Deliver Content Personalization through Machine Learning

Deliver Content Personalization through Machine Learning

Content Personalization is the most revered keyword in the digital world today, where content is the king, and technology serves as the impeccable tool! All businesses across industries have some form of virtual presence- websites, social media handles, etc. Content exists indispensably everywhere. The digital world feeds on content and people are subconsciously and deliberately, both ways, being driven by the immense power of content in their day to day life. Content personalization plays an important role here. Your customers will love to see content that is personalized to their likes, dislikes, preferences. And as personalization is quite predictive once you know your customers (target audience), you can devise mechanisms exclusively catering to their unique needs. Machine Learning has started playing a key role here. As Bill Gates has said so aptly“If your business is not on the internet, then your business will be out of business.”And, if your business has adopted digital technology capability in the form of ML, you are above par, and perfectly driving along the digital line!ML  is helping marketers to scale their content marketing strategies ina big way!

Let’s see how Machine Learning  AI Capabilities are enabling content personalization at length, leading to organizations’ ability to scale and enhance their customer experience!

Optimization of Content Delivery

Optimizing means locating the essential points in a customer’s journey and adding a personal touch to them. Contexts play a trigger to the need of creating and optimizing specific content between customers. Machine Learning algorithms help deliver the right content at the right time for innumerable individual website visitors based on their data about what they have done in the past. Along with NLP, ML   does scanning of content, first, then goes deeper to it and understand core meaning alongside the context, and then end up indexing, building a custom library for specific usage. This facilitates the automated delivery of personalized content across the web, email, or desktop and mobile platforms.

Boosting Content Efficiency

What is your topmost priority in your wishlist while sending emails to target audiences? Of course, content engagement. How to assure increased content engagement metrics from your target audience? The email content is thriving even though chat apps and social media channels have emerged as popular user interface modes. Email marketers are heavily relying on Machine Learning capabilities for content personalization and relevance. The former use ML to segmentize markets, as well as for market-timings and copywriting aspects of email marketing. The ML technology boosts the overall effectiveness of content efficiency in email marketing. Just that you have to identify the most suitable Machine Learning email marketing tools for your business. So, you see, Machine Learning capabilities take care of boosting the efficiency of the billions of emails sent and received per day. As per a recent Statista Report, around 306.4 billion emails have been sent and received in the erstwhile year 2020, this figure is expected to rise to 361.6 billion-mails on daily basis by 2024.

Individualized Content-Experience

Active content users are those users who give more time to content and have a higher rate of engagement on a particular landing page(s). Traditional website metrics such as the number of page views, number of sessions are not sufficient for an individualized experience. Deep content analytics, powered by  Machine Learning algorithms,  go beyond this traditional type. They focus on all those metrics that provide real insights on content engagement like those active users just we spoke about!ML analyzes these data at scale, on a real-time basis, based on the exact momentous content engagement patterns of users. This way, AI, ML capabilities powered personalized tools allow the individualization of content as they use these insights for automating cross-channel varied content distribution to web users as per their unique interests, preferences, and behaviors.

You have the data! What next?

The Basic Algorithms and Advanced Algorithms features of ML  lead to the ultimate Content Personalization of users visiting various websites and social media platforms. The  Predictive Content Personalization Engines collaborate with the Data Management Platforms and together they perform activities like syncing, merging, and segmenting data. Consequently, user-specific content promotions, messaging recommendations, etc. are executed and delivered.

Notable examples – Netflix, Amazon, Spotify

ML-based Predictive Content Personalization goes hand in hand with the e-commerce industry, entertainment industry, and so on. Amazon leverages the massive potential of e-mail recommendations and says that this is proving to be more efficient than on-site personalization. Netflix uses dynamic page metrics and follows recommendations generated by ML that are unique to visitors’ tastes and preferences. Spotify leverages the power of ML-backed personalized playlists such as Discover Weekly, Release Radar, Spotify Radio, and some new ones, too, all emphasizing the content personalization aspect.

Tighten your seatbelt– Content Personalization is the key to your business

Predictive content personalization, powered by Machine Learning algorithms enables an organization to provide a unique experience to each user, visitor, or prospective customer. Real-time high-quality recommendations, personalizing every touchpoint along a customer’s journey while safeguarding data privacy and security aspects, ML helps content personalization in a way that dramatically boosts the chance of conversion rates. That’s what your ultimate business goal, isn’t it?

We offer a wide range of customer-Centric Machine Learning Services to deliver personalized content for your audience, that can integrate well with your marketing communications or with existing applications.

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