Five Steps to Strategically Choose AI For Customer Service

AI and customer service; it’s a hot topic! But when I talk to customers, they say, “I get there’s something to AI and customer service, but how do I deliver business results and value with AI?” If you are wondering how AI can move the needle on the metrics you get measured on every day, below is a short guide on how to get the best business results when considering AI as part of your Customer Service strategy.

Step 1: Focus AI on Metrics that Matter
Implementing technology without strategy makes us do the wrong things faster! Or at the very least, spend a lot of money without getting business results. Studies show while 80% of executives want to use AI in their business, only 20% have an actual strategy. (1) First step? List the strategic metrics you are measured on every day and then think about how AI can help you to:

    • Reduce call volume (call deflection via satisfying self-service)
    • Increase First Contact Resolution (FCR)
    • Reduce Average Handle Time (AHT)
    • Increase agent productivity, morale, retention (reduce attrition costs)
    • Improve CSAT, NPS, customer lifetime value (CLV)…

With that information, you can begin to strategically decide how to use AI to transform your customer service operations and KPIs, positively impact customer and agent experiences and directly affect your bottom-line.

Step Two: Closely Compare AI Solutions
Artificial Intelligence isn’t new, so what is? Exponential advances in AI capabilities, as well as, integrated and packaged AI solutions. These new capabilities are allowing AI to become a real business asset, but not all AI solutions are created equal. A classical approach to AI requires specialized teams of:

    • Data Scientists (to sample data, build the models, tune them for accuracy)
    • App Developers (to build it into the customer service application)
    • UX Designers (to make the interface to the AI user-friendly)

These dedicated resources are expensive and difficult to find. And AI development is not the core business focus of a contact center. The result? Wasted time and money and longer time-to-value. When choosing an AI solution, look to see how much work is required on your end to implement a solution. To make AI intelligent, all systems require some work. The question to consider is how business/user-friendly is the application? Do you need to hire a team of AI and UX specialists to get benefits in customer service? Or can you deploy the AI quickly and get back to focusing your efforts on delivering amazing agent/customer engagement?

Step 3: Consider an Integrated Solution
Data. Data. Data. AI is all about the data. So, consider where the data in customer service resides. The customer record data lives inside the CRM platform. And the customer interaction history lives inside the customer service application. Since AI is only as good as the data it interacts with, look for an “AI-inside” solution; one where the AI is built into the CRM platform and the customer service application.

And it’s even better if the same AI solution is also integrated into other applications that Sales, Marketing, E-commerce and other parts of your business. The more contextual, historical information about that customer across all your departments, the more intelligent the AI is and the better business results it can provide. With an integrated AI solution that’s built for business users, there is no need for specialized implementation teams because the:

      • Data is already prepped
      • Models are automatically built and
      • AI is already integrated into the CRM platform and the customer service application.

What does this mean to you? Faster time-to-value. With an integrated solution, AI can easily learn from the customer data to deliver contextual customer/agent answers. So, whether you are delivering self-service or agent-assisted service, intelligent AI service is satisfying service.

Step 4: Select an Agile Solution
How many times have you wanted to change something in your customer service application, but don’t because it’s so difficult — even though it would transform the agent/customer experience? This is where using an agile platform and application leads to faster, better business results.

As you are considering adding AI, ask yourself, “How quickly/easy is it to make changes to the AI solution, as well as to the agent and self-service application?” Look for a drag and drop integration layer that allows for easy configuration of process flows to set up customer service AI. This way AI isn’t some futuristic “ideal” that sounds good when you say it fast but in reality, it takes forever to drive business results. Consider choosing an integrated AI customer service platform/application that is agile – so you can make changes on the fly to quickly deliver on the brand promise of great customer experiences.

Step 5: Use a Solution with a Pre-built UI/UX
And while this step is listed last, it may be one of the most important. Why? New technology often becomes “shelfware,” i.e., technology that is owned or licensed but not utilized because it’s difficult to implement, use or change.

A solution with a prebuilt UI/UX interface makes the customer-facing interaction intuitive, which builds trust, so customers use it. The last thing you want is a throwback to “bots of yesteryear” that didn’t have the advantage of AI or a poor user-interface. If customers can get their answers using a bot, call and email volume will be reduced, while delivering a great experience.

And for the agent? Key to great service is empowering agents with the best possible tools. AI integrated into the agent desktop and console classifies cases and identifies key information needed to serve the customer even before the agent gets the case. And then enables the agent with the best possible next actions. AI is not meant to replace agents, it’s meant to empower them to deliver exceptional customer service.

