Simultaneously, Customer Experience (CX) has become the domain in which companies set themselves apart from their competitors, and the utilization of AI for enhanced Customer Experience has become a critical success factor in today’s dynamic business environment. The struggle of operationalizing AI with CX is now a primary focal point for all brands.

Across the board, brands are preparing their CX operations for the AI revolution. We continuously see brands reallocating CX investment to focus on AI integration, restructuring the organization by creating AI executive leadership roles, and executives shifting their expectations of CX.

1,500 C-suite executives from various businesses participated in a recent study by an AI strategy consulting firm, and the results revealed some fascinating patterns. A significant amount, 76%, of these executives said they need help with the challenges of implementing AI across their companies. An equivalent number of them think that if they implement AI, their companies might maintain a strong foothold in the next five years.

Roughly, 24% of executives said they have successfully operationalized AI at scale, reaping its substantial benefits. Their achievements include a remarkable 5x return on investment and a 45% increase in business valuation metrics.

These highlight the critical importance of operationalizing AI with CX at scale for businesses to stay competitive and thrive in the evolving landscape of technology and customer expectations. Make no mistake, with the reallocated AI investments into CX come executive expectations of operational scalability, customer retention, and ROI. Going from a cost center to an actual profit center is no longer a goal, it’s an expectation.

The Key to Operationalizing AI with CX

Operationalizing AI within the context of CX entails integrating AI technology methodically to improve each step of the customer experience, customize interactions, and streamline operations. AI is being used in both B2B & B2C industries for a wide range of purposes in differing ways. Both industries however have the same foundation of success.

1.   Clear Objectives and KPIs

Establishing well-defined goals and Key Performance Indicators (KPIs) is crucial for directing efforts related to AI and CX. To build a plan for your projects, identify specific targets such as decreasing response times or increasing customer satisfaction. KPIs support progress monitoring and the ability to measure success against business goals.

2.   Analysis of Service Journey

Opportunity mapping for AI integration can be identified by thoroughly mapping the customer and employee journeys. You can optimize touchpoints for increased satisfaction and efficiency by identifying places where AI can improve interactions, expedite procedures, and create a seamless customer experience.

3.   Data Gathering and Administration

Effective data collection and management are crucial for AI-driven CX. Gathering data from various sources and ensuring its quality, security, and compliance create the foundation for informed AI decision-making, enabling insights into customer behavior and preferences.

The Combination to Value with AI-Powered CX

Operationalizing AI with CX opens the door to many possibilities, but to ensure you unlock the vault to reaching holistic value, you need the right combination. The right combination is found in critical components that produce insights, provide efficiency, and promote loyalty.

1.   Feedback Program

A dynamic CX environment is created by establishing a continuous feedback system with customers and employees. This is more than predefined after-call surveys, this is the ability for customers and employees to provide freeform feedback and even product ideas. Adding a freeform feedback program makes it easier for customers to put their experience in their own words. Prior to AI, this type of feedback would be hard to produce anything fruitful, but AI’s ability to mine data and turn that data into insights allows brands to keep the consumer experience up-to-date with changing expectations.

2.   Process Automation

Robotic Process Automation (RPA) with AI make frontend and backend processes more efficient and even smarter; think of it as automation with intent. Together RPA and AI can make use of structured and unstructured inputs to create intelligent process automation. Start with menial tasks, proactive alerts, and repeatable processes. RPA can perform your redundant processes, your people however, have skills that AI and robots don’t; use them for what they’re best at… being human!

3.   Data Digitization

AI is only as good as the data it pulls from. Create a clean-data initiative within your organization and start with a data repository where text, images, and even sounds are turned into digital format. This component is maybe the most crucial of all when deploying AI and pursuing an AI-powered CX environment. As a single source of truth, a digital repository is not only a source where you can ensure data is accurate, but also ensures your artificial intelligence platform has some actual intelligence feeding it.

4.   Global Observability

What starts with global observability turns into predictive analytics that models and forecasts customer behavior, enabling proactive interventions like personalized recommendations and targeted marketing efforts. This empowers businesses to anticipate and meet customer needs effectively. Use AI to track user journeys, gain insights into your disparate operational teams, and visualize backend processes for a complete view of operations.

5.   Empowered Culture

To maximize the synergy between the workforce and technology in the customer care section, make sure your staff is proficient in using AI technologies. Employees who receive training and assistance are better equipped to utilize AI’s potential and provide more productive, customer-focused services. As employees grow in their ability, empower them with greater responsibilities and trust them to make customer satisfaction decisions.

