Utilizing big data is now common among many advanced enterprises.
The word “big data” contains image data, movie data, sales data and so on, but they can be classified into 2 types; quantitative data and qualitative data.
So far in the marketing site, mainly quantitative data has been focused on.
However, qualitative data is now beginning to have more important implications.
For example, in convenience-store chain, analyzing quantitative data tells; when and where the products are bought, who bought them ,and what are bought through the numeric volume.
Furthermore, analyzing sales data allows you to do Market Basket Analysis and find out purchasing behavior.
However, analyzing quantitative data by itself has the limitation, namely, ‘the reason’ WHY?
- Why is this product popular?
- Why is that service unpopular?
Then, how can we break the limitation?
The key is Voice of Customer, Voice Of the Customers, such as enquiries, free comments in surveys and SNS data.
Many hints to improve your product and services are contained in the abundance of text data.
Another limitation lies here; how can we handle such an abundance of text? It takes tremendous man-power to read Voice of Customer one by one.
In this time, here is another key solution called Text Mining technology.
Text Mining can help you “strike” a benefitting words.
Text mining literally means to mine the data for text based patterns.
Analyzing and examining consumer behaviors, preferences, and trends can lead to higher conversions, better margins and happier customers.
And in the marketing world, that is as good as striking gold!
Now, the important point for company is “How this can help?”.
Through text mining, you can easily find out the way (how and what) your customers think about your products and services.
Here is an example.
If you are a marketer of cosmetics and use the text mining technology to analyze opinions of the customers that have been submitted to the Customer Service Office, you can find out the words which are characteristically used like “skin” “scent” “effect”.
Plus, through dependency-relations analysis, you can find out both positive opinions such as “good – affect”, “moist – skin” and negative opinions such as “skin – tingling”, “smell – bad”.
If many of them saying “smell – bad”, text mining gives you further details as follows, “Do not like the oily smell”, “The smell that remains after wiping is bad”.
As you may already noticed, Voice of Customer contains numerous hints to improve the products qualities and promotion strategies.
Get the higher conversions !
Using text-mining tools, such as Mieruka Engine, we can automate the analyzation of the qualitative data, and give you further insight as to the real reasons why the product sales are good or not.
Combining this qualitative insight with the quantitative data findings, you are be able to get a fuller picture of your customers. You will quickly soar above the wall to the higher conversions, and make your customers happier.