The most important thing to take away? When considering AI for customer service, focus on what you do best, delivering great experiences. Avoid choosing systems that require you to become or hire a bunch of rocket scientists. Choose a solution designed to allow customers to easily get the answers they need on their own, your agents to intelligently engage with customers and for you to deliver business results that matter.

References:
Is Your Business Ready for Artificial Intelligence? MIT Sloan and BCG Study, 2017
https://www.bcg.com/Images/Reshaping%20Business%20with%20Artificial%20Intelligence_tcm30-177882.pdf

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Facebook’s Artificial Intelligence Has The Ability to Search Photos by Content

The term artificial intelligence was coined 60 year ago. But now its starting to deliver. Lumos’s computer vision platform was initially used to improve the experience for visually impaired members of the Facebook community. Lumos is now powering image content search for all users. What does this means to you? You can now search for images on Facebook with key words that describe the contents of a photo, rather than being limited by tags and captions.

How does this work? It starts with the huge task of computational training. For the object recognition used in Facebook’s image search, the artificial intelligence (AI) system started with a small set of 130,000 public photos shared on Facebook. Using the annotated photos the system could learn which pixel patterns correspond to particular subjects. It then went on to use the tens of millions of photos on Facebook. So what this means is that the caption-reading technology trained a deep neural network though public photos shared on Facebook. The model essentially matches search descriptors to features pulled from photos with some degree of probability. You can now search for photos based on Facebook AI’s assessment of their content, not just based on how humans happened to describe the photos with text when they posted them.

How could this be used? Say you were searching on a dress you really liked in a video. Using the search it could be related back to something on Marketplace or even connect you directly with an ad-partner to improve customer experiences while keeping revenue growth afloat. So it seems it can help both customers, customer experience and companies selling things as well as ad partners.

What else is new? Facebook released the text-to-speech tool last April for visually impaired users so they could use the tools to understand the contents of photos. Then, the system could tell you that a photo involved a stage and lights, but it wasn’t very good at relating actions to objects. But now the Facebook team has improved that painstakingly labeling 130,000 photos pulled from the platform. Facebook trained a computer vision model to identify 12 actions happening in the photos. So for instance, instead of just hearing it was “a stage,” the blind person would hear “people playing instruments” or “people dancing on a stage” or “people walking” or “people riding horses.” This provides contextually relevancy that was before not possible.

You could imagine one day being able to upload a photo of your morning bagel and this technology could identify the nutritional value of that bagel because we were able to detect, segment, and identify what was in the picture.

So it seems the race is on for services not just for image recognition, but speech recognition, machine-driven translation, natural language understanding, and more. What’s your favorite AI vendor?

@Drnatalie, VP, Program Executive, Salesforce ITC

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Has The Age of George Jetson IoT Time Come? Alex Was the Star of CES

Alexa Voice Service (AVS) is the software that allows owners to control compatible devices with their voice. From the various  reports it was estimated there were 700–1,100 Alexa-controllable products at CES. And the Amazon / Alexa logo was everywhere at CES.

Is the Age of George Jetson here? In a smart home, everything from the the HVAC to the TV to window shades can be controlled. However it’s not easy to really have a whole house of Artificial Intelligence (AI) controlled devices. Why? Many of the IoT-enabled devices don’t talk to other devices if they are made by different manufacturers. Opps! The IoT world awaits THE killer app, like Apple Homekit or Google Home. We are still waiting for them to provide all encompassing, unified smart “home.”

The Amazon Echo is a hands-free speaker controlled with your voice. It connects to the Alexa Voice Service to provide information, news, play music, report on sports scores, deliver weather reports… The uses for AVS and Alexa are limited only by your imagination.

When something is connected to Alexa, the device instantly becomes pseudo-interoperable. Interoperable technology is not an evolutionarily stable strategy for most IoT manufacturers. Interoperability is the ability of different information technology systems and software applications to communicate, exchange data, and use the information that has been exchanged to do something.

What CES showed us is that voice control seems to be the unifying app for IoT. And Alexa is the biggest name in voice control. Smart devices are generally controlled with apps. If there is an app to control the smart device, the app allows AVS to directly control the smart device. So you could say, “Alexa, tell Crestron I’d like to turn the lights on in the bedroom” (for your Crestron) or “Alexa, I would like to turn the heat on the downstairs thermostat to 70 degrees” (for your Iris Smart Home System). It’s easy to see the value of voice control in so many ordinary situations. What’s interesting about AVS is that even though Crestron and Iris have nothing to do with one another, you can control them both with your voice.

