can all agree, it’s Big, and getting Bigger. For good or bad, we are consuming and creating
mountains of it. It’s readily available. And with things like the reductions in server costs, it means that, in data
terms, brands are currently living in an era of“all you can eat”.
We desperately need a“data diet”. A healthy balance between e.g.
organic“unstructured data”, locally source data goodness, or even
the“wild free range”social kind . And that diet doesn’t have to include
the nasty, manufactured,‘aggregated’stuff.
How can brands, with the help of their friends, get“data fit”? i.e. how can
they consume the right kinds of data, make big data an organisational
reality, and how can they use it to improve their marketing performance?
Big Data certainly doesn’t need a PR manager. Coverage by definition often
sings the praises of data gluttony and the need to adopt and consume more,
and consume a greater variety. There is a chorus of commentary around
topics like the rise of specialist ad agencies focused on big data driven ad
automation (reference the IPO of Rocket Fuel and others in the US), and
management consultancies (McKinsey et al) pointing to real value improvement of data driven corporates.
On top of this we have had revolutions in the spheres of behavioural economics and psychology , whilst
creatives, designers and UX professionals continue their love affair with data visualisation.
All of which should mean that, from a brand marketing perspective, we should have entered a golden period
in the fusion of marketing, UX design, and brand investment behaviours. But we haven't, yet. Which begs the
question why.
This lack of real traction with some brands around“Big Data”only leads to reactionary viral quotes like:
“Big data is like teenage sex…everyone talks about it but nobody is doing it”or“Big data is like a pair of
stilettos…likely to attract a lot of attention at the risk of serious discomfort”or“Big data is like…(INSERT YOUR
OWN JOKE HERE)”. It should be eliciting more than a punchline.
Part of the issue is the fact that brands themselves are
a bit like teenage girls. A bit self-obsessed, overly
focused on taking selfies, and counting the number
of likes. Exhibit A are my own two daughters. Just like
good looking Brands, they attract a lot of attention...
and Brands collect data as naturally as girls attract boys.
For any fathers of daughters out there…you willl know
that boys, like data, can suddenly appear everywhere
from nowhere. Some of them talk a good game.
Some of them don’t. Some of them look the part.
Some of them don’t.
And just because there are a lot of them doesn’t make it good. In the same way that just
because a brand has a lot of data doesn’t make it good. How do brands know what kind
of data is right for them? What kind of filters are in place? And what kind of data should
we believe in and trust?

2. At the most basic level, brands are still struggling at managing“first base”. They need better filters in place to make
sure they are collecting the right stuff.
The data has to be Smart Data.
(There is no point in having a lot of dumb data)
The data has to be Clean Data.
(Who knows where it has been)
The data has to be Purposeful Data.
(It has be there for a reason, linked to objectives,
with good long term intentions)
This is the first step towards getting“Data-Fit”.
Get the basics right.
Cleanliness and Purposefulnes of data should almost be givens - it is nothing more than proper due diligence on
the validity of sources and linking data to brand and business objectives. Making data‘Smart’on the other
hand demands a bit of contextualisation of it. For example, one of the companies sharing the platform with us at
iCom are Johnson & Johnson baby care. Their approach to contextualisaing data invloves the beautiful
simplicity of capturing one piece of information about expectant mothers - their due date. By collecting this
upfront, they, in one simple step, contextualise all of the other attitudinal and behavioural data they collect about
mothers on their path to birth. It makes all the other data“Smart”.
But beyond collecting the right data, brands also have to apply it where it matters most.
At Naked we believe that this lies fundamentally in the zone of linking data with creative workstreams - Intelligence
and Creativity being the only two things that are not commoditised in agency-land. But data and creativity are rarely
spoken about in the same breath. Data has, until fairly recently, been kept away in a brand or agency’s IT department
where the creation of engaging consumer conversations is not on the agenda. Similarly,‘creatives’don’t tend to have
the analytical and technical DNA to understand data and the insights that should feed into their work.
This has to change. Brands need clear plans in place to unlock the potential hiding in data to inspire exciting creative.
We believe that data is fundamentally reflective of
what brands and consumers SAY and DO. What
brands say to people. But also what people say to
themselves and others. At the epicenter of this are
the STORIES we tell each other and ourselves
about expectations and brand experiences.
By definition, at Naked we focus a lot of
our attention on working to unpack this kind of data
and use it as a source of insight AND content. Data
tells a story, and Stories are data. We are working with
our clients (like Virgin Atlantic) to rationalise and link
all the data they and we have access to. And that
work is increasingly informing what Virgin says (via
it’s Digital and CRM comms) and what
it does (via the design of experiences).
It feeds“CXM”not CRM. And the‘X’equals experiences AND expectations management. That is
where data truly fits in modern marketing practice, and where it acts as healthy nourishment

3. But most attempts at going beyond the superficial
adoption of data fail. Like most diet plans fail.
And more often that not these failures stem from
organisational failures. Organisational barriers.
At the recent iCom14 conference we shared our
advanced 3 -step“Data Diet Plan”:
1. Be data selective (and practice daily)
2. Apply where valuable (link data with creativity)
3. Recognise organisational barriers
What are the typical barriers to Big Data
within organisations? Here are 6 of the most critical
things to get right.
The reality is that most organisations are
victims to legacy systems. This is can be
especially true with airlines approaching
their 30th Birthday (such as VAA). Investment
is KEY, & VAA are always hungry for more
software, better quality data and more
internal capability.
Data often resides in silos across the
organisation. Getting visibility and linking it
up pragmatically is the key. At VAA we work
hard developing these internal relationships,
and externally we work with our partners -
to get that visibility and improve our shared
“single customer view”.
Most organisations still rely on a blend of
internal and external expertise. Internal
training, new skill adoption and building
effective cross-functional data relationships
across the business is key. Choose your
agencies and partners well.
When it comes to daily data mining, we
have found it important to take baby steps
and look for those“easy wins”, which deliver
real benefit in line with the organisational
objectives. If it makes money, this massively
helps data in the business. Focus on daily
data“Portion Control” BUT snack regularly
on the tasty stuff with clear commercial uplift.
Like with any diet or step plan, celebrate
success. Attend conferences, learn from
others and covet (and, as with Virgin, win)
Data Creativity Awards. Showcase data’s
value, and investment in the right kinds of
systems, people and software to do more
of the‘good stuff’should follow.
Beware that Data comes with consequences.
“Teenagers should be given chats about Data
Permanence, as well as the birds and the bees”
(SXSW 2014). We should clearly never
take for granted the footprint of our personal
and Customer data, nor Info Security and
Data Governance procedures.
Our message for brands and teenagers alike is“get data fit”.
Select the best kind of data nourishment. Apply dailywhere it has the greatest impact,
specifically dovetailing it with up-front creative workstreams where possible. Recognise the
organisational barriers, and learn how others have overcome these.