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Get Adaptive Content Delivery with Hushly’s Content Personalization Tools

Marketing today is all about personalization, and that remains true for B2B marketing as well. By utilising content personalization tools you can offer your site visitors custom content recommendations via custom content marketing. This level of personalization increases your ability to offer relevant content to both known and anonymous visitors, increasing the likelihood of engagement and conversion later.

First-time site visitors are often not ready to buy immediately. In fact, up to 96% of website visitors are not ready to invest their money right away. They are, however, open to and often interested in learning about your product. They want to hear about your company, see what you have to offer, and sometimes even test whether or not your products or services will work for them.

By providing web content personalization, you show them content that fits their needs. Content engagement and consumption is encouraged as they explore your site and discover your business with adaptive content delivery. This results in higher qualified leads.

Artificial Intelligence (AI) and Content Personalization Tools

Hushly AI Recommendation Engine

Hushly’s adaptive content delivery AI engine is hybrid in nature, meaning that it combines recommendations from multiple models to build its content personalization tools. Each of these models focuses on a specific method of recommendation. Each of the recommendations are fed into our arbitration engine, which determines the best set of content assets to deliver. Hushly uses four main models in its custom content marketing AI.

Content Similarity Models

These models are trained using the unsupervised machine-learning method. They use natural language processing (NLP) to read the content and metadata of content assets and group them into similar topics for custom content marketing.

The Hushly AI uses this type of model to recommend assets that feature similar content to the assets that have already been viewed by a particular site visitor. For example, if a web visitor views content that uses terms specific to non-profits, these models recommend other content assets that are also related to non-profits. This is the simplest form of web content personalization.

Collaborative Filtering Models

The collaborative filtering algorithm is where things really start to get interesting. These models are trained using a supervised machine-learning method. They use the individual interaction history from the site and the visitor information of all the past visitors to form connections between content assets for similar users and incorporate those connections into adaptive content delivery.

The Hushly AI uses this model to recommend pieces of content that were viewed by other similar visitors who also viewed the same content as the current visitor. It may sound complicated, but you’re probably already very familiar with this type of custom content marketing. Nearly every major consumer site has something similar in its “shoppers who viewed item X eventually bought items Y and Z.”

Session-based Similarity Models

This is a deep-learning model that works by using recurrent neural network (RNN) methodology on the entire session history of past visitors. By modeling the whole session, our AI engine can provide super accurate recommendations based on the visitor’s course through the content stream.

Using this model, Hushly’s AI recommends pieces of content that were viewed by users who took a similar path in viewing content assets as the current web visitor. This broadens the site’s adaptive content delivery system further so that entire viewing journeys are considered rather than just snapshots.

Popularity Models

These models consider the popularity of content assets across all historical visitors on your website. This is the widest scope model, bringing together information from individuals who may have very little in common.

Using these models, Hushly’s AI recommends trending content assets as well as most popular content assets to a web visitor. These models offer powerful recommendations for a brand-new visitor for whom no interaction history is available to provide web content personalization recommendations.

Content Personalization Tools: Intent & Firmographic Triggers

You aren’t the only one utilizing web content personalization! At Hushly we believe our customers (that’s you!) deserve a custom content marketing experience. That’s why Hushly provides you with a set of personalization triggers that you can select. These help establish adaptive content delivery to your ideal customer, and they can override AI recommendations.

These triggers include, but are not limited to:

Intent Signal:

  • Buying Stage
  • Profile Fit
  • Topic Cluster
  • Profile Score
  • Intent Score

(Source: Bombora, 6Sense, etc)

Account:
  • Industry
  • Buying Stage
  • Revenue Range
  • Existing Customer
  • Company Name
  • Company Size
  • Company Domain
Traffic Source:
  • Paid Traffic (LinkedIn, GoogleAds, Facebook, Twitter, etc)
  • Organic
  • Referral
  • Direct
  • Unknown
Traffic Type:
  • Page URL or URL Path
  • Referrer URL
  • IP Address
  • Device Type
  • Geo (Country, State, City, Region)

Add Even More Value by Providing Personalized, Related Content to Your Customers

Your goal is to ensure that your content is available to the right visitor at the right time through web content personalization, all while ensuring that their custom content marketing experience is exceptional. Hushly’s content personalization tools can help with adaptive content delivery. Contact us to see it in action with a custom Hushly experience on your site.

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