For companies, personalization is no longer a nice to have. It's a need to have, and if brands have any chance of obtaining and keeping customers, they need to get personal.
Today's consumers have far greater expectations from their experiences and interactions with brands. Mantras like "service is king" and "the customer is always right" have been thrown on their heads, and are being taken to a new level when it comes to wowing and keeping customers. Additionally, consumers are consuming content through a growing number of channels including mobile devices, social media, web, mail, email, television, etc. - mounting the pressure for brands to gain a deeper understanding of their customers if they want to stay ahead of the competition.
Consider the following stats:
- 61 percent of consumers feel better about a company that delivers custom content, and are more likely to buy (source: Demand Metric)
- Marketers see an average increase of 20 percent in sales when using personalized web experiences (source: Econsultancy)
In an effort to become more 'personal,' we're seeing more and more companies incorporate algorithms into their product recommendation strategies. Think of your favorite music streaming sites or even your bank: How often are the recommendations and offers delivered to you correct? Do you feel that based on your experiences and your past behaviors, these companies are delivering content that is unique and personalized for you?
What good are these efforts if they're not doing what they're intended to, delivering timely, relevant offers and interactions to customers?This got me thinking about customer experience management, and why data and personalization are the keys to customer experience and marketing success.
Companies built to be data-driven are good examples of effective customer experience management at work. Take for instance, Google. Google gathers massive amounts of data about its users' activities, locations, interests, and more, merely from their web activities. As a result, their experience with Google is more personalized than that of say, their banks. Google Now goes so far as to tell customers today's weather before they start their day, how much traffic to expect before they leave for work, when the next train will arrive as they're standing on the platform, or your favorite team's score while they're playing. And the best part? All of this happens automatically.
Companies must leverage the existing user data they have stored and are constantly receiving (and there's a lot of it.) to create user experiences that are so much more personalized than those created by companies that count merely on web traffic activity and information. Because end users' expectations of their vendors are increasing, and consumers have more of an affinity for those vendors that offer more pertinent information and instruction and deliver offers that add convenience to their lives.
This presents an exciting opportunity for businesses to use their data to better personalize user experiences. Productively utilizing customer data allows businesses to determine what a customer is most interested in and create an experience where content, products, and/or services are presented to customers before they even realize they need them.
Successful customer experience management strategies require the anticipation of future needs--looking at behavioral patterns, market trends, and user experiences for proactive measures to secure a personalized, unique, and memorable experience across multiple channels. This, in turn, enables the customer to feel understood and valued, and likely to develop loyalty-a good basis for customer retention, up-selling, and cross-selling.
To achieve this, companies must go beyond placing customers in aggregate categories and instead know them at the individual level, based on preferences derived from all available data sources. No more hunting and re-hunting in pools of raw interaction data, no more batch processing or broad, static segmentation exercises. Companies need to have access to thousands of relevant metrics for immediate action.
To understand which offers are relevant and will appeal to each customer, and how and when those offers should be made, companies need automated processes to address each customer at the individual level. The more a company can understand the customer as an individual, the greater its ability to support relevancy. Knowing which offers to deliver at the appropriate time and place to be most meaningful to that individual customer.
While no one has a crystal ball into the future, there is data available now that companies can access to predict the propensity customers might have for a new or existing product, a service or a particular content offering. It's all about your data and using it to deliver personalized content to customers. This is how you create great customer experiences, loyalty, and greater customer lifetime value.