Want to grow organic traffic?
WordLift can help.
This AI-powered marketing tool uses machine learning, natural language generation (NLG), and natural language processing (NLP) to scale and automate SEO.
We spoke to Valentina Izzo, marketing content manager at WordLift, to learn more about how this AI-powered marketing solution works.
WordLift is the SEO service designed to help businesses speak Google's native language by converting unstructured content into structured data that search engines understand.
WordLift uses machine learning, natural language generation, and natural language processing to analyze the content of a website. It adds schema markup by enriching the information with data that search engines need to understand to rank the website better. This way, businesses get better visibility on Google and other search engines, more organic traffic, and greater user engagement as they find content relevant to their search.
In addition, WordLift uses these technologies to find new solutions for SEO at scale.
WordLift uses AI for the following use cases:
Most SEO tools provide insight into how to improve a website. WordLift creates a knowledge graph and automates some of these SEO tasks to help a website rank. We call it agentive SEO: from analyzing search intent to creating content, from building internal links to improving on-page user interaction.
With WordLift it is possible to create a knowledge graph. It is based on a modular and scalable platform that can handle billions of data points. For each website, we create a dataset connected to DBpedia or Wikidata and vice versa.
WordLift integrates knowledge graph directly into the CMS used by the company, where the content is created and managed. This is possible with any type of CMS, as APIs and webhooks are provided.
WordLift helps businesses operating in all market sectors, including ecommerce, of small, medium, and large sizes. For ecommerce websites, we have a special plan and extension they can use if they have WooCommerce.
The challenges of today’s AI solutions are related to the inability of these systems to reason over data in a meaningful way.
Deep learning is essentially a pattern recognition technique that can’t alone create trustworthy AI systems. While foundational models have unlocked a wide range of opportunities in the digital marketing space, the risks of using them in production environments are still too high in most cases.
A large language model like GPT-3 might be able to write the description of a pair of sunglasses proficiently, but it might mention the color of a lens that doesn’t exist. Building knowledge graphs sets the base for hybrid models that combine deep learning with symbolic reasoning.
We primarily focus on creating semantic rich data for companies by helping them build an SEO-friendly knowledge graph. Creating a knowledge graph for your organization has two key advantages:
Artificial intelligence is shaping the online world. Commercial search engines like Google and Bing have changed dramatically over the past two decades.
As search evolves, so do the SEO tools marketers need to cope with these changes. Meeting this challenge requires finding solutions that are different from the past and involve both humans and machines. Even in this changing scenario, where machines are getting smarter, human intervention remains essential.