Innovative AI and ML enhances data analytics to drive on-demand customer engagement
The notion of real-time engagement has been promoted for years now, as have the use of Artificial Intelligence (AI) and Machine Learning (ML) in customer data analytics. Chances are, these are all buzz words you’ve heard before.
Is the buzz too loud? Don’t grab your fly swatter just yet!
While dealing with the short term effects of COVID-19 on businesses, the attention to long-term planning is apparent. Brands are noticing the importance of understanding the context of their site visitors’ online presence, and are actively enhancing their marketing strategy to better meet their customers’ expectations, and deliver hyper-personalized experiences. For some Brands, transforming their customer experience strategy is key to differentiating themselves among competitors. Adopting innovative and disruptive technologies, such as AI and ML, is imperative for customer experience (CX) and marketing leaders looking to be ahead of the game.
Let’s Break it Down …
Customers have come to expect Brands to own high-grade Crystal Balls and hire a team of Mind Readers. Now that’s innovation!
Seriously now, customers HAVE become more agile and resourceful. In this rapidly changing environment, customers expect Brands to adapt to their pace, across their preferred channels (e.g. app, website, social media, physical location). Digital transformation continues to ‘raise the bar’ and the expectation for instant gratification. However, convenience should not come at the cost of meaningfulness. Delivering what is most relevant to your customer at the moment of engagement reflects understanding, a personal touch if you will, that adds positive sentiment to the experience.
The global effects of COVID-19 and the measures taken to ‘flatten the curve’ have changed how consumers perceive convenient and meaningful experiences, and it will continue to shift rapidly until we settle into a new norm. Relevancy is fluid, Brands must continuously adapt the experiences to meet customers’ expectations and sentiment; deal with the short-term as they strategically plan for the long-term. The hospitality industry provides a good example. With restrictions on travel and stay-at-home orders, creativity is called for. Some hotels are offering speciality food recipes that are synonymous with their Brands, delivering a relevant and meaningful experience while sustaining Brand awareness. For the long term, being relevant and contextual might mean offering visitors flexibility in reservations and assuring proper distancing and sanitation for guests. The latter could include contactless-technology, such as choosing your room, check-in and check-out with a personal mobile device, maintaining preferred room temperature digitally, and so on.
Staying attuned with your customer’s expectations involves acquiring customer data, analyzing it, and deriving an actionable outcome that promotes your marketing/ business goal. Businesses need to seize the moment (pun intended) with real-time insights to propel their customer’s journey across all channels and create meaningful personalized interactions and experiences. Delivering these actionable outcomes within a few clicks, while the person is still browsing a website or an app, creates a real-time experience.
For example, in-session intelligent insights can perceive a contextual change in buying behavior and location that results in quickly sending an offer or information that is relevant to the consumer based on their location. Consider this – a coffee shop loyalty member usually buys a cold brew, however, she is now at a colder location scrolling through the warm beverage menu after choosing ‘picked up from a location’; the action could be an offer suggesting order-ahead and a nearby pickup location plus a suggestion of a seasonally appropriate local beverage. Or, maybe the nearest location is temporarily closed so the offer would include other delivery options and an offer specific to her loyalty tier to ‘sweeten’ the deal. Businesses can scale 1:1 interactions like these in real-time with AI and ML technologies.
The data and analytics. ‘Real-Time’ – a look behind the scenes.
Real-time, very simply put, refers to the way the business data is streamed and analyzed.
Event Stream Processing enables in-session integration and processing of data from multiple channels, whether streamed from online sources or offline in-house sources. Continuous Intelligence capabilities add the insightful depth and business dimension to the analysis. The insights produced, enable a cross channel view of the customer behavior, giving a better understanding of customer needs at a point in time, achieving quick actionable decisioning. Data and analytics literacy is key for effectively leveraging these technologies. Machine Learning capabilities enhanced with Artificial Intelligence take the analytics and derived insights to the next level; achieving better accuracy, quickly, and at scale – adding the predictive actionable layer to the insights. Almost like adding a fourth dimension of effective real-time decisioning.
‘Learning’ and ‘Intelligence’ are key – these technologies enable quick intent prediction based on in-session behavior analytics (learning). AI technologies deepen the decision making such that it can determine best action (Intelligence) in the moment, as the customer is engaging. The outcome is a ‘real-time engagement’ decision driven by the Business’s goal.
How ‘Real-time’ Impacts the Customer: The Value Proposition
‘Striking while the iron is hot’ is especially important as the landscape of digital commerce becomes more crowded and the ease of ‘shopping around’ for opportunities is luring. Like clock wheels, it all interconnects. The better the data, analytics, and insights align the more it adds value for the insight-driven business. In terms of customer experience, we see the true value proposition in how real-time engagement enhances experiences by recognizing in the moment how the customer is engaging across channels, tailoring a relevant experience (hyper-personalization), and rapidly predicting next steps with accuracy. For the business, this means high conversion rates. In terms of the customer’s journey, the value is in gaining the customer’s trust and loyalty by being constantly relevant. For the business, this means higher retention rates and customer lifetime value.
Higher conversion and retention rates can be translated into measurable ROI (Return Of Investment) or other revenue business goals.
Personalization is not just about the content, it’s about establishing connection with your customer, promoting trust and loyalty, through continuous relevancy. All of us – consumers, marketers, and Brand leaders alike – are facing uncharted territories and a developing new norm of connection and communication shaped by the advantages of digital technologies. Staying relevant, engaging in real-time, can add a sense of personal interaction and connectedness.
Example of a Use Case
A customer is on a hotel Brand’s website switching views between two packages being offered. Perhaps the user is trying to compare or has not yet decided on the dates of travel; an on-the-fence customer. At this moment the Brand can use many strategies like (but not limited to): discount offers, helpful comparison information, options to chat with a live associate, quick, real-time availability and weather comparison (based on location), or a convenient ‘book now pay later’ option. The Brand can tailor the response to meet the customer at that point in time.
Let’s say the customer went idle and logged back in on the Brand’s mobile app. The app can recognize that the user is a preferred customer and immediately inform them about loyalty discount or point eligibility and location-relevant COVID-19 measures the hotel is taking, based on the user’s previous engagement. In this case, the app is correlating the customer’s in-app activity with her profile using historical data to personalize the Brand-to-user-interaction with context and relevance.
Think About It!
The use of intelligent solutions to harness and analyze data on the go helps produce better real-time insights which in turn enables powerful real-time interactions and customer journeys. It also makes the process adaptable, agile, and easily scalable; from a long-term perspective. Engaging in-the-moment enables adding value to the information that the user desires. It is about providing the right message at the right time through the right channel, based on real-time activity of every user, and not communicating to them after that moment is gone. It is near impossible for a Brand to create such scenarios and scale real-time actions without the use of advanced tech solutions. Like ZineOne’s platform, which leverages innovative use of Artificial Intelligence and Machine Learning capabilities to enhance analytics, increase predictability, and improve in-session decisioning. Fast response time means your business can engage with hyper-personalized value for your customer and ultimately shape how the customer perceives your Brand.