Marketing Scientists are Experience Designers, Storytellers, Technologists, Brand Champions, Data Analysts, Experimentalists, Systems Thinkers, and Change Agents, and– to define a few of their work terms.
Have you ever wondered what it takes to be a marketing guru or a scientist in the same field? There’s not a single particular criterion for choosing a person as a marketing expert.
We cannot think beyond advertising a brand and positioning it in the market, in the best possible manner. In fact, the process of marketing involves a lot more than that, if you are true to the trade.
A marketing scientist has to work from the basics, like analyzing data, gather insightful inputs, develop on the retrieved information, and then form a story of a brand that would thrive and establish itself unfailingly.
So, in short, a marketing guru is a multifaceted personality that would require performing different roles at varied points in time based on the work. Marketing is a cumulative result of several bits of the short process plays. The actual role of a marketing scientist differs from organization to organization.
Data Analysts Using Experiments and Data Collation Methods
Every company has its own needs based on the product and/or service they deliver; hence their marketing processes and strategies are bound to vary. Many professionals, who have been working in this field for a very long time, face challenges upright.
In many companies, marketing scientists are given an entire array of disarranged data and they are expected to find something useful for the employers. It might sound a little uncomfortable to beginners, but the vast field of marketing thrives only based on profound research.
The data and numbers should always form a picture in your mind, the instant you lay your eyes on them. As a marketing expert, one should be able to play with them and derive benefactor outcomes for the client company.
This is not at all unprofessional and unreasonable, mind it! You ought to learn to make the head and tail out of scattered information otherwise you aren’t the correct candidate for market research.
So, whenever you are faced with this challenge of confirming business out of the variables, the first thing that you must think of is to look at the data intently, apart from confirming the budget and time.
Creating meaning for Marketing
Sometimes, the data shown is in the form of questionnaires and maps. So one can try to compare and collate the information given, trying to form patterns.
Checking the data for Marketing
The second step is to decipher the errors. Most raw information is filled with irrelevant stuff, which needs to be cleared out. Once, the data is filtered, it becomes easy to relate.
Setting objective for Marketing
In this step, one needs to understand how will be the data useful for his client? What is that the company wishes to derive from the information to suit its business interests?
Once, it is understood about the derivatives of the data and how is it going to benefit the client’s business, goals can be set and presentations made. Building upon the organized information becomes easier than before.
All the above cannot be achieved through any preset programmed software, only a human brain with exceptional analytical capabilities can perform the tasks. Organizing the data and recording the same isn’t a cakewalk.
It requires a lot of mind-boggling while scaling the data and weighing the depth of it. Some of the information might score high while few lay down below the ladder. The remnants are to be cleaned up and the creamy layer ascertains the client’s wannabes.
Few people find the process extremely interesting and get completely immersed in it. While, for others, the work might look like a mountain and boring! Certain software like SPSS, Excel, and CSV are lingua franca for data files but they won’t work everywhere and on all data. So, ultimately the onus lies on you as an adept marketing scientist, who is expected to bring out magic from loads of information collected.
Data Analysis for Marketing Scientists
Analyzing the data is a crucial step in the beginning. Marketing scientists are expected to do so with élan, but sometimes following certain set methodologies like ‘regression and ‘Bayesian’ may not apply to all possible data analysis.
There are certain nuances and minute observations that are noticed only by the researcher but every detail cannot be communicated to the client. However, the major skill of the marketing guru is to formulate understandable data-driven solutions, which will raise the business and gain ROIs.
Advertising solely depends on what is the aim of the business. Who all, your client wishes to touch or influence? What are the most impactful areas and way-outs?
All this can only be determined by the expert in this field who should stress solution-centric analysis rather than stressing prevalent methodologies. ‘Significance testing’ is one way to suggest rough cut-offs from a business standpoint.
Random sampling is used in this process, which does again not fruit able when it comes to surveying research. The significance testing isn’t an independent trial and succumbs to type I error, which accumulates over time.
Eminent statistician George Box stated that ‘all models are wrong but some are useful. Over the course of his distinguished career, he came to the conclusion that not every model is suitable for any exercise.
So, it’s a variable factor and depends solely upon the marketing guru to realize which one to apply where. There are several decisions that a marketing scientist must take based upon his strong intuitive capabilities, which may or may not be viable.
As a responsible client, a company should back up the poor fellow with as many details and background information as possible and shouldn’t just let them loose in the dense forest of numbers.
As a beginner in marketing science, one can rely on semi-automated methods like data mining and predictive analysis but these techniques cannot guarantee results. They can only be used for the perforation of data or making predictions.
There are several decisions and possible outcomes that can be delineated by the marketing scientist at large. Which of them will be benefitting the business most is the cause that should be upheld by both the client and the personnel?