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Social media dot-to-dot: How dynamic analysis can improve customer insight

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20th Feb 2014
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As a planner, the satisfaction that comes from finding that piece of hidden insight or hither-to unseen opportunity which could unlock more business for a client is something that will always be an important part of the job.  The one thing that is changing, though, is how we actually find these.

Over the past few years there has been a significant shift in the way we generate data driven insight and the nature and skills sets that are required within the analytics teams.  As is often the case these shifts have been enabled by technology and the digital environment. 

In the past brands have been focused on building customer and prospect databases and using  technical analysts to undertake “static analysis”.  Static analysis is very much based upon a predetermined dataset, typically transaction or response based, and sometimes also enhanced using third party variables.  Ultimately, it has been used to deliver segmentation delineated by past behaviour and consumer lifestyle description. 

This approach is undoubtedly a way of adding value by delivering better honed targeting strategies and helping to improve the efficiencies and effectiveness of direct channels.  The shortcoming of this segmentation approach, though, is that it has only been able to answer the question of whom to communicate with.  What it hasn’t done is deliver meaningful insight that will answer the other two killer marketing questions:  what motivated their behaviour and how should you engage with them to achieve real impact. To unlock answers to these missing insights, analysts have tended to turn to qualitative research.....

...but that was then.  Now, brands no longer need to own all the data or undertake expensive qualitative studies (which are sometimes at best directionally significant rather than empirical) in order to join the dots between these insight gaps. The big difference is that the digital data environment, in tandem with a multitude of simple-to-use analytic tools, allows businesses to get far deeper insight. By “borrowing” these tools and accessing the digital data stream it is now cheaper and faster than ever before to understand the contemporary thoughts and feelings of distinct consumer groups – in real time. This means that we now have the potential to create ideas that will really cut through and engage with target audiences as a result of their heightened relevance and timeliness.

So what can this new ‘dynamic analysis’ look like?

A good example is Philips Shavers. Profiling their electric shaver customer database versus the blade market revealed that they sold well to older men aged 40+ but struggled to capitalise on the huge opportunity of young men aged 20-35. This insight, while interesting, didn’t explain how they could overcome the level of rejection they were experiencing from the younger audience. 

Through the use of simple and free analytic tools that analysed online conversations and journeys, it was found that they considered electric razors to be old fashioned – something their dads used - and that technology and innovation were considered to be the domain of blade razors.  Plus David Beckham was quite cool too!

Beyond this it was also identified within the digital data environment that, although young males are not particularly interested in shaving per se, they are incredibly interested in self-expression and experimenting with their own image and persona.  This data insight allowed the brand to create ideas that resonated strongly with the target group and drove engagement that could never have been achieved through “static analysis” of Philip’s huge but limited database.

That said, the power of segmentation should not be dismissed as a result of these new analysis opportunities. It is still providing a very effective way to help businesses such as Monarch Airlines to improve the ROI of their direct marketing activity through analysis of the transaction and response histories contained within their customer database. However, we can now bring so much more insight into play by mining the data available from the consumers’ wider world. 

For instance, recent analysis of consumer behaviour from Skyscanner, a leading flight search company, showed that there was a regular spike in searches at the end of the weekend as travellers sought inspiration for their next trip away. The most popular searches at this time were the “everywhere” option, highlighting peaks in consumer curiosity when they are most open minded and looking for content that can excite and feed their minds. What this told Monarch is that they need to inspire these customers with the possibilities and choice offered by Monarch - not just  offer them destinations based on where they have been before. As the customer progresses on their journey to purchase we will of course bring the best practices of data-driven CRM to bear - recognising them, their preferences and content that will convert their curiosity to commitment.

What’s also interesting about these new opportunities for gaining insight, is that they are not only changing the look of brand strategies, but also the make-up of the agency insight team; we now essentially have a whole agency of “data analysts”. They are skilled at using tools that allow for dynamic data-mining and deep insight generation. Google Analytics, Google Trends, NetVibes, Addict-o-matic, Social Mention – these are just a few of the inexpensive, or even free, tools that are driving insight possibilities.

This exciting new world of insight enables us to focus on the full ‘curiosity journey’ customers go on, continuously identifying new behaviours and new differentiating data attributes that sit outside of the “static database” and allow us to exploit possibly the most dynamic channel available to our clients, CRM. 

Ashley Patterson is planning director at direct response and relationship marketing agency WDMP.

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