Author: Jenny Parvanova

The Black Hole In Big Data

Posted by in Big Data

Since you are already here, you probably are curious about Big Data’s possibilities and the opportunity it offers for your business. According to Forbes, every new day bears 2.5 quintillions of data. Predictions point out that by 2020, every person online will create around 1.7 MB of new data every second, every day. And how could it be different, when on Google alone, people create more than 40 000 search queries every second. All information you have looked for stays virtually engraved and that is how Big Data is created. And do you know what this information is good for? Consumer behavior.

And, since I believe you are already considering to dive into the sea of Big Data possibilities, stay alert. Our Hitchhiker’s guide in Big Data’s interstellar space will start with a serious but an easy to overcome obstacle. Of course, if you are armed with relevant information.

The black holes in big data

Big Data helps us answer some really important questions – when we define the parameters of our business, it could help us solve the who’s, the what’s and the when’s. There is a parameter that Big Data is helpless to reveal, and, unfortunately, the most important one – the why’s. The data gathered could bring to light some demographic clues of your clients, the products they prefer to buy and the hours and days they are most active in. But, the concrete reason that stays behind the customer’s purchase decision stays unrevealed by Big Data’s numbers. And unless a business has the most detailed picture of consumer behavior, developing a working and successful strategy for influencing the consumers could be a risky business.

How To Understand Consumer Behavior

There is one more factor that forms a black hole into Big Data. It could be presented as a complementary one because while it frequently matches the Why’s, they do not axiomatically replace each other. The why isn’t always emotional, it could be a product of rational decision. When a person visits an Apple store, they can buy an iPhone 7 because its technical characteristics are decent and they will exploit its possibilities in fullest (a rational decision); because everybody else has it (imitative behavior and need of belonging to certain community) and because it’s pretty in Rose Gold (that’s me!).  While here we have three potential scenarios, only the last one is an emotional factor. But marketers need to follow up all three and more of them (because they are more) and to project onto them their potential buyer personas.

business-analytics

Big Data itself doesn’t give answers. It provides the context to solve your marketing riddle. The fact that 39% of you website’s visitors are women from 31 to 45 is significant but still, doesn’t show enough about your shopper’s behavior. It could not inform you about the meaning of your brand to them, their attachment to your product/ service and the reason for it – because of design, functionality or any other trait. And this is crucial for your marketer strategy.

It is more like a rule than an exception, that big data practitioners and experts do not take into account the emotional factor when they discuss experience and engagement metrics. The e-word usage and understanding is much needed because it could strengthen (or even build) contextual frame that is so necessary to understand consumer behavior in its more complex and full appearance.

Failing to read and understand the map of emotions, the accurate big data could give clues but not a chance to reach the final destination of success and continuously attracted customers. The big question that will get you to the top is “Why client X will go back to my page?” and this is where the e-word blends facts with perceptions. This is how we should handle the e-black hole of big data.

The fail of exploiting the full potential of big data could lead to a disastrous scenario. Incorrect reading of big data’s clues results in irrelevant ads and positioning which is just a waste of money, missed opportunities, ruined brand image and loss of potential clients. I don’t try to undermine the value and role of big data in building brand image and properly based customer segmentation and targeting. Big Data has so many advantages over the survey gathered data – it expands the focus to a much larger target audience, it is definitely less error prone and it gives immediate results much faster because it doesn’t need to be input into systems, encoded and afterward analyzed. Unfortunately, a business cannot count on Big Data only in order to boost its image and results.

Consumer behavior

In order to formulate your business priorities correctly, to create the right buyer personas and develop your market and business strategies in a winning manner, there is one must-do rule –   establish a complex and systematic whole picture that blends both big data’s opportunities with customer’s emotional experiences. It turns out that the good old survey methods are not so out-of-date and could add influential nuances to the whole picture. The opinion research methods, such as focus groups or survey panels could provide rewarding contextual info of consumer behavior. Only via enriching our methodology palette we could fill in the Big Data holes.

Aside from using surveys and other techniques and methods that will give us clues to the Why’s of Big Data, segmentation remains crucial to your product’s success. Here comes the role of Adtailor’s service that can help you navigate into the interstellar space of Big Data and make information your ally.

What else could you do?

Bring in as many employees as possible into Big Data’s possibilities

If you concentrate Big Data’s functionality into one central team, the process of disseminating the info gathered could take time and nowadays, coming up late is not an option.

Use data with enthusiasm

Big Data is more than information, it is a tool that could be transformed and utilized in various ways depending on context, ideas, and priorities. In order to exploit its potential and maximize its benefits, you must squeeze off all of Big Data’s opportunities. Using as much APIs as possible and decode the information they give you regarding the particular business targets you put could be a big advantage of your product.

Quality does matter. But so does speed, so, don’t look only for amount and results, take your chronometers and do it ASAP.

Considering the fact that Big Data is practically alive – most of it, around 90% is created in the last 2 years, and also the idea that amounts of data disappear as fast as they’re generated, one must be quick and adaptive in the acquisition, learning and exploitation of Big Data. Quantity, quality, and speed are the three variables that must be maximized if you want to boost your business to the top.

When we talk about marketing strategy, the key word here is holistic because those brands that incorporate and integrate as many ways of analyzing information and data sources will have the greatest growth opportunities. Systems must be viewed as a whole, not as its forming parts. And there is no element, not even the most detailed and complex one, as Big Data could weight more than a complex method that incorporates it. As Aristotle confirmed, “The whole is more than the sum of its parts”. To ensure its companies, researchers must not oppose different methods but need to look for the best recipe to incorporate them all into their business strategy.