Scaling contact centers with human resources has been a tried and true tactic for growing customer service. 

But recent challenges in hiring, retaining, and forecasting demand have shown the many limitations and frustrations with this method. Human agents are expensive, hiring and training them is time and resource intensive, and having enough agent capacity at all times is nearly impossible – especially these days.

Contact centers that rely on human agents to scale will continue to be reactive and frustrate customers with hold times.  Alternatively, contact centers that adopt Contact Center Automation already have the ability to quickly adapt to changes, are more operationally and cost efficient, and see higher customer satisfaction.

Here’s how scaling your contact center with automation gives customer service organizations an advantage.

Meet demand 100% of the time, without compromising on quality

There have been multiple studies on wait times and customer expectations, and the findings are clear. Customers are willing to wait just a few minutes or not at all. Nearly two-thirds of surveyed consumers said they’re willing to wait two minutes or less before they hang up. Over 13% said no hold time is acceptable. 

Contact Center Automation enables contact centers to meet customer demand 100% of the time, without compromising on the quality of customers’ experience. It provides contact centers a 1:1 agent-to-customer ratio at all times, so customers never have to wait on hold. Their call or chat is immediately picked up.

Replicant leverages proprietary transcription, inference classification, and named entity recognition models as well as a high-performance Natural Language Understanding (NLU) engine with built-in continuous learning. 

The result: a 96% peak inference accuracy, rich context from unstructured inputs, and a 20-millisecond response time. Replicant delivers conversations that regularly return higher CSAT scores than live agents.

Spikes in call volume are flattened

Repetitive requests are usually the types of requests you’ll receive an outsized volume of when experiencing a spike. Airlines are a perfect example of this. When flights are canceled due to weather, airlines experience an influx of customers asking to rebook their flight.

Having a scalable capacity flattens these spikes, since Contact Center Automation acts as the first line of defense in taking all incoming requests. 

While some requests may require a live agent, automation drastically reduces the amount of requests that human agents need to take. 

This helps prevent agents from being overwhelmed. With a 90% success rate in resolutions, and 50% reduction in average handle time, Replciant is able to minimize escalations, while making handoffs that do take place faster and more efficient than ever.

Increase your speed and flexibility of ramping capacity up or down

You’ll rarely ever get a heads up that allows you to plan and adjust your capacity. When contact centers are reacting to fluctuations in days or weeks, it can negatively impact customers’ perception of your brand. 

With Contact Center Automation, your capacity adjusts in minutes because you’re no longer increasing or decreasing the number of human agents. 

Automation can quickly ramp up in response to higher call volumes and scale back down just as quickly when volume goes down, keeping costs predictable and controllable.

This speed and flexibility enables companies to grow their customer service faster. Since agents are only handling a fraction of all request volume, you can rapidly acquire new customers and ensure they’re supported no matter what challenges arise. 

Cost becomes predictable

Forecasting and scheduling requires contact centers to commit to a certain amount of agent capacity and pay for that amount. This is a fixed-cost model that locks you into paying for whatever you’ve anticipated. If you’ve underestimated, you’ll also need to ask for more budget, which you may not get.

When contact centers can instantly scale their capacity with demand, costs become predictable too. You’ll only pay for the capacity you use, which is the amount of time the Thinking Machine is on the phone with customers.

Replicant makes it easy to design and test flows with low-code, drag-and-drop conversation components called Replicant Powers that come pre-built with design best practices. Comprehensive integrations work out-of-the-box with any CRM, CCaaS, and telephony stack. 

And, enterprise grade scale provides a secure, high availability infrastructure that runs 24/7 with 99.95% uptime commitment, redundancy, and HIPAA, SOC 2, PCI, and GDPR certifications.

All this means that your ROI can begin compounding as soon as you deploy – in weeks, not months or years.

Lower costs

Contact centers that adopt Contact Center Automation have lower costs. Aside from only paying for the capacity you use, you don’t pay for wait times and calls are 50% shorter. Scaling with automation is a lot cheaper than scaling with humans. Even compared to a highly optimized BPO, automation is about 55% cheaper.

Having no wait times, the perfect amount of customer capacity at all times, and reducing customer service costs by half no longer needs to be a dream. Contact Center Automation enables you to achieve these results today.

Learn more about Contact Center Automation with our definitive guide.

The post How to Meet Customer Demand, Flatten Call Spikes, and Lower Contact Center Costs With Automation appeared first on Replicant.

While one negative customer interaction can seem harmless, it happens across thousands or millions of interactions in a business. These small things compound and “erode the foundation of CX.” This is why every single touchpoint with a customer is incredibly important and why customer experience (CX) is top of mind for business leaders.

We recently talked to leaders at AAA, HomeAdvisor, and CX Effect on what they’re prioritizing today in customer experience and how to succeed with a customer experience strategy.

Conversational self-service is becoming increasingly more important for AAA

For Lisa Rivier, Director of Sales and Road Service Strategy Operations at AAA, member experience is always number one. “Everything we do is for and by our members, so we always put ourselves in their shoes.”

Aside from that, they’re focused on optimization, business process improvement, automation, and containment. They want to empower members to resolve issues themselves, especially on the first call. Not only does self-service reduce the number of calls that come back into their contact center, but members also get what they need the first time. It’s a win-win for the business and customers.

AAA is focused on offering self-service through the phone and SMS, since they’re seeing their members move away from web-based chat. Members either want a phone call or a text message because it’s the easiest way for them to engage and get help. They also want conversational experiences that are instantaneous. Rivier explains the importance of this:

We know that our members and customers fumble as they’re trying to get the information that we’re asking from them, so the natural language has to be acknowledged. We have to be able to move through that process and understand how people actually converse and talk, which helps us increase our containment rates and get back to that one-call resolution.

HomeAdvisor leans into omnichannel experiences and self-service

HomeAdvisor is a digital marketplace that connects homeowners with local service professionals. As a marketplace, they serve two customers: the professionals who offer home services and the homeowners.

In 2021, they’re focused on improving the onboarding experience for professionals by educating them and providing business help. To measure success, they’re looking at professionals’ attention and engagement with HomeAdvisor. For homeowners, they offer three different verticals, so they’re focused on making all three services accessible to homeowners — regardless of the brand website they’re on.

Sean Miller, VP of Operations at HomeAdvisor, also sees self-service being a key part of their customer experience. There are plenty of ways that self-service can make both homeowners and service professionals happier. If homeowners can call in, request the service they need, provide their location, and get immediately matched with a local professional, it becomes incredibly easy for homeowners to find and schedule the service they want. For professionals, the ability to add service locations to their account without having to talk to an agent creates an effortless experience.

Where to start with improving your customer experience

Identify your biggest problem, get data to build a business case, and align your stakeholders

Customer experience encapsulates all parts of a customer’s lifetime with your brand. With so much opportunity to make a difference with your customers, where should you start? Robbins asks, “If you could snap your fingers and solve your number one problem today, what would that problem be?” Your answer is your starting point.

Most business leaders know their biggest problem. However, they can’t solve it due to one of three reasons. The first is they don’t have access to the data that proves their problem and validates their business case. The second reason is they have too much data, so identifying what’s most actionable is difficult and requires a lot of work. Lastly, they have access to data but they lack stakeholder alignment.

If you’re overwhelmed and need guidance on where to start, Robbins summarizes what to do in three steps:

1. Can you identify your number one problem?
2. Do you have access to the data that you need to build a business case?
3. Do you have the right stakeholders at the table?

When setting KPIs, you need both lag and lead measures

Once you’ve identified your problem and what needs to be done, Robbins believes success comes down the KPIs and measurements you set.

There are two types of measurements: lag and lead measures. FranklinCovey defines these as, “While a lag measure tells you if you’ve achieved the goal, a lead measure tells you if you are likely to achieve the goal.” Robbins says:

Look at our contact centers. How many things do we measure that are after the fact? They’re all lag measures. We get caught in the whirlwind and we don’t look at the lead. We don’t look at what’s predictive of if we do this, we can expect this to happen on the other side of it.

When Robbins works with business leaders, he asks them how they define success today and how they’ll know it when they see it. By identifying both lag and lead measures, you’ll not only know when you’ve reached success, but also that you’re on your way there.

Even with these steps laid out, transforming your customer experience isn’t easy. It also often involves introducing cutting-edge technologies and implementing significant changes internally. Get more guidance from ADP’s Director of Digital Transformation in our on-demand webinar on “Championing Innovation and Disrupting Customer Experiences.”

And if you’d like to engage with and learn from more customer experience leaders, sign up to be notified of upcoming Replicant events.

The post What CX Leaders Are Prioritizing to Improve the Customer Experience appeared first on Replicant.

During the Gartner 2021 Application Innovation & Business Solutions Summit, Mullen led the “Strategic Roadmap to the Language-Enabled Enterprise” session. To help companies avoid this cognitive debt, Mullen laid out the steps and components that are needed to assemble a strategy for automating how machines understand, process, and generate natural language.

Takeaways

• “To be strategic, we have to get to grips with vendor/technology strategies, orchestrating and scaling the virtual + human workforce, managing the end-to-end data pipeline and information architecture.”
• “Unbundle the confusion of technologies and vendors into three core competencies to develop your strategy: information architecture, application engineering, and AI and algorithms.”
• “You don’t need to model the whole universe of language: general knowledge can be free, data common across industries can be bought, industry-specific and company-specific data should be developed and controlled.”

