Content Recommendation Engines – Helping You Reach Consumers

The rise of content-based marketing has sparked a slew of new challenges for businesses and brands hoping to put their products and services in front of interested consumers. While there are many different tactics for pushing your products and services to the frontlines of consumer viewing, it’s absolutely essential that your messages reach the right audience, at the right time.

This means that distribution of content is just as important as the content, itself. Effective storytelling requires an actively engaged audience, or it won’t translate into the conversions and sales your brand is seeking.

What is a content recommendation engine?

A content recommendation engine is a feature which uses predictive analytics to help you place the appropriate content in front of your target audience. It combines targeted personalization with algorithmic processes designed to assess user profiles and their associated patterns of behavior, in order to predict user preferences and automatically recommend content or products likely to be of interest to that specific user.

So, how is this useful?

Consider Amazon’s approach – their content recommendation engine is commonly used to suggest products related to items currently in their user’s shopping cart, or to promote items which align with that specific user’s previous purchases or browsed items.

The same process can be used on your brand’s website to recommend products, services, or content related to a visitor’s current inquiry. For instance, your content recommendation engine could be easily designed to discover and suggest blog posts, articles, or informative content of relevance to each user, or to promote videos, case studies, or presentations related to other items they’ve viewed.

Content recommendation engines are an effective use of smart technology – they are designed to run in the background, incorporate new information without oversight, and analyze patterns of content consumption in relation to the sales cycle, automatically. They can be programmed to interact with site visitors throughout the entire sales cycle, using big data and predictive analytics to help you optimize marketing efforts, improve visitor retention, and boost conversions and sales.

The greatest benefit to using a content recommendation engine is the ability to develop predictive suggestions, based on a user’s established behavior, or through comparison between similar users. These predictive suggestions can often accurately assess a user’s needs or interests, suggesting content not specifically sought out by that customer, but determined to be of probable relevance.

This means that a user who visited a site expecting to view or purchase “A”, is now exposed to “B” – and may be pleased to find themselves facing content they would not have discovered otherwise. This increases the likelihood that they will make a purchase (often, increasing the amount of sale, directly) – which is why the experts at Strongpages have developed a content recommendation engine designed to put your branded content, products, and services in front of your target audience – every time.

For more information on how Strongpages can help you more accurately target your audience, and boost sales, contact us today.