How generative AI is improving customer experience and service calls
Generative AI and large language models are making customer experience platforms more accessible and humanized. These advances in recent months build on years of AI development that customer service and experience company NICE has put into their experience software. The company unveiled generative AI use cases at this week’s NICE Interactions event in New York. Enlighten Actions and Enlighten Copilot use OpenAI generative models added to NICE’s AI-for-CX Enlighten platform. “It makes applications broader and more easy to get to,” said Barry Cooper, president of NICE CX Division. Using AI for customer service calls helps agents serve customers more efficiently. It also makes customer data available to inform experiences and actions across the customer journey. “We started in service, but once you go to digital, you quickly go into ‘async’ (asynchronous communication),” said Cooper. “The moment you go to digital, async — WhatsApp and those kinds of things — the likelihood for an interaction to last for days, weeks, years is much greater. And then the likelihood of something that started as service to move to sales or other things is much greater because you have this open channel of communication [with the customer].” Why we care. In the wave of new generative AI products and features for martech applications unleashed since OpenAI’s launch of ChatGPT, it’s easy to forget the history of chatbots in customer service. Marketers now look to use generative AI and large language models to help them navigate a CRM or ramp up production of marketing content across the entire marketing org. However, CX and customer service remain critical sources for getting to know customers better and retaining them with better experiences. Enlighten Actions and Copilot features. NICE’s Enlighten AI offerings have already been on the market for three years; NICE’s CXone for eight years. By implementing these platforms, organizations move from having to manually spot-check customer service calls for quality and training to having 100% of customer interactions ready to be analyzed and acted on across the organization. As a result of adding generative AI, Enlighten gives consumers access to self-service as effective as the best agents, Cooper said. And it gives call agents “super powers” by solving more customer issues quickly with easy-to-use dashboards that help generate solutions. For instance, if a travel customer has a canceled flight (as many attendees in New York had with the Canadian wildfire smoke that fogged up the city), an agent would have hotels generated in their dashboard which they could then offer to book for the customer. And at the supervisor level, managers can easily spot trends and see that many customers in New York were having the same problem. Generative web content. Enlighten Actions will also identify common problems and generate web articles and publish them automatically. They will be search engine optimized so that they come up as a top search in a search engine. These articles then serve as another self-help tool for customers who search on Google first instead of searching for clues on the company’s homepage or messaging a live agent or chatbot. The end goal for these automatically-created articles is to help customers and cut down on call volume, but they have potential for broader content marketing uses. Data payload. Generative AI helps make interactions more conversational, but the deep knowledge about customers comes from interactions with them through Enlighten and through knowledge within the organization. “The payload is knowledge,” said Cooper. “We didn’t go to the Internet to get that knowledge, it doesn’t exist on the Internet. If you’re H&R Block, and [you create an article] ‘How to solve this tax issue’ it’s very specific and doesn’t exist on the Internet.” The Enlighten platform applies AI to hundreds of stages in the customer journey that are mapped out in their previous and ongoing platform CXone. This means that marketers have an effective way to identify opportunities across the customer journey, based on what a customer shares during a conversation with an agent. Additionally, marketers can draw on customer data elsewhere within their stack — from a CRM for instance — to add more context when a customer calls or messages. Dig deeper: How CMOs should respond to ChatGPT’s marketing impact Disney ups sales. Disney uses a number of NICE CX solutions and was among the number of companies present at the New York conference. Disney was able to identify and measure trends in agent calls and improve strategies that led to sales. Craig Nordengren, a system integration and development manager at Disney, was tasked with using the technology to improve the sales of “Magic Moments” photo sessions that visitors to Disney World can purchase for an extra cost. A full analysis of calls showed that when agents mentioned “Magic Moments” to a customer during a call, this was more likely to lead to a sale. Nordengren implemented an incentive structure not just for more sales, but for more mentions of “Magic Moments” by the agents. Disney could then see the improvement of individual agents by having a running count of how many more times the agents said “Magic Moments.” “We make sure that these are actions agents should be able to accomplish, but it’s a little bit of a stretch, so they can do it,” said Nordengren in a session at the conference. “And then we go into analyzing the performance and making adjustments, and this process keeps going over and over again.” The advantage of using AI is that as processes repeat, the models get smarter and more insightful about the specific business that uses it.
