Data Driven Digital Marketing in 2016: What are the implications for content strategies?

by Adam Halperin on Friday 18 December 2015

Content Strategies in 2016


Data driven digital marketing in 2016 will bring with it new challenges for content marketers to overcome. The implications for content strategies will encompass the role of attribution in an increasingly connected world; creating personalised experiences for customers utilising individualised insights; and utilising data driven storytelling, or ‘data journalism’, as a form of content marketing.


The role of attribution


Attribution modelling is an essential part of any digital marketer’s toolkit. An attribution model determines which part of a consumer’s journey should receive the credit for an end purchase (or ‘conversion’). Credit for conversions is often assigned to the last ‘touchpoint’ that a user clicked on before entering a website. For example, this might be a link in Google’s ‘organic’ (unpaid) search results, which then directed the user to a website where he or she bought an item.


However, marketing innovation has resulted in increasingly sophisticated methods of evaluating the consumer’s path to conversion. The ubiquity of cookies and the growth of data-rich social media now empowers us to look beyond simplistic methods of demographic targeting, and instead adopt multi-touch attribution models to develop enhanced insight into campaign performance data. 


These developments give us a greater understanding of the factors truly driving consumer engagement, rather than simply relying on last-click attribution. The actionable recommendations that can be obtained from multi-channel, cross-device data in 2016 will help us to create increasingly targeted creative campaigns, and use more intelligent budget strategies. Rather than simply understanding which channels facilitated the eventual purchase, we can now also understand the touchpoints that were influential earlier in that customer’s decision-making process. 


Increases in connectivity


As digital interaction becomes increasingly integral to our daily lives, we are seeing our longstanding marketing conventions transformed. For instance, with constant connection to mobile technology, our mobile devices are continuously logging and collecting real-time data such as our location, whether or not we are actively interacting with them at the time.


Google can now analyse the stores you visit via your phone’s location-based settings and then cross reference this data to determine whether you also visited the store’s website beforehand. Beacon technology is translating the personalised communication methods previously only found online into the offline shopping experience. Regent Street recently became the first shopping street in Europe to use beacon technology to deliver personalised content to shoppers, with offers, suggestions and customer information. 


The rise of the ‘internet of things’ (connecting everyday devices and appliances such as wearables like fitness trackers to central heating, fridges and cars) is providing a service to consumers and making our lives more efficient and productive, whilst at the same time creating unlimited opportunities for businesses to collect, cross reference and analyse data. 


The continued rise in the usage of mobile apps will bring huge amounts of data collection with it, far more than can be collected through traditional browsers. In turn, this will have implications for the way content is published. 



In 2016 it is imperative for content marketers to properly research their data, find trends and then utilise them in their campaigns. This provides business justification for investment, generates an understanding of target audiences, and also aids in the creation of content itself.


Analysing data for personalised content marketing


In order for us to target users with the best content, we must be able to understand their personalities and interests. Marketers can now study a customer’s content / consumer journey from their first interaction with a piece of content, such as a news article, email, video or infographic, all the way through to social media interaction with a brand and a final purchase days or weeks later. 


These data insights enable us to make faster and more accurate decisions than ever before, such as determining the optimum content strategies in order to increase the chances of conversion. Attribution models in 2016 are more challenging than previous years, yet they are also potentially vastly more rewarding.


As algorithms increasingly understand the subtle nuances of language, marketers can investigate whether there are changes in online sentiment in response to campaigns, and if these changes correspond to fluctuations in purchasing patterns. 


Real-time marketing campaigns can even be planned using predictive analytics to correspond with user purchasing patterns. This means users receive the most relevant messages not only for what they are most likely to buy, but also for when they are most likely to buy, and how much they are likely to spend on a specific day and time.


The challenges of personalisation


In 2015, Teradata published their Global Data-Driven Marketing Survey, a worldwide look into data-driven marketing trends. Teradata’s research reveals ‘dramatic shifts’ since 2013 in ‘how companies and marketers are deriving business value from data, integrated marketing platforms, and customer-centric data-driven marketing strategies.’ 


Teradata found that 90% of marketers see marketing individualisation as a priority, moving from segmentation to more personalised strategies, of which data-driven marketing is ‘viewed as the means to the end’ in terms of achieving individualised insights. 38% said the most important challenge marketers currently face was ‘improving customer acquisition and retention’. 


At the time of the study, three quarters of marketers said that they used data ‘systematically’, compared to a third in 2013. Nevertheless, marketers were found to still have difficulty with personalising their communication efforts, with only half regularly applying data to ‘engage consumers’, and 44% admitting a ‘lack of consistency in omni-channel marketing’. 80% of marketers said that marketing silos (separate marketing channels that work independently) ‘prevent them from knowing how campaigns are performing across different channels’.


