How to REALLY make actionable data really actionable

Actionable data is a buzzword that seems to get tossed around casually in job descriptions and team meetings all the time. But what is actionable data? And how do you use it … really? Data points in and of themselves simply point to action, growth, activity, or tasks completed. On their own, they only tell you what is happening. Not why. Actionable data transforms those data points into something you can use to guide your business strategy and make good decisions. Your data should track more than activity. It should reveal the causes, motivations, and psyches that guide behavior so you can adapt your business to meet your customers’ needs. Now, we’re going to tell you how to do that.

Actionable data hinges on choosing your KPIs wisely

Before you begin setting up data tracking tools and collecting information, ask yourself what you are tracking and why. Start by reviewing your business goals and choosing KPIs that relate to those metrics. Don’t focus on data that simply shows activity. Instead, focus on data that relates directly back to your goals. If you want to increase sales or customer satisfaction, consider what data might be an indication for sales or engagement success. Once you’ve picked a few metrics, confirm your choice with the following two question test: 1. If this metric were to dramatically increase or decrease, would the business care or feel a sense of urgency about this change? 2. If so, what types of action would you do in response? If you can’t answer those two questions, or the answers suggest the metric you chose is more of an activity tracker than a business indicator, don’t bother charting it. We can help you figure that stuff out.

Don’t confuse correlation with causality

To act intelligently in response to your findings, you need to be certain that the data you’re collecting shows causality – rather than correlation – to a business metric. For example, imagine that an electronics retailer began running two advertising campaigns: one online and one offline. Their goal was to determine whether their customers responded best to online versus offline advertising. Assume they had enough budget to run two ads in major newspapers, so they ran a promotion before Black Friday and around Father’s Day to appeal to holiday shoppers. The return on their investment was fantastic. Online, their budget allowed for digital ads every other week, but not on specific geographic or demographic targeting. The return on that investment was significantly less. The fact that their holiday newspaper ads outperformed their “spray and pray” online banners doesn’t show causality between amazing sales and newspaper advertisements. The cause was seasonality … not advertising channel. If, for example, that same company invested their entire budget in newspaper sales expecting the same return on investment week over week that they enjoyed before Black Friday, they would be sorely disappointed. Avoid this pitfall by doing a gut check on whether your data can point to an actual cause.

Timing is everything for actionable data

Good data doesn’t simply reveal what happened to your business. It can also help you predict what might happen in the future. Good forecasting can support your budgeting, planning, cash flow, pricing, promotion, and resourcing strategy. So yes, basically everything. This is why establishing causality between different variables is so important. Knowing that certain metrics influence other outcomes can help you prepare for likely impacts as variables change or work toward influencing driving behaviors. It is also important to deliver these forecasts with enough time to act or affect change. They say that hindsight is 20/20, but it doesn’t change your bottom line. Sync your forecasting and analysis around your natural business planning and work cycles. Telling your web team that they need to update your landing pages in a week, when you know that they work on monthly planning cycles, does not set yourself up for success.

Pay attention to the competition

While you might not have access to your competitors’ revenue and sales information on a granular level, you can easily track their social sentiment, media placement, reach, broad web metrics (such as visitor volume), and third party content about the brand. Some of these insights may be quantitative in nature, such as trending sentiment or page visits. However, competitors’ qualitative data can be an extremely useful tool as well. This is especially true if you want to increase your share of the market or focus on competitive switching. Qualitative data, in particular, can reveal how your competition’s customer service performs, what products customer want, what features give you an edge, or how you can serve your target audience differently.

Make your actionable data easy to digest

Once you’ve uncovered some great insights and establish some ideas about how to impact your business, you need to package your data – aka your proof – in a way that is digestible and contextual. Realize that senior-level audiences may not want to see all the hard work you did to get to your forecast or dig into the nitty gritty details of your data mining. Showing that you did a lot research doesn’t prove that you are right. Showing critical data and putting it in context against your business drivers does. Generally speaking, your decision makers will want to see concise, consolidated readouts that show what’s happening and why it matters. The people who can analyze and use data to its fullest advantage are not always the best people to translate that into “business speak.” Sometimes they are. But if they aren’t, team up with the right individuals to make sure your findings are presented in a context that is easy to understand and that inspires meaningful change. And yes, that means all those amazing Excel charts might not be your smoking gun. There’s a reason that data-driven decisions are so popular: they reduce risk and increase the likelihood of success. Increase your ability to use data by focusing on insights and actions first.

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