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Keep AI From Feeling Like Sci-Fi With Our Terminology Guide

When the conversation turns to AI, there’s often a Sci-Fi novel’s worth of terminology and jargon that the uninitiated reader has to decode. If you’re looking at using automation for service, then here’s a quick guide to the difference between AI, Machine Learning, and Deep Learning.

Watch Our Webinar with Solvvy here – The Truth About Bots and Intelligent Automation

Artificial Intelligence as a concept has been around since at least the ancient Greeks, who designed some mechanical devices that could be loosely-termed as intelligent. However the term itself is around 60 years old, and the first applicable AI technologies have only just started coming to market in the last few years.

Machine Learning is a more specific subset of AI. It describes machines’ ability to learn from their mistakes and improve over time. A good example of Machine Learning in practice example is the recent Google AI that beat a world champion at Go. The more the AI plays, the better it becomes at spotting patterns and predicting its opponents’ moves.

Deep Learning is a further iteration of machine learning. It describes machine learning algorithms that run on multiple layers, mirroring how our own neurons function. A now common example of deep learning is the way that smart assistants like Alexa or Siri process speech.

Also important is Natural Language Processing. NLP is the ability for a computer program to understand human speech, regardless of slang or dialect. By being able to make sense of written or spoken language in the messy and error-filled ways humans normally express it, AI capabilities become much more applicable to everyday life.

What does this mean for service? Artificial intelligence and intelligent automation can take over existing tasks and create new efficiencies that your organization couldn’t dream of previously. Machine Learning is just one example. By suggesting responses agents can use to common customer queries, a partially-automated system could learn the most effective replies and language for your customer base. Deep learning capabilities should extend to IVR trees, and put an end to the common “Sorry, I didn’t get” response from many systems that currently rely on processing speech. And NLP is crucial for chatbots, and for analytics that look at all of the conversations your agents have across chat, social, and any other text-driven medium.

It’s important to build a solid understanding of these exciting technologies as they become more prevalent and relevant to the service and customer experience sphere. To learn more, listen to our webinar with Solvvy: The Truth About Bots and Intelligent Automation.

How Your Brand Can Master The DTC Experience

Read Our White Paper on the DTC Experience HERE

The Direct-to-Consumer (DTC) revolution is shaking the foundation of retail business. As digital advancements make it even easier to cut out middlemen and deliver totally new kinds of experiences, customers have come to demand DTC brands provide them with the same kind of convenient, personalized and memorable experiences they get from traditional stores. Those that can innovate, adapt, and bring a higher caliber of experience and smarter ways to buy using the vast amount of consumer and product data available will be the ones that succeed. Those that don’t will lag, unable to bring a truly modern experience to their customers.

The time has come to reconnect with your customers and focus on a lifetime of experiences, rather than on optimizing a single, specific journey. Here’s how your brand can communicate and sell directly to your audience today:

Curate collections of essential products for customers

Focus on a few good items done right at a fair price point. This approach is key to tapping into modern shopping trends, encouraging brand loyalty and repeat business by making products that become an essential part of customers’ lives. Huge selections and hundreds of locations are no longer likely to breed success.

Pioneer new models like subscription and shared ownership

Harness the power of digital tech to connect everyone and everything, putting surplus or unused goods to use, and creating experiences that effortlessly sync with our everyday lives. As customers, especially millennials, are willing to buy used or share ownership if it means great savings, consider using tech to implement shared ownership models in your brand practices.

Make delivery and returns easier

As more customers buy online, delivery and returns are becoming even more crucial to the customer experience. Focus on fast delivery and low-friction returns to make up for any hesitation customers might have about buying online. All the more so for large, traditionally hard to ship items.

Deliver personalized, 1-1 service

Adjust every aspect of the online shopping experience to meet customers’ needs, using the latest CRM, machine learning, audience segmentation, and personalization technology to create an immersive digital journey.

By integrating orders, shipments, and conversations, with internal and external customer data,  Kustomer helps brands get a comprehensive and actionable view of all customers, driving informed service decisions.

Want to provide your customer-centric business with a full suite of support channels, smart segmentation and automation tools within a single platform? Download our white paper to learn more.

Kustomer Expands Artificial Intelligence & Machine Learning Offerings

Customer Support technology is evolving fast and can be tough to keep up with. Lots of you have asked us about new technology like AI, bots and more. Today we’re announcing our two first entrants to Kustomer Labs that expands our artificial and machine learning offerings. We’ve been working with both for several months and love what they are doing.

What Is Kustomer Labs?

Kustomer Labs is an internal group here at Kustomer that evaluates the newest cutting edge Support technologies for you. We pick the best ones and offer them as integrations/plugins to the Kustomer platform.

Our goal is to offer our more visionary and adventurous users access to the coolest new things we see. We will collect feedback and determine how we will integrate the Kustomer Labs companies more deeply with Kustomer.

Want to learn more? labs@kustomer.com.

Init.ai: Conversation Intelligence

Training new and existing Support staff is time consuming and expensive. This NY-based company uses cutting edge AI to provide suggested responses, automate routine conversations and analyze interactions at scale for actionable insights.

We introduced them to the team at Sticker Mule who have already signed up and are preparing to go live with them! Team members at Sticker Mule rely on Init.ai to recommend a response or suggest an action that they can then personalize to deliver a consistent, friendly response to their customers.

“Thanks to the Init.ai integration, our team will be able to resolve issues, with fewer back-and-forth questions to the customer,” said Anthony Constantino, CEO, Sticker Mule. “The combination of Init.ai and Kustomer allows us to have a glue between those customer conversations and the data in our CRM.”

Want to learn more? labs@kustomer.com.

Abot Labs: Work Automation

We’ve spent hundreds of hours with Support teams. One of the most common complaints we get is that they want to spend more time interacting with customers and less time on menial tasks like basic response.

Abot Labs is newer to Kustomer Labs. Abot helps businesses and customers save time by making automated help more human. Their AI-powered agent enables companies to meet customer expectations and scale more quickly.

Their technology enables your team to spend less time on the painfully boring questions like Password resets and more time building high quality relationships with customers.

Want to learn more? labs@kustomer.com.

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