We all believe in the power of data to help make better decisions. However, the reality doesn’t always match the belief.
In a recent CMO Survey conducted by the Fuqua School of Business, marketing leaders report planning to increase marketing analytics investment by 376% over the next three years. However, in the same survey CMOs report only leveraging analytics in about 31% of their most strategic decisions.
What gives? Well, a few things actually. There is a lack of process and tool selection strategy to measure success, as well as a lack of people to translate marketing to analytics. This is a big problem for the enterprise, and clarity is in short supply.
This blog post will introduce four concepts to help you bridge the gap between your analytics investment and insights and action:
- Tool selection
- Data connection
- Leveling up and translating across the enterprise
- Treating analytics like a people business
Picking a tool
Many companies obsess over tools because they are the easiest problem to solve—everyone is trying to sell you tools! Yet very few companies with amazing tools are doing equally amazing things with analytics.
Taking the wrong approach to tool selection is part of the problem. Instead of buying tools based on their capabilities, select tools based on how the vendors solve for your primary use cases. They have to show you—not just tell you—it is possible.
Second, don’t be hasty in jumping on the real time reporting bandwagon. Just because a tool can report in real time doesn’t mean it is useful to you. How many business functions can you confidently optimize in real time? Many organizations know that the answer is precious little.
Good marketing strategy takes many business cycles to put together. Real time reporting is useful for letting you know something major is broken—use it for that. Otherwise, don’t get swept up in that current. Your analytics investment should focus on “right time” rather than “real time”.
Connected data is useful data
Most of your data, such as email performance, website metrics, and CRM leads, ends up in silos. But if customer and prospective customer interactions do not occur in a silo, neither should your approach to analytics. There are real people behind your analytics data who have different motivations, intents and needs that you also need to pay attention to.
As a marketer, simply ingesting a ton of digital clickstream data isn’t enough. If you don’t know the likelihood of a user with particular behaviors turning into a customer, you don’t know enough about the people behind your data. To gain these insights, make sure your analytics game plan involves crushing data silos and bringing all metrics together into one system. This is definitely the most challenging aspect of implementing a cohesive enterprise reporting system. But in the long run, it will help you get the most out of your analytics investment.
Level up and translate across
At Search Discovery, we use a challenge question when we sit down to build dashboards: “That’s interesting, but is it useful?” Anything you will look at again and again must be stripped of all interesting data, and focus exclusively on the useful. An analytics metric is only useful if it corresponds to important business objectives.
For example, consider those at a senior level in an organization. They do not need to know every keyword that drove a paid search click this past month. But they do need to know what mix of media in the last quarter drove new customers, and how that differs from last quarter’s strategy.
Data is most effective when reporting focuses on what is specifically useful to that organization’s goals. It is essential to make sure your analytics investment uses reporting processes that track metrics and create dashboards that communicate useful data in a way that translates directly to business impact.
Analytics is a people business
Depending on who you’re talking to, you’ll get a different answer for why analytics reporting is broken at an organization. The analysts believe it is because no one listens to them or pays attention to their insights. And the executives don’t have time for analysis framed by people with poor business acumen and one sided perspectives based on one data set.
As an executive, one of the best paths to resolution is to “adopt an analyst”. Teach them what decisions you are trying to make. They will in turn start educating you on how the available data can assist in those decisions. Begin that partnership at the individual level, and then scale it across your organization.
Poor insights come from bad or misunderstood questions. Build a bridge to your analyst by explaining more whenever possible. And let them teach you how their data maps to the metrics and KPIs that you use to run the business.
So what’s the moral of the story? Selecting a tool puts you on the right track to building an analytics program, but your investment’s utility may not be quite so fleshed out. No organization will continue to invest without a return, so it’s crucial to approach data connectivity strategically and nurture the people-centric side of your analytics program.
If you need help driving connection, translation and education to maximize ROI on your reporting systems, talk to us. We can’t sell you any tools, but we do offer solutions that help organizations get the most out of their analytics investments.