Step 1
Identified conversation patterns and information flows that help improve wait times and address employee issues in specific cases.
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Retail success story: Multinational beauty company
Agriculture – Sericulture
Partial Information due to Confidentiality Clause
Partial Information due to Confidentiality Clause
How the beauty multinational strengthens employee efficiency by improving the customer service experience with TBBC as their ally
A multinational company with over 50 years of experience in direct sales. Their purpose is to “Drive beauty for personal fulfillment” and they support millions of women in achieving their independence. They have the brands Ésika, L’Bel, and Cyzone.
Challenges
What did the beauty multinational in Colombia want to solve?
To improve the efficiency of the employee orientation call center and reduce costs.
Due to a significant increase in call volume and long wait times in the queue, the company’s HR and financial indicators were negatively affected.
Solutions
TBBC Scope
1. Improve the efficiency of the employee orientation call center.
2. Reduce call wait times in the queue.
3. Optimize processes to decrease operating costs.
Scope
1. Identified conversation patterns and information flows.
2. Developed an artificial intelligence-based system.
3. Developed an IBM Watson-based chatbot.
Step 2
Developed an artificial intelligence-based system that integrates various company tools and knowledge bases to increase efficiency in case resolution.
Step 3
Developed an IBM Watson-based chatbot capable of determining the intention and importance level of a problem to provide automated solutions or transfer the case to a human agent if necessary.
Step 4: Recognition
There is no one who loves pain itself, who seeks after it and wants to have it, simply because it is pain, but because occasionally circumstances occur in which toil and pain can procure him some great pleasure. To take a trivial example, which of us ever undertakes laborious physical exercise.
Our Solution…
Applies to sectors such as:
– Financial
– Banking
– Healthcare
– Retail
