Reimagining artificial intelligence for an omnichannel world

State of AI in omnichannel world

Great customer experiences are built on great customer journeys but in an omnichannel world, journeys can easily lead to wrong turns. For example, in self-service, 80 percent of customers will try self-service first, yet Gartner estimates that only nine percent of inquiries are resolved in self-service.

In the past, this misalignment between customer demand and customer outcome was not understood. A business may have seen fewer sales, but it was not easy to identify why.

Today, CX practitioners know the secret to creating a positive customer experience lies in the vast amounts of complex data their omnichannel contact centers generate. They know customers want quick responses about their orders, useful information on products and availability, or reassurance on their transaction. These simple service issue needs, however, often remain unidentified and unaddressed.

This report explores how data can be used to proactively enhance the customer journey and experience through the application of AI-based tools. The report examines how such tools can analyze omnichannel data and address recurring and frustrating customer pain points with intelligent routing and frameworks that support empathy and understanding between agent and customer.

Featuring insight from Fifth Third Bank, Solera, Netflix and Payoneer, it covers the key industries where simple service issues are costing dear.

“Through analytics we can share with our regulators that we’re going the extra mile when it comes to ensuring we’re following their guidelines and regulations.”

Kevin Anderson

Speech analytics program manager at Fifth Third Bank

The modern, omnichannel world

A proliferation of new communication technology and channels has seen automated, intuitive and autonomous customer support become a standard for every organization.

In CX Network’s Global State of Customer Experience Report 2022 more than half (52 percent) of survey respondents said customers want self-service options. Elsewhere, automation and channel integration were both top 10 investment priorities for the year.

According to a survey conducted by Aberdeen Strategy and Research, half of all contact centers now utilize nine or more contact channels, including phone, email, SMS, online messaging platforms and social media. An omnichannel operation of this magnitude generates an unprecedented inflow of data, which requires management and investment.

Also read: Omnichannel experts insights ebook

Tools based on artificial intelligence (AI) can utilize vast amounts of data, encompassing everything from initial web search to intent and likely outcome to paint a real-time picture of customer needs. This means CX leaders must remain mindful of the need to ensure the quality of their data is high enough for analysis on customer preferences, purchase history and journey to date. They must then strategize how these insights will be mined and select tools to do the job.

The original pioneers of great, data-based, omnichannel CX – the likes of Amazon, Netflix and Apple – utilized AI to build their own tools to tap omnichannel data and gain a deeper understanding of business and customer needs.

Lauren Maschio, senior team manager of product marketing for NICE, says: “The common thread across these innovators, regardless of industry, is that they raised the CX bar by using their omnichannel data to become smarter and offer something better, by embedding AI as the core brain that makes every touchpoint smarter.”

Today, the availability and application of AI-based tools is widening the gap between those who deliver a first and second-rate experience. Those who follow often deploy CX innovations through dedicated projects and departments. Those who lead, deploy across teams as part of an organization-wide initiative.                               

Figure 1

US-based healthcare insurance provider

As Saki Takeda, director of product management at Netflix, says true omnichannel is about integration of data, teams and experiences.

Takeda says: “It is important to think about data more holistically and prioritize investments in building a strong data infrastructure that will surface 360-degree customer views and provide end-to-end visibility of customer journeys and experiences.”

Takeda says further steps should be taken to ensure automated systems are not delivering conflicting communications or services.

The role of AI

Organizations that are data-driven create a better overall experience: they can personalize services, prompt stalled journeys and inform and empower their agents. But there is, quite simply, too much data.

In response organizations have turned to tools which use AI and machine learning to analyze past events, predict future outcomes and, crucially, inform the necessary response. This has seen widespread adoption of smart omnichannel routing, a gamechanger for intelligently connecting customers to service agents and creating hyper-personalized experiences that drive efficiency across back-end and customer-facing operations.

In 2016, the largest health insurance provider in a populous southern US state took this approach when looking to improve its member experience and operational efficiency (see page 3).

It deployed NICE Enlighten AI to focus on predictions that maximized the effectiveness of its existing resources. Behind the scenes this reduced ATT by 24.8 percent, allowing 1,500 agents across three divisions to work smarter without any training.

Members received a more personalized and timely service as the tool streamlined conversations with better matches, reducing members’ effort to get the assistance they need for intensely personal healthcare.

Identifying pain points

Standard customer satisfaction surveys often fail to capture which areas of an experience are affecting overall satisfaction.

Fifth Third Bank had traditionally depended on surveys to track customer sentiment but knew they lacked substance. They were disproportionately weighted toward one customer segment, limiting the visibility into service issues. Furthermore, they produced only a small sample size of subjective responses and demographic data was not grouped effectively. (see Figure 2)

Figure 2

Fifth Third Bank

The US-based bank had had little visibility on customer sentiment, how agents were shaping individual experiences and the further training agents required. Yet it had an ambition to rise to the top of an independent third-party CX ranking and improve its internal satisfaction KPIs. The bank also wanted to gain improved understanding of customer intent, both in the moment and over time.