Understand vendor and technology strategies

There’s been a rapid increase in the number of vendors and technologies. Technology has also evolved, changing how we automate experiences and language.

Markets are also consolidating, giving way to language platforms. Historically, natural language solutions have been tied to a specific modality, such as email, speech, or search. However, you don’t need different approaches to modeling the language and topics that are used for each modality. The models that you develop should be able to be used across multiple modalities. Now, we’re starting to see multimodal language solutions, where a single platform can handle multiple modalities by leveraging the common components and data.

Natural language automation requires sociotechnical engineering

You don’t just need technical engineering for natural language automation. You also need sociotechnical engineering. Sociotechnical engineering combines technical elements, such as data, algorithms, and infrastructure, with social elements, like domain experts, processes, and culture.

Gartner found that when you introduce natural language automation, about a third of the staff will be happy to engage with it, a third can be convinced, and a third will try to break the technology because they view it as a threat. While it’s true that automation has taken away some tasks from humans, it’s also given them new tasks, roles, and responsibilities.

Three new roles have been created due to natural language automation:

• Exception handler: When the machine can’t complete a task, the task will be passed to the exception handler to complete.
• Trainer: Humans are trainers of these automated systems. When machines can’t complete the task, you don’t want to just hand the task over to the exception handler to complete. You also want to train the system so it improves.
• Quality control: Organizations need to insert humans throughout the pipeline to do quality control. This role checks the language output of the automation and compares it against human output.

To succeed with sociotechnical engineering, it’s critical to have an interface that humans can use to give feedback to the AI. For example, indicating which outputs are correct or incorrect. Having a user interface also moves you toward explainable AI, where humans can question the AI and look at the rationale behind the AI’s answer. If you don’t have these interfaces and your vendor can’t provide them for you, you’ll need to design them yourself.

Sociotechnical engineering can’t just happen on a per project basis. It needs to be ongoing, and it’ll take a variety of parties and skill sets to accomplish. You’ll need to work with vendors to get your data in shape and bring in third-party proprietary data, NLT scientists to develop an information architecture, and expert staff members to refine your model.

Develop your strategy around three core competencies

In putting together your natural language automation strategy, there are three core competencies that you want to address:

• Information architecture: The concepts and objects that are the model for your organization are also the foundation for developing language automation. Build concept and object models for your industry and adjacent models. Keep in mind, you don’t need to do this all at once. Avoid the cognitive debt by working across different business units and joining up your efforts. Everything else outside of this can be bought or integrated.
• Application engineering: Designing, integrating, and orchestrating natural language automation requires a balance between building and buying. There aren’t enough developers to build everything yourself, and by only working with vendors, it’ll cost a lot. Involve as many staff and in-house experts as possible in the process. Empower them by giving them the tools to build language automation and use external parties to complement them.
• AI and algorithms: Advances in AI are still happening, so expect rapid change over the next few years. Design your systems with this in mind by making sure you can pick and choose from a variety of models and engines. Only build your own models, algorithms, and engines if you need differential performance.

“Realize your strategy with a three-tier buy/build architecture”

Mullen says “90% of the chatbots live today will be discarded by the end of 2023.” That’s a lot of money that’ll be lost. To avoid this, you want to choose the best-of-breed technologies to develop with, have flexible design tools that can be used to create experiences across any modality, and build and refine your information architecture.

In bringing your strategy to life, “You don’t need to model the whole universe of language: general knowledge can be free, data common across industries can be bought, industry-specific and company-specific data should be developed and controlled.”

If you’re ready to bring natural language to your voice channels and automate customer service, see how an enterprise company realized tremendous cost savings with Replicant Voice in six weeks.

Gartner, ‘Application Innovation & Business Solutions Summit – Americas’, Presentation (Strategic Roadmap to the Language-Enabled Enterprise), Anthony Mullen, May 26-27, 2021

The post Building Blocks Every Enterprise Needs for a Natural Language Automation Strategy appeared first on Replicant.

We’re excited to share that after two rounds of phenomenal demos and pitches from the six competing companies, Replicant was named the most innovative CX solution by the audience. With your support and our partners at Talkdesk, we won $10,000 for BUILD to empower the next generation of leaders and entrepreneurs.

Thank you everyone for helping us support @BUILDNational today.

And thanks to @Talkdesk for hosting an exciting #CXdigitalshowdown. The competition was fierce! https://t.co/igmfs7U2xv

— ReplicantAI (@Replicant_AI) May 26, 2021

See why Replicant was named the most innovative customer experience solution in this three-minute demo.

The post Replicant Wins $10,000 for BUILD in Talkdesk CX Digital Showdown appeared first on Replicant.

Three customer service leaders from Extended Stay America, Freshly, and Support Ninja share what they’ve learned from the pandemic, changes they’re making for the future, and upcoming challenges.

How Extended Stay America and Freshly reacted to the pandemic

Extended Stay America leveraged their business continuity plan to fill in the gaps

Like other hospitality companies, Extended Stay America saw a slow down in business at the beginning of the pandemic. However, they bounced back much quicker than others. The construction boom drove construction workers to their hotels for long-term projects. They also saw an increase in traveling nurses staying with them.

Since business was down, they weren’t running the training classes they usually conduct from January to June each year. When they suddenly experienced an increase in call volume, they were short-staffed. To meet demand until they could get staffing back up, they handled it with an extended business continuity plan (BCP). They applied a lot of their BCP logic until they could get their staffing back up to a point where they could handle all calls.

Freshly leaned into automation to service customers faster and save agents time

Freshly, a company that offers meal delivery kits, experienced a big spike in customer demand at the beginning of the pandemic. They saw an increase in customer interactions across all contact channels — not only because they now had more customers to serve, but also because there were more unique questions. For example, customers were now asking whether couriers wore masks or handled the packaged kits with gloves. At the same time, they were also moving their agents to work safely from home.

“[W]e found ourselves leaning into … automation and AI as a way for us to support our customers and support our agents and maintain efficiencies across the board,” says Megan Merrick, Associate Director, Innovation and Brand Experience at Freshly. They relied on live chat self-service during this time, and the impact was significant. Instead of having agents take roughly six minutes to help customers skip an upcoming order, they were able to automate those requests and save agents thousands of minutes each day.

Learnings from COVID-19

The technology infrastructure of your contact center needs to be prioritized

Reflecting back on the last year and looking forward to what’s to come, Matt Magnuson, VP of Call Centers at Extended Stay America, says they didn’t have the technology infrastructure that they’d need in the 21st century. The pandemic exposed the need to accelerate some technology plans that weren’t previously urgent.

Experimenting with a new contact channel can lead to meeting customers where they prefer to engage

During the pandemic, Freshly started serving customers through Facebook Messenger. This not only took some volume off of other contact channels, but Freshly also learned that many of their customers preferred to reach them through messaging. “So we started staffing our channels where the customers wanted us to be and where we knew we could flex a little bit more automation to be able to support them pre-conversation with an agent,” explains Merrick.

Customers either love or hate automation, but contact centers can make small changes so automation is enjoyable

Merrick also adds, “The other thing we learned is that when you do automation really, really well, your customers love it. If you don’t do it really, really well, your customers are going to hate it.” When they launched live chat on their website, they learned that making small tweaks to help the AI collect information about the customer or interact with the customer can change how many customers abandon the automated experience.

They also saw this reflected in customer satisfaction (CSAT) scores. “If people aren’t happy with the automation and they want to talk to an agent and they’re finding that there’s any type of friction, we’re going to see those scores tank. And when we make it easier to either get the information that you need or at least you find a sense of security, I would suppose, that you can get out of the automation and reach an agent, we tend to see that rise.”

Challenges ahead for contact centers

The battle for talent is getting more competitive

As many activities that were shut down or drastically reduced during the pandemic start up again, companies are starting to prepare for the increase in customers. The biggest hurdle to scaling customer service right now is access to talent, says Anne Bibb, VP, Global Head of Customer Experience at Support Ninja.

Magnuson agrees, as he sees the biggest risk being how competitive recruiting might get. “If you talk to most contact center leaders, they’re expanding their geos. Even folks that are staffing or recruiting domestic call centers where they might have just had a small geographical area, now that’s expanded.” Contact centers are looking for the best talent, regardless of location.

With a remote workforce, employee engagement is more difficult

With a more geographically dispersed contact center workforce, Bibb sees employee engagement becoming a challenge. You’ll need to make sure all employees are treated equally.

As employee engagement becomes a widespread pain point for customer service organizations, Bibb anticipates solutions will pop up. She predicts there will be new technology to help ensure employees are taken care of, “because employee experience and customer experience need to be equally taken care of in order to make sure businesses are successful.”

There’s more unpredictability on the horizon and some industries are facing pent-up customer demand. Contact centers can easily weather fluctuating demand by using AI and automation to achieve elastic customer service. Download our “Ensuring Your Contact Center Capacity Always Matches Demand” guide to see how to bring elasticity into your contact center.

If you’d like to learn from more customer service leaders, sign up to be notified of upcoming Replicant events.

The post Customer Service Leaders Share Learnings From COVID-19 and Challenges Ahead appeared first on Replicant.

