7 Digital Analytics Trends that will Dominate in 2017
“Analytics without application to an actionable strategy is meaningless”- Mike Grigsby.
In the preliminary days of web analytics things were quite simple for marketers. There were fewer marketing channels and primarily one device to look out for i.e. the desktop. But today, with proliferation of channels and devices it makes it extremely daunting for marketers and analysts to comprehend and measure customer journey.
2016 has mostly revolved around predictive analytics, big data, emerging platforms, system integration and new tools. As per Newton’s theory, a change in motion of a body indicates a force in operation and this is the time for this force from 2015 to drive the momentum of marketing analytics in 2016.
Here are 7 Digital Analytics Trends I believe will dominate in 2017
2016 was a shift from descriptive analytics to predictive analytics, but 2017 would be about upgrading from predictive to prescriptive analytics. Marketers not only want to know about what will happen next, but also want to know what the optimal action should be. With automation being the theme everywhere, the next level is about data (insights) driving decision automation.
Descriptive analytics to a certain extent is automated and in 2017 you’d see more investment in driving insights and automated decision making instead of mere reporting of data. Companies are moving towards machine learning and to make it more accessible we have services from Google Prediction API, IBM’s Watson Analytics, Amazon Machine Learning and Azure ML Studio from Microsoft. Analytics would be used to understand customer patterns and programmatically suggest profitable customer paths to marketers to route customers in that direction. For instance, Amazon uses prescriptive analytics for product recommendations based on customer data around original purchase and product engagement patterns. This helps Amazon to provide better user experience and also increases customer spend. Editor’s Note : To deepen your understanding of Data Analytics and grow in your career, you should enroll for Coursera’s course on Marketing Analytics and Digital Analytics. You can also look at multiple other courses on Analytics here.
Until recently most analysts have been creating measurement framework based on a funnel based approach where the focus is on acquisition, volume based metrics and not on customer profitability. McKinsey analysis of a recent ANA survey revealed that “only 13 percent of companies feel strongly that they have identified their customers’ decision journeys and understand where to focus marketing, while nearly half cannot measure the critical stages of the consumer decision journey”.
Companies have been obsessed about channel metrics and this is the time when the need is to shift focus to a more customer centric measurement framework. 2017 would be about aligning customer journey perspective with the firm’s perspective of conversion funnel i.e. which analytics method to use to measure business objective at each stage of the consumer purchase cycle. This would eventually drive the company strategy to be centered on consumer behaviour. You can read more here.
In the current digital landscape, companies are sitting on massive volumes of data (raw & processed). Now is the time for businesses to look at innovative ways of leveraging the data, for driving future action and direct impact to bottom-line revenues, which is now readily available.
Data around customer transactions, interactions across devices and channels needs to be assessed based on their value and the best possible strategy needs to be developed to utilize full potential of data monetization, either in the form of increasing revenue streams or using the data to create efficacies within the organization to reduce cost. Successful digital revolution will be based on forming data streams in and out of the function and finding new ways to monetize them.
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