Ask any retailer or marketer how to reach consumers today, and he or she will tell you we’re in the age of content. We can point to Google for having a major hand in shifting this climate. The search engine emphasizes providing users and customers with information relevant to their needs, not just employing SEO practices that increase a website’s rank and encourage sales.
Content doesn’t just mean the information on a Web page, however. It can be applied to almost any form of contact you have with customers – email marketing lists, social media and more. Businesses need to make every interaction with their audience engaging to promote purchases, as content that doesn’t engage consumers ultimately ends up being a waste of time, effort and money.
Retailers with an online presence should therefore take steps to ensure the content they provide matches what their customers are searching for. A proactive method is to use predictive modeling tools to gauge how audiences will react to a given piece of content. As CMS Wire indicated, predictive analytics helps marketers and retailers understand how audiences experience content, allowing them to tailor their online posts to produce the best outcome.
Predicting well-performing content
According to Digital Marketing Magazine, anywhere from 60 to 90 percent of all content is wasted. These published posts either fail to convert shoppers or aren’t interesting enough for them to view. With predictive analytics, however, retailers can see how a given topic or idea will perform before it’s ever created. They end up producing less wasteful content and instead make posts their audience finds relevant and interesting. This keeps shoppers on a retailer’s website for a greater length of time and increases the likelihood of a sale.
As Convince and Convert discovered, using predictive analytics allows businesses to create 77 percent less content but still increase their page views. Instead of creating posts and studying how well they perform after the fact, marketers and retailers can knowingly write content that reaches a maximum number of viewers with predictive analytics.
It won’t always be easy, CMS Wire noted. Predictive content analytics requires data and analysis more intricate than other systems. Custom BI solutions and predictive modeling tools are necessary to ensure retailers collect the right information and use it in the best possible manner.