As companies look to keep up with rapidly changing consumer behavior and expectations, they’re investing more in digitally transforming their business. However, digital transformation is a huge undertaking and creates change that typically isn’t welcomed. To help business and customer service leaders succeed with this, Kugathasan joined us to share his tips on how to bring innovation and digital transformation to your business.

Tie your innovation initiatives to company goals

In order to get your innovation initiatives off the ground, you need your senior leadership and team on board. You need buy-in from senior leadership so you can get the resources you need. To do this, Kugathasan says you need to tell a good story and align yourself with the broader mandate of the organization. “How can you tie your story of innovation or what you want to do as a project or a series of projects into that type of story, rather than just saying we want to innovate. I think that’s where people get things wrong in the first place.”

Get team adoption by taking people on the digital transformation journey with you

Once you’ve got senior leadership on board, now you need to get the team behind you too. Kugathasan sees similar principles between getting senior leadership and team buy-in, but what’s different between the two is their underlying motivation.

To motivate team members, some companies have taken the carrot and stick approach. Team members have to carry out the initiative. Otherwise, there will be consequences. But Kugathasan has a different perspective:

People want to do something interesting in their day-to-day. Bringing them along that journey as you’re improving that client experience gives people in the team level a lot of different things.

Innovation presents opportunities for people to build new skills, work on new projects and tasks, and flex their muscles. “Finding those right motivators in that team level is important or equally as important as executing on that project,” adds Kugathasan.

Overcome risk-averse and skeptical stakeholders by figuring out their underlying assumptions

When facing people who are resistant to change, Kugathasan sees negativity and skepticism as the result of underlying assumptions. Getting to the root of those assumptions and finding ways to prove them out in smaller increments is the key to working with risk-averse or negative stakeholders. And whether their assumptions are true or not, “we still owe it to ourselves to test.” In these situations, Kugathasan often asks himself:

Is it better that we’re doing things exactly the same or do we owe it to ourselves to test something different or try something different?

When you start this dialogue with those teammates or stakeholders, you’ll find they’re often open to giving you their perspective. In Kugathasan’s experience, there’s very few people who are negative just for the sake of being negative. But if you do run into someone like that, Kugathasan recommends corralling everyone around that person to bring them on board. People are willing to follow a plan their peers accept, even if they don’t accept it themselves.

So the next time you encounter a negative or risk-averse stakeholder, understand whether their negativity stems from a valid reason and see if you can find a solution. Otherwise, look at the ecosystem and the people around them. If everyone else is on board, ask them why they aren’t too. However, Kugathasan offers the reminder that there’s a number of different ways to approach this and the best method will depend on each person’s role within an organization.

Mapping out and understanding your business processes is a prerequisite to rapidly modernizing your business

Fast tracking the modernization or transformation of your business relies on two things, according to Kugathasan.

The first is how well you understand all the moving parts of the business — the core functions and the underlying technology and infrastructure. To do this, Kugathasan recommends mapping out your business processes at a high level. If you were asked to put together a simple one-pager on each business function and the processes and technology that tie them all together, would you be able to do so? If you can’t, you need to start with this exercise. Then, plan on refreshing it annually.

The second is how “you envision and start to construct a path to either build on top of it or to replace each of those pieces with better and faster parts or much more efficient parts.” Kugathasan compares an organization to a car. You can change the engine, frame, wheels, and other parts to make a car go faster. This achieves your goal for speed without having to buy a new car. The different parts of a car are like the technologies, interfaces, and channels used in your processes. The key to fast tracking modernization is understanding how all of these different parts connect and then identifying opportunities to improve upon them.

Innovation thrives or dies based on company culture

When asked what the biggest obstacle to innovation is, culture immediately came to mind for Kugathasan. “Innovation in any organization comes from a central mandate, and that mandate needs to come from the top-down. Building that culture of self-improvement is really a value that’s nurtured by senior leadership. Without that, you’re not going to be able to sustain any sort of innovation.”

You can’t just say you’re going to be an innovative company and try something new once in a while. Companies need to put substantial effort into innovation, including allocating funding and resources to it. Also, “You need to foster this culture of innovation to make sure it’s not just a one-time event.” Innovation goes beyond doing a single project or working for a few months to solve a problem. “Innovation, I think, is a continuous journey. And the foundation of that is culture,” says Kugathasan.

Hear more from Kugathasan in this on-demand discussion about championing innovation and disrupting customer experience.

If you’d like to engage with and learn from digital transformation leaders like Val Kugathasan, sign up to be notified of upcoming Replicant events.

The post ADP’s Director of Digital Transformation and Payment Ops on Getting Buy-In and Adoption appeared first on Replicant.

Replicant is honored to be selected as one of Forbes’ top 50 AI firms to watch in 2021, after being recognized on The Information’s list of the top 50 most promising enterprise AI startups.

Over the last year, we’ve helped multiple Fortune 500 companies use the power of voice AI to reimagine customer service and support their customers during the pandemic. Our customers have:

• Eliminated hold times
• Elastically scaled their customer service capacity with demand
• Reduced their contact center costs by 50%
• Resolved 90% of Tier-1 issues without agent involvement
• Scaled to 30,000 AI-powered calls per day within 10 weeks

“We wanted our customer service to feel seamless and personal without the typical burdens of automated calls like customers repeating themselves, having to wait on hold, or getting stuck in IVR menus. Replicant’s ‘Thinking Machine’ is the perfect solution – it’s providing new innovation while reducing hold times by 50%, bringing average handle times down from 10 minutes to 2-5 minutes, and reducing call escalations,” said Connor Shepherd, Founding Partner and Head of Product of Because Market.

We couldn’t have gotten this far without our clients, who have shared our belief that machines are capable of having natural, complex conversations beyond what IVRs and home voice assistants offer today. Thank you to our customers for your continued partnership.

We’re just scratching the surface of what’s possible with voice AI though. We can’t wait to unveil what we’ve got in store for the rest of this year. “Every time I wait on a long hold, listening to the hold message on a loop, I am reminded why we started Replicant and how much work is still ahead of us,” said Gadi Shamia, CEO and cofounder of Replicant.

Contact us to learn more about how Replicant can help you transform your customer service with voice.

The post Replicant Named a Forbes Top 50 AI Firms to Watch in 2021 appeared first on Replicant.

A recent study found that 76% of all consumers prefer to reach customer service over the phone as their preferred channel of communication. And this trend isn’t going anywhere, with 92% of American millennials owning a smartphone.

But delivering high quality customer experiences can be costly. That’s why many call center leaders are looking to call center outsourcing services through business process outsourcing, or BPOs, to lower their call center costs and scale customer service operations 

However, there are often hidden costs associated with outsourcing your call center and emerging technologies offer better alternatives. Let’s take a look at what business processing outsourcing is and whether it might be the right solution for you.

What is business process outsourcing?

Business process outsourcing (BPO) is the outsourcing of roles and responsibilities to a third-party service provider. It’s typically done as an attempt to reduce costs and increase efficiency or productivity. 

Call center outsourcing is a type of business process outsourcing, and the most typical outsourced service is customer service over the phone. Most outsourced call centers handle inbound phone calls, often leveraging a low-wage workforce that allows them to reduce expenses.

Types of call center outsourcing services

There’s many different ways to categorize outsourced call centers. One way to look at them is whether they handle inbound or outbound calls. Another way is the type of service these BPOs and offshore call centers perform.

Inbound vs. outbound call center outsourcing

Inbound call center service providers answer incoming calls from customers. They can handle a variety of requests, such as updating account information, placing an order, or providing tech support.

Outbound call center service providers make outgoing calls. Outbound calls are typically used either to sell a product or service to consumers or conduct market research. Outbound agents can also qualify leads, proactively provide reminders, or place orders with third-parties.

BPO services offered

Classifying BPO providers by the type of service they offer is more specific than whether they handle inbound or outbound calls. Call center BPO companies offer a variety of services across many different industries. Here are just some of them:

• Phone answering services
• Technical support services
• Order taking services
• Reservation booking services
• Appointment setting services
• Claims processing services
• Troubleshooting services

Pros and cons of using a call center BPO

Before making the investment into offshore call center outsourcing, it’s important to understand the pros and cons of outsourcing your customer support function to a third-party service provider. 

Pros of outsourcing to a call center BPO

• Lower costs – Instead of hiring agents locally, BPOs use low-wage labor to power call center operations — often in offshore locations.
• Fewer staffing issues – The call center BPO takes care of staffing agents. This includes associated risks and workload, like paperwork, liabilities, and hiring costs.
• 24/7 support over the phone – BPOs located across different time zones allow companies to offer real-time phone support while local agents are off the clock.
• Call center equipment procurement and management – BPOs provide call center hardware, like noise canceling headsets. They also provide call center software and tools, with features like analytics and call recording for easier monitoring.

Cons of outsourcing to a call center BPO

• Less quality control – BPO call center agents aren’t employees of your company, so they often lack visibility into your company culture, values, and mission. As a result, they risk failing to accurately represent your brand to customers.
• Poor company knowledge – BPOs often have high turnover rates. Agents are constantly being pulled from one account to another, which means BPOs are less invested in ensuring every agent knows your business inside and out. 
• High training workload – Even with BPOs, companies must still provide thorough customer service and company-specific training material, which can be time consuming and require frequent manual updates.
• Wasted budget – It’s impossible to accurately predict call center demand. Call centers are often either overstaffed or understaffed, which means that at some point, you’re bound to pay bloated BPO costs for unused agent capacity.
• Bad customer experience – Most customers immediately recognize when they are being serviced by an offshore BPO, given the impersonal and scripted nature of interactions with BPO agents. This can be a problem when customers are becoming ever more demanding of brands and the customer service they receive, making it a costly decision to bet on when you risk customer churn. 
• Security risks – Security and data protection are a growing concern. BPOs have recently become the target of security incidents, costing companies monetary losses, reputation damage, and even legal repercussions.

