Few marketers would admit that they truly have a handle on their analytics. But don’t blame it on the marketer. Marketing efforts are, by nature, hard to quantify in terms of dollars, revenue or impact. They tend to result in phantom impressions and estimated changes in perception – or what we call brand engagement (which is the bucket where we tell ourselves we cant measure it but its working). But this type of vague sentiment isn’t going to cut it for much longer.

Business owners and senior executives are increasingly demanding more tangible and quantifiable metrics and for marketing to be more data-driven. As a result of this demand, there’s been a swift emergence of tools, technologies and methodologies all claiming to help marketers measure their impact. Consequently, the number of companies and technologies offering business intelligence solutions can overwhelm the digital marketer while the lay-marketer struggles to get a grasp on the most relevant metrics. Marketers are searching for answers, like…

• Which analytics are most important and what should I be tracking?
• There are so many technologies and terms – how do these differ?
• What’s the best solution available on the market?
• How do these technologies integrate with my current marketing technologies?

The short answer is this really depends on the organisation, its objectives and the stage of development. To help sort through the chaos, here’s a quick look at the some of the most powerful tools available to marketers that are tuned into analytics.

• Measuring the effectiveness of your website: Marketing analytics need to be driven with a properly devised strategy and complementary systems. For example a marketing automation system, a CRM system, a content marketing space and an analytical interface like Mixpanel are highly recommended.
• Measuring the impact of your content marketing: Any organisation that uses marketing automation or CRM need the ability to track customer journeys and identify the content pieces that are most relevant to influencing the purchase behaviour. Kapost’s Content Scoring can help with this task by taking a granular view of the effects of singular marketing deliverables to revenue.
• Predictive modelling: The most nascent – but arguably the most powerful – marketing analytics tool is predictive modelling which takes conventional data kept by marketers, compiles it and crunches it to reveal patterns that predict buyer behaviour. Lattice Engines delivers predictive capabilities that help marketers focus on the production of money makers.
• Return on Investment: Don’t forget to plan your reporting. Marketing Evolution is an example of technology that helps marketers with their ROI plans.

• Without a doubt marketing has created a tsunami of numbers that enable the discovery (in real-time) of which messages are working best with which people, in which context, in which media, and with the ability to optimise accordingly. At a time when marketing is being measured more directly against top-line revenues, knowing how to analyse and interpret this data defines the businesses that excel and the businesses that will choke. It’s therefore critical to build the capacity within marketing teams to leverage these systems. This shift in the traditional skill sets of marketers requires a new way of thinking and a new way of preparing future marketers to effectively leverage big data in marketing.