“With data collection, ‘the sooner the better’ is always the best answer“
- Marissa Mayer
Surely all the marketers out there have noticed a rapidly growing direction towards big data, analytics and increasing complexity in their departments as well as their daily pursuits. Marketing specialists and their multi-channel campaigns with Google, Linkedin, Facebook, Twitter and other social media ads combined with data sources from sales, finance and other key components of a corporation or mid-sized firm only adds to increasing data complexity within an organization.
Companies which understand these trends endeavour to take action towards data analysis – from data aggregation, through key findings, all to way to actionable insights for relevant stakeholders in the company. These marketing analytics „officers“ should be held accountable for implementing these and optimally drive value through new markets expansion, cost reduction , customer satisfaction or new product development efforts– all based on data driven insights.
„Leaders in data-driven marketing are more than six times more likely than laggards to report achieving competitive advantage in increasing profitability (45% vs. 7%) and five times more likely in customer retention (74% vs. 13%)“.(Forbes, January, 2015)
Volume, variety and velocity of big data is growing by the day and impacts daily reality of all marketers. There is plenty of choice in the marketplace when it comes to big data and analytics technology and tools, provided by multi-nationals or Sillicon Valley startups, so there is certainly no shortage of options for a company of any size when having considerations on any data management initiatives.
So how to go about a marketing and customer data analytics initiative? Generally speaking, it would be advisable to start with an analytics effort sooner rather than later, regardless of where you would put yourself on the analytics maturity curve (beginner to advanced).
Before moving forward with marketing analytics initiative make sure you identify key objectives based on defined analytics framework divided into milestones which are in sync with company existing processes.
Do you know who your best customers actually are and what they want? Can you determine what is valuable for them? Once you identify key objectives, embark on the analytics journey and hold key stakeholders accountable for results, all based on operationalized goals and company vision.
As we already know, big data out there is only going to grow bigger, both as internal and external data sources and their convergence. There are data techniques to be leveraged or left out, e.g. pattern recognition, machine learning, sentiment and text analysis, all depending on specific company objectives.
It is crucial to focus on correct data segments within the data sources reality which should again be determined by having campaign objectives set correctly – this way you increase your chances of impactful analytics exercise putting the company on growth trajectory as an optimal scenario.
Do you have certain framework in place? What is your experience driving an analytics initiative? Please share your thoughts.
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