With the focus now on customer-facing technologies that could support these goals, in 2021 Fifth Third Bank extended its use of NICE Nexidia Analytics and added Enlighten AI, which had previously been used to analyze only a fraction of the overall agent pool.

The full-scale speech metrics and analytics deployment covered the full consumer banking team and expanded to dispute resolution, collections, commercial clients and retail direct sales. It further saw agents trained to understand the full scope of the project, technology and its benefits. By the end of the year, customer sentiment was the bank’s leading CX metric.

Kevin Anderson, speech analytics program manager at Fifth Third Bank, says: “We have found the teams that inundate sentiment into their culture perform better.”

Anderson adds: “Enlighten AI analyzes every interaction and provides additional intelligence on agent behaviors for more effective coaching conversations that improve the customer experience. Our goal is to be number one from a customer experience standpoint.”

When Fifth Third Bank worked with NICE to deploy AI-based speech analytics it quickly ascertained that more than 100,000 calls a month were from customers who needed help logging into online accounts. Using the tool to improve the customer journey, the bank updated the language on its website and saw call volume decline significantly.

Also read: CX in retail 2022 with AI and automation

Looking ahead, the bank plans to expand the use of speech analytics to support compliance and risk management goals.

“Through analytics we can share with our regulators that we’re going the extra mile when it comes to ensuring we’re following their guidelines and regulations,” says Anderson.

The next part of this report examines the importance of real-time omnichannel interaction data and analysis. With a real-life example from the financial services industry, it explains how effective analysis can identify and address costly service issues.

The omnichannel customer journey

As Bain & Company explains, the customers’ journey is the sum of all the experiences that occur while interacting with a company or brand.

To create a competitive experience in the digital age, the customer journey must be non-linear and hybrid, with digital touchpoints and channels incorporated alongside the traditional. It must also be a constant work in progress to account for upgrades, new channels, new customer demands and redundant processes.

Shirley Campbell, customer experience director at financial services company Payoneer, says: “Digital experience investments must be made around the core of CX. When customers choose our digital channels, they look for easy, simple, personalized, fully self-service experiences. They do not care if your chatbot has the best AI or NLP engine if the bot is not designed with the right tone, personalization or simplicity.”

Campbell continues: “If your company is looking to stay up to date with digital CX trends, I strongly suggest making it about choice. Focus on personalization, on end-to-end self-service and automation that will simplify the process for customers and reduce their efforts while interacting with us.”

In CX Network’s 2019 Global State of Customer Experience report, customer journey mapping was the number one investment priority for the year ahead. By the 2022 edition it had dropped to fifth place behind digital customer experience, CRM, customer insights and automation.

According to Ashley Lickenbrock, CX strategy lead at Bayer Crop Science, this indicates a reprioritization of resources in responses to the increased sophistication of tools to support journey management and analysis.

She says: “If, in 2019, companies focused on investing in CJM management tools and baselining, and they have been iterating since, it would make sense to me that more money is going into enabling those journeys via automation and digital.”

“If your company is looking to stay up to date with digital CX trends, I strongly suggest making it about choice. Focus on personalization, on end-to-end self-service and automation that will simplify the process for customers.”

Shirley Campbell

Customer experience director at Payoneer

To map and refine an effective digital journey real-time data from every customer touch point must be gathered and analyzed. With the right analytical tools, it is possible for a company to see its products and brand through the eyes of its customers.

For the omnichannel organization this means continued analysis of channel use and likely preference to tailor communications in-line with the personalization demands of customers.

Identifying service issues

Such reflection often uncovers service issues, such as the 100,000 customer calls experienced by Fifth Third Bank (see page 4). These drain time, money and customer loyalty, and can see further problems emerge in other areas of an organization.

NICE’s Maschio says: “Service challenges can encompass product, process and agent skill issues. AI can be used to perform omnichannel analysis to uncover and understand problems in each of these areas that impact the customer experience.” More than 80 percent of customers will try self-service first, yet Gartner estimates that only nine percent of inquiries are resolved in self-service. This means that 71 percent end up in live service, which costs 100 times more than self-service.

Maschio says: “AI can analyze historical conversational data from voice and text interactions to identify and prescribe the best self-service opportunities with the greatest ROI, making it easy to know where to focus. This data-driven approach helps organizations increase self-service containment and decrease costs for human-assisted channels,” she adds.

Analysis at this level can also be an effective user-testing tool when new channels are deployed.