6.   Real-time Assistance

AI’s capability to deliver real-time assistance may be its crowning achievement in the CX space. Whether customer self-service, voice bots, chat bots, or agent assist, real-time assistance reduces response times and enhances customer interactions. This not only improves customer satisfaction but also boosts operational efficiency.

The Biometrics of Measuring CX for Business

Being able to measure the impact of operationalizing AI with CX is more than just a safe play, it needs to be a requirement in your AI strategy. Not only will it validate the project efforts and identify ROI, but it will provide insight into future AI endeavors and help set expectations within your organization.

1.   Cost-Benefit Analysis

For financial sustainability, it is imperative to routinely evaluate the return on investment (ROI) for AI and CX initiatives. This procedure guarantees that the value produced outweighs the expenses incurred, enabling resource optimization and well-informed modifications. It is important to understand how your company quantifies operational efficiencies along with hard dollar returns.

2.   Integration and Scalability

Creating AI-powered CX solutions with scalability in mind enables future growth and smooth integration with current systems. Due to its adaptability, AI can develop with your company and remain relevant as your operations change and expand. If your organization struggles to be agile or to efficiently deploy cutting-edge technology at scale, consider a technology partner who can guide your organization through the rapidly-changing technology of today.

3.   Continuous Improvement

Continuous testing, calibration, and optimization of AI-powered CX strategies maximize their effectiveness and responsiveness to organizational and customer needs. This iterative approach helps fine-tune the customer and employee experiences, will achieve better results over time, and will allow your brand to differentiate itself from the competition.

Considerations When Operationalizing Artificial Intelligence

Businesses can lower the risk of legal trouble and consumer trustworthiness, both of which can damage a brand in an instance and take years to recover from. Be diligent in entrusting data security and compliance to reputable partners, while preserving the experience customers expect from your brand.

Unprejudiced Assessment

You need an unbiased assessment of your project. An objective analysis of CX and AI projects aids companies in making data-driven decisions. With no internal biases or prejudices, this impartiality guarantees that projects are rigorously assessed, resulting in better decision-making and improved project outcomes.

Compliance and Security

It is critical to understand the intricacies of data security and compliance, minimizing the risks of breaches and regulatory issues. In today’s data-sensitive world, an understanding of cybersecurity best practices and data protection legislation is crucial.

Ensuring the protection of consumer information requires a high priority for data security and compliance. Establishing governance strong security measures for AI-driven processes, AI-accessible data, and AI-generated information is a must in order to ensure data protection rules.

AI Ethics

Putting AI ethics into practice keeps decision-making powered by AI transparent, equitable, and trustworthy. Businesses can promote credibility and responsible AI usage by following ethical norms, which help them avoid biases, assure privacy, and uphold data protection rules.

Embark on Your AI & CX Journey Today

AI provides businesses with a potent tool to improve CX in previously unimaginable ways because of its ability to make use of large data, boost operational effectiveness, improve customer satisfaction, and enable a competitive edge. AI is forever intertwined with CX, and it has the power to deliver unforeseen capabilities. It is important to see AI as another piece of the CX puzzle – and it may be the defining piece – if you know where it fits.

Black Box is here to assist you in operationalizing AI with CX to deliver business value.

The post Unlock Business Value with AI: Operationalizing AI with CX appeared first on Execs In The Know.

For the majority of CX history, companies have been primarily focused on repairing their relationships with customers, instead of preparing for issues. Although proactive customer support is not a new idea, companies still struggle with how to heighten its impact with big data.

The combination of technology and proactive support is creating a monumental shift in CX by making strategies more customer-centric, improving customer loyalty by 5%, and increasing overall revenue. By curating thoughtful customer experiences and meeting customers on their terms, CX operations can be less of a cost center and more of a profit center.

Proactive customer support is critical to any CX strategy because of its ability to anticipate customer needs and their preferences, and provide a well thought out experience with a brand. By keeping simple customer queries at bay, it reduces operating costs and unnecessary friction which keeps bottom lines low and CSAT scores high.

Proactive Customer Support: The Stats and Facts

A proactive approach to support is an organization’s ability to foresee certain problems before they occur and implement early processes to help contain the negative impact it might have on customers.

For instance, if a retailer is experiencing a hiccup with a logistics company that’s causing mass order delays, they can do one of two things:

Quickly train agents on their response to the influx of calls they are about to receive (reactive)

Promptly send out an SMS message to impacted customers letting them know their delivery is delayed by X amount of days (proactive)

 Option two clearly offers the least amount of friction with customers and immediately decreases the amount of potential call volume and thus, reduces costs long term. By strategically implementing proactive support, companies have reported a:

• Reduction in inbound call volumes by 20-30% in 12 months
• 25% decrease in operations costs
• 3-5% increase in customer retention

But being proactive isn’t just something companies should strive for, it’s what customers want. A survey found that 87% of customers want to be contacted proactively by a company about service issues.

