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Zendesk Utilising Machine Learning to Predict Customer Queries

Adrian McDermott, Zendesk’s president of product, is convinced that artificial intelligence (AI) and machine learning are set to have a radical impact, particularly on enterprise software and the changes are already taking effect at a worrisome pace.

He also argued that a lot of what enterprise software systems do is not only somewhat repetitive but can also be enhanced through machines.

McDermott said to Which-50 at Zendesk ’s local user conference held in Melbourne that the company was gradually but certainly considering each aspect of its product and thinking about how it can leverage AI in a move to make it better. He added that most software companies including Zendesk are currently facing a similar obstacle, how all developers will have to know how to create a machine learning model.

Zendesk was established in 2007 to create customer service software. Currently, it boasts over 7,200 paid customer accounts in Australia as well as a research and development center located in Melbourne that works on incorporating machine learning into its products.

The company launched its first ML product back in 2015 dubbed Satisfaction Prediction. This feature projects the likelihood of a ticket to be resolved with a negative or positive outcome based on the analysis of all the customer support tickets that a company receives.

Zendesk has also leverage ML in powering a feature dubbed Answer Bot, which helps in matching customer questions to help desk articles with the objective of resolving the problems without an agent’s involvement.

With that, the machine can spot the recurring customer queries across the system and recommend suitable content that ought to be included in the knowledge base.

Thinking like a Growth Marketer

AI will also be used in making customer support increasingly predictive as opposed to waiting for a customer to initiate contact when something does not work out. McDermott said that customer support requires embracing a growth marketing mindset in a bid to anticipate customer requirements and offer a better overall experience.

According to McDermott, one of Zendesk’s hypothesis is that its buyer is getting more of the customer journey and becoming increasingly sophisticated. He added that buyers have a right to receive the same technology that the most complex growth marketers are utilizing.

For this reason, Zendesk bought Outbound io, a marketing automation firm, back in 2017. The product has been rebranded Zendesk Connect, which is a proactive messaging tool that enables support experts to build dynamic customer segments for all previous customer interactions.

Changing Client Base

In 2014, Zendesk went public with a yearly run rate of a whopping $100 million. In the past four years, the annual revenue rate has risen to $500 million. This figure puts the company halfway to its objective of hitting $1 billion by 2020.

McDermott claimed that the changing customer base has come about in two different ways whereby one stems from existing clients scaled rapidly while the other through targeting enterprises deliberately.

He went ahead to say that Zendesk signed up numerous customers who grew significantly. In fact, individuals who registered with three agents rose to become 10,000 agent customers. For that reason, the company is proud of creating a product that scaled to such use cases and grew with them.

Source Which50

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KC Cheung
KC Cheung
KC Cheung has over 18 years experience in the technology industry including media, payments, and software and has a keen interest in artificial intelligence, machine learning, deep learning, neural networks and its applications in business. Over the years he has worked with some of the leading technology companies, building and growing dynamic teams in a fast moving international environment.
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