An alternative to call center BPOs: Why brands choose conversational AI instead

Conversational AI technology has significantly advanced in recent years. Voice AI today is sophisticated enough to have natural conversations over the phone to fully resolve customer issues at scale for enterprise businesses. 

Businesses across industries, including insurance, retail, hospitality, and financial services, are overlooking BPOs and leveraging conversational AI to power customer conversations instead. Here are the top reasons why companies are making the switch:

AI is cheaper than a highly optimized call center BPO

With conversational AI, you never have agents sitting idle while the clock is ticking and you’re paying for it. When your business receives hundreds of thousands of customer support calls a day, idle minutes and even seconds can add up very quickly.

The beauty of voice AI technology is that you only pay for what you use. You can meet inbound demand head-on and never pay for a single second the AI is not on the phone. Call centers have reduced 50% of their costs through conversational AI, while also delivering more efficient and effective customer service. 

Conversational AI provides a superior customer experience

Voice AI technology enables brands to offer fast, personalized, and 24/7 customer service over the phone. With voice AI, you’re never waiting on agent availability, so hold times are eliminated. As opposed to live agents, AI is available around the clock and ready to handle high call volumes any time of day.

Call centers report higher resolution rates and faster resolution times as voice AI technology gets smarter with every customer issue it resolves. Now, your most important customer conversations can improve without needing to manually update call scripts or train new agents.

Higher agent engagement and satisfaction

Adopters of conversational AI actually cite improvements to their agent experience. Conversational AI resolves transactional Tier-1 customer service issues, which leaves call center agents with more time to focus on customer issues that require human empathy and ingenuity. Call center agents feel more engaged and empowered when they resolve these types of customer issues instead.

Voice AI technologies can also automate front-office and back-office work, like caller authentication and tagging call dispositions, which frees up agents to focus on more productive work. All of these improvements to the agent experience reduce the risk of agent fatigue and employee churn, positively impacting your call center.

Increased security and compliance

Conversational AI platforms sit on top of existing contact center and CRM technologies, and often incorporate security and data privacy best practices that are on par with major contact center technology providers. With BPOs, on the other hand, common cybersecurity threats like data breaches or hacking are a higher risk and out of the purview or control of the companies that employ them.

Enterprise conversational AI platforms are often fully compliant with current data protection regulations at the state and federal level. They employ world-class physical security controls to protect and store sensitive customer data.

Advanced call center analytics and insights

With conversational AI technology, data collection and analysis is completely automated. Real-time conversation transcription, conversation disposition tagging, and contact center and CRM integrations make it effortless to capture and automatically log call data for better insights into your customers.

Call center managers and business leaders gain access to key business metrics and visibility into every call, empowering them to deliver better customer service and make more informed decisions off of rich customer data.

The post Call Center Outsourcing: Pros and Cons of Using a BPO for Your Call Center appeared first on Replicant.

With the evolution of AI, contact centers are starting to overcome these challenges. By using AI to bring elasticity into their operations, contact centers can always match their capacity with customer demand to achieve 1:1 customer service. The concept behind this is called elastic customer service.

What is elastic customer service?

Elastic customer service is the ability to scale customer service up and down based on customer demand, without ballooning costs, training new agents, offshoring, or planning for seasonal fluctuations. Contact centers achieve elasticity by using AI to create a 1:1 agent-to-customer ratio and maintain that ratio at all times. Whether you’re receiving double or 10 times the amount of your normal contact volume, AI is capable of responding to all customer requests immediately.

Having the ability to quickly expand and contract your capacity creates a more fluid and flexible model where contact centers can meet the needs of customers and the business — no matter what’s happening. Your contact center will always be able to service your customers the moment they call, eliminating hold times and improving customer satisfaction.

Autonomous contact centers are the key to adopting an elastic customer service model. They use the power of voice AI to resolve Tier-1 customer service issues without burdening agents with repetitive, high-volume calls or keeping customers on hold. If an issue can’t be resolved by AI, customers are seamlessly transferred to a live agent. Customers don’t have to repeat themselves because agents are provided with a detailed summary of the call, enabling them to pick up right where the AI left off.

How elastic customer service provides a better method for scaling contact centers

Contact centers have primarily used human agents to scale. However, scaling this way is costly and difficult.
Whether you’re hiring more on-site agents or outsourcing, employing more agents is expensive. On-shore full-time agents cost about 80 cents to $1.50 per minute, while off-shore BPOs cost 40 to 60 cents per minute. Aside from the monetary cost, there’s also the time and effort spent hiring and training new agents.

Agent reliability is also unpredictable. High turnover means contact center leaders don’t always know if an agent is going to quit or simply decide to not show up the next day. It’s impossible to predict when agents will get sick or when there are conditions that prevent agents from coming into work, like a snowstorm.

Even when there’s only a small number of agents out for a day, this creates a major disruption in your operations. The ratio of customers to one agent increases, which puts more pressure on agents to get through calls as quickly as possible. This impacts customers’ experience, as they have to wait on hold and may receive lower service quality.

Instead of slowly scaling your operations with human agents, elastic customer service enables contact centers to adjust their capacity in minutes. AI quickly ramps up in response to higher call volumes and scales back down just as quickly when volume goes down. Plus, AI works 24/7, can take any number of calls simultaneously, and never tires from handling repetitive calls. By having AI act as a first line of defense for incoming calls, fewer calls need to be answered by live agents.

This speed and flexibility enables companies to grow their customer service faster. Since agents are only handling a fraction of all call volume, you can rapidly acquire new customers and ensure they’re supported.

Download The Ultimate Guide to Elastic Customer Service to learn more about the advantages of elastic customer service and how to adopt it.

The post Elastic Customer Service: The Key to Efficiently Scaling Contact Center Capacity With Demand appeared first on Replicant.

Understand AI and automation are tools for business optimization

Most business leaders understand the value of AI and automation. If you need to make the business case for it, you’ll have to make sure company executives know what the value of these tools is.
AI, machine learning, and automation are all ways to optimize and modernize your business processes. All these tools work together to provide you with “a cohesive way to address your business problems.” They create a compelling value proposition because they can facilitate a digital transformation that moves the business forward and puts you at the forefront of your industry.

Take a phased approach

According to Prescott, AI and automation initiatives have often failed because:

[T]hat’s primarily because [you’re] biting off more than you can chew [or] going for moonshots instead of low-hanging fruit.

There’s a lot of different steps you have to take to actually prepare yourself, prepare the environment, prepare your workforce for this change. And when you skip past those steps, that’s when you start to see the hurdles and the challenges in relation to actually being able to execute successfully on a vision to have an artificial intelligence imprint in your company or build machine learning models in your company.

This is why Prescott emphasizes how important it is to understand that adopting these tools will be a phased approach.

Prepare and start with clear, realistic, and short-term goals

For Prescott, preparation is key to succeeding with AI. “There’s a lot of hype around the AI piece, but we often don’t hear a lot about what it takes to prepare your company and even your employees for that initiative. And I believe that’s what sets you up for success.”

To be successful, Prescott advises companies to start with automation. Automation is the biggest indicator that your company is ready to advance to AI. When you are ready, the best processes to apply AI to are mature processes that offer a high volume of data and where the data is reliable, accurate, and complete. Once you’ve identified which processes are ripe for AI, you need to deeply think about where you want to go with AI, be realistic about what you can achieve, and start with your short-term objectives. Then, you can work toward your long-term key objectives and results.

Take a top-down and bottom-up approach

Prescott says about 30% to 40% of companies who attempt AI fail within the first one to two years. Spotify is a rare success story though. In 2020, Prescott rolled out 100 bots across the company. Her secret to success is taking both a top-down and bottom-up approach.

Going from the bottom up, they trained employees who were on the ground to identify automation opportunities and understand where processes can be optimized. By knowing how to look for use-cases in their daily work and in their work with other teams, employees across the company helped bring automation opportunities to Prescott’s team. Instead of keeping their initiatives at the senior level, Prescott’s team engaged the entire company. As a result, they sourced a wide variety of use-cases and had a better understanding of cross-functional work and systems.

At the same time, their top-down approach helped them understand the reasons why senior leadership would embrace digital transformation. They identified the goals that Prescott’s team could help them achieve. This helped them automate processes that would provide ROI for multiple stakeholders and teams.

Most companies will only take one approach. They’ll train employees to automate some simple tasks, or they’ll go for such large enterprise-wide initiatives that they miss great opportunities that are smaller. By using both a bottom-up and top-down approach, Spotify was able to scale their automation and AI efforts rapidly.

To learn more about implementing AI in your business, see how chatbots and virtual agents are disrupting the customer service industry.

Sign up to be notified of upcoming Replicant events to engage with and learn from AI experts like Sidney Madison Prescott.

The post Four Tips for Successfully Implementing AI and Automation at the Enterprise Level appeared first on Replicant.

