MANILA, March 20, 2014 – In the developing era of big data marketing, people in this industry will have to adapt to specific methodologies for analyzing and filtering tons information to deliver goods to consumers. Indeed, Amazon is already doing this with their anticipatory shipping patent geared toward selling people products before they even know they want them.
The thinking heads in every business’ marketing department are now looking for the best and latest tool, algorithm, or agency that can yield those data to use as the foundation for their marketing strategies.
The attraction of obtaining this kind of an advantage is so riveting that companies dive right into the process without assessing their own resources with regard to meaningfully interpreting these data. One key obstacle that needs to be hurdled by the Leo Burnetts of our time is perhaps counter-intuitive: they should learn not to trust their own judgment.
Rise of the “Little Data”
In a Bloomberg “Business Week” article by Drake Bennet, the writer featured ReD Associates, a consultancy firm that practices what he calls “little data.” The firm uses a small sample of data that are discussed by highly qualified individuals resulting in subjective information they transmit to their clients. This deviates from the normal practice of using large amounts of data being employed by firms.
The firm uses sociological concepts to come up with solutions that benefit their clients. Does this approach work? Intel and Samsung think so. The brainstorming process involved employs philosophical concepts such as phenomenology and hermeneutics to find out what customers consider invaluable. These concepts, normally confined in classrooms and ivory towers, clearly have some practical uses. Liberal arts students have at least one thing going for them after all.
A considerable amount has been written regarding the practicality of these concepts in marketing. These studies emphasize that marketers should not just observe the everyday lives of consumers, but immerse themselves in the experience of the same people they are trying to sell products to.
One such approach to understanding human experience is phenomenology, generally described as the study of structures of consciousness as experienced in the first-person point of view. In a literal sense, it is the study of phenomena, the study of the meaning of the things around us as they equate with our day to day experiences. This core concept—finding meaning of the world in our daily experience—is what ReD Associates espouses.
Applying Phenomenology to Marketing
Interpreting phenomena using this approach is purely subjective. For that reason, it has its critics in the field of sociology, which is to be expected, given the often inflated egos of these academics. To block out some of these critics’ voices, a methodology has been formulated to embed objectivity into findings based on the interpretation of experiences.
The steps of this phenomenological method include the following:
- Identification of shared experience;
- Bracketing of bias and expectations;
- Collecting data; and
- Location of the universal nature of an experience.
To visualize the process better, here’s a practical day-to-day example of an experience.
When a person buys a new mobile smartphone, one that is neatly packaged in a compact and stylish box, the possession of this object gives him a feeling of sophistication. This is an experience that is shared by many consumers of these products.
Evidence of this is found in the hundreds of YouTube videos showing some guy unboxing his latest gadget. The feel of the phone in the hands, the sleek design that catches the eyes, even the smell of the printed manual is an experience shared by everyone who buys a new, state-of-the-art smartphone. An acknowledgement of the visceral reality of this experience is the first step toward assessing situations using phenomenology.
The second step in this method is to suspend (Note: not eliminate) a person’s biases and expectations from the experience under examination. By unboxing the phone, one cannot help but expect to experience a satisfying feeling out of that one simple act of taking the phone from the box.
But there can be anxiety that arises from thinking whether the purchaser can sustain the monthly bills that are an inevitable consequence of the acquisition of the phone, or the vexing question of whether it is worth the price that was paid for it. There could also be a feeling by the purchaser that he’s been let down because the phone may not live up to his expectations. All these potential prejudices should be bracketed and suspended from the initial interpretation—satisfaction—to avoid any research biases.
When the possible shared experiences are identified, and once biases and expectations are suspended, the next step is to collect the data. These are qualitative data that are now presumably free from research prejudices. Excitement, a sense of accomplishment, and pride of owning this gadget would now be some of the feelings one might experience when bringing home a new smartphone. We then reduce all these feelings to their essence, which is the last step of the method.
All these feelings share a common theme that can be summed up in one essential experience or feeling if you will. Let us say for argument’s sake that this feeling is happiness. A person is happy to own the latest gadget for a handful of reasons. It can be because he considers it as a reward to himself for doing well in his job, or that he can finally afford one after months of saving up. The experience of happiness may be a universal concept at its core. But it has a different meaning for each person who experiences it.
Employ Quantitative and Qualitative Data
The fundamental message of marketing is to know what people want and then give it to them. In the example above, people want to feel gratified and above all happy after accomplishing or purchasing something. Based on this premise, it becomes the marketer’s role to let people experience those things through the products they offer.
Simply relying on a sea of data to gain more insight into the consumer’s experiences and the meanings attached to those experiences likely will not be sufficient. The fact that we are dealing with feelings and experiences will not be reflected in reams of statistical figures, at least not yet.
It is possible that algorithms employed in some studies in this area will become more sophisticated and shrewdly predictive in the future, especially when it comes to predicting consumer behavior accurately. This could make the jobs of marketers, whose task is to correctly analyze and interpret the data, even easier.
The on thing that most proponents of big data marketing do not account for, however, is that people are continuously malleable. They can also change and can change without warning. A key example: witness the difficulty that youth-oriented clothing stores and boutiques experience in predicting ephemeral and often short term fashions—fashions that can be out of fashion within hours or days of restocking store shelves with supposedly trendy—but now suddenly passé new merchandise.
Clearly, culture and perspectives do change and what is reflected in the gathered data should not be the sole basis of the marketing strategy to be formulated. On the other hand, subjective analysis will remain important because the areas of study always involve people—people who still retain the capacity to feel genuine, spontaneous emotions in their daily experiences—emotions that more than anything else, can intimately link with the purchase decision.Click here for reuse options!
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