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Hyper-Personalize Consumer Engagements! How Do You Do That?

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Get Response, the email-marketing provider recently released a report that found targeting to be a mainstay for long in the modern digital marketing industry. 42 percent of marketers send everyone on their mailing list very small emails. This practice is the exact opposite of personalization, and a definite way to drive the respondents to look for the Unsubscribe button in the mail. Until recently, the choice available for personalization has not fulfilled customers’ demands for more relevant content. For example, segmentation tools often require merchandisers to look for and then select a message; tasks are time consuming with most inaccurate data. Say, it is very cold in Himachal and a merchandiser promotes woolen garments to all 20-30 years men and women located in Chennai. However, he does not promote this to people who have purchased shawls yesterday! Irrelevant messaging can cause many such customers to tune out most of the time. Instead of doing well, the feature only harms your business more.

The Challenge- Consumer Engagement

A retailer would know that shopping has changed drastically over the last few years. Nowadays, shoppers stay on sites for shorter period, especially when they are not presented with relevant offers and content from the site. Mobile devices have brought new challenges to the already finicky customer behavior. Shopper behavior and data across all channels need to be user specific. Overall, customers are less forgiving of any generic engagements to an e-commerce site.

For retailers not all is lost yet. New technologies in big data and machine learning are becoming accessible to brands and companies of all sizes. These new technologies have also opened up possibilities for retailers of true one-to-one personalized customer engagements, every single of them. With little data, more personalized customer engagement can be issued.

Predictive Intelligence- The Key to Personalization

Predictive intelligence engine is a tool that crunches customer data and context in real time to understand the behavior and preference of that particular customer. Instead of considering a customer as a part of a broader segment, predictive intelligence uses data science for the creation of predictive model for every unique visitor. These predictive models are continuously learning based on customer behavior, thus, enabling brands to offer the right message to each individual customer.

One of the best feature of this is that it is applicable for loyal customers as well as new customers. The technology does not ignore inactive users of the site too. As predictive intelligence is a very useful feature, it allows retailers to capitalize and cater to the large segment of people located throughout a country or the world, the people we know as infrequent shopper.

More About Predictive Intelligence

The beauty of predictive intelligence is that the predictive engine does everything for you behind the scenes. All you have to do as merchandiser and marketer is to set the strategy for customers. So when you choose to “show alternative” or “show compliments” the intelligence tool will do it all without you even having to take care of the matter.

Whether you have tried to personalize your site several years ago or whether you have tried personalization techniques most recently, now is the perfect time to consider predictive intelligence for your business. Personalized engagements are major differentiator in a competitive environment as online retailers try to grab attention and dollars of customers.

Does Personalization Really Work?

VentureBeat, conducted a research on its series on State of Marketing Technology, showed the value of reaching out to customers as unique individuals. The result of the research conducted, showed that a small single simple change-like the change in the subject line of the email sent to customer pushed the open rate of email up to 29.3% on average. The company also reported that personalized content on the website drove page views of another company up by 300% and another reported a conversion rate boost of 219 percent.

The true standard of hyper-personalization is interacting on a one-to-one basis with every customer and not segments. To understand an individual’s desire of purchase at any point of time requires the retailer to have deep customer insight and the capability to analyze data. Using this data to build a trust-based relationship with customer will help the retailer’s business in the end.

Conclusion

Predictive intelligence also termed as sophisticated personalization looks into several set of different data and correlates them with consumer behavior and their purchases across channels. Modern customers demand relevance and value from marketing in exchange for their loyalty. It is an unspoken agreement between retailers and customers. By treating customers as individuals, retailers can turn buyers to loyal customers. They can earn trust, all while boosting revenue per visit and overall growth.

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Hyper-Personalize Consumer Engagements! How Do You Do That?