Wednesday, 19 October 2016

Using Preference Data for More Relevant Customer Emails and Messages

In marketing, personalization is the new name of the game. From emails to PPC ads and even SEO, the focus nowadays is to tailor the message specifically to the individual receiving them. According to a study, purchasing patterns of 86 percent of consumers were affected when the marketing message was personalized to them.

Not all customers are created equal after all, and before any personalization can happen, you need to identify what key factors set one customer from the other. Once you understand what makes them different, you will be able to target messaging and even develop your product for both your customer and business.

The way to differentiate your customers? It’s preference data.

Preference data refers to data about what and how users prefer to buy, or what ads people find interesting. The use of preference data in marketing to customers has become more common, not only among large retailers, but small and medium enterprises as well. Collecting and analyzing preference data has allowed marketers to segment their customers based on behavioral data.

Understanding customers better requires greater insight into a lot of factors including geography, demographics, products, bought, etc. Surveys and generalizations are helpful, but modern businesses need more data if they want to gain the upper hand over the competition. Customer service records, social media activity, and even referral sources—all of these can be used to gather preference data. Use this customer intelligence to create content that speaks to your users via their preferred medium whether it’s through your ads, emails, and website content.

Many conversion failures have stemmed from getting information about customers wrong. That said, it’s important to ensure the accuracy of the data you collect, so double check and double check again.

Using Big Data and Preference Centers to Personalize Email Marketing,

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