A recent TED Talk from ethnographer Tricia Wang dealt with the dangers of big data without context; is she right to question the $122 billion industry?
Well, in short, yes – but it would be more a shared link than an article if I left it there, and thankfully Wang’s argument was nuanced – leaving a lot to be discussed.
We’re big believers in data at Click, but we always try to frame the importance of data as important as part of an holistic approach to search marketing. According to Wang, a former Nokia employee – we’ve been offering good counsel.
Have you found yourself wondering this week how Nokia is only just (some time later this month if news stories are to be believed) releasing its flagship smartphone? The answer, according to Wang, is an overreliance on data without context.
The TED Talk makes the analogy of data as an ancient Greek Oracle (without the hindrance of intoxicating vapours) in that the oracle itself is not the important thing, but those around the oracle who interpret the information disclosed.
The point of this analogy is not to present a case for analysis, however, but for context. Wang began researching in emerging markets for Nokia in 2009 – small data sets, but rich data – and discovered that, in contrast to Nokia’s data, the developing world wanted smartphones.
It didn’t go well.
So, with Wang revealing that 73% of big data projects are not profitable, why do we continue, both Click Consult as an agency and as an industry, to push data as necessity for the modern marketer? The reason is personalisation. While we firmly believe that data is a case of more is more, it absolutely must be placed in context.
Data can be incredibly useful, but it shouldn’t be used to confirm or deny suspicions. While it is desirable to use data to prove or disprove hypothesis, demonstrate success, data can also lead you down the wrong road if it is not used correctly.
When search is continually changing due to advances in computing, machine learning and artificial intelligence, data has become abundant, what has not spread at the same rate, however, is the framework to use data within. This is why those three quarters of brands investing in data are not seeing results – not that data is bad, but that they are not using it properly.
This goes to the heart of Wang’s talk, and while search marketing may not be dealing with the multi-million pound investments in data that Nokia seems to have wasted, the lessons remain the same. In order to use the data, you have to contextualise it; you have to learn all about the small details in order to adequately view the big picture.
It is here that, at least until sufficiently advanced computer modelling becomes readily available to brands of all sizes, that marketing techniques such as ‘buyer personas’ take on a new lease of life. With the amount of data available to brands it is possible to flesh out your personas with granular data taken from multiple sources.
While most brands cannot be expected to pay for an ethnographer to live and breathe the culture of potential consumers, they can ensure that they are keeping an eye on its demographic. It is also reasonable to expect that for brands looking to expand in their own country that data readily available can serve a similar purpose (at least until you can afford your own in-house academic).
What is a buyer persona?
A buyer persona is a mix of ideal and fiction, assembled from research into consumer actions, data and interactions with your brand on multiple owned platforms (branded site and social media profiles etc), buyer personas represent an inferred identity and attributable demographic for your target audiences.
Using data to build buyer personas
The data accessible to brands now is manifold and available across various platforms which feature their own native analytics, from Twitter to Facebook, LinkedIn, Google Analytics and many more besides there are ways to build and add flesh to the bones of your buyer personas. It is important, therefore, to build personas intelligently – is your audience the same across platforms, is it the same across services? While it may not be possible to develop multiple personas for each platform or service, generalisations which are too diffuse are the enemy and you should try to develop them as well as possible from available data.
As the above charts show, for example, Click Consult’s own audience is predominately in the 35-34 age group, approximately split between two thirds male and one third female – this is generally unsurprising in an industry which could, for better or worse, be split in much the same way – however, it does represent a starting point.
We can then look to flesh this out using other data. Twitter, for example, as part of its native analytics, gives a ranked order of interests we can use:
While it must be noted that this data is skewed by previous persona development and targeting, if we were to assume that this was the first time around we could see that our followers are interested in technology, tech and business news, marketing and entrepreneurship (though one facet of this data to note would be a preference for comedy which could present an opportunity when deciding on communication tone and voice).
From our LinkedIn page we can get a look at our followers’ level of seniority:
This tells us that we’re looking at a mix, but predominately manager level and above level of seniority and (in a separate report from the same platform) that they are concentrated within ‘Marketing and Advertising’ and ‘Information Technology’ (skipping ‘recruitment’ which is more than likely every brand’s second highest industry by follower count).
We can also see (across platforms) that our audience is – as you would expect – predominately English speaking and heavily weighted as UK based with a smaller percentage based in the US.
We can also find that our site visitors predominately use Chrome or Safari and that (from this data an unsurprising revelation) that the most common mobile devices used by the audience are Apple branded.
This is all useable data and, while there is plenty more you can use to flesh out your personas (entry and exit reports, behaviour flow, popular pages, site search etc), this gives us enough to make some rough inferences.
If we split our personas into three (for this example) we can deduce that two out of three of our personas are male and one female, we can assume that all three are iPhone users (imperative for coding your emails – see our @media query blog), we can give them all (reasonably for such a small split of the data) the position of senior marketing management, we know we can tempt them in with news on technology and marketing, that they have a sense of humour and that 80s pop cultural references will probably fall on deaf ears.
With just a few reports from some of the available platforms (and there are plenty of others with useful native analytics) we can make some judgement calls that help us decide upon some (clearly loose in this case) personas.
From here we can set up things such as RSS feeds with tech news to reshare via social and we can ensure we continue with our efforts to provide marketing blogs and resources. In addition, we know we have to be optimised for mobile and producing AMP articles. We call also surmise that we need to pitch our content at a senior level of knowledge more often than at beginners in the industry (say with an advanced guide to SEO) and that we could increase our output of news relevant to a growing American audience.
This is the contextualisation of data – by ensuring you monitor what your audience is interested in (and run regular updates of the process to ensure you don’t miss opportunities) you can get to know at least an avatar of your consumers and constantly flesh out your personas so, like Nokia, you don’t miss an emergent trend.
While not every brand can afford an ethnographer, there is absolutely no brand that can afford to learn from and contextualise the wealth of data now available to them. So if you aren’t yet doing so, now is the time to start.
Need help finding your audience? Why not contact Click Consult today. We’re experts in search. Simple.