In today’s fast-paced world, automation has emerged as a revolutionary force reshaping the technological landscape.
From self-driving cars to intelligent virtual assistants, automation is rapidly permeating various industries. Because of its increasing popularity and the importance it plays in streamlining processes and reducing costs, it has become a critical part of many organizations’ digital transformation strategy.
So far, enterprise automation has been mostly reactive. It has been implemented as a piecemeal, noninvasive method to automate routine, repetitive tasks, and structured processes and data. Business drivers, goals, and means for business processes, IT operations, and software development of enterprise automation have expanded for the next chapter of the digital journey.
According to IDC’s Future Enterprise Resiliency and Spending Survey, Wave 1 (January 2023), 30% of organizations are more than 50% done with their automation goals for their front office businesses.
The promise of automation means we will continue to see new use cases pop up. This is particularly evident with the ever-increasing amount of data that organizations need to compile, organize, and analyze. B2B buyers’ expectations for agility, flexibility, and the ability to roll out new products and services quickly have also pushed companies to embrace automation.
Digital journeys and automation are now the dynamic duo that will run a viable digital business at scale.
Rapid innovation in AI-assisted automation adds another layer of possibilities to what can be accomplished. Below, we’ll discuss a couple of ways in which automation is being used today to deliver a better customer experience overall.
Personalization at Scale
Automation plays a crucial role in the ability of businesses to tailor and customize customer experiences, communications, and offerings. Starting with data collection and analysis, automation streamlines the process of gathering customer data from multiple sources such as website interactions, purchase history, social media activity, and customer surveys.
The use of artificial intelligence (AI) and machine learning (ML) within automation enables algorithms to extract meaningful insights from the data gathered and make informed decisions. With automation tools, businesses can create and update customer profiles. Data is incorporated from various sources in real-time. These profiles give businesses a holistic view of each customer, allowing them to effectively customize their experiences.
Automation tools can also help organizations generate and deliver content in real-time. From personalized product recommendations based on browsing and purchase history to email marketing campaigns based on customer segmentation, dynamic content delivery ensures that customers receive relevant and engaging information that resonates with their specific needs.
Enterprise automation means artificial intelligence continuously supports decision-making and automated actions that proactively optimize and enrich outcomes. This process spans across the entire organization and will maximize the business value.
Proactive Engagement
Automation enables organizations to proactively engage with customers based on triggers or predefined conditions. For instance, when a customer abandons a shopping cart, an automated workflow can send a personalized email with a reminder or a special discount to encourage them to complete the purchase.
These workflows can be designed to address various customer interactions such as onboarding, upselling, cross-selling, and re-engagement. Automation can extend proactive engagement to social media platforms where businesses can monitor customer mentions, comments, and questions.
An infrastructure that’s scaled and agile delivers a great user experience. As part of digital transformation, leaders must enhance their risk and controls environment to be more intuitive and automated.
AI and ML have had a considerable impact on automation, particularly in how they’ve enabled better customer experiences. The introduction of generative AI has been met with enthusiasm. Automation use cases are already being created that have the potential to impact customer experience. Some examples of where automation within CX is headed:
- Resource reallocation. Automation continues to take over manual tasks that humans perform daily, freeing up resources to focus on more complex, skill-driven activities. Everything from recruiting to medical diagnoses will be assisted by AI-driven automation, giving back valuable time to highly skilled employees to meet the unique needs of each customer.
- Communication mining. Communication mining uses intelligent automation to extract valuable information and insights with AI and NPL (natural language processing). These come from various forms of communication data such as text messages, emails, social posts, customer support interactions, phone calls, recordings, and more. By mining communication data, organizations can gain insight into customer preferences. They can identify emerging trends, improve customer services, and make data-driven decisions.
- Employee experience. Investing in employees and creating a positive work environment not only leads to happier, motivated, and engaged employees but improves customer service. With automation handling routine and time-consuming activities, employees can work on high-value projects and achieve higher levels of productivity. Automation can also provide opportunities for employees to develop new skills and expand their expertise. When employees feel empowered and have the right tools to be productive, they are more likely to deliver a positive customer experience.
The future of automation in CX is intelligent, automated, and engaging. The brands that achieve the most favorable results in CX are those that will merge automation and intelligent tools with human ingenuity and compassion.