Holistic omnichannel journeys with AI

Beyond the basics of customer age, demographics and purchase history, omnichannel AI tools can take into account three important and interrelated components:

• Customer behavior: how customers think, feel and behave in relation to the organization and its products, including sentiment, loyalty, benefits sought and purchase patterns.
• Interaction history: a record of each touchpoint between the customer (or potential customer) with your organization, including both virtual and human agents, as well as the company’s social channels and websites.
• CX events: activities along the customer journey, such as abandoning a cart.

Each of these influences the other and must be considered to gain a holistic picture of the customer. Omnichannel interaction data allows the contact center to provide a unified experience across agent-assisted and self-service, voice and digital, as well as inbound and outbound channels.

Also read: Five CX trends in retail

The next part of this report examines how agents can leverage omnichannel analytics to engage with customers while driving their own professional development and job satisfaction.

Informing interactions

After the great resignation many enterprises are settling into the realities of working with new leaders and colleagues and ensuring they stick around. As reported in CX Network’s Global state of customer experience report 2022, employee engagement was listed as a top 10 trend for CX practitioners for the first time in 2022.

This increased focus on the employee experience has seen organizations race to create positive cultures, present their teams with new training opportunities and invest in new tools to make their work more engaging.

Claire Hill, CX Network advisory board member and customer experience director for Studio Retail Ltd, says: “Better tools that drive better employee experiences are generally driven by an employee-centric culture that is adopted by the business and permeates throughout it, including in product design. In this way, attrition is reduced through better colleague experiences because the end-user experience is consistent with the company values.”

The need for high-tech and effective tools will continue to grow in importance as younger generations comprise a larger share of the global workforce. It is estimated that Gen Z, the second generation of digital natives, will comprise 27 percent of the workforce by 2025.

Happy agents = happy customers

Productive and positive customer interactions can boost employee engagement, setting the scene for more positive interactions and less employee and customer churn. A key component for this success is data.

NICE’s Maschio says: “Contact centers can empower agents to deliver exceptional service while reducing costs with an AI-based real-time interaction guidance solution. Agents receive contextually relevant guidance while interacting with customers on processes, compliance, and behaviors to improve their performance. The result is that interactions are shorter, responses are more consistent, and friction is reduced.”

When it comes to manual notetaking, advances in automation and AI mean that contact centers can now automate agent summaries with high levels of accuracy, capturing all relevant customer intents, actions and outcomes on all interactions. This reduces costs and results in less post-call work and lower average handle time, in addition to increased agent productivity.

The informed agent

As detailed earlier in this report, omnichannel data is a powerful tool and is fueling the AI engines that inform agents in the contact center.

Customers that have reached the contact center through self-service often have more complex problems to solve. Here, AI can present omnichannel data to the agent to provide greater context and knowledge of the problem and allow them to provide personalized service.

Automotive software company Solera was looking to upgrade its administrative services to put its data to good use and boost the overall customer experience. It deployed Enlighten AI for sentiment and agent behavioral analysis to improve employee engagement and performance.

Sarah Blair, VP operations – North America at Solera, says: “It is truly an amazing thing what data can do to achieve results more consistently.”

She adds: “The only way to do this is to have the data and information available quickly and effectively. You need the machine to help you identify what to coach on. Enlighten can tell me exactly what my reps need coaching on, so it is individualized, helpful, productive, positive and continually tracks their improvement. This means we are able to reward and incentivize those folks for the great behavior they’re capable of giving.”

The company’s 1,000 representatives achieved a 13 percent improvement in customer sentiment in 60 days and the company saw a cultural change that opened up development opportunities for representatives.

“It is truly an amazing thing what data can do to achieve results more consistently.”

Sarah Blair

VP operations – North America at Solera

Conclusion

With the average omnichannel operation now utilizing nine or more contact channels, customer-facing organizations see massive inflows of complex data every day. While this creates a challenge for the IT department, it presents a significant opportunity for those in CX.

Omnichannel data is a treasure trove of customer insights waiting to be mined. It can reveal digital dead ends, enhance the employee experience and better measure overall satisfaction.

The appetite to mine this data is growing. As CX Network’s research demonstrates, recent years have seen CX practitioners and leaders reprioritize their investments to focus on customer journey data and analytics tools.

In doing this they have sought to understand their customers’ sentiment, activity and intent, but not every project is a success. Some projects are deployed in siloes, some lack the financial support for agent training while others fail due to the quality of data.

As the case studies in this report detail, AI-powered tools analyze speech, text, customer journey, customer sentiment, agent behavior and desktop activity. They can also deliver where previous projects have not.

The organizations leading the way take this a step further by weaving the data collected from each channel into different channels to discover how the hybrid human-digital interaction can be further refined. In an omnichannel world it is the secret to creating an exceptional customer experience.

Read the PDF report here