The Loyalty Revolution
There has never been a more important time to reassess your approach to customer engagement, customer experience, and customer loyalty. The customer experience has shifted irrevocably, and the brands that have stood the test of time are those that understand the need to constantly evolve to stay relevant with their audience. What sets these brands apart is that they maintain their core attributes while transforming particular aspects to enhance their meaning and connection, thus providing a relevant customer experience that keeps people engaged over time.
Pursuing Customer Relevance, Digitally
It is not about simply delivering a good or bad experience. Today’s digital customers do nearly everything online: whether it's shopping, studying, tracking their health, or offering feedback about products or services. Engaging them requires a strategic combination of marketing optimization and multichannel interaction capabilities.
To succeed in today’s digital era, marketers need an in-depth understanding of who their customers are (in terms of their behavior, needs, demographics, and digital habits) to craft an experience that is relevant to them. This is the area where organizations should apply predictive analytics and machine learning to deliver targeted experiences to consumers, and increase conversion rates and boost sales.
Personalization: The Art of Respecting the Customer’s Time
The forthcoming generations won’t watch advertisements on television, or constantly be spammed by irrelevant offers; they will be able to choose what they want to consume. In other words, they will be able to opt out of almost everything. What does this imply? Being forced to consume content that is not relevant to a customer is not a pleasant experience and it takes away their most important resource: time.
When customers are unengaged and unsatisfied, the results become evident. They simply stop communicating, clicking, and returning. The best marketing investment that needs to be made is personalization. Customers are looking for brands they can connect with and experiences that are relevant to them at every stage of the marketing journey; be it awareness, consideration, or the decision stage.
The perfect personalization strategy involves a deep understanding of customer preferences, structured and unstructured data, and conversations across all channels. On the basis of these parameters, brands can preemptively anticipate customer needs.
By leveraging technology and machine learning, it is possible to deliver relevant experiences to the customer. However, brands across various industries such as healthcare, insurance, and retail are still in the process of either considering or adopting augmented reality and machine learning to provide seamless and intuitive experiences.
According to a study conducted by Business Insider, the primary barrier stopping companies from personalization is the shortage of resources dedicated to it. The second barrier is the lack of a clear roadmap that involves online and offline engagement.
Organizations today must step outside the traditional retail paradigm and focus on the five Ps that resonate with customers and form a comprehensive test of relevance: purpose, pride, partnership, protection, and personalization. Also, with the right combination of predictive analytics, artificial intelligence, and machine learning, the opportunity brands need to leverage is to understand the digital DNA of customers.
Take the Step. Analytics is just a formality.
In today’s competitive times, marketers need enhanced predictive capability and improved data optimization to ensure accurate customer segmentation, which, in turn, leads to better customer engagement and loyalty. While sifting through enormous amounts of data is not easy, leveraging it effectively is critical. Smart analytics can help marketers become data-driven decision makers.
Our digital decisioning platform, DecisionMinesTM, empowers business leaders to make informed decisions by synthesizing the Art of Judgment and the Science of Data. We go beyond investing in the basic blocks such as analytics, discovery, and automation, helping marketers determine which pieces of data to actually gather and turn that data into action.