Predictive analytics


However, despite the improvements to data analysis, the usefulness of data collected may degrade over time. This means content marketing has now reached an important crossroads. In the ultra-competitive world of digital media, we need to be lightning fast in providing actionable content and personalised stories based on analytics data. Predicting what kind of content will be the best received, even before it has been released, is set to become a key priority. 


While still in its infancy, Twitter’s new ‘Moments’ feature heralds the coming of an era of data driven storytelling. The aim of Moments is to utilise user generated data to create bite sized stories and features on current events as they unfold. In 2016, content marketers need to start viewing content less in terms of one-off posts or campaigns, and more as ultra-relevant current event themes and trends, which can be explored in episodic formats, and updated in real-time.


Image sourced from

Image sourced from


Utilising data insights in content creation and the emergence of data journalism


A good content marketing strategy will always include insights about what customers actually want to see and hear, and not just about what we want to say about our brand. Companies are adopting content marketing strategies that vary hugely in quality and usefulness for the end user. These range from the most basic blog posts to high-budget film pieces, but some are now also attempting to break the mould and be viewed not just as brand advertisers, but as legitimate publishers of valuable information. 


A 2015 study by BuzzSumo and Moz found that most content published online is of low quality, and goes unnoticed when it comes to shares and links. Looking at 100,000 randomly selected posts, they found that more than half the posts had 2 or less Facebook interactions, and over three quarters had no external links. Even when it came to studying a larger sample of 750,000 highly shared posts, they found that half still had no external links, and across a total sample of 1 million posts it was found that there was no overall correlation between shares and links. Interestingly, a strong positive correlation of shares and links was found for ‘research backed content and opinion forming journalism’.


By introducing and utilising one of the most important current media trends, ‘data journalism’, brands are attempting to mimic how mainstream news sources currently publish information. One such example is The Guardian’s data blog, a trusted source providing a wealth of information on traditional broadsheet topics such as politics and economics, ranging from election result analyses, to the impact of religion on public life and the world’s most expensive cities.



Most businesses today have far more data than they know what to do with, and yet the majority still prefer to keep this data private and used only for internal strategy. Data journalism takes the insights that companies usually undertake to further their business intelligence and instead, utilises them to reveal compelling and insightful stories. These are narratives that are likely to be of interest to their customers, on topics they may not normally receive detailed information about, usually presented as infographics and other attractively designed visual pieces. 


These data-driven, graphically presented stories can often attract a large amount of social media attention. Providing data analysis and curation in the public domain establishes your brand as an industry influencer, and an authority on a specific topic, which can in turn lead to interview requests and an entirely new avenue of link generation from mainstream media citations. Data is particularly important for B2B companies as a way to distinguish themselves against their competition by displaying proof of expertise through knowledgeable insights. This approach also provides an opportunity for creative content in industries that may otherwise be perceived as ‘dry’, in which compelling content is more difficult to create. 


As an added bonus, companies can observe the reactions and responses to their data-driven content from third-parties, which may afford them with fresh insights they might not have previously considered, as well as providing them with an improved understanding of their target audiences. Companies can use this understanding to further shape their traditional content marketing features in a manner that unites their customers’ interests and personal profiles. 


Despite being infrequently updated (only once or twice a year) for the past few years, the popular OKCupid dating site provides an excellent example of this approach. The dating service has delivered an array of data journalism pieces for their online dating users in the form of a trends blog, releasing statistics they have gained from analysing online dating patterns to improve their matchmaking algorithms. 


Examples of data driven content they have produced include observing the odds of a single chat message turning into a conversation depending on the compatibility of users; explaining how long a person’s relationship will normally last depending on a how often they use Twitter; or the best questions to ask on a first date according to user surveys. These insights are interesting to users due not only to the natural human tendency to be curious about our own nature, but also their apparent practical value for relationship prospects.


Another great example of an attractively designed, data-based infographic is the following one from AirBnB, which celebrates a milestone of 1 million nights booked via the website. Despite being specifically designed to gain publicity, it is still able to capture an audience’s attention using company data to tell an interesting story.



Final thoughts


We have the ability to provide more intelligent and valuable insights through multi-touch attribution models than ever before, yet accurate data-based insights are one of the most underused assets of marketing departments for campaigns. Content marketing has reached saturation point, and for us to rise above our competition, our ideas must be ever more innovative.


By combining data-driven content with anonymised user data in order to protect customer privacy, digital marketers now have the ability to target specific niche audiences with quality information that is relevant to them. 


This method of content marketing in 2016 will enable businesses to not only drive the efficiency of their marketing activity, but also to build trust from their customers. This will be achieved by being more transparent in demonstrating how their information is being used to provide useful functionality such as personalised services and products.


Adam Halperin – Content Marketing Manager