“AI is starting to deliver on its potential, and its benefits for businesses are becoming a reality,” says Svetlana Sicular, VP Analyst, Gartner.
Two areas where we see an increasing deployment of AI-based applications are customer service and marketing. In marketing, it’s used for a more personalized and automated communication, while in customer service, AI allows for a more efficient handling of service incidents, thanks to intelligent advisors that support both agents and chatbots.
And the prevalence of such technology is only expected to rise. In fact, Gartner predicts that 70% of customer interactions will involve emerging technologies such as machine learning applications, chatbots, and mobile messaging by 2022, a stark contrast to just 15% in 2018.
Let’s take a closer look at how these technologies can have a positive impact on the customer experience (CX) across customer service, marketing, and sales.
It’s estimated that the chatbot revolution is only in its infancy. According to Verified Market Research, the Global Conversational AI Market is projected to reach $18.02 billion by 2027, thanks in part to the reshaping of omnichannel deployment methods and the low cost of chatbot application. Chatbots are of undeniable interest for customer relations as they make it possible to simplify and speed up the search for information while providing precise and personalized answers.
Users no longer have to search for information on a company's website. They can simply interact with the bot through a discussion interface that’s already familiar to them. Linked to the company's information system, the bot accesses the client's files directly and can therefore provide a personalized response. This has the double advantage of increasing customer satisfaction and optimizing customer relationship management by reducing the need for human advisors.
For example, illycaffè “added a chatbot built with Oracle Digital Assistant technology to enable the most digitally savvy customers to text their questions about product features, availability, and pricing to the chatbot through a portal in the website,” Oracle’s Linda Currey Post shared with Forbes. “Human customer service agents then take any questions the chatbot can’t answer. After replacing its product-oriented, ecommerce website with a site focused on a more customer-oriented ecommerce experience, illycaffè boosted company revenue by 24% during the first 18 months.”
Employee satisfaction is another key component in providing a positive customer experience, and Hilton is one brand that has recognized that the experience they offer their employees is just as important as the one they provide to their customers. The chain, which has tech innovation in its DNA, meets these employee expectations with a number of digital technologies, including chatbots.
As Oracle’s Emily He shared in Forbes, “Hilton employees use digital chatbots to answer common questions. These repetitive tasks are well-suited for automation, freeing up more time for the HR team to spend on high-value tasks that require white glove human service, thus increasing customer satisfaction and loyalty.”
Such analytics also benefit direct-to-customer brands by helping them personalize their messaging and communications. One great example is Nespresso, which has embedded IoT sensors into some of its coffee machines. The sensors are designed to capture information on each user’s most used capsules and drinking habits, which the company can then use to personalize its offers to each person’s preferences.
Another Nestlé brand, Nescafé Dolce Gusto, uses Oracle’s cloud-based email marketing application to reach, convert, and cross-sell to consumers worldwide. Oracle Eloqua Marketing Automation makes use of AI for send-time optimization, fatigue analysis, subject line optimization, and more. NDG has doubled its email opt-in customers to six million, increasing overall buying frequency and helping sell new flavors in countries where NDG piloted a loyalty app.
Winning customers is about getting to know them as individuals by understanding and anticipating their needs. To retain them, companies must offer a level of service that will create satisfaction. Artificial intelligence helps with both.
Many confident sales representatives will insist they don’t need AI to be successful; however, a percentage of every sales force typically performs below expectations for a time because they’re inexperienced, new to the company, or have a sales territory that’s too large to handle. Applications that can guide them with intelligent recommendations to focus on the most valuable prospects at the right time will make a substantial difference. And the bigger the territory, the more effective this extra help can be.
Machine learning-based CRM selling tools center around clean, complete customer data from internal and external sources that sellers can trust. Leading European biotech company QIAGEN, dedicated to driving digital acceleration across the entire value chain, recently provided valuable insights on how they use machine learning to guide their roughly 1,000 sales representatives around the world.
At a virtual event hosted by Swiss business media Finanz und Wirtschaft, Dr. Thorsten Harzer, Vice President and Head of Digital Accelerator, explained how QIAGEN uses AI to “supercharge their field sales force” and generate additional revenue in the millions.
First, they compiled all the data they collected from Oracle Eloqua and other sources and consolidated it into a single data lake. Next, they sat down with their sales reps to find out how they prepare for a sales pitch and which data signals they use to detect additional demand. They could then translate these best practices into algorithms, the core of their AIMS framework (Artificial Intelligence in Marketing & Sales).
The entire sales force began to receive alerts and tasks driven by the algorithms, and based on their reps’ feedback, the QIAGEN team was able to further improve the algorithms and compare alerts to ultimately limit the notifications to only tangible and actionable insights that reps considered a true value add.
In addition, QIAGEN also compares their customers’ buying behavior with typical workflows of similar customers, performs a gap analysis regarding their share of wallet, and makes recommendations about additional items to sell (and at what price level) based on geography and competition to help close the gap.
Done the right way, ML and AI not only lead to extra revenue and profit, but they can also improve your reps’ employee experience, which can only lead to a better customer experience overall.
To fully realize the potential of machine learning and artificial intelligence and deliver the best possible customer and employee experiences requires access to comprehensive customer data in real time—a customer data platform (CDP) that can provide a single source of truth. Then, no matter who accesses the data—whether one of your sales reps, customer service chatbots, or an employee from the back office—customers will receive the personalized experience they’ve come to expect and employees can make each and every customer interaction matter.