Chatbot Preparation: Customer Analysis
As the next of the business and service analysis, it is needed to analyze your customer.
Even though it can be done with the analysis of business or service, conceptually, it will be better to separate it to them.

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Customer analysis is based on their demographic data, which means a number of customer, age proportion, sex, address, and so on.
Also, you can use and include additional information you have collected by marketing agreement.
Customer analysis is strongly associated with the business and service analysis.
Actually, the key reason for customer analysis is that it makes you to make a good strategy, consider how to build its architecture or service process, and then forecast a number of chatbot user.

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For example, if an age group of the customer is young, you can offer relatively complicated service with trendy designs, which means that the chatbot can be more functional.
On the other hands, if an age group of the customer is older, you need to focus on easy user interface, experience, and service process.
Additionally, you will be able to make good standards to plan chatbot’s strategy, service type, and its range, if you add more something about your customers’ characteristics, which only you can know or analyze.

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Few companies have fundamental considerations about chabot’s necessity in the long term view.
Because of chatbot is a new technology, I do not recommend a big investment in the initial stage.
Rather, if you are not sure about chatbot, just build it from small things, and enhance it in small and quick. It is generally called ‘Agile Process’
However, when it comes to customer analysis for chatbot, there is unexpected point, which is that you can make a good effect more than expected if you can build the chatbot for the customer not being familiar to ‘Digital’.

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Practically, after the chatbot’s project, old age groups showed positive points about usability and bounce rate, even though its a number of use is not much.
In other words, this situation means that old age groups naturally input something chatbot requests because there is relatively no doubt about chatbot service.
However, the customers being familiar to ‘Digital’ can quickly judge if it is a chatbot or not, and then start to disbelieve it after the judgement.
As its result, its usability and bounce rate are so negative.

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Chatbot Preparation: Customer Analysis
Through the process of customer analysis on the above, finally, it makes you to decide to set-up the standard about service quality for the opening day.
This being so, the customer analysis is one of important factors for chatbot preparation.
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