Semantic solutions: Categorizer | Summarizer | Comparator | Spell Checker | QAS
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User Case

One of our partners is a MLM cosmetics company. Thus, Sales-representatives are the main source to find out about customers preferences. They make presentations for people, tell about their cosmetics and sell it.

According to their Marketing the Sales should write a weekly report with customer feedbacks and sent it to the Head Office.

With the company growth it became hard for the Marketing Department to handle all the feedbacks.

"Our issue was to take the reports with feedbacks and classify them by groups: negative, positive, wishes and problems. We served the reports out to the specialists who were in charge of this information processing. However, we didn’t have the possibility to process the information because of the large reports quantity. Automatic systems which we used didn’t solve our problem completely. Either these systems were too difficult to install and set up or they showed too low effectiveness percentage. So, to be short, lots of the documents remained unprocessed".

EffectiveSoft specialists analyzed the problem and found out that the low automatic tools effectiveness was caused by following factors:

  • the reports were written in free style
  • there were spelling mistakes
  • every sales- representatives used different stylistic terms
  • different file formats

Their Sales-representatives were recommended to use the semantic documents categorizer – Intellexer Categorizer SDK in order not to change the established document management process.

"This solution is easy to set up and cheap to use. All that we should do is to create a catalogue structure and select for every category some etalon documents. Then the program works automatically. For example, to part necessary reports and unnecessary (without any customer feedback) we create 2 categories and take 2 etalon documents – with and without feedbacks. First document will be an etalon fingerprint for the first category and the second one is for the second fingerprint. Click Update and all our documents are sorted by 2 groups. Now to learn the customer attitude to our products we should take 2 reports with positive and negative feedbacks. They will be the etalon documents. Click Update and get the result: negative feedbacks are few. But we also must learn them and take necessary steps to improve the quality of our products."

The solution is easy to setup. Generally speaking the customer may use Intellexer Categorizer for any issue.

"We discovered a new possibility to lead analytical researches based on a large amount of reports. For example, some cosmetics components may cause an allergic reaction. We need to learn how strong our customers can be subjected to the allergy. So, we take the document, describing all the possible allergic symptoms and using Intellexer Categorizer find all the documents with any information about the disease. As a result we recieve only few cases of individual intolerance. Thus, we can launch the production of a new cosmetics line but with the notice on the package about the possibility of occasional complications."

Andrew, Director of Marketing