When Shift Happens

Although in the moment proactive support decisions make an immense impact on operational costs and brand perception, the real value and shift in CX comes when it’s powered by big data.

Big data is the collecting and analyzing of data and should be used throughout the customer journey, not just the beginning micro moments–an opportunity I see a lot of CX leaders overlook. When you couple big data and proactive support approaches, you move away from the break-fix style of support and shift toward a strategic predict-pivot methodology.

For example, if a customer is trying to upgrade their subscription, and have no luck using self-service tools, email, or chat the last resort is calling the company. When the customer is prompted by the IVR, a company should know their channel hopping history. Ideally, a proactive automated message that addresses the customer and asks if they are calling about switching to a different subscription or something else. Once their selection is made, they should be routed directly to an agent for help. This proactive approach eliminates the stress and frustration of a customer repeating themselves and increases speed to solution.

By consistently monitoring how customers use your products, services, and self-help resources, it empowers CX teams to proactively respond to issues before they arise. By piecing together the breadcrumbs of a customer’s journey, companies can utilize that data to view the full distance of the customer, past purchase behavior, and their likely next step.

How to Get Started

A lot of ideas and concepts in CX take a lot of time and money upfront, but proactive customer support that’s powered by big data works with what you have already. To begin the process, review your customer feedback from last quarter and extract the weaknesses customers noted.

What do these problems mean for this quarter and the quarters to come? What data do you have around the issues to inform what a proactive approach might be?

Start making a new chapter in CX history by starting a proactive, data-based shift in the way you deliver experiences to your customers. Once you get started, you will definitely notice a positive difference in key metrics like AHT, call volume, CSAT, and NPS. The combination of big data and proactive customer support has saved some companies up to $10 million. How much will you save?

Guest post written by: Jennifer Turner, Vice President, Business Development, Retail, TaskUs

The post The Next Monumental Shift In CX: Combining Big Data and Proactive Customer Support appeared first on Execs In The Know.

The following post is a guest blog from Inbenta. 

Two seconds is a long time in the online world. In that time, Google will process around 100,000 search queries, global users will send more than 4.5 million emails, and nearly 60 million Whatsapp users will receive a message.

However, it is not a long time if you are an online retailer. According to a recent study, two seconds is all a customer needs before they give up on your website. The picky customer just got pickier.

The customer is still king

It won’t surprise you that the online market is leaving its high street competitors in the dust when it comes to being the preferred shopping method for customers. What is interesting is that the ‘tech savvy’ Millennials are not the only ones choosing to shop with their feet up.

In fact, according to research from KPMG, Generation X consumers (those born between 1966 and 1981) made more online purchases than any other age group while Baby Boomers (1946-1964) spent more on average per transaction. Putting all your eggs in the Millennial basket might not be such a good idea after all.

This is especially the case when you consider what the different generations of customers value within a company. While 59% of consumers would try a new brand for a better service experience, younger consumers are keen to be treated as unique individuals and so prefer companies which offer personalized promotions and an ability to anticipate what they want. When you have two mouths with different tastes to feed, how do you keep them both satisfied with the same meal?

The obvious solution is to ramp up your customer service team to kill two birds with one stone. The problem is that to maintain your profit margins and pay the extra salaries on your books, you will have to push prices up. Obviously, that is not a wise move in an increasingly crowded market.

Of course, you could decide to accept that you will lose some customers and choose instead to target new ones who are willing to pay a premium for a better experience. But according to the White House Office of Consumer Affairs, it is 6-7 times more costly to attract a new customer than it is to retain an existing one.

Natural language processing: the solution to online retailer woes

Fortunately, there is an answer, and it comes in the form of a new technology which utilizes an invention almost as old as the human race itself.

Natural language processing (NLP) ensures your online search engines can understand natural language, therefore, allowing customers to ask questions online exactly like they would to a shop assistant in person.

Instead of relying on keyword search which will only match you with what you want when you type it exactly, NLP is based on semantics and is able to understand the exact meaning behind a question regardless of phrasing, slang or jargon used.

For example, a customer might ask the following questions:

– Can I order by check?

– Can I check my order?

Given that both questions use the same words, keyword matching might present the same answer. NLP however, is able to detect that both have different meanings semantically. The result is a seamless experience for the customer whose questions are answered immediately without having to be diverted to an agent.

NLP: a more personal experience

Companies can also provide the personal experience craved by Millennials through NLP by ensuring customers can communicate online how they might in store.

