T he UK Energy companies are still lagging in the customer care. The Ofgem that regulates the energy market in UK often penalizes companies with poor customer care. Big six companies certainly experienced a lot of it. The smaller players stepped up the game initial by having all their operations online that would reduce the customer inconvenience and issues. They are also facing the same issue, the inability to cope to the volumes of customer query.
A lthough most issues were pertaining to billing issues. It’s usually the estimation of the energy consumption that causes the error if the meter readings are not provided at the regular interval. Issue would be the amount charged during winter season. Other than this there are some normal query regarding the smart meter installation, new meter installation, type of meter, Economy 7, tariff, Power cuts or shutdown to narrow down a few.
Customer care of energy companies still rely on the call center and live chat support which means it’s a one to one play. As energy company gain more customers than the volume of customer care agents there are high chances the volume of customer inflow would overwhelm the agents available. What about the non working hours?
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C hatbots are build to handle customer queries. Most queries have the same answer only the semantics or the slang of the customer words vary. So a chatbot trained with machine learning and RNN can identify and group questions that have similar intent. That would resolve lot of queries in a instant . Grouping questions instead of having them scattered increases the odds of resolution. The chatbot can be trained on the FAQ and previous customer logs to address concerns that are repetitive or easy to resolve. Email support can automated the same way to address repetitive scenarios thereby generating quicker response.
E nergy companies could add submit meter reading, new tariff to the menu part of the chatbot so that it’s easy to send meter reading. Other normal works can be done like to requesting a call back from appropriate department. One of the main inconvenience customers face is being transferred back and forth to different deparment and long waiting hours. By identifying the intent, appropriate department might take a call back or connected with via live chat to address the issue.
Chatbots can also be used on the offensive to showoff new tariff that may be beneficial to the customer. When a customer gets a flawless care experience, then they’re most likely to spread it in their social. It acts as a media for the energy companies.
Chatbots not only makes addressing query easier, it also streamlines query so that the query is handled by the appropriate department. It’s ultimately saves time for the customer and the business.
Instead of seeing customer care as a sparse model that has many queries, it can be seen as a dense model with many query but a similar intent.
Enabling these features would significantly reduce the call or chat volumes to live agents.
Incredible Aspect of having a chatbot is collection of customer data for further analysis thereby enhancing customer care.
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