Shared autonomy between humans and machines

Human-in-the-loop is the idea of human-assisted machine interactions. When humans have shared or partial autonomy of a machine, they can help solve issues that machines run into. This is extremely useful because it’s difficult to account for every single scenario a robot might encounter when you take it out of a controlled environment and place it into the real world. “There’s this enormous long tail of what can actually happen in the real world,” explains Cuan.

Cuan offers the example of a delivery robot. Even if the robot has a perfect map of where to go and it’s a perfectly sunny day, the robot may run into unforeseen obstacles that it doesn’t know how to handle. There may be something blocking the ramp that the robot needs to drive up. This would be the perfect time to call a human operator or teleoperator and give them control of the robot in order to solve the issue.

Machines will take many forms

Cuan believes we’re headed in the direction of creating machines that are physically soft and malleable. The robot might be made out of soft material, like cloth or plastic. It wouldn’t matter whether the robot ends up in a situation that wasn’t anticipated, since it isn’t able to hurt anyone.

Infrastructure made for robots

Lastly, Cuan sees the rise of infrastructure that’s built for robots. For example, autonomous vehicles could be successful today if we blocked off a part of the road for them that humans couldn’t move through. This provides a more controlled environment for the vehicles to operate in. By adapting infrastructure, we can make autonomous machines less dangerous when they’re operating out in the real world.

Ultimately, the future of human and machine interactions will mostly lie in between giving machines 100% autonomy and none. “Anyone who is betting on full autonomy is doing so with the narrowest of possible scopes and tasks.” Think of the Roomba, an autonomous vacuum cleaner. It does one task — vacuuming. And it’s constrained to one environment — a room or house.

“You have a lot of other things in the middle that turn this spectrum from two dimensions into infinitely many,” says Cuan. With infinite opportunities in the middle of the two extremes, this is where companies can get the most out of their AI and automation efforts right now. Humans and machines are collaborating today, and they’ll continue to do so in the future.

If you’re interested in bringing human-AI collaboration to your business, download our free guide on The Contact Center of the Future: Human-AI Collaboration for Happier Customers.

Sign up to be notified of upcoming Replicant events to engage with and learn from AI experts like Catie Cuan.

The post Shared Autonomy, Materially Soft Robots, and Specialized Infrastructure: What the Future of Human and Machine Interactions Looks Like appeared first on Replicant.

Let’s take a closer look at how voice AI is shaping customers’ retail experience.

24/7 Immediate Customer Service

When customers want support, they want it now. Fifty-one percent of consumers believe businesses need to be available 24/7, and 83% of consumers want to interact immediately with someone when they contact a company. Instead of staffing or outsourcing to meet this demand, retail companies that implement voice AI will always have a first line of defense for customer inquiries. No matter what time or day a customer calls, voice AI will answer the call immediately.

Automated and Quick Resolution of Tier-1 Issues

Voice AI can fully resolve Tier-1 issues, such as:

• Provide order updates
• Process returns
• Advise on the nearest store location
• Send a return label via SMS
• Answer balance inquiries
• Explain product features

Since customers don’t have to wait on hold, they get an immediate solution to their question or problem. At the same time, this frees up human agents to focus on more complex work or emotionally sensitive issues.

Incorporating voice AI into self-service options also vastly improves the customer experience by reducing the average handle time. Boston Consulting Group found 45% of call time is “dead air.” This is time when a human agent is searching for information, the customer is on hold, or the customer is waiting to be transferred. By integrating with CRMs, voice AI can pull customer information instantly and even update records, which helps cut call times in half.

Consistent Customer Experience

Lastly, retailers need to remain agile, resilient, and responsive to customers’ needs, whenever and wherever they need support. This requires retailers to improve efficiencies and response times across every customer service channel, including the phone.

According to Salesforce’s State of Service report, 76% of consumers expect “consistent interactions” when it comes to customer service. However, 53% of consumers felt that a company’s various departments, such as sales, marketing, and customer service, don’t share information cross-functionally. Customers repeat their issue over and over, creating frustration and negatively impacting customer loyalty.

Voice AI seamlessly integrates with other systems and channels, including CRMs, ticketing software, SMS, and web. It can automatically provide agents with a summary of the call when customers are transferred to an agent. And customers no longer have to repeat themselves, since the agent is equipped to pick up right where the customer left off with the AI technology.

Voice AI can even trigger text messages or send customers web pages and forms, so customers can provide and access information through the easiest method possible. By synchronizing interactions between online shopping, text messaging, voice calls, and other channels, retailers can better serve their customers in a cohesive and consistent manner.

Both online and brick-and-mortar retail companies benefit from adopting voice AI. They can provide their shoppers with faster resolutions that don’t sacrifice on quality. Customer service call centers that are augmented by voice AI not only guarantee 24/7 service, but also create a consistent and personalized customer experience. When combined, these improvements increase customer satisfaction and help retailers create loyal, happy shoppers.

Learn how retail and e-commerce companies are using Replicant Voice AI to automatically resolve Tier-1 issues, provide personalized service, and upsell customers.

The post How Voice AI is Transforming Customer Service for Retail Companies appeared first on Replicant.

Although most people haven’t been traveling in the last year, this will likely change as more of the population gets vaccinated. Hospitality companies need to be prepared to capture and retain this business when it happens. Hotels can achieve this by using voice AI to provide contact-free hospitality while delivering a top-notch customer experience.

Offer Smart Hotel Rooms That Drive Customer Satisfaction

According to Statista, 4.2 billion digital voice assistants were used worldwide in 2020. The number of digital voice assistants is forecasted to increase to 8.4 billion by 2024 — a number exceeding the global population. With increasing use of digital voice assistants as the main point of interaction with smartphones and home devices, consumers are now demanding similar experiences in their everyday lives, like when they stay at a hotel.

With a “smart hotel room,” guests can control much of their experience through AI-enabled voice devices. Smart hotel rooms combine “AI and voice recognition technology to integrate virtual assistants into [the guest experience].” With this transformational technology, guests can use voice control to get personalized assistance, such as requesting the thermostat be turned down or asking for directions to the on-site gym. Guests can speak naturally in their native language because AI understands different languages, accents, dialects, and slang, which results in a more seamless guest experience.

Due to COVID-19, more consumers prefer touchless interaction. “In fact, 62% of consumers expect to increase their use of touchless technologies once this crisis subsides.” Smart hotel rooms not only reduce contact, but also make it easier for guests to settle right in and have a comfortable stay.

According to Oracle’s Hotel 2025 study, a typical hotel guest spends 12 to 15 minutes trying to figure out how to operate the thermostat, TV, lights, and other controls in the room. A voice-activated solution can quickly solve this frustration for guests. According to the same study, “78% of hotel operators said voice-activated controls for lights, air conditioning, and room devices would be mainstream or in mass adoption by 2025.”

And what do guests say? According to Oracle’s study, “59% of consumers said that voice-activated controls for lights, air conditioning, and room devices would enhance the guest experience, [while] 36% would stay more often if offered this service.” With hotel rooms evolving into a more personalized experience for travelers, voice AI helps hospitality companies personalize and improve the consumer’s experience.

Provide AI Concierge Services to Scale Customer Service

In addition to smart rooms, hotels can offer AI voice-enabled concierge services. Guests can interact with virtual agents to book an appointment at the spa or get a restaurant recommendation, for example. When AI handles the mundane, repetitive requests, front desk personnel can better handle more complex needs or focus their time on creating personal relationships with hotel guests. Additionally, voice-enabled agents can respond quicker and ensure more accurate responses, reducing the cost of human error.

As the world recovers from COVID-19, there’s pent-up consumer demand for travel. However, hotels are facing a difficult situation. They don’t know when and to what extent the demand for travel will return, and they need to meet that demand with reduced staff and budgets. Being able to efficiently and quickly scale customer service is more important than ever. Using voice AI, hotels can serve more customers with the same amount of resources and scale customer service up or down as demand fluctuates. AI can respond to any number of calls, ensuring every customer is immediately helped and doesn’t experience a wait time.

The new customer service model for hospitality is not a thing of the future. It’s here now. By incorporating voice AI into your customer service strategy, hotels can enhance the customer experience while driving efficiency to keep guests coming back for more.

The post How Voice AI is Transforming the Customer Experience for Hospitality appeared first on Replicant.

In order for contact centers to thrive, organizations need to solve these underlying problems. How can contact centers and customer service leaders do this? The answer lies in AI and the introduction of an autonomous contact center.

Three Fundamental Problems of Contact Centers

Despite outsourcing and attempts at automation, contact centers have historically faced three major problems that still persist today.

Difficulty in accurately forecasting supply and demand

Even with workforce management software, it’s difficult for contact centers to accurately predict call volumes and always have the perfect number of agents on staff to meet demand. Contact centers end up with either too many or too few agents, which leads to higher costs or long hold times and poor customer experiences.

High turnover rates

The problem above is exacerbated by the fact that agents don’t stay at contact centers for very long. Call centers see an average of 30% to 45% turnover rate. Some even have turnover rates in the three digits. Turnover is so high because most agents prefer less mundane work. When agents are fielding repetitive Tier-1 calls, it can lead to burnout.

Poor customer experience

The more repetitive the tasks, the more difficult it is for agents to stay focused and engaged. While they’re working, they may also be checking social media or texting a friend. As a result, their quality of work and the customer’s experience suffers.