How to accelerate your marketing career using generative AI now
Generative AI is a high-value, additive capability for marketing, not a replacement for talent. The elimination of marketing roles and jobs is reactionary. Proving the point: 81% of marketing leaders say gen AI won’t reduce team size, according to a May 2023 Norwest Ventures generative AI survey of marketers. Nearly one in five respondents in this same survey expect to hire more people to take advantage of generative AI capabilities. However, marketers who don’t dive in and embrace AI to elevate their work risk falling behind in their careers. The best marketers are getting on their front foot right now, figuring out how and where to apply generative AI and all its variations. AI will advance your career if you understand where and how to apply it. Dig deeper: 5 ways to harness AI in B2B content creation For historical context, we turn to tech innovator and investor Marc Andreessen: “We had two such anti-technology jobs moral panics in the last 20 years — “outsourcing” enabled by the Internet in the 2000s, and “robots” in the 2010s. The result was the best national and global economy in human history in pre-COVID 2019, with the most jobs at the highest wages ever.” It’s not your replacement AI and all its derivatives (machine learning, natural language processing, etc.) is the fastest, biggest shift I have been a part of in my lifetime. In fact, the market will grow twentyfold to $2 Trillion by 2030, according to Next Move Consulting. The AI revolution screams career opportunity. Software providers are bringing new AI tools and adding AI capabilities to products marketers use every day. Applied thoughtfully, generative AI is having an immediate impact helping marketers and teams save time, increase efficiency, and enable new capabilities. Staying ahead and adding key skills are required to deliver more value as a marketer amid the AI boom. However, to truly adapt, we need to comprehensively understand exactly where and how it’s going to impact our roles and responsibilities. Reiterating, the best advice here is to dive in. Taking lessons from significant transformations including the rise of the Internet (1990s), the proliferation of mobile (2000s), and the adoption of marketing technology (2010s), here are three essential applications of AI in marketing. 1: Shorten research and planning cycles Marketers are using AI to quickly compile market trends and data required for GTM planning and execution. They are also automating the packaging and dissemination market and customer insights to your product, campaign, comms, and sales teams. Robotic processing bots can create apps quickly to automate everyday tasks from report generation to website updates to checking and improving content. Last week at a marketing summit, I heard the phrase “Generative AI is the new intern.” 2: Create content in all formats your customers use Content creation and enhancement is the No. 1 application of generative AI for marketers. Marketers are using AI to create foundational content such as educational blogs and articles, SEO optimization, social media posts, newsletters, and time-consuming product documentation. The ability to create video from text and vice-versa has been a game changer to offer audiences and customers choices for content consumption. AI-generated content also frees up time to create specialized content — signature storytelling and value-creation content pieces that help differentiate your company and solutions by providing more profound value to your prospects and customers. These generative AI-enhanced capabilities all deliver on your B2B customers who want self-serve research and content consumption before engaging with a sales representative. 3: Deliver new levels of personalization and experiences Data is key in understanding, engaging, and delighting your audiences and customers. AI makes it easier to sort through vast amounts of big data from more sources with AI playing the role of the efficient processor, synthesizer, and analyzer. AI can also help marketing teams build the right messages for the right audiences at the right time, delivering new levels of personalization which is critical to developing long-term customer relationships and impressing prospects. With more data processed faster and AI’s capability to track patterns that no human can identify, marketers can drive enhanced one-to-one, tailored experiences delivered across multiple channels such as social media, email, text, and websites. Be proactive and experiment with AI now AI tools and applications abound today. You can elevate your knowledge of the use of generative AI quickly because generative AI is so accessible. To jump in and advance your practical knowledge, compare notes with peers on what they’re using and doing, and tap into your formal and informal community of pros you trust (LinkedIn, GTM Insights, Pavilion, Propolis to name a few), and follow valuable resources like @MarTech. Or simply prompt your generative AI-powered search tools to understand how these tools are progressing. Sometimes, your company may not support using AI or limit access based on policies. No worries. There are so many tools to use in your everyday life that will help you get up to speed to understand how AI works and what’s possible. Many of these apps have free versions you can use and experiment with. And, it should be said that if your company leaders aren’t encouraging the experimentation and adoption of generative AI, it may be a sign your career prospects may be limited. Something to factor into your career plans. No excuses. Let’s go!
