Today’s CMO #4: Analytics – It’s Time to Get Back to Basics

“Analytics” means different things to different marketing and business pros. After a deep dive to create our marketing analytics and a whirlwind tour of our customers to scope Integrate’s next version of our analytics suite, it’s clear we (CMOs and marketing pros) need to simplify our approach. Always trying so hard to prove we can account for everything, we often unknowingly, make it more complex to focus on what matters. And, we have so much data we can compile, especially with powerful new tools available to us, that we may be overshooting what we need in order to deliver business impact. So, my new mantra is “Get the basics right and build from there.”

Word Cloud "Business Analytics"Let’s start with a definition since “analytics” seems to be used in so many different ways by pundits and practitioners alike. “Analytics,” according to Business Dictionary, is used for anything that involves measurement. The reality is analytics involves studying past historical data to research potential trends, analyze the effects of certain decisions or events, or evaluate the performance of a given tool or program. The real goal of analytics is to improve the business by gaining knowledge that can be used to make improvements or changes.

We can use two big analytics “buckets” to frame our effort, each having unique values and overlapping purposes. To advance our capabilities and impact, it’s important to measure and analyze both:

1) Marketing outcomes: The analytics marketers use to guide and improve marketing performance, investments and decisions, encompassing everything from creative to channels to technology.

2) Business outcomes: The analytics marketers use to measure overall business value, in order to prove marketing department ROI and to secure funding for key initiatives.

In order to understand which marketing strategies and tactics are working and which aren’t, we need marketing analytics. The presentation of data in insightful ways guides marketing pros in areas such as content topics, social media channels and web design. This allows us to shed the guesswork and, instead, use data to drive decisions, spending less time on low-value banter. For example, the ever present conversation “I think this color looks better” advances to “The design using this color is getting 23% more engagement.” And the subjective opinion “I like this style of content” becomes an objective fact: “The interview-style blog post outperformed our standard prose post by xx%” (these are real conversations we had last week).

With marketing performance data in hand, business analytics are essential to measure the impact on the organization’s bottom line – the ultimate outcome. Business analytics guide our investment in areas like media, events, digital and talent. It allows us to measure customer impact such as acquisition, life-time value, revenue and profit created from our marketing spend. This is unquestionably the language we as marketers need to use with our stakeholders.

In order to get back to basics and measure marketing and business outcomes, there are three fundamental questions marketers must ask:

Who are we developing/adopting the analytics for?

It’s nearly impossible to develop or review analytics until we can answer: “Who cares?” This allows you to identify the stakeholders who must agree upon the data needed to improve their results and/or measure their outcomes. Marketing program managers may need campaign analytics, content consumption and prospect engagement data, for example, while sales and business leaders may need to understand the contribution of marketing to sales pipeline, revenue and return on media spend. Another critical factor is frequency. Marketing managers may need more real-time or frequent data while business leaders/analysts may only require a monthly or quarterly summary. Once you identify the stakeholders, you set the stage to get the most return on your analytics software and/or the time you spend compiling the data.

What exactly do we need to measure?

One of the best ways to develop your analytics system is to start with the end-game and work backwards. The adage “What does success look like?” is a mantra to help focus on a set of analytics that will steer you in the right direction. Of course, the shorter the path to measurement and action the better. This exposes another trap that’s easy to fall into. We get so enamored by data – by how specific it can be – that we bury the headline or what’s important and confuse our stakeholders. More data does not translate to useful, impactful analytical insights.

Are our analytics actionable?

There is a massive gap between “reporting” – data used to track info – and “analytics” – data presented in ways that improve understanding and guide better decisions. As a former CFO I used to work with always says, “Reporting is CYA, analytics are DTB [drive the business]. We need more DTB and less CYA.” This means if you’re going to spend time setting metrics, measuring and analyzing, make sure you can do something about it. You can always report on how many clicks you got or how many articles you got published, but if you don’t know why you got those clicks or which content performed best, it really doesn’t matter. WARNING: this is easier said than done. It’s a change in mindset and approach for most organizations that has huge upside for both impact and credibility with stakeholders.

Less is more is a bit counter-intuitive in the era of big data. However, the back to basics approach on analytics – including asking the three core questions outlined above – will help you focus on actionable analytics. The results are improvements in defined areas of marketing performance and increased credibility with stakeholders by delivering measurable business results.

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