In today’s highly inconscient world, customers are desirous of good experiences and not just deals. For your online business to be successful, customer engagement is not only necessary, but crucial. More than ever before, consumers have begun to expect meaningful engagement in the form of personalized recommendations, tailored offers and individual attention in return for their loyalty and referral.
According to an annual IBM survey, “as many as 65% believe customer engagement will be the primary driver of growth going forward.”
And to add to that, analytics is one of the very few ways that offers you valuable information about your customers’ preferences, their online behavioral patterns and many other such insights that eventually help you engage with your customers with the right message at the right time via the right channel. These are the ingredients that keep a customer happy and coming back for more.
In short, the best possible way to bridge the gap between your brand and your consumers is to draw actionable insights from available analytics data to enable great customer experience.
Using analytics for customer engagement
1. Personalized Customer Segmentation
The best thing that a marketer can possibly do is to try and commit to learning more about their customers as emotion-driven human beings. Targeting visitors based on their browsing patterns, preferences and lifestyles works towards delivering a customized experience.
Collating consumer data based on analytical reports helps you to message your customer efficiently. This negates the need for manual guesswork and offers precise insights about what product works best for your customers. Data also allows you to make practical budgetary decisions.
Make the best use of data by segmenting your website visitors based on their attributes and behaviors, and then send them highly personalized messages. That is the best way to ensure that the most relevant ads reach individual users.
Good to know fact: According to AdAge.com, when the computer technology company Lenovo implemented this method, its “click-through rates increased by 30% and resulted in greater conversions and sales.”
2. Set triggers based on user behaviors
Study your customers’ interactions. You will receive new insights about how to actively engage people with your brand. When customers click on a particular link or sign up for a specific mailing list, their behavior should be a clear behavioral indicator for your team.
Apart from simply collecting the data, go deeper and monitor the dynamic behavior of your customers. This way, you can also detect your customers’ next course of action. The science of prediction in analytics via pattern recognition and machine learning, powered by Big Data is clearly headed for glory days. Predicting behavioral patterns lead to better timing for customer engagement. This kind of learning helps marketers to understand what to present to the customer so that he is not disengaged from the activities by identifying opportunities to introduce new mechanisms of engagement.
3. Engage In Consistent Communication
Over the years, customers have come to expect a certain level of communication with your brand. Wanted or not, people will always share their opinions about your business. Track and enhance customer sentiment by improving your competency in real-time reporting.
This kind of conversational marketing helps the system to understand customer sentiment and what is being spoken about your brand across the web. It is no more about just “Buy My Product”, it is more about understanding the customer’s preferences and customizing his offer.
Conversation marketing makes use of technology to build & maintain relationships with customers. The key is to gradually increase sales over a customer’s lifetime, rather than a single purchase.
ROI and revenue may not effectively measure method. Optimize conversational marketing with conceptual analytics.
Remember: Investing in metrics that measure loyalty can impact how you approach the customer lifecycle.
Understanding that real-time analytics is the key to the future of customer engagement, retention and loyalty will be crucial to the future of marketing. Artificial intelligence and predictive analytics is making this increasingly possible to simulate a human-like, emotion backed experience for customers across industries.
The need to adapt to this science and process is the order of the day and the sooner one aligns with it, the better for their future.