The digital marketplace has made it a commercial need for every firm to be a technology company in some form. This implies that IT departments are called upon to work throughout the company to deliver business goals rather than their traditional “gatekeeper” function of maintaining the core technological infrastructure.

Is marketing a science or an art? The burning question for everyone is whether data will govern or support marketing. Will creativity and human touch remain a part of the advertising process, or will algorithms entirely replace them? The intuition versus data debate has been a recurring one. MIT researchers have even developed an algorithm that trumps human intuition. That doesn’t imply an end to the debate in favour of machines – only that humans progress from the earlier role of observing and analysing data to making decisions and acting on it. Machines, for the most part, do not. Or at least not yet.

Marketing was traditionally thought to be mostly an intuitive endeavour. However, since digital technology has pervaded our personal and commercial lives, the customer connection is now mediated by a plethora of devices, systems and information services.

Until this decade, data was mostly used for evaluation purposes. Common functions included determining how effectively a campaign performed, the expenses and the return on investment (ROI). Data was sometimes extrapolated to generate forecasts. There is now a paradigm shift whereby marketing professionals are entrusted with leveraging technology to enhance customer experience, boost client growth and satisfy loyalty targets.

As customers increasingly connect with businesses through digital channels, progressive companies recognise that this shift creates tremendous potential for the marketing function to improve and streamline processes. As a result, they have become increasingly reliant on IT for web and data-based marketing operations, including big data mining for business intelligence, followed by behavioural targeting, the Internet of Things, digital audience growth and consumer geotagging and geo-tracking.

There is a potential to use big data to enhance competitive advantage by identifying unmet needs, alternate, richer segmentation criteria, more precise targeting of offers in terms of time and channel, being forewarned of PR issues about to escalate and, finally, identifying issues that might lead to customer churn. Marketing teams now collect data using numerous applications or websites, and with proper attribution modelling, they can trace each brand encounter along the consumer journey. After parsing and analysing all of this data, marketing teams can determine which creative assets produced the most engagements, which channels provided the best ROI, and more. Organisations may fine-tune their efforts based on these insights to achieve the finest customer experiences and the most return on marketing expenditure.

All this comes with its set of challenges. There is so much data in the world today that downloading it would take over 180 million years. Businesses have a challenge since the human mind cannot process terabytes of data on its own. Gartner properly summarises this challenge: “Organisations have access to unprecedented volumes and a variety of data, but deriving insights continues to be a struggle.” Even though humans cannot process and analyse so much data manually, technology can.

Another distinction we need to draw is to differentiate between being data-driven and being data-informed. The former allows data to guide your decisionmaking process whereas in the latter case data acts as a check on your intuition.

The fact is that neither data nor intuition is good enough by themselves. In the words of an article in Forbes, informed intuition is the ideal combination. It creates a synergy between art and science by skilfully merging data-backed insights to inform creative, or typically gut-driven, marketing elements. Using data to guide intuition does not imply you should disregard your gut instinct. Sometimes your gut instinct can reveal information about your target audience that research alone cannot. Other times, your gut instinct will give you insights into the facts that you would not have developed otherwise. Informed intuition, on the other hand, is that you back up your gut instincts with evidence. Sometimes, that means seeing things from a new angle. Other times, it may mean performing additional research or networking with individuals in the business to learn more about how to reach your objectives. Informed, datadriven marketing may assist in balancing creativity in a way that produces incredible outcomes.

The transformation of the interplay between brands and people poses a challenge for marketers not in terms of the data they collect, but rather what they do with it. You can have the most sophisticated technology, but it will not deliver the ROI you want unless it is backed with marketing intelligence that combines data insights. Some manifestations of data-informed marketing are:

Sentiment Analysis
Before the rise of social media, marketers relied on surveys and focus group data as a proxy for what customers desired. The small sample of prospective clients available and the researcher’s methodologies skewed the results most of the time. The customer’s genuine voice was frequently only heard when it was too late, as a complaint. Data-driven machine learning algorithms can analyse a review, remark, or query to discern the topic, the product it relates to, and the customer’s opinions. This is almost like interviewing every client who wants to speak to you. Because these technologies are developed using genuine user-generated content, their reliability is strong. The best aspect is that the algorithm can recognise emotions portrayed by emoticons, which are increasingly replacing facial expressions in online communication.

A/B Testing and Bandit Testing
Choosing which image or slogan to use is a constant challenge. Data provides us with the opportunity to make a nearperfect prediction of the ROI of marketing expenditures even before a campaign is launched. Although A/B implies a choice between two possibilities, it may be expanded to A/B/n to accommodate as many options as needed. Two or more variations of an ad can be run on a platform of choice on a sample group to see which variation performs better. In terms of marketing, acquiring this sort of data saves money that would otherwise be spent on an underperforming set of ads. Bandit testing, an automated expansion of the A/B approach, harnesses the true potential of data. Instead of evenly dividing the sample, the computer dynamically guides visitors to the favoured choice of the moment, leaving the other in the background with lesser visitor influxes.

Multiple Channel Strategy
The capacity to design scalable, repeatable procedures and forecast reactions and financial outcomes. The beauty of data is that a lesson learnt in one channel can be successfully reused in another for a multichannel approach. For example, if Google Analytics indicates that website visitors fall into a particular demographic, this is a good approximation for targeting similar consumers via Facebook ads. On the other hand, it also provides insight into a category that has not been targeted.

Combining gut-driven creativity with statistics can help you achieve more satisfactory marketing outcomes. In the form of data-backed insights, there is an enormous amount of valuable information available to customers. Marketers must leverage that data to inform and validate assumptions to increase the total return on marketing spend.

Fauzia Kerai Khan is CE, I&B Consulting, Assessing, Learning, Consulting. fauzia@iandbconsulting.com