Alexa has finely tuned automatic speech recognition (ASR) and natural language understanding (NLU) engines that recognize and respond to voice requests instantly. Alexa is always getting smarter with new capabilities and services through machine learning, regular API updates, feature launches, and custom skills from the Alexa Skills Kit (ASK.) The AVS API  is a programming language agnostic service that makes it easy to integrate Alexa into your devices, services, and applications. And it’s free.

And you can create meaningful user experiences for an endless variety of use cases with Alexa Voice Service (AVS); Amazon’s intelligent voice recognition and natural language understanding service. AVS includes a full range of features, including smart home control, streaming music content, news, timers… and can be added to any connected device that has a microphone and speaker.

But while Alexa has a head start, Google Home, an Echo competitor, is very likely to quickly catch up. Google Home though, works with a completely different set of protocols and has different “awake” words. These are command words that make it pay attention and carry out the request. It seems that we may need to learn to speak to different systems in different ways – perhaps we’ll need lessons in Alexa speak and Google speak as well as and Siri and Cortana speak!

So is the Age of George Jetson here yet? Sort of. What will be interesting is to see if there is a start-up that will pull all of this together so that us regular humans don’t need to become AI experts to connect and use the technology.

Dr. Natalie Petouhoff, VP and Principal Analyst, Constellation Research

Covering customer-facing applications

 

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Capgemini Collaborates with Celaton on Artificial Intelligence in the Cloud

What’s the Partnership Between Capgemini And Celaton Mean to Your Company? Capgemini, consulting, technology and outsourcing services, has announced a new global collaboration with Celaton, a specialist Artificial Intelligence (AI) company, to license and use its inSTREAM, cognitive learning technology. The 3 year contract, signed between Capgemini and Celaton, will extend Capgemini’s already strong automation capabilities, help to drive further efficiencies and add Artificial Intelligence to Capgemini’s Business Services solution portfolio.

What Does Celaton’s inSTREAM Software Do? It streamlines the handling of unstructured unpredictable (and structured) content such as correspondence, claims, complaints and invoices that organizations receive by email, social media, fax and paper. This minimizes the need for human intervention and ensures that only accurate, relevant and structured data enters business systems. Unique to inSTREAM is its ability to learn through the natural consequence of processing information and collaborating with people. Capgemini’s extensive knowledge and experience in business process services will also enable Celaton to accelerate and improve inSTREAM’s capabilities.

What Will The Partnership Provide For Clients? The cooperation will enable Capgemini to increase efficiency, shorten turnaround times and enhance quality in areas where incoming documents and queries need to be processed, improving overall customer satisfaction. At a time when more and more customers expect the use of AI and modern automation tools, the alliance will help Capgemini’s Business Services advance their market leading use of automation and AI for its core business. Earlier this year, Capgemini introduced an Autonomic Platform-as-a-Service (PaaS) offering founded on best of breed technologies to deliver intelligent automation solutions on-demand for enterprises. The Autonomic PaaS aims to improve the predictability of organizations’ operations across their infrastructure, applications and business processes. The Celaton agreement is a further commitment from Capgemini to develop advanced client solutions using intelligent automation, cognitive and AI technologies.

Is This Offered in a SaaS or Cloud Mode? The addition of Celaton inSTREAM expands Capgemini’s Business Services’ extensive Software-as-a-Service (SaaS) portfolio with an artificial intelligence-based processing solution for incoming unstructured content –which is driven by its global automation Centers of Excellence. It is an important element in ensuring the delivery of maximum value to its customers.

Notes From The Executives: Lee Beardmore, VP and Capgemini’s Business Services Chief Technology Officer said, “There is significant industry debate on how cognitive computing and artificial intelligence will impact the BPO market. We are taking our delivery from debate to global implementation and are proud to partner with Celaton as a leading vendor in the business process AI space. Building on the introduction of Capgemini’s Autonomic Platform-as-a-Service, Celaton’s technology extends the penetration of cognitive computing into our delivery of business process services.”

Andrew Anderson, CEO of Celaton said, “I am delighted that Celaton and Capgemini have committed to this global partnership. The transformational impact of AI has been proven with many organizations and yet this emerging technology is often greeted with scepticism. Capgemini’s global reach and credibility will have an impact on the perception and adoption of AI and I’m very excited that Capgemini’s customers will soon be able to realize its significant benefits.”

My POV: AI is very important to the emerging capabilities of company’s to add cognitive computing into the delivery of business processes of discerning unstructured content. And with social and digital content abounding, there is no storage of unstructured content. And there is unlimited potential in the value of this unstructured content if it can be harnessed. This duo will give brands that opportunity.

@DrNatalie Petouhoff, VP and Principal Analyst, Constellation Research

Covering Customer-facing Applications That Drive Better Business Results
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