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Being data-driven in the experience economy

Using AI-powered brand, product and customer sentiment insights

Guest blog by Sheryl Kingstone, Research Vice President & General Manager – VOCUL, 451 Research.

Significant disruption across industries and the rising influence of the empowered consumer continue to exert pressure on businesses to deliver differentiated and consistent experiences across the entirety of the consumer journey. Simultaneously, business models are shifting, with the increasing popularity of the subscription economy changing the long-term economics and relationships between brands and consumers. These shifts demand a new approach to engagement models that emphasize loyalty-building and retention exercises. This is forcing the evolution of the entire technology stack and organizational culture to enable real-time, contextually relevant experiences.

Over the years, improving the customer experience has remained the top driver for digital transformation, making it critical to understand where businesses are making investments in new digital technologies and improving processes to more effectively engage customers, partners or employees across sales, marketing, support and commerce functions.

Data remains a vital battleground for creating unified customer experiences

Businesses need to access and unify disparate sources of consumer data – and effectively contextualize and operationalize information – to push critical insights that shape the customer journey. For businesses to effectively compete in this shifting environment, they need to capture, analyze, understand and act on information. They also need to recognize patterns, comprehend ideas, plan, predict, solve problems, identify actions and make decisions on a grand scale. The explosion in connectivity, intelligent devices and digital interfaces overlaying this information is increasingly making it possible to create personalized experiences, augmented by real-time context and customer preferences.

Since the universe of what is ‘knowable’ about customers is expanding, new machine-learning technologies help augment and scale business decision-making. Combining human expertise with machine intelligence can be powerful because human interpretation alone can miss contextual clues in massive data sets.

The abundant growth of data, along with demands for rich media content and regulatory compliance, are requiring new approaches to manage customer data and intelligence. Sixty-eight percent of digital leaders are prioritizing the creation of a single view of the customer across disparate data sources, along with investment in newer digital platforms that enhance both customer experience and business agility (see Figure 1). It drives the largest wedge between digital leaders and laggards, with a 21-point differential between companies that have formal digital transformation strategies and ones that don’t.

Customer Insight Separates Digital Leaders from Laggards
Figure 1: Customer Insight Separates Digital Leaders from Laggards

Today, more than ever, customers and citizens expect businesses to serve up on-demand, personalized experiences. Machine learning can aid in assisting organizations to meet these expectations, but first, decision-makers need to understand the current opportunities where machine learning can be applied.

AI and machine learning improve contextual relevance

Businesses are looking to move beyond segment-based rules analysis and toward algorithmic decision-making that enables hyper-personalization at scale – and at the same time, factoring in individual affinity along with overall intent, which results in greater relevancy and effectiveness. Self-learning algorithms allow marketers to auto-adjust or adapt based on any one factor or a combination of factors, such as individual customer or visitor behavior, geolocation, inventory levels and manufacturer incentives. The advances in predictive machine-learning intelligence build on a variety of algorithms to achieve real-time hyper-personalization at scale.

The most meaningful (and ultimately profitable, for those that provide them) experiences will be informed by data-driven context clues, which will only increase in number as the amount of available data – especially unstructured data – proliferates. The ability to mine data using text analytics and other techniques to extract insights on emotions that can have a positive impact on consumer behavior is essential. The need for text mining increases as growth for new types of connected devices capturing unprecedented volumes of behavioral data accelerates.

With the empowered customer increasingly demanding greater choice over the interactions and relationships they have with enterprises, experiences – not products – will remain the battleground of the future. This demands that organizations rethink their engagement model. It is now essential to view each stage and point of interaction along the customer journey as an opportunity to deliver consistent, differentiated experiences to attract, win or retain customers.

Watch the webinar, “Being Data-Driven in the Experience Economy: Use AI-powered brand, product and customer sentiment insights” to learn more.

Sheryl Kingstone is the Research Vice President & General Manager – VOCUL, 451 Research. Sheryl leads 451 Research’s coverage for Customer Experience & Commerce, which covers the many aspects of how customer experience is a catalyst for digital transformation. She oversees the company’s coverage of a variety of customer experience software markets spanning ad tech, marketing, sales, commerce and service.

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