It’s one thing to know whether an individual customer is intrigued by a new mattress or considering a replacement for their sofa’s throw pillows; it’s another to know to how to move these people to go ahead and make a purchase. When deployed strategically, artificial intelligence (AI) can be a marketer’s trusted customer experience ally—transforming customer data into actionable insights and creating new opportunities for personalization at scale. On the other hand, when AI is viewed as merely a quick fix, its haphazard deployment at best can amount to a missed opportunity and at worse undermine trust with an organization’s customers.

This phenomenon is not unique to AI. In today’s fast-moving digital economy, it’s not uncommon for performance and results to lag behind expectations. Despite the enormous potential of modern technology to drastically improve the customer experience, business innovation and transformation can remain elusive.

According to Gartner, 89% of companies now compete primarily on the experiences they deliver. As marketers and other teams turn to these systems to automate decision-making, personalize brand experiences, gain deeper insights about their customers, and boost results, there’s often a disconnect between the technology’s potential and what it delivers.

When it comes to AI, frequently, organizations fail to realize the full benefits of their AI investments, and this has real business repercussions. So how do organization ensure that their investments deliver on their promise for fueling innovation, transformation, and even disruption? To find success, it requires the right approach to operationalizing the technology, and investing in AI capabilities that can work together throughout the entire workflow to connect various thoughts and processes together.

Getting real about AI. Realizing the value of AI starts with a recognition that vendor claims and remarkable features will only go so far. Without an overarching strategy, and a clear focus on how to operationalize the technology, even the best AI solutions wind up underperforming and disappointing.

Related work from others:  Latest from MIT Tech Review - How existential risk became the biggest meme in AI

 There’s no simple or seamless way to implement AI within an organization. Even with powerful customer modelling, scoring or segmentation tools, marketers can still wind up missing key opportunities. Without ways to act on the data, the dream of AI quickly fades. In other words, you may know that a certain customer likes hats, and another customer enjoys wearing scarfs but how do you move these people to an actual purchase, or deliver the right content for where they’re at in the buying lifecycle?

The winning approach is to start small and focused when it comes to implementing AI technology. Be mindful about what types of data models you can build with AI, and how they can be used to deliver compelling customer experiences, and business outcomes. Collecting and analyzing actionable customer data is only a starting point. There’s also a need to develop content that matches personas and market segments and deliver this content in a personal and contextually relevant way. Lacking this holistic view and AI framework, organizations simply dial up speed—and inefficiency. In fact, AI may result in more noise and subpar experiences for customers, and unrealized results for an enterprise.

Moving from transaction to transformation. A successful AI framework transforms data and insights into business language and actions. It’s not enough for the marketing team to know what a customer likes, for example, it’s essential to understand how, when and where an individual engages with a business. Only then, can a brand construct and deliver a rich customer experience that matches the way their customers think about and approach a brand. This includes an optimal mix of digital and physical assets, and the ability to deliver dynamic web pages, emails, and other campaigns that customers find useful and appealing. When a marketer understands intent and how a person travels along the customer journey, it becomes possible to deliver the most compelling customer experience.

Related work from others:  Latest from MIT : Technique protects privacy when making online recommendations

With this framework in place, marketers can read the right signals and ensure that content delivery is tuned to a person’s specific behavior and preferences. It’s possible to send emails, serve up ads and mail brochures that reach consumers when they are receptive and ready to engage. Whether the customer is into hats, scarves or electric guitars, the odds of successful marketing increase dramatically.

Putting AI to work. Only when an organization has mapped AI workflows and business processes—and understands how to reach their customers effectively—it’s possible to get the most out of AI solutions. These solutions can address the full spectrum of AI, including reading signals, and collecting, storing, and managing customer data; assembling and managing content libraries; and marketing to customers in highly personalized and contextualized ways.

A good way to think of things is to imagine that a person hops in a car with the intent of driving across the United States. If the journey is from Los Angeles to New York, for example, it’s tempting to think the motorist will take the most direct route available. But what happens if the person loves nature and wants to visit the Grand Canyon or Yellowstone National Park along the way? This requires a change in routing. Similarly, an organization must have the tools to understand how and where a person is traveling in the product lifecycle, what ticks the person’s boxes along the way, and what helps them arrive at a desired destination with a minimum of friction and frustration.

AI can do this—and it can serve up promotions and incentives that really work. Yet, to build the right customer experiences and the right journey, marketers must move beyond AI solutions that deliver a basic customer score or snapshot, and instead obtain a motion picture-like view of a customer’s thinking, behavior, and actions. To that end, building out one AI capability or buying one point technology to address a single aspect of customer experience isn’t enough. It’s about being able to connect a set of AI capabilities, which are orchestrated throughout the entire workflow to connect various thoughts and processes together.

Related work from others:  Latest from MIT : Stratospheric safety standards: How aviation could steer regulation of AI in health

Only then is it possible to deliver an optimal marketing experience.

Delivering on the promise of AI. To be sure, with the right strategy, processes, and AI solutions, it’s possible to take marketing to a more successful level and deliver winning customer experience. When marketers truly understand what a customer desires and how they think about a product and their customer journey, it’s possible to tap into the full power of AI.

What’s more, this approach has repercussions that extend far beyond attracting and retaining new customers. When organizations get the formula right, marketers can engage with their best customers in a more holistic and natural way. In the end, everyone wins. The consumer is greeted with a compelling customer experience with relevant messages that display products and services they are interested in at every step of their journey and the business boosts brand value and loyalty.

At that point, AI finally delivers on its promise.

If you’d like to learn more about how AI can help your company deliver personalized content at scale, visit here.   

This content was produced by Adobe. It was not written by MIT Technology Review’s editorial staff.

Similar Posts