Publicis Groupe joins human vs. AI content verification initiative C2PA
Global marketing and communications company Publicis Groupe announced it will join the Coalition for Content Provenance and Authenticity (C2PA), an initiative aimed at providing a framework for authenticating human-produced content. Publicis Groupe, one of the “big four” agency companies, will serve as a Steering Committee member for C2PA. Steering Committee founding members include Adobe, BBC, Intel, Microsoft and other media and tech firms. Why we care. Generative AI products and features have flooded the market this year following OpenAI’s release of new ChatGPT models. Content creators and the companies that employ them are concerned that generative AI will use assets created by humans without attribution or compensation. This compromises the business model for publishers and agencies while potentially exposing brands and other organizations that use content to liability when using protected intellectual property without knowing it. Content authenticity. The C2PA was launched in 2020. Its aim is to build and standardize a framework for content verification of human-made assets and authenticating the provenance of assets used by AI. The organization successfully implemented the C2PA Specification, which verifies original content such as photos, video and audio. These assets maintain a provenance attached to them to which future users can refer. For instance, an image shot by a freelance photographer will be listed as an original source, followed by a publisher like The New York Times, who paid for the image’s use. This framework, if adopted widely throughout the content supply chain, will expose those assets that don’t have a verifiable provenance. “The C2PA’s efforts help protect that invaluable IP and ensure authentic creative visions are brought to completion — and verified along the way,” said Carla Serrano, Chief Strategy Officer, Publicis Groupe, in a company statement. “And people can feel confident knowing that the content they’re viewing is unique, original and straight from the source.” Responsible AI use. Participation in C2PA signals an effort by major content, communications and tech companies to set standards for responsible AI use. Many of the Steering Committee members have created AI tools of their own. Publicis Groupe created a portfolio of tools, including Marcel, an internal custom-made AI platform used by its 98,000 employees. And earlier this year, Adobe introduced Firefly, a suite of generative AI tools for content creation. C2PA has also joined forces with other partner organizations, including the Microsoft and BBC-led Project Origin Alliance and the Adobe-led Content Authenticity Initiative (CAI). Dig deeper: 3 ways B2B marketers can use generative AI
How to create a knowledge base for marketing work management
Marketing work management tools can benefit your organization in a number of ways, including adding productivity and efficiency. They also help manage teams that work remotely. But with all of these capabilities, it’s important that team members know how to use them. Building a knowledge base for your marketing work management system is essential to making sure everybody using it is on the same page. Here are some tips on what to include in your marketing work management knowledge base. “The knowledge base…is for your team and any collaborators in the tool so that they can reference at any time instructions and guidelines on how to use the tool best,” said Brianna Miller, director of marketing and demand generation at healthcare compliance analytics company Protenus, at The MarTech Conference. The marketing work management tool is important for adding projects, submitting them for approval and sharing other important updates. Communications related to projects should be done, in most cases, within the work management tool. If a project request or another project-related update comes in through another channel, there should be guidelines in place on when to leave these updates where they are and when to add them to the marketing work management tool. Here is an example of guidelines to follow. Your organization might use email or messaging apps like Slack differently, but this is at least a good place to start. Guidelines on how a task or project can be initiated You should also have specific guidelines on how a project can be initiated. These guidelines should be broken down by channel. Provide examples on how requests should be handled when they come in via: Email. Slack/Teams and other messaging apps. A meeting (virtual or in-person). Request forms. Dig deeper: How to decide if you should get a marketing performance management platform Guidelines on who can create a project and change key project information “Have guidelines on who can create projects and change key project information,” said Miller. “This small thing can make a big difference because then there’s one ownership and there is one person who knows when the due dates are and when the project might be changing.” Set up naming conventions for projects and tasks Clear titles help team members understand the kind of task they are looking at in the marketing work management tool. This saves time and helps avoid errors. “As great as any search functionality is, and any tool, creating clear titles will save your team so much time,” said Miller. Your organization’s naming convention might consider using a “drill down” method, which proceeds from more general terms to more specific words about individual projects. Here are some other rules to consider adopting for your team’s naming conventions: Use numbers and dates in the title. Add context by naming the department and project type. Shorter is better. Use verbs to designate task-related actions (write, design, draft, review, etc.). Guidelines on processes in the system Include guidelines on processes in your knowledge base so team members know how to go about completing tasks and projects. Also, clearly define the difference between tasks and projects, and be specific about what processes apply to the task level versus the project level. Here are some examples of guidelines on processes: All work should be documented in the task description. The comments section should be used if something specific to the task needs to be discussed. Only if the question is related to the project as a whole should comments be made on the project level. Once work is ready for review in the task with attachments uploaded, mention team members who are required for review and change the status of the task to “In Review.” Once the review process has been completed, the task owner will change the status on the task to “Complete.” When a project is completed, the Project Owner should move the project to the appropriate “Archived” folder. Register and watch The MarTech Conference here.