With AI, a New Contact Center Model Can Emerge

To solve these problems, companies are looking to AI to help automate repetitive, task-oriented aspects of their customer service. However, not all efforts have succeeded. In fact, most automation efforts have failed to deliver on their promise or have frustrated customers. Phone, in particular, has been difficult to automate because it requires AI to process the context of a customer’s call, accurately understand the request, and respond back quickly.

Companies that have tried to develop voice AI in-house are rarely able to put the technology into production or process thousands of calls with the AI. Companies that don’t build a custom solution have turned to IVRs. Because IVRs use either primitive AI models or phonetic recognition, IVRs require customers to learn their language. Customers have to say numbers, specific phrases, or keywords that the IVR recognizes. When IVRs fail to contain the problem, customers get passed onto an agent and have to repeat their issue. This leads to greater frustration.

Autonomous contact centers provide a more effective way of leveraging AI technology for customer service. Using the power of voice AI, they act as the first line of defense by resolving Tier-1 customer service issues, without burdening agents with repetitive, high-volume calls or keeping customers on hold.

They also provide customers with multi-experience, omnichannel support across voice, SMS, mobile, and other channels. When the AI can’t resolve an issue, it’s escalated to an agent and a summary of the interaction is shared with the agent. Customers don’t have to repeat themselves, and the agent can jump straight into solving the problem.

How Autonomous Contact Centers Solve the Three Fundamental Problems

Using a combination of AI, visual IVR, and seamless integrations with existing contact center software, an autonomous contact center can solve the three fundamental problems that contact centers currently suffer from.

Tier-1 issues are immediately resolved

Machines are great at performing tasks that have a defined beginning and end. For example, looking up the status of a delivery, updating an order, or finding the nearest store location based on the customer’s address. By fully resolving and not deflecting these types of issues, an autonomous contact center takes away tedious tasks from agents. In turn, agents are freed up to handle the emotionally sensitive or complex problems and to build relationships with customers.

Elastic customer service that automatically scales with demand

An autonomous contact center can answer as many phone calls as needed — no matter how much call volume you get. “The system is elastic, which means if you send 10 calls an hour, 100 calls an hour, 1,000 calls an hour, we don’t care. We’ll take as many calls. There’s never going to be a hold time,” said Shamia. When supply shrinks and stretches with demand, you no longer have to worry about having enough agents at all times and spikes in demand are flattened.

Increased customer satisfaction

Customers don’t care whether a human or AI helps them, as long as they don’t have to wait on hold, their issue is resolved as quickly as possible, and they don’t have to repeat themselves when transferred to an agent. Autonomous contact centers increase CSAT by meeting these expectations. Every call is immediately answered by the AI, and calls are quicker and more efficient. When speaking with a machine, there’s no chit-chat. Customers also don’t have to wait while agents are manually entering information or navigating between multiple systems. By plugging into CRMs and contact center software, the AI technology instantly finds and updates information. It also automatically generates summary notes for deeper call insights and less manual data entry on behalf of agents.

Where an Autonomous Contact Center Fits Into Your Tech Stack

Since IVRs are used widely, most people immediately understand an autonomous contact center through the lens of an IVR. However, autonomous contact centers are different from IVRs and have a lot more capabilities. An autonomous contact center can either fit in front of or behind an IVR. It can even replace an IVR.

When an autonomous contact center is in front of an IVR, it’s the first interaction that customers have. The easy issues are automatically resolved without any agent interaction, while the more complex issues are handed off to an agent. When the autonomous contact center sits behind the IVR, it will interact with customers after they have chosen a menu option.

You don’t need to rip and replace existing technology, since an autonomous contact center works alongside your IVR and other systems.

How to Get Started With Autonomous Contact Centers

Identify a use-case for automation

The easiest way to get started with an autonomous contact center is to identify a single use-case where it can be applied. Find a simple and repetitive call driver that could be resolved by a machine. Then, figure out how much volume of that use-case you have, the current cost of having agents handle that issue, and the ROI of automating it.

Determine which systems need to be integrated

You also need to identify the systems that need to be plugged into the autonomous contact center. For companies that are built on a modern system architecture, the AI can easily plug into your systems through APIs. However, companies that are built on older systems may need to first upgrade their infrastructure before they can implement an autonomous contact center.

Ensure your data is up-to-date and accurate

The success of your autonomous contact center depends on the quality of your data. To autonomously solve Tier-1 issues, the contact center technology needs to pull information from other systems and update them. If you have outdated knowledge bases or CRMs, the AI will draw from this bad information. Before you implement this type of technology, make sure your data is up-to-date and accurate.

Implement one use-case to realize business value

Even if your systems and data aren’t in an ideal state, you can still start transforming your contact center into an autonomous one. When choosing your first use-case, find one that’s isolated and touches few systems. “Because if you can reduce 10% of the pressure off the call volume, it doesn’t matter where you reduce it from,” explained Shamia.
Automating even a small percentage of your calls positively impacts your operations and customer experience. You shouldn’t hold off on implementing an autonomous contact center just because you can’t automate all of your call volume immediately. “The full potential might be realized in five years. But the initial potential, we can realize now,” said Shamia.

Bring an Autonomous Contact Center to Your Organization

You can reduce call center costs, increase CSAT, and scale customer service elastically with Replicant, the world’s first autonomous contact center. Replicant brings always-on, elastic capacity to every customer experience with voice AI.

Replicant Voice resolves Tier-1 support issues over the phone, using natural and human-like contextual voice AI. It eliminates hold times, manages unpredictable call volume, and gives agents more time to resolve emotionally-sensitive and complex issues. Unlike many AI solutions, Replicant Voice can be implemented in just a few weeks or months. It’s also been deployed by Fortune 500 companies to resolve over three million calls a month and reduce contact center costs by 50%.

The post The Future of Contact Centers Lies in AI and Agent Collaboration appeared first on Replicant.

Our Virtual Chocolate Tasting & CX Panel  on February 11th was our most engaging one yet. We kicked off the evening with an educational, but more importantly delectable, chocolate tasting guided by master chocolate maker, Ricardo Trillos, founder of Cao Chocolates.

The second half was spent with our impressive CX Panel where we were joined by customer service leaders with a combined 60+ years of experience in the contact center space. Our panelists, made up of leaders from ADP, Lenovo, Nordstrom and Sun Basket, led us into a discussion around contact center trends, bringing to the table their unique perspectives and field experiences. 

If you didn’t have the chance to attend, that’s ok; here are four key contact center predictions we’ve identified, coupled with commentary and color from our CX panelists!

1. Proactive Customer Service

During our last panel, one of the top themes we discussed was the shift from reactive to proactive customer service. Gartner too predicts that proactive customer service will be a key initiative in 2021 and beyond. Many contact center leaders are transitioning their customer service from being a reactive function to being a proactive function, leveraging outbound communication like text and phone calls to address issues before the customer does. 

According to our panelists, one way to achieve proactive customer service is to not just factor in the quantitative data that your contact center provides, but also the qualitative data like listening into customer calls or reading transcripts. 

2. Contact Center as a Profit Center

Historically, the contact center has always been one of the most costly business operations. But with the changing times, the contact center has never been more important. According to Forrester, customer service will become a lifeline for 33 million devastated consumers experiencing unprecedented difficulties. 

This is further exacerbated since most, if not all, customer touchpoints are  virtual and no longer in person. This has put enormous pressure on contact centers to maintain the frontline for their agents while delivering exceptional customer service. 

The reputation of contact centers as being cost centers is now being challenged as they become the backbone for customer retention, loyalty and reducing churn. The migration to online customer experiences has also forced businesses to take sales online as well, and many businesses are leveraging their contact centers to upsell customers through outbound calls. Now, other departments like marketing, sales and customer success are leveraging the contact center to fulfill other functions and customer touchpoints. 

Contact centers are becoming the pinnacle of customer interactions – influencing how and when you make an impression on your customers – as “in-person” engagements remain on hold. 

3. Remote Workforce

2020 changed a lot, maybe everything. For customer service and call centers, the past year brought about a drastic shift in traditional workforce models and many agents are now working from home. Contact center leaders had to act quickly to accommodate their agents and their new work from home setups, putting agent safety first.

One way our panelists are setting-up their agents for success with remote work is by ensuring that they have all of the appropriate equipment needed to effectively do their jobs. This means thinking about laptop security and software needs, accessories like noise-canceling headsets, and shipping and handling logistics to make sure  equipment  is in stock and arrives on time. 

The implicit camaraderie in call centers was another element that CX leaders had to think about in recreating  an engaging remote working environment. Setting up the appropriate digital channels and checkpoints were some of the ways that leaders made sure that their agents had open lines of communication and appropriate forums to engage with their peers and also surface concerns or questions to their managers.

4. Hybrid AI and Human Customer Service

According to Forrester, automation and AI in the contact center will continue to take on easier tasks. This in turn is influencing business leaders to reassess their outsourcing strategies toward more highly skilled agents to better handle complex customer issues that require human empathy and ingenuity.

According to one of our CX panelists, one way of achieving this is to first structure your contact center data to understand your biggest opportunities for efficiency and automation. By first identifying and mapping out inbound call use-cases and call volumes, contact center leaders can prioritize their most costly call center operations and leverage AI to automate common customer issues like password resets. 

