The scope of artificial intelligence (AI) never ceases to intrigue the human mind. From interactive search assistants and employee management systems to self-learning user segmentation tools and complex ambient intelligence, AI has always remained a progressive technology limitless in its potential.
With recent leaps in technology, AI has forayed to the forefronts of digital marketing, creating innovative solutions to automate, organize and personalize corporate marketing, giving entrepreneurs the opportunity to improve the effectiveness of their business strategies.
In the past few years, AI’s rising demand has served as a key stimulus in its further development, to the extent that countries such as the UAE now have a dedicated ministry for AI.
While the applications of AI are innumerable, modern industry verticals crucially rely on faster, affordable and more accurate modes of marketing. By utilizing AI in digital marketing practices, entrepreneurs can benefit from higher response value from the target audience and ultimately achieve a stronger competitive edge against other online brands and e-commerce websites.
Here’s how AI has affected some of the most common online marketing practices and why entrepreneurs must leverage from them.
Improving relevancy and quality of content
With the latest AI integrations, search engines have become just as responsive in understanding user queries as identifying publisher’s intent when they upload content.
AI integrated search engines are now doing a far better job in serving that searcher intent, using deep learning algorithms to grade relevancy, reader-friendliness, and authenticity before displaying content.
This means publishers will have to generate higher quality content since its rankings predominantly depend on how well it addresses its intent to the target audience.
AI integrated search engines respond to user intent signals more authoritatively against predefined algorithms. At the same time, machine learning capabilities of search engines allow them to gather information and predict, anticipate and influence trends in content marketing. This enables content marketers to use this element and shape their content accordingly to drive desired outcomes.
Giving personalized experience to users
By utilizing AI interventions, online marketers are now able to improve engagement, extend retention, personalize user experience and boost sales. One of the most successful yet underrated techniques is search engine optimization (SEO).
Surprisingly, AI integration does not affect SEO from the traffic perspective but instead helps enhance its application on everyday online searchers simply by personalizing their experience when interacting with the brand.
AI in SEO also yields an interesting work impact by efficiently responding to the brand’s key performance indicators (KPIs) while at the same time building it a robust digital footprint in the market.
When practising SEO, data makes the most important ingredient of the AI model, helping it harness the power of user individuality and build persona-based intelligence. Since every customer demands unique treatment, AI utilizes these personas to embody their preferences and design the most fitting solutions for them.
More importantly, SEO practices come with a sound appeal, costing significantly less for longer-lasting impact against traditionally high-dollar practices.
Generating responses through deep learning
With Google’s recent updates this year, paid advertising has undergone significant changes in terms of how well an advertisement is created, optimized and displayed.
AdWords campaigns no longer require humanized optimization and are managed through Google’s own machine learning algorithms. Not only does Google modify the appearance of the campaigns precisely according to geographical, demographical and socioeconomic components, but also integrates the millions of search signals they already have.
Apart from modifying campaign appearance, AI will also serve an imperative role in improving the advertiser-customer relationship by facilitating interaction through deep learning. It works by capturing essential patterns to filter out the most predominant characteristics, which are then used in differentiating users into segments.
For example, when a customer from a particular segment interacts through the landing page, the chatbot will examine the data to generate a response precisely according to his or her preferences. This not only strengthens the advertiser-customer relationship but also grades the quality of the lead.