Three Keys to Unlock the Potential of Big Data
Taking advantage of the insights buried in Big Data is all the rage in many companies. An omnibus term, Big Data is the accumulation and synthesis of all kinds of customer data collected but lying dormant within an organization. However, exploiting its potential could be a daunting task for many managers. Here are three foundational steps to help kick off a high return, low risk analytics program:
Begin with a hypothesis
Big Data presents so many opportunities it’s often difficult to know where to start. The journey can finish at many end-states, some providing real business value but others offering nothing actionable. Moreover, data analytics competencies are not easy to assemble. Analytics experts are expensive and often difficult to find. You need to know where you are going if you want to extract value and not waste time and money.
One way to ensure you are on the right track is to create a hypothesis about your customers that is directly linked to corporate strategies and metrics. For example, an explicit hypothesis could be that the existing digital marketing plan is not effectively targeting the needs of the highest potential customer segments. This hypothesis would then be tested against the insights produced from an analysis of the pertinent customer and operational data.
According to Casey Futterer, vice-president of strategic new business at Nielsen Canada, “Coping with large amounts of data with few analytical resources creates an imperative for laser focus — what issue to solve, what action to take. Important issues will relate to questions of: who? (consumer/shopper); what? (proposition); and/or, how? (plan).”
Balance left and right brain thinking
Many assume Big Data is a mathematical and IT exercise based on customer relationship management data. While these three drivers are critical to producing meaningful insights, they cannot tell the entire picture about the customer, particularly if the data is internally siloed or incomplete. For example, firms can find in Big Data a link between nice weather and increased purchase behaviour but they often can’t tell you why these correlations occur. Do people buy more because it’s sunny outside, springtime or because of a recent price promotion? Without knowing the ‘why’, marketers will have a difficult time turning the insight into something actionable that generates solid financial returns.
To get to root causes of behaviour and a critical 360-degree view of the customer, managers need to look elsewhere at non-quantitative factors — the right brain or emotional side of behaviour — through tools such as ethnography, neuroscience and qualitative consumer research. In addition, managers should round out their quantitative analysis with a holistic examination of the customer experience including service, channel interactions and their actions with competitive offerings.
“There is no magic box that spits out the answer,” says Futterer. “Managers need to combine analytics with emerging tools and your team’s collective experience and brain power to extract insight and drive action.”
Test and scale
Once you know where you are going and have the right approach to get there, its time to put your strategy into action. When it comes to high-impact initiatives like Big Data, prudent firms walk before they run. This is often done for practical reasons. For one thing, few senior managers have direct experience with complex analytical tools or methodologies. Secondly, Big Data programs can be costly to implement. Finally, organizational and IT challenges may initially limit data accessibility and quality.
Using pilots is a common sense approach when experience and investment are low, and uncertainty is high. By running a number of small tests, managers can identify resource requirements, learn by doing and build internal momentum behind quick wins. Pilots could be structured around important questions such as which purchased products trigger the cross-sell of other items. Or, they could be run in specific geographies, lines of business or with single products.
Finally, collecting and analyzing more data does not always lead to better results. According to the former CIO of CIBC and McGraw-Hill Companies, Peter Watkins, “There is a common fallacy that more data is better. Best practice research shows that it is not the volume, rather it is the variety of data, and the better quality of that data, particularly on customer behaviour and characteristics, that enables smart analytics to produce rapid insight and speedy action.”
Properly executed, analytics has the potential to transform an organization. Tapping this opportunity need not be intimidating or unmanageable. Following an analytics strategy that aligns to marketing goals up front, adopting a holistic analytical approach and focusing on generating quick wins and learning will increase your firm’s chances of success.
Source: Three Keys to Unlock the Potential of Big Data by Mitchell Osak
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