Agents also benefit as mundane tasks that they were previously responsible for can be automated; freeing up agents to take on more interesting and engaging customer calls so that they can truly become your companies’ brand ambassadors. 

Call center leaders are leaning more and more on using speech analytics to gain rich customer insights. Through speech analytics technology, leaders can more effectively identify and catalogue common issues at scale, leveraging the truest source of data: your customers’ actual words.

Replicant’s powerful artificial intelligence technology, for example, helps customers understand and interpret complex and colloquial speech patterns including slang, accents, and technical terms which allows it to recognize customer intent instantly for faster resolution. 

Sign up to be the first to know about our upcoming virtual get togethers! Don’t forget to register for our upcoming Customer Spotlight Webinar on Thursday, March 9th, where we’ll chat with a CX innovator about how he was able to reduce contact center costs by 50% with Replicant. Those who register will receive a $25 Postmates gift card to enjoy lunch while they watch the webinar.

The post 4 Contact Center Forecasts for 2021 appeared first on Replicant.

At Replicant, we believe in taking a fresh approach to connecting with our prospects and customers, which is why we regularly host digital events to inspire thought-provoking conversations.

Our goal is to bring together CX leaders and provide them with a forum to share ideas through experiential and interactive environments. This is, after all, the direction customer service is moving towards: delivering personal, high-touch, and connected customer experiences. 

On January 21st, 2021, we hosted a Virtual Sparkling Wine Tasting CX Panel where we were joined by influential leaders in the customer service and contact center space from companies like ADP, AAA, The General, Pizza Pizza and Wells Fargo. While enjoying a seasonal selection of boutique sparkling wine from Napa Valley’s Carboniste, we opened up the discussion with questions that got our guests thinking about the next wave of CX trends in 2021 and beyond – everything from inspiring our best work in hybrid working environments, to digital transformation, to AI & automation. 

We wanted to share some of the top themes and key takeaways that came away from our discussion with CX leaders: 

Call center agents are thriving in flexible work environments

No one had a template for what 2020 had in store; instead, business leaders had to react fast and put employee safety first. Despite the bumps along the way, some of our contact center leaders were delightfully surprised to find that remote work for their call center agents had unplanned upsides. They reported seeing increased agent productivity, declining turnover, and higher satisfaction when it came to both saving time and money on things like daily commutes. 

That said, there have been some setbacks that contact center leaders are working through – agents need quiet working environments with a strong internet connection and the right equipment. Not every agent was set-up to work remotely, successfully which required greater attention from contact center leaders. That said, contact center leaders found that when they showed up for their agents and put the right programs in place, their agents in turn showed up for them. 

“A flexible work environment for our call center employees was really attractive for them. Not just for full-time employees, but also part-time and seasonal employees, and giving our agents the opportunity to decide which shifts they wanted to work.”

Connected customer experiences are the way forward 

Customer expectations and standards are only becoming ever more demanding. Disjointed systems, departments and data not only impact operational efficiency, but frustrate customers with disconnected experiences. Technologies and processes that help connect the customer journey and reduce friction will become not just important, but critical for customer retention and “stickiness”. Having a fully integrated customer relationship management system and a contact center surfaced as key to creating more holistic customer service experiences.

Customer service should be proactive, not reactive 

Contact center leaders emphasized that soon, proactively resolving customer service or support issues, will not be a trend but a necessity. Traditional customer service has been very reactive whereby agents are incentivized to resolve customer issues fast and under an SLA. 

Thanks to AI and machine learning, automation technologies are empowering call center agents to resolve customer issues proactively by already identifying a customer’s problem when they call in, or through outbound tactics like notifying customers ahead of time that an issue has been identified, like a delayed order. When implemented correctly, AI & automation are perhaps the biggest gateway to unlocking proactive customer service, which is something we are very excited to be working on at Replicant.  

Automation is a competitive advantage

The digital transformation journey for enterprises has been a work in progress for many years, and automation has been at the forefront of this transformation. Business leaders are looking to new technologies that can help automate repetitive and redundant business processes to increase operational efficiencies and turn their contact centers into centers of excellence. 

Moreover, the digital transformation journey is quickly turning into a race – with customer service differentiating one company from the next – competitors that innovate and adopt the latest technologies to transform CX, the fastest, are quickly gaining market share. Leveraging automation to resolve Tier-1 customer service issues over the phone through voice AI is one such technology that CX leaders are relying on to deliver faster and better customer experiences to outperform the competition. 

“If you look at organizations doing high volume transactional outbound calls, like reminders or follow ups, those are calls that are very simple in nature where AI, machine learning or conversational interfaces can really be helpful to drive down costs.”

High touch and personalized experiences are in demand

With the advent of high-tech that has enabled contact centers to automate customer service processes, the demand for more personalized and human connections is also increasing. 

Call centers that have automated a fraction of their inbound customer service calls through voice AI have noted that call center agents have more opportunities to focus exclusively on delivering high-touch customer experiences with remaining callers, as a result. 

When Tier-1 customer service calls that can easily be resolved by AI are filtered out from phone calls fielded by agents, agents report feeling more empowered and motivated to provide personalized customer service to resolve complex issues that rely on their empathy and problem-solving skills. This partnership between AI and human collaboration is leading to more productive and satisfied agents as agents are able to do more of what they do best. 

Be sure to join our upcoming experiential events to get insights into how innovative CX leaders are disrupting the customer service space. And don’t forget to join our Virtual Chocolate Tasting & CX Panel on February 11th, 2021 to continue the conversation with like-minded customer service leaders. We cannot wait to have you there!

The post 5 “Top of Minds” for Customer Service Leaders in 2021 appeared first on Replicant.

AI helps cut costs and improve capacity as call centers downsize

COVID-19 caught many call centers flat-footed, unprepared for a sudden flood of calls and unable to train new agents fast enough to meet demand. According to an April survey of 250 business leaders, 64% of call centers reported downsizing their operations in response to COVID-19 — even as customer issues increased. Call centers who were able to temporarily boost capacity now find themselves overstaffed as customer service calls have leveled off. 

Companies with existing investments in Voice AI, however, found themselves in a prime position. Unlike human agents, Voice AI offers elastic capacity — the ability to ramp up quickly in response to demand and scale back just as fast. Replicant’s Voice Responder can quickly scale from answering 10 calls an hour to answering 1,000, a pure ROI impossible for human call centers. Pre-coronavirus, one company with voice AI reported an ROI of $39 million and a 30% reduction in misrouted calls, which means even more savings as call volumes increase due to the crisis. Some of the world’s largest call centers, including Vodafone, Verizon, and AT&T, were already using Voice AI to reduce costs. 

Leaders know that traditional call center layouts, which often require agents to sit near each other in open-office floor plans, put people at high risk for coronavirus —  as shown in South Korea, where one employee infected 97 other in a single-floor call center. Remote call center operations, meanwhile, have difficulties of their own, including customer privacy concerns and legacy technology that makes remote work difficult. As call centers face higher demand than ever, Voice AI can step in and bridge the gap.

Voice AI can help boost revenue, too

But as businesses face the world’s biggest economic downturn since the Great Depression, cutting costs alone isn’t enough: they still need to drive revenue. AI can help there, too, by improving sales and payment collection rates. 

In the same survey of 250 executives, 40% of businesses reported that sales would benefit the most from improved customer self-service, while 20% said that payments would benefit the most. If payments are difficult to make and answers hard to find, customers are less likely to pay their existing bills and much less likely to purchase again from the same company. By investing in self-service technology like Voice AI, which 78% of executives expressed as a priority. businesses can bolster their revenues in a time of economic uncertainty. 

As Amy Allen of CSG notes, there are also situations where humans prefer virtual assistants to humans who may judge them, like when discussing payment plans. Instead of feeling ashamed to call, customers are more likely to set up a plan and pay on time when they can speak to a helpful Voice AI.

Voice AI means higher-value, happier human interactions

Just as self-checkouts haven’t replaced grocery store workers and ATMs haven’t replaced bankers, Voice AI won’t fully replace humans. Instead, it will enable higher value human interactions, making human employees happier with their jobs and less likely to quit. Instead of answering the same questions on repeat, human agents will be empowered to deal with complex issues.

The extra call center capacity offered by Voice AI will also make human to human interactions more pleasant: a customer who’s been on hold for an hour is more likely to be confrontational than a customer whose problem was quickly diagnosed and routed to an agent. And when human agents have more time to help each customer, they can display the kind of human emotion and empathy that Voice AI can’t. As so many of us are grieving lost loved ones, lost opportunities, and the loss of life as we know it, a caring human on the other end of the line can make a real difference. 

Good customer service is like toilet paper: you only notice it when it’s gone. In the early weeks of the pandemic, as demand for toilet paper spiked, customer service calls spiked, too, resulting in unhappy customers around the world.

In the next wave of the crisis, Voice AI can’t help with the toilet paper — but it can make sure there’s no shortage of great customer service.

The post What’s the “Next Normal” for the Call Center? appeared first on Replicant.

Artificial Intelligence (AI)

Artificial intelligence (AI), in its most simplistic terms, is an area of computer science that gives machine’s the ability to mimic human intelligence and behavior. Whether it’s through using speech recognition to communicate, visual perception to recognize objects, or predictive analytics to identify and understand patterns in data, AI aims to simulate human-like qualities.

