Good marketing is effective communication. You’re letting people know what you do, what you make, in a way that makes sense to them, feels vital, maintains their attention. Now that big data is in the mix, there’s potential for a ton of noise. The business best able to cull what’s vital from the deluge of data, turn it into information and communicate it loud and clear will ride the landslide of data to success.
Good marketing is effective communication. You’re letting people know what you do, what you make, in a way that makes sense to them, feels vital, maintains their attention. Now that big data is in the mix, there’s potential for a ton of noise. The business best able to cull what’s vital from the deluge of data, turn it into information and communicate it loud and clear will ride the landslide of data to success.
Pulitzer Prize winner Roger Sessions said, “Communication is two-sided – vital and profound communication makes demands also on those who are to receive it… demands in the sense of concentration, of genuine effort to receive what is being communicated.”
The average adult attention span is eight seconds, shorter than that of a goldfish. Marketers make demands on the span. We ask people to pay attention, please do something. We can use big data to make sure we’re not wasting anyone’s eight seconds. The less attention people are capable of paying, the more attention becomes a commodity—the more valuable it becomes. We’ve got to be asking the right questions and making the right demands of the attention span.
Time is valuable, and in a sense big data represents time. The time it takes for a customer to access important technical support information from your homepage. The amount of time a car takes to come to a complete stop with worn out tires on an icy road. When we manage data well, we’re indicating we care about people’s time—we’re showing we care about what the numbers represent.
In order to manage the data and use it effectively, we need software solutions like Hadoop, for which the global market is reportedly growing at around 55 percent. Using Hadoop is like using plumbing instead of manually hauling your water from the well.
But then it’s a matter of what we do with the water. It’s the quality of what we make that counts.
Flipkart is a company focusing in on giving customers quality through their use of big data. They want to simulate the capabilities of the human brain.
They want to turn data into intelligence. Tim Fletcher said, “Transforming big data into intelligence is simply about seeing the existing data in a new and meaningful way to help you strengthen your business, performance, productivity or relationships.” Companies that use data intelligently are 5% more productive, and 6% more profitable, than companies that aren’t data-driven.
In the case of Flipkart, they want to understand what their users want. They’re already the leading shopping app in India. But they won’t sit back, and by asking questions about user experience they are really doing a kind of marketing. The best customer service presents a picture of who you are to the customer. This picture is the one that ends up representing you to the consumer.
That picture Flipkart wants to create is alluring. The human brain is capable of empathy, which means Flipkart’s new model would be simulating empathy for the user. Is it possible? How could computers be capable of understanding how we feel?
Through the use of constant data feedback and advanced programming, a computer wouldn’t actually be able to have empathy, per se—we haven’t figured out how to make synthetic materials have feelings. But it could have a level of understanding that feels like empathy. The Flipkart app is paying so much attention to specific user experience metrics, and harnessing the use of image recognition in such a way, that it very well may feel like you’re walking through the store with a knowledgeable shopping attendant who can answer your questions immediately. And, if the app is using data to communicate effectively, the questions it asks you will never be annoying, leading, or superfluous.