For example, a customer might approach a shop assistant and say “I’m looking for a medium black coat which is waterproof and has a hood.” An NLP powered search will be able to digest this question and provide the options available that fit this description. Instead of having to click one by one to narrow down their search options, users will have the product they want in next to no time.

In addition, NLP can be used to analyze the big data accrued from customer searches to match customers with products that they might want. For example, someone buying a new laptop might then be shown a laptop case, mouse and portable charger. Each user will be offered a unique, individual experience thanks to NLP.

There may not be a friendly shop assistant waving you into your store, but NLP can provide an online product more personal and enriching than ever before.

Inbenta is a leader in natural language processing and artificial intelligence for customer support, e-commerce and conversational chatbots, providing an easy-to-deploy solution that improves customer satisfaction, reduces support costs, and increases revenue.

Interested in finding out more about this topic or Inbenta? Inbenta is one of the subject matter experts that will be sharing their insights and expertise at Customer Response Summit Chicago, September 19-21, 2017. CR Summit Chicago will feature keynotes from Amazon, Lyft, Square, and Microsoft. For more information about our leading event for CX professionals, visit our event website. 

The post Customer Service: Dealing With Increased Expectations appeared first on Execs In The Know.

The following is a guest blog written by Edward Kowalski, Associate Vice President, Retail Marketing, at Sutherland Global Services. To download a free white paper on the topic, visit  http://www.sutherlandglobal.com/Retail/WP-20160104/Default.aspx

Most retailers are missing a key opportunity. It’s a way to take what’s now an expense and instead use it to build awareness, create loyalty and even grow profits.

It’s customer care.

Companies should combine customer care with customer experience, big data and predictive analytics. It’s a transformation that requires retailers to break down silos and start sharing information that’s widely available.

Consider the constant signals customers provide, based on multiple experiences, with brands across multiple touchpoints. Retail marketers use the information to develop a customer journey that’s seamless, relevant, authentic and omni-channel.

But it’s a missing link that needs to be shared with the customer care team.

Retailers should develop a new system that arms customer care agents with intelligence that spurs personalized engagements. This helps resolve complaints, increase Net Promoter Scores, improve customer satisfaction, create loyalty and, yes, generate revenue.

Here are the steps we recommend:

– Share information – Marketers analyze data and analytics, creating a 360-degree view of customers. It allows them to create intelligent communications so customers receive the right message, at the right time, through the right channel.

That customer intelligence forms the blueprint that drives strategic marketing plans. But it’s rarely shared with customer care agents who routinely have direct 1:1 communications with customers. Without the analytics needed to guide a customer’s journey, customer care is typically limited to solving at-the-moment issues as quickly as possible.

We helped a fashion retailer give customer care agents the tools needed to become an integrated part of the customer experience. The agents saw each customer’s purchase history, for example, allowing them to customize product recommendations. The result? Sales conversion climbed from 15 percent to 25 percent, the basket size increased by 7 percent and the average handle time dropped by 23 percent.

– Make it personal – Retailers have long tried to “know thy customer,” which is why they now analyze and segment data. Once they acquire a better understanding of customers’ buying behaviors, their predictions alter their strategies.

Product-centric programs are out. The focus now is enhancing the customer experience. No matter the communication channel, when businesses personalize shopping effectively, it creates a brand loyalty with customers.

This happens on intelligent websites, for instance. They collect user data and, based on a customer’s preference, they dynamically present different retail offerings. Today, as omni-channel marketers and ecommerce leaders make this shift, it should also carry over to customer care.

The more customer care agents know about customers, the more they can create personalized experiences across channels and devices.

– Help customer care agents make real-time recommendations – After unlocking information, retailers should provide customer care agents with an automated set of intelligence that enables personalization. Now the customer experience journey gets extended through the customer care channel.

Customer care agents can deliver a consistent, relevant, authentic and timely experience if they have tools that provide information, intelligence and recommendations in real-time. It’s efficient and effective.

After breaking down silos and unlocking all of a company’s information about customers, retailers must integrate that intelligence with the dashboards customer care agents use. This is made possible through the integration of Customer Engagement Management Platforms. Dashboards powered by these platforms will showcase insightful data and analytics, providing a full view of the customer and automating customized recommendations (in the form of next best actions). In turn, this provides the highly valued, personalized customer experience.

In addition to unified customer views and real-time recommendations, these platforms also provide robust business intelligence tools to measure the outcomes of customer engagement. If retailers understand those outcomes, they can incorporate the customer voice into the customer experience design.