As Forbes author Bernard Marr wrote, “It’s no longer a primary objective for most to get to AI that operates just like a human brain, but to use its unique capabilities to enhance our world.” AI is not meant to just mimic human capabilities, but to improve them as well.

Voice AI

Voice AI allows humans to use their natural voice as an interface to ask questions of, give commands to, and perform tasks to communicate with machines. Today, voice activated machines can intake voice dictation, interpret it and execute short commands to reply to users. Humans are becoming more comfortable using their voice to interact with technology as devices like Apple’s Siri, Amazon’s Alexa, and Google’s Home Assistant gain traction. Voice is also the fastest and most interactive way to communicate with customers when it comes to customer service, but it’s difficult to scale as it usually means relying on call centers for high touch customer service. See how voice AI provides an opportunity to reimagine customer service for call centers with greater efficiency and scale.

Conversational AI

Conversational AI is often used interchangeably with Voice AI and typically describes chatbots. Chatbot magazine states, “A chatbot is a service, powered by rules and sometimes artificial intelligence, that you interact with via a chat interface.” Chatbots are generally designed with a defined purpose, whether that be helping a customer purchase a product, scheduling an appointment, or simply having “someone” to chat with.

We like to think of conversational AI as much more than just chatbots. Conversational AI is voice AI plus more – the more being the added element of natural, human-like conversations that make interactions with machines flexible. In order to have a conversation, a machine must be able to discuss back and forth with many turns, express thoughts, understand multiple intents and share contextual information. These qualities are what make human to machine communications “conversational”.

Digital Assistants

Digital assistants, otherwise known as “intelligent assistants” are computer programs designed to assist a user by answering questions and performing basic tasks. Humans can place an order, check the weather, or set a timer with digital assistants. Some examples of digital assistants include Amazon Alexa and Google Home Assistant for consumers and Microsoft Cortana for enterprise users. Voice assistants built into our mobile experiences such as Apple’s Siri or Android’s Mycroft can also be labeled as digital assistants.

In a study conducted by PwC, it was discovered that 18-24 year-olds have been the fastest to adopt and experiment with new voice technology features. Surprisingly, 25-49 year-olds utilize voice technology the most, and 65% of this demographic use voice devices once per day. Digital assistants have become widespread in our consumer lives and are setting the stage for fast adoption of voice AI and conversational AI in other areas of our lives like customer service.

Interactive Voice Response (IVR) and Interactive Virtual Assistants (IVA’s)

IVR’s are computers that use menu dialog systems to assist humans through voice and keypad recognition. Oftentimes they’re used in customer service calls and attempt to direct customers to the right agents, sometimes offering limited self-service capabilities. IVA’s are an evolution of the IVR with slightly more emotive characteristics. IVA’s make it “easier” to talk to the computer as you would a person by using aspects of conversational AI and voice AI. These solutions have come a long way but still have limitations when it comes to meeting the expectations of customer service which is why we’re so excited about upcoming advancements in conversational AI.

Virtual Agents

A virtual agent is an AI technology that’s designed to mimic the abilities of a human agent. This form of conversational AI is widely used for customer service. This term is occasionally used to describe a human agent that works remotely, but in the AI industry, you will almost always see it referring to a machine agent.

As UCtoday describes, virtual agents “go a step further by performing advanced customer service functions like giving customers recommendations. They can even answer FAQs, and help them find information needed to satisfy the reason they contacted support in the first place.”

Key benefits of virtual agents:

• Cost-efficient
• Provide 24/7 service
• Relieves human agents of overload by solving repetitive, Tier-1 customer issues
• Understands and records customer data
• Uses conversational AI for a human-like effect
• Trainable and consistent
• “Learns” and becomes more efficient over time

“Essentially, this technology can provide basic information to customers or employees, help guide the users through questions, and automatically reroute complex conversations or issues to an actual human agent if needed.”

AI is a cutting-edge technology that’s quickly integrating into our daily lives, especially when it comes to digital assistants and customer service. With every new breakthrough comes new industry terminology, and we’re here to help you keep it all straight. If you have any questions on industry terms or want to learn more about our own conversational AI technology, feel free to visit us at replicant.ai.

The post Your Fast and Easy Guide to Customer Service AI Terms appeared first on Replicant.

The digital age has brought about an era in which people expect nearly instantaneous gratification. The fast pace of the modern world makes people even more loathsome of the times when they are forced to a standstill. However, studies have shown that the limit of human patience isn’t a fixed duration but instead adjusts according to various factors of the situation at hand.

Let’s examine some of the factors of patience and their link to customer service.

Patience Factor – Confidence

It turns out that expectation plays a large role in a person’s willingness to wait for a payoff. In fact, a correlation between the certainty level of receiving something and how long people can stand to wait has been reported in this study on serotonin’s link to patience. The basic idea supported by this study is that the act of waiting for something is made more bearable if the person waiting has a high degree of confidence (roughly 75%) in actually receiving the reward.

This is important information for those in the customer service business as it suggests that providing a strong customer service experience that results in the customer ultimately ending the interaction satisfied with the outcome will increase their willingness to wait a bit longer for that quality experience. The more confident a person is that a pot of gold really is at the end of the rainbow, the more likely they are to keep walking towards it.

Patience Factor – Quality

McDonald’s recently challenged the patience of its customers when they first began testing a new product: fresh beef patties made to order. As outlined in this article from Huffington Post, their initial rollout of the new product was done as a blind test in some regions where customers were not informed that they would have a longer wait time but ultimately receive a better product at the end of the wait. The immediate result was frustration as customers were unexpectedly told to pull into a parking spot to wait for burgers that just a week ago would have come out immediately.

However, once consumers were told ahead of time that wait times would be slightly longer (about a minute longer on average compared to the frozen, pre-cooked product) but result in a tastier, juicier product that was made from 100% fresh beef, they were much more willing to wait.

This shows that consumers are willing to wait as long as the end result is worth the extra time. Consistently providing a great customer experience that results in positive outcomes will generate positive word of mouth and result in greater brand loyalty. The better the experience you offer, the easier it will be to gain and retain customers.

That doesn’t mean you can expect people to sit on hold all day long until you eventually provide a great experience. However, this does show that customers are willing to wait longer for issues that are of greater importance to them. This suggests that using automation to quickly address common issues would be ideal while problems with more weight to them are better resolved with a human touch.

Patience Factor – Speed

According to a Zendesk survey, 66% of B2B customers switch to new vendors after having poor customer service experiences. The same survey reported that a customer’s satisfaction with the customer support staff is most often directly related to how long it takes for their issue to be resolved. 69% of Zendesk survey respondents said that the speedy resolution of their complaints was an important factor in their overall satisfaction with customer service interactions.

Anyone who has ever been on the phone with customer support knows how tedious and frustrating the experience can be. General feelings towards customer service calls are so negative that they have been the subject of numerous stand-up comedy routines and rants over the years. Further exacerbating the negative association that people have with calling into support lines is the fact that people generally only speak with customer service when something is going wrong. This creates a sort of perfect storm of negative emotions where customers are already on edge and expecting to have a bad time right from the start.

Providing quick resolution times is no easy task for customer service call centers. Scaling up a call center to deal with customer traffic is expensive and doing so on the fly is nearly impossible using traditional staffing methods. One of the primary tools that is utilized to reduce the average resolution time is an interactive voice response (IVR) system. The promise of the IVR is the ability to answer every call as it comes in and begin the process of addressing customer issues.

IVRs: The Imperfect Solution

IVRs attempt to resolve simple issues quickly but are generally ill-suited for tackling issues with even the slightest bit of nuance. Traditional IVR solutions are more about creating the illusion of quickly addressing a customer concern rather than actually solving the problem. In an ideal world, these systems would scale to sudden influxes of customer concerns and reduce the overall response time of a call center by resolving simple issues without requiring a human agent to intervene.

However, these systems have earned the ire of customers across the world with their slow response times, poor voice recognition, and grating robotic voices. According to a survey conducted by Vonage in the UK, 54% of consumers believe IVR makes for a poor customer service experience. The most common emotion respondents associated with using IVR systems was frustration. 37% of respondents cited unnecessarily long IVR menus as a primary point of consternation while 35% felt like the systems wasted their time.

Clearly, speed is an important factor for keeping customers happy. Unfortunately, IVRs don’t actually reduce the time it takes to resolve a customer complaint. Instead, they essentially act as an arguably more aggravating method for putting customers on hold. This is why we made it our mission at Replicant to craft real conversations that go far beyond what a standard IVR can do.

We use the power of artificial intelligence and machine learning to provide next-generation, Conversational AI on the phone (AKA virtual agent) that is capable of holding real and complex conversations that do not waste the customer’s time or place a strain on their patience. Our service uses natural-sounding text-to-speech technology combined with machine learning to provide an unrivaled customer service experience. Since we deploy machines to answer those transactional calls, customers benefit from no wait time and a much shorter call compared to a call with an agent.

Replicant is capable of addressing common customer issues while gathering pertinent information for more complex issues which is then passed onto human agents. This saves customers time and frustration by never requiring them to repeat themselves while also saving customer service agent’s time by giving them access to the information they need to quickly get to the bottom of the problem. Replicant provides your organization with the ability to increase the quality of your customer service interactions while drastically reducing resolution time—saving you resources and improving brand loyalty in one stroke.

The post Patience Factors and Customer Service appeared first on Replicant.