“Half the money I spend on advertising is wasted; the trouble is, I
don’t know which half.”
Digital Marketing and its elusive promise of complete and instantaneous visibility
across all activities has tantalized marketers for the best part of three decades.
The notion that any interaction between a customer is trackable, and therefore
has an obvious appeal to those marketers tired of being seen as the
However, as many have found out, effectively capturing and utilising the troves of
digital marketing data available is easier said than done. The reality is, most
companies have no idea how to capitalise on the considerable
data intelligence that is available to them. Yet, for the brands that are able to do
so – the positive business impact is immense. With a recent study from Mckinsey
which surveyed 1000’s of MNC showed those companies
who achieved the greatest overall growth, were able to attribute a significant
proportion of that boost from their ability to utilise data and analytics (Read:
Catch them if you can, how leaders in data and analytics
have pulled ahead).
So what are the steps that brands take to fully realise the potential of data that is
available to them?
1. Build a 360-View of the CustomerFirstly, brands need
to build a 360-degree view of a customer – or at least as close as possible - by
capturing, storing, and organising data in such a way
that it can be meaningfully dissected. This means capturing as many of the millions
of data signals that customers provide each and each and every day. These signals
can range from simple behaviours such as opening
an email, clicking on a banner ad or applying for a loan to more passive signals
such as turning 18 or letting your gym membership expire.
Most companies have elements of a 360-degree customer view, but often they reside in
silos without the ability to ‘stitch’ all of the signals together. To
overcome this, data leaders are increasingly turning
to Customer Data Platforms. And while this relatively ‘new kid on the
block’ technology has transformed a brands ability to build a holistic view of
the customer, the technology alone will not solve the
Critically, brands need to strategically decide on what specific data they want to
collect and how they will collect it (Cookies, Interactions, forms etc.). Too often
brands skip this step – expecting data to answer questions
without first defining those questions.
Brands also need to ensure that all this collected data is clean and consistent,
which can be both a strategic and technical challenge.
Creating a logical data taxonomy is one of the most painstaking but important tasks
that a brand can undertake on their data journey. Having a standardized naming
convention means your data is consistently categorized across
multiple sources and channels, thus allowing you to undertake the second step of a
data journey - meaningful analysis.
2. Data Analysis: Mining data for actionable signals
Data is only beneficial to an organisation if it can be actioned upon. However,
marketeers (and their agencies) often fall into the trap
of undertaking quasi analysis on a host of vanity metrics that provide no relevant
insight on how a digital experience or media program can be improved.
Often this takes the form of isolated channel analysis – i.e. the Open Rate on the
eMail campaign was 10% - without any degree of audience level analysis or action
While even the most rudimental segmentation can lead to actionable insights (the Open
Rate for Segment A was 5% and Segment B was 15%.) such simplistic analysis can
distract brands from the true power of data.
True strategic analysis should allow marketers to gain a deeper understanding of
their customers and the unique relationship they have with a brand – who they are,
what they have in common with other customers, what content
they are most likely to engage with etc. etc.
Consider the diverse audience of a university’s website. At the highest level
the organisation may cluster into prospective students, current students,
researchers and staff. However, this is only a surface level
understanding – direct or indirect signals may lead us to learn the faculty they
belong to, level of engagement they have with the organisation, tenure of engagement
and so on.
With the right technology in place, advanced data models allow for clustering of
customers into narrow segments based on a continuous loop of signals, with each
interaction leading to a progressively fuller picture of the
customer. With this, marketers are then able to dissect their audience into
increased granularity and uncover a host of actionable triggers and insights.
Decisioning and Distribution: Personalising the experience Armed with a
deep understanding of their audiences and a host of actionable insights and triggers
against them - the next step for a marketer is to
decide exactly what to act upon. It is important to note here that not all need to
be actioned upon.
It is here that an integrated technology stack, combined with rule-based automation
becomes the most powerful tool in a modern marketers arsenal.
Whether it be a fully-fledged Experience Platform, stand-alone Content Management
System, Marketing Automation Platform or simple Email Service provider – marketers
now have a plethora of technology solutions that allow
for the distribution of personalised experience.
Continuing on with the University example; this stage may include using a CMS to
personalise website content based on whether a visitor is an existing and
prospective student. Or a triggering email based with tailored content
based on the course guide that was downloaded.
The potential scenarios that can be delivered by these technologies are practically
endless – only restricted by volume of actionable data and content available.
3. Ongoing Testing and Learning The last step that
markets need to be aware of in making the most of their data is the capacity to
test, learn and evolve these decisioning strategies and content.
Data-leaders are those that have an embedded test culture, looking at results to
understand “what did I learn” rather than “can this data prove I
made the right decisions”.
Marketers who understand that a successful data journey comes from a collection of
incremental improvements in strategy and execution rather than a single “home
run” are well placed.
In conclusion Data enables brands to understand who a
customer is, how and where they are interacting with a brand – and, more
importantly, data makes it possible to craft and influence those
interactions. In essence, data is the single most important ingredient that allows a
brand to improve the entire customer experience through personalised content and
For marketers that fail to act on the data they have at their disposal they are at
risk of losing relevance and remaining as the ‘colouring in department’.