The platform’s tools should help customer care agents:

– Pick data from disparate sources

– Correlate the data and enrich individual customer profiles

– Provide cross-dimensional views from the customer’s viewpoint

– Interface and deliver relevant recommendations (Next Best Actions)

– Deliver these actions to the customers at their preferred touch point with context and relevance

This creates more relevant, more meaningful interactions between the customer and the agent. Eventually, it also means a seamless and desirable customer care experience that prompts more long-term customer loyalty and advocacy.

– A better way to measure success – Traditional customer satisfaction measures (C-SAT) become less helpful as the standard of retail customer care becomes more consistent and homogenous. Instead, consider Net Promoter Score (NPS). This measures the most powerful form of marketing: a customer’s willingness to promote a service or product to family and friends. Earning that loyalty shows the retailer’s brand commitment to its customers has been noticed and appreciated. That loyalty means customers shop – and purchase – more frequently.

To hear more about this topic and others like it, from Sutherland Global Services and our other subject matter experts, join us at Customer Response Summit Phoenix, February 23rd-25th, 2016.

The post The Missing Link Retailers Need to Turn a Cost Into a Revenue Generator appeared first on Execs In The Know.

WINNIPEG, MANITOBA. March 3, 2015 – Chad McDaniel, President at Execs In The Know, will be moderating the webinar, “If it’s Broken fix it. Mending Broken Customer Journeys Through Digital Transformation,” Thursday, March 19, 2015 from 1:00-2:00 EDT. Daniel Hong, Senior Director of Product Marketing Strategy, will be speaking on behalf of customer engagement software andservices provider, [24]7 Inc. Yogena Austin, Sr. Business Web Analyst, Web Technology/Salesforce Team at Duke Energy, the largest electric power holding company in the United States, will also be a speaker in the webinar.

The webinar will explore how to identify and mend broken customer journeys, often caused by automation, escalation, and channel crossing. It will touch on topics like virtual agents, intelligent chat, visual IVR, customer effort, tracking metrics and analytics, and digital engagement solution technologies, to help create a next generation customer journey.

“Having a seamless customer experience works hand-in-hand with driving customer satisfaction and loyalty,” said Chad McDaniel. “[24]7 Inc. and Duke Energy have a wonderful partnership story to share, that highlights how they were able to address their own customer journey mapping concerns and the exact deployment models used to correct them.”

To register for the webinar visit https://attendee.gotowebinar.com/register/4869604323173159682.

About Execs in the Know

For over 15 years, Execs in the Know has built a reputation of excellence in the Customer Management Industry and a worldwide community of over 50,000 Customer Experience Professionals. Execs in the Know connects people to engaging industry content, thought leadership, current trends, peer-to-peer collaboration, networking, and industry employment opportunities. Examples of this can be seen at their Customer Response Summit events, roadshows, webinars, workshops, Blog Talk Radio segments, Industry Benchmarking Series, blogs, thought papers, and social communities.

To learn more about Execs in the Know, visit www.execsintheknow.com. For more information on their Customer Management Recruitment Solutions, visit www.justcareers.com.

About [24]7 Inc.

[24]7 makes customer service and sales simple. Our platform and applications use big data and predictive analytics to understand customers and drive better service and sales results for large enterprises. We do this over 2.5 billion times a year for the world’s leading companies. [24]7’s platform enables an omnichannel interaction experience. We connect customer interactions across an enterprise’s web, mobile, chat, social, and phone channels. It’s all in real-time and in the cloud. Our solutions drive immediate business results. We increase revenues, reduce service and sales costs, and create more satisfied customers. [24]7 serves the Global 100 market leaders in the Financial Services, Retail, Telecommunications, Technology, and Travel Industries. [24]7 is noted by Forbes as one of America’s Most Promising Companies. [24]7 is a trademark of 24/7 Customer, Inc. [24]7 is based in Campbell, California. For more information, visit: www.247-inc.com.

[24]7 is a trademark of 24/7 Customer, Inc. All other brands, products or service names are or may be trademarks or service marks of their respective owners.

About Duke Energy

Duke Energy makes life better for millions of people every day by providing electric and gas services in a sustainable way – affordable, reliable and clean.

Duke Energy is the largest electric power holding company in the United States, supplying and delivering energy to approximately 7.2 million U.S. customers. They have approximately 57,500 megawatts of electric generating capacity in the Carolinas, the Midwest and Florida – and natural gas distribution services in Ohio and Kentucky. Their commercial and international businesses own and operate diverse power generation assets in North America and Latin America, including a portfolio of renewable energy assets.

Headquartered in Charlotte, N.C., Duke Energy is a Fortune 250 company traded on the New York Stock Exchange under the symbol DUK.

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