One of the most fulfilling parts of my role at Anvil is helping senior marketing leaders successfully integrate analytics and business intelligence (BI) into their decision-making process. While a successful integration is more about training and culture than it is about software and platform solutions (more on that another day), one of the first things we discuss is terminology. For marketing leaders with more traditional backgrounds (think communications, branding, marketing or PR), analytics, data, and BI are all very new and very technical. Leaders are often hesitant to ask basic questions in a larger setting, so we have these discussions in a more intimate 1:1 setting where they can really dig in and get their questions answered.
So what is one of the most foundational questions I’m asked? It’s to simply define the difference between reports, analytics, and business intelligence. Our Director of Analytics, Brett Lohmeyer, has a great way to differentiate between reports and analytics, so I’m going to steal it from him. Thanks, Brett!
So what's the difference?
Imagine you’re driving a car and you get a speeding ticket. The ticket is similar to a report. It’s simply a snapshot in time. You were going X miles per hour on this road, at this time. Your speedometer and dashboard, on the other hand, is representative of analytics. It’s the real-time feedback of what’s happening — your speed, gas levels, engine temperature, etc. So, if you’re a marketer and you’re asking for a report, you’re asking for a snapshot in time of performance, for a website, a campaign, etc. Accessing the analytics, however, can give you real-time information and enable you to learn more about what is happening right now.
Business Intelligence is a term that is used incorrectly more often than not. BI is when multiple data points are combined to find insights within a comprehensive database. BI isn’t just multiple reports or analytics from different sources placed side by side. Instead, all of the data from the different sources (think email, Facebook ads, and e-commerce sales info) is combined into one database so you can see front-to-end performance using a key indicator, such as an individual’s email address. This allows you to see not only that someone bought something from your website because they found you yesterday via a Facebook ad with a specific headline, but you can also run lifetime value reports over time to see how that customer continued to buy. This is the key difference between the insights a platform like Google Analytics (or even Data Studio) can provide compared to Power BI or another BI platform. Correctly merging data sets to see a complete picture of performance takes time and expertise, but allows for much deeper insights.
How can I learn more?
If you’re a senior marketing leader and you’re focusing on deepening your understanding of analytics, consider attending the first ever Data Over Instinct Summit in October. We’ll be discussing topics such as the pros and cons (and costs!) of building an internal analytics team versus outsourcing, building a 3-to-5-year analytics growth strategy, and many others. Learn more and buy your super early bird ticket now.