How Cognitive Learning and Messaging can be Used to Engage Customers in 2017
Andy Roy, Vice President of Strategy, Brandify discusses that 2017 is the year that machine learning, chatbots and other cognitive technologies transform brand to consumer engagement. He suggests how marketers can now deliver more personalized and on-demand interactions with consumers “in the moment”
Of the ways cognitive will impact 2017, chatbots are taking center stage because they allow marketers to dynamically personalize a response based on the user’s intent and interests. This can create deeper engagement, for example, with virtual sales assistants. Sentiment analysis and text analytics allow brands to respond to ratings and reviews based on the emotions and topics expressed by customers.
We view the local search experience as an evolution. From the Yellow Pages in the past, to Google search and mobile apps in the present, to bots, messaging and augmented reality in the coming years. Advances in artificial intelligence are enabling conversational commerce to simplify the buying experience. While we are still far from relying on AI for critical decisions, brands will find ways to deploy AI to work side-by-side with humans.
The question is, how can brands prepare to engage the customers of tomorrow?
After all, it’s not really reaching out to customers that’s the challenge: it’s being omni-present and connecting to those customers through their existing technology in the moment, without increasing labor costs, to provide a personalized experiences. By piecing together sentiment data together as quickly as possible, brands can recognize patterns, and provide better experiences online and in-store.
Pattern Recognition and Cognitive Learning
Deep cognitive learning of consumer preferences and pattern recognition helps develop a unified profile of user behavior. With the customer journey growing increasingly complex, making sense of the varied touch points is required for brands to facilitate customers along the way.
Comprehending meaning is definitely a complex process. As Facebook’s Yan LeCunn has mentioned, deep cognitive learning of language comes from layering different levels and examples of sentiment to construct algorithms that can recognize and make sense of user intent. However, this process of layering and training systems on the intricacies of user speech is integral when we think about satisfying the local intent of users.
By the end of 2017, we can foresee that the top national brands will build these cognitive technologies, possibly through messaging, for users to connect with brands nearby.
Engaging Away From the Store
The best mobile app is the one that doesn’t require a user to download. Rather, it already lives on a device in the form of messaging. Facebook Messenger alone serves over 100 million active users and allows developers to use its platform, so engaging customers outside of store locations can be more personal and effective through chat bots. Kik’s head of messenger services, Mike Roberts, told Adweek that “Messengers are the new browser and bots are the new websites.” Machine learning provides the predictive insights that chatbots can deliver on-demand and in the context of an interaction.
Brands will increasingly use messaging to engage users outside of stores through to maintain a seamless experience across search and social experiences. Some are already using bots for things like order processing, product recommendations, tips and tricks and promotions. For example, Sephora’s Kik chat bot plays on the user’s interest in products by serving as a shopping consultant and finding relevant products, beauty tips and tutorials that can then be accomplished with products from store locations.
Enhancing the In-Store Experience
When a user visits a physical store location, IoT technology such as beacons and mobile apps can work in combination to trigger “in-the-moment” marketing. At this point, we are seeing this strategy take form with big-box retailers like Lowe’s are using the virtual reality capabilities of Holoroom to show the possibilities of their products. But, imagine a world where after this in-store experience, the conversation with the brand continues after the sale, creating loyalty without resorting to coupons or discounts.
Strategically, this will be where semantic learning and pattern recognition will transform the customer experience in the coming years. We can anticipate by this time next year, innovations in understanding user location in relation to sentiment and intent will bridge the online-to-offline experience gap and help brands engage users in a way that fosters long-term relationships instead of one-time purchases.
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