Big data is everywhere. More and more companies are increasing analytics budgets to cull through enormous amounts of available information, whether it’s to better understand visitor behavior on their website, stay up to date on their top customer support issues, or gain some other critical business insight.
Some 5.5% of marketing budgets are being spent on marketing analytics, with an expectation of an increase to 8.7% in the next three years, according to a recent CMO Survey; however, only 3.4% of senior marketers say they have the right analytics talent.
No matter what type of data puzzle you’re trying to solve, it is vital to seek out a strong analytics team, whether internal or external to your organization, if you are to make sense of all the key trends and patterns hiding in your data.
So, how do you know whether your analytics team is effective? Here are eight key indicators.
1. Is There a Question?
Data is used for problem-solving. Without a problem to solve, there would be no purpose to data.
The first and most basic question that must be asked when starting an analysis is this: “What am I trying to solve for?” An analyst can be easily sidetracked when digging into vast amounts of data, and that question is critical for guiding that digging.
Of course, what question you ask depends on what business goal you are supporting. And that could be anything from “What city should we expand to next?” to “What new product feature would drive more sales?”
2. Is There a Story?
Storytelling plays a critical role in effective data analysis, and the story synopsis is the flashlight in the darkness of big data. Storytelling helps analysts to keep all their facts straight and to fact-check their calculations, assumptions, measurement approach, and data quality. If the data isn’t intuitive to the story, then something is wrong or there is a missing insight.
A consistent and understandable story can ensure data accuracy and help identify data-quality issues. It also encourages the analysts to play with the data and use available tools to build a complete story. But perhaps most important, it fuels effective communication when your findings are presented to product managers or executives. A good story reinforces why the data matters.
3. Emotion vs. Data
People choose with emotion and then justify their decision with fact. And analysts are not immune to that human trait. Hence, it is important to know what is driving that emotional decision and whether the emotion is clouding the analysts’ judgment or steering them in the right direction.
Good people-management skills and an understanding of what motivates the team will aid with enabling them to best articulate their process and findings.
4. Are Your Analysts ‘Dolphins’?
People who are not seeing both the macro and the micro views also tend to miss the big picture strategically, and there is no room for that. Look for “dolphin” analysts—those who dive between the macro and micro layers of data, in addition to being compelling and effective oral and written communicators.
5. Right-Brained and Left-Brained Analysts
The best analysts don’t always come with a computer science, stats, or math degree. They might come from the social sciences (psychology, political science, marketing) because they have a deep passion to understand why people do the things they do.
Look for people who are highly gifted in using both sides of their brain (not easy to come by): those with an insatiable appetite to understand both why people behave in certain ways and what variables can be modified to influence those behaviors.
6. Visual Aids
When making presentations, simpler is better and a picture says a thousand words. Make sure that when your analytics team presents its analysis, you’re getting a clear and concise view into the story being told.
Displaying the data and insights in charts, illustrations, and graphs that back up your story and help you communicate your findings to executives and product managers is part of an effective communication plan.
7. Thou Shalt Not Be Misleading
Is your analytics team representing an anomaly or the bottom/top of the range as an average? Are all relevant disclaimers being communicated? For example, at first pass the data might show a dip in sales over a defined time period, pointing to a change in customer behavior, but after closer examination you find there might have been a site outage or some other outside factor that affected sales.
Before making big decisions, make sure your analytics team is not being too hasty in making assumptions and make sure that your data is being accurately represented. In other words, do some fact-checking and ask all the tough questions before the big presentation, so you can really flesh out the true story and continue to analyze new pieces of data to make sure your argument or story is well founded or supported.
8. It’s All About the Action!
Is your analytics team delivering actionable insights? Is it addressing all relevant audiences? The team’s work doesn’t stop with the story being compelling or even making the presentation. In business, it’s the Never-Ending Story, so it’s critical to clearly identify and act on the next steps. Analysts who put their passions behind not only in creating the story but also in driving the action afterward are worth their weight in gold.
Too many great insights are left on the table when someone doesn’t take ownership of them and help to drive the agreed-upon actions home.