What is data contextualizing and how to do it?
Let me begin this post with an example. You check out the time spent on a blog post by a user and find that to be 30 minutes. You are deliriously happy that the user has spent so much time reading your work. What if the user had slipped into the kitchen to fix a cup of coffee, and then come back to glance through your post, before moving on to another page? The time spent on the post still shows 30 minutes, though you are not quite sure anymore that it means good news for you, since the user barely read a single line!
This is the crux of my post today. Data is meaningless without context. The data you collect in the above example that of time spent on the web page to be 30 minutes, is misleading because you have not put that figure into a context.
In my experience of interviews with clients and digital marketing teams, I have noted that sales pitches are rarely clinched on data and statistics alone. You have to place them in a context and explain what the numbers mean. Data and numbers simply explain how you have done in the days gone by. It does not throw any light on the days ahead. That is what business owners need to know: the path ahead.
You can shed light on the roadmap ahead only when you draw conclusions from your data and numbers. Take a cue from what a renowned Harvard University professor’s theory: data is of the past; it cannot help you foresee the future. Only by placing the data in a context can you achieve that end.
It is also a fact that business and brand owners often misread data to think that because the numbers are good, or great, it means the work can proceed ahead on autopilot mode! I have known digital marketing teams being shown the door despite excellent statistics of achievement because the client felt that when such numbers are already under the belt, there is no need for a team anymore! You can dispel those ideas only when you tell them what the future holds for the brand, by basing your arguments on the data you have collected and displayed.
You can contextualize data in a simple format, following a few easy steps.
The first one is to introspect and observe. You will pick up nuances about the brand, the products and services, along with buyer psychology and preferences. With this information, you will move to step two. Here you will figure out the questions of ‘why’ and ‘how’. To help you with the answers, you have to rely on data and stats. Compile data to find answers to these questions only. Do not go overboard with the numbers.
Finally, develop a blueprint for the future. This will help you explain to the client what the numbers means for their brand’s future.
What this line of thinking does for you is that you know you are dealing with data, in the context of an equation. Data is not the equation. It is only a part of it. Clients are not irritated because you are throwing them too many numbers without footnotes!
A good example of how data can be useful when placed in context is in the field of content marketing. Most brand and business owners pick up metrics like social media shares, comments, likes, etc. What really works for content marketing teams is the loyalty of the online viewers. How many times does each of them visit in a day or week? Measuring that would mean knowing how many actually care about your content. You can then look to develop your content’s performance on those metrics.
Make no mistake in thinking that I’m undermining the necessity of data! Digital marketing can hardly survive without collecting data. What I’m making a case for is the need to contextualize data. Let it not be meaningless numbers. Inject meaning and the numbers tell their own story. Data alone cannot be the key to your success.
Till next time!