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Tag Archives: Machine Learning

2018 Predictions for the Service Leader: Part 4 – Technology

We surveyed a number of customer service/experience leaders, from many of today’s leading brands, in our community to get their predictions for 2018. Over the coming weeks we will be releasing their thoughts on specific CX topics including customer expectations, channels, operations, technology, use case studies/data, and security/risk.

Click here to catch up on Part 1 – Customer ExpectationsPart 2 – Channels, and Part 3 – Operations.

The fourth installment of this series focuses on thoughts on technology.

• AI will begin to automate tasks for the agent and the customer – however AI will take longer to mature than previously thought, due to data infrastructure not mature enough to fully leverage.
• Companies will begin to shift from handling transaction to personalizing service.
• Digital will continue to experience strong growth, powered by mobile usage.
• Messaging channels will continue to grow social volumes.
• More conversations around the “social ethics” of AI deployment.
• Continued push on technology – moving infrastructure to the cloud.
• Deep/machine learning will play a role in 2018 for brands to meet customers where they are. I think brands are starting to get on board with the concept of machine learning and using data to predict behavior. But deep learning can extend beyond things like chatbots. If a brand can predict what a customer might be looking for, it can tailor content to the customer that allows the customer to self-service, send push notifications, etc.
• Thinking about AI secondarily to the types of use cases and outcomes desired that require it.
• Companies will have to address AI and ML in their strategies for customer acquisition and engagement. 2017 may be seen as a year of hype as lots of new vendors emerge on the scene. Expect consolidation and actual AI/ML deployments to increase in 2018.
• Interest in – and deployment of – customer journey analytics tools will increase, as companies try to identify and solve problems upstream before they occur.
• Strategic enterprise automation (front to back office) will help businesses begin to improve the customer experience, while optimizing back office operations, leading to stronger sales and a better bottom line. Examples include automated machine learning/AI, self help, chatbots/avatars, to RPA and beyond. Continue reading

Intelligent Self-Service: Balancing Support Costs with CSAT

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The following is a guest blog from Coveo

The overwhelming majority of support leaders have recognized that their organizations’ self-service channels are their customers’ most preferred method for getting support (and that assisted service has become something they want to avoid). Customers want to find the answers to their questions independently and conveniently. As such, 97% of companies are investing in improving their customers’ self-service experience in 2017.

Self-service is dramatically more cost effective than other service channels, both in cost per resolution, and because it reduces the overall case load on contact centers. According to TSIA, phone and email support are each well over 100x more expensive per incident than web self-service, while chat costs over 30x more. Read more about that here.

New technologies are making it possible to create an intelligent self-service experience – one that is easy, relevant, and intuitive – that can generate results quickly.

For example, WatchGuard Technologies created an intelligent self-service experience, that improved its case deflection rate from three to 11 percent within only four months.

Customer satisfaction is of utmost importance to WatchGuard. The company provides several customer support options, including a 24/7 call center, and a wide range of online technical resources such as a knowledge base, technical documentation, video tutorials, product datasheets and user forums. However, before implementing an intelligent self-service solution – and despite all their available resources – the self-service capabilities were still falling short. Results from a TSIA Benchmark Review helped them realize that their self-service site was not intuitive to their customers and there was no easy way to search and filter through all the information.

Watch Joanne Miller, Managing Director of Product Training and Publications at WatchGuard Technologies, explain her journey to intelligent self-service in this video.

Making self-service easy.

Your customers expect to be able to find the answers they need with minimal effort. Unifying your content and making it searchable allows them to do so. A unified index consolidates all of your organization’s information from across your entire ecosystem and creates a single hub that puts relevant information at your customer’s’ fingertips. Intelligent search taps into that index to find exactly what is being searched and delivers the answers your customers need, when they need them. Continue reading

The Future of Chat

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The following is a guest blog from Leslie Joseph, Senior Director, Product Marketing at [24]7. For more information about [24]7, visit http://www.247-inc.com/.

Decades ago, the idea of putting a man on the moon seemed like an impossible dream. Yet, in 1969 Apollo 11 became the first manned mission to land on the moon. Fast forward to today, scientists at NASA have explored the surface of Mars and it won’t stop there with planned Mars landings in the 2030s. Technology has a tendency to evolve at neck-breaking speeds, which can make it challenging for businesses to keep up.

The future of enterprise chat is much the same. The technology has been around for years but its capabilities, both for the customer and for the agents, are evolving rapidly.

Forrester Research has stated that chat is quickly rising as the channel of choice among consumers to connect with companies, both in usage terms as well as overall satisfaction. However, consumers now know what qualifies as a great experience on the web, having been exposed to “best in class” experiences from tech giants like Apple and Google, and they expect the same level of service from every business. Consumers expect companies to be smart about addressing their needs, using data to provide intuitive experiences that are out of this world.

There are four key ways in which the chat channel can adapt to the continued advancements in technology and customer experience. Businesses should start preparing by examining four pillars that form the blueprint for the future. Continue reading