Experiences, not price, will be the battleground of the future.
Customers value experiences, and those experiences often come in the form of stories. Selfies, social feeds, chats and influence stats grab consumers' attention, who in turn share their personal encounters.
We have Snapchat stories, Instagram stories. We even have interactive personalized video stories where every audience member charts their own unique rich media experience.
The shift to storytelling gives businesses an opportunity to regain their footing by creating more interactive and personalized engagements with customers.
The old model for building experiences was to create one story — a basic customer journey — and pray that millions of people read or experienced it. Now, thanks to AI, we can create millions of unique stories tailored to an audience of one.
Blending AI and storytelling will have a dramatic impact on improving the customer experience.
Why? AI technologies can achieve scalable contextual relevance as intelligent applications take over the execution part of storytelling.
Change the Game: Combine Storytelling and Technology
Dynamic content, data and intelligent automation all improve customer experiences. By embedding intelligence into customer-facing processes, businesses can build deeper connections, recommend next best actions and create more contextually-driven interactions.
The data improves algorithms, which factor in overall intent, resulting in greater relevancy and effectiveness.
Storytelling and technology are now linked. Using AI to automate storytelling will require new levels of trust in the algorithms and data, which play a powerful role in improving the context.
Since the universe of what is “knowable” about customers is expanding, new machine learning technologies help us to see further and deeper to improve business decision making. Users aren’t limited to what they themselves discover. Combining human expertise with machine intelligence can be powerful, because human interpretation alone can miss contextual clues in the huge data sets.
According to 451 Research data, 80 percent of businesses called machine learning for automated contextual recommendations important for creating personalized customer experiences. Machine learning helps uncover more enticing and engaging stories that resonate with individuals.
The Key: Turn Data Into Meaningful Intelligence
Creating a “story of one” requires constant information updates (e.g., transactions, events, contexts, interactions and behaviors), which then tie into a unique customer identity to build a complete customer profile. Using machine learning-based algorithms turns that information and identity into prescriptive insights. These algorithms identify customer opportunities and determine how to best engage across multiple channels and devices.
For example, machine learning can help email effectiveness by dynamically adjusting subject line headers based on likelihood to open messages. Or by rapidly finding content that drives conversion for each individual.
It’s also a game-changer for customer service: machine learning can improve self-service adoption and help contain up to 80 percent of all customer interactions in self-service channels.
Using machine learning to trigger contextual responses throughout the customer lifecycle improves customer relationships. This includes all conversations related to consumer engagement and purchase conversions through new channels such as SMS, web or mobile chat (e.g., WhatsApp, LINE, Web WeChat, Snapchat), or a social interaction such as Twitter, Facebook or Instagram using a link or buy button.
Storytelling Is Not Just for Online Experiences
The retail vertical isn't the only one feeling the collision of digital and physical worlds — it’s happening across multiple industries and brands.
It’s virtually impossible to plan for all potential customer journeys, because each is essentially a non-linear, self-directed interaction — or micro-moment — across a customer’s channel of choice. Facets of the physical journey, when tracked, can be used as influencing factors in digital interaction.
For example, the retail industry must rethink customer experience and leverage new, intelligent technologies to address the digital divide between digital and physical experiences before, during and after a purchase. There’s an opportunity to add more value to the customer journey, be it through personalized information, location-based services or empowering front-line associates.
83% of businesses rate the use location-based data correlated with customer profile data for contextually relevant communications as important
Location-based technologies can create micro-stories along the customer journey to allow easy discovery of local content, services and more. Add intelligence to the mix, and customer interactions grow even more relevant as you aggregate insights into behaviors and preferences.
The entire outdoor or indoor experience can become a learning opportunity to display personalized location information, product information, pop-up coupons, video demonstrations and more. Consumers can request help based on location, such as a dressing room or clothing rack. The dressing room itself is being digitized to provide inventory availability and recommend other products based on items already in the room through a digital display.
With the help of data and intelligent automation, storytelling is creating new, engaging micro-moments that enhance the overall customer experience.
Yesterday’s world was about one-way customer interactions. Today’s is about two-way engagement anywhere, on any device.