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Imagine, a government that has great strength and ability to explore data was often dizzy looking for data, and so is businesses that rely on data from the government.
Indeed, every time you create a marketing plan, one thing that makes marketing people dizzy is about data. They are always confused, what kind of data they are looking for should be the basis of making the marketing plan. Even if they know what data they should look for, the next question is, where they have to find the data.
Finding data is like looking for needle in a hay. If you just look for it alone, will not be met. But if you use a lot of people as team work to figure, it is easiest to find. So, probably not hard to find but the cost to search for it could be huge (because you need more effort). And the result in that data are not 100 percent accurate. Examples of the most frequently asked by marketers is how to find market share data.
Why was not easy for marketers to seek market share data? Look, 70 percent of the distribution channel (for consumer products) use the traditional channels such as grocery stores, markets, hawkers, and others. This channels are plentiful and its points are scattered everywhere. If you want to perform data collection, it is relatively more difficult and longer than in developed countries. Why ? Well answer this question. Which small traders have sophisticated data? All sales are written into the notebook. Even the hawkers were only recorded on a piece of scrap paper.
In developed countries, most of the retail business already use information technology such as barcode so that the quantity and value of sales was quickly documented. So there's market share data can be quickly known.
Funny thing is, sometimes we find the data we want to be accidental. A marketer ever want to find out how the growth of industrial products that sells. Weeks out of the department, but the results did not exist.
Finally, the answer is found through a newspaper that is willing to be discarded. In the news there is a statement from the government issued a statement that the Value Added Tax (VAT) in the industrial sector grew by 7 percent last year. That is, if it is assumed that products market in grew about 7 percent. Not bad to strengthen the planning, even found it in the garbage!
In the world of marketing research, there are two types of data mining. The first is the data extracted by the sources that are primary. Examples are data from the consumer directly. The second is the data that is extracted from secondary sources. That is, the data obtained from other parties who have been doing data mining. An example is through government offices, banks and others.
Digging through the primary sources of data are relatively much more expensive. You should use the search team to gain large enough data. Conversely, to explore secondary data, you only need a few people to request data. The only question is the credibility of secondary data is often a question.
A problem in extracting data is the honesty of the data subject. Many companies are often low profile when dealing with taxes, but became high profile when it comes to business publications. That is, sales tax reports are shrinked, but when interviewed figures are exaggerated.
On the other hand, there are many business people who lack respect for data. Looking at the marketer's case, what is the real value of the data? If seen how he found the data in the garbage, these data may not be rated high. Another example, many business people see the size of the data from the thickness data reports. The thicker the more expensive. But if only a piece, let alone just one digit, that is getting cheaper. But try to see the process that must be endured for days to find a single figure, perhaps the marketers are willing to spend a million dollars than a lost opportunity that occurs because of the search for data.
With these problems, in the end the marketing people more often use a lot of data when making planning assumptions. Even more extreme, some do not believe the data at all and rely on instinct. However, sometimes instinct is not always true though. The data are actually more aimed at strengthening confidence than an excuse to execute the strategy. But if too many assumptions, it is better to use a strategy that is straightforward.
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