The application of artificial intelligence (AI) to generate web content is the next big thing in the ecommerce market. Considering that automated content analysis is the next benchmark, the strategies that go into the process need to be examined. If we analyze the problems with automated content creation, it’s obvious that there are a few challenges to address. To create quality ecommerce content, human and machine intelligence need to work together.
The application of artificial intelligence can yield great results in terms of generating great quantities of content. However, the quality of that content may lack the insights that human intelligence can offer. Product descriptions must be relatable. The content should excite the customers and sway their buying decisions. The AI’s algorithmic implications may provide factual product descriptions for ecommerce, but incorporating emotive quality may be a challenge that machines can’t quite meet.
Value Added Sentences Increase Description Quality
AI created content is constructed on a bed of existing data. Therefore, one of the problems with automated content creation is that the AI can’t generate fresh ideas. AI generated, machine-driven content is lacking ‘common sense’. Algorithmic implications can easily identify and describe a black dress or a cotton shirt. What they can’t do is describe the value additions that mean so much to the reader, such as the texture, the design or the feel of the material. While AI can produce a product description, it can’t make a joke, engage a reader with insights or highlight the usefulness of a subtle feature. Hence, automated content may fail to engage a reader.
Convincing Descriptions Make an Impact
AI generated content can speak of the attributes of the products, but lacks the value additions related to those attributes. While AI generated content can effectively feature a description of the product, it will not involve any subjective opinion about the product. The lack of such opinion is often obvious to the reader, and such clinical descriptions may unfavorably sway their buying decisions. Human intelligence is needed to make the leaps in logic that elevate product descriptions from boring facts to creative, convincing content.
Keyword Optimization Brings in New Readers
When addressing the problems with automated content creation, search result rankings must be mentioned. Regardless of the quality, AI-generated content that doesn’t appear in search results hasn’t reached its intended audience. Machine generated content often doesn’t abide by the rules of keyword optimization. If keywords for product descriptions or category pages are not properly optimized, then the customer’s searches will be fruitless. Optimization depends on, again, leaps of logic, which consider keyword phrasing, placement, context and related terms. Content that grows out of human intelligence keeps the buyer’s search concerns in mind while optimizing.
Competent Descriptions Increase Convertibility
Since machine generated content is laid upon existing data and facts, it may fail to update itself. Therefore, the content may lag behind that of competitors in the e-commerce market. Lack of proper updates at regular interval creates a gap. This also results in making the content non-convertible in terms of generating organic traffic in the Google search page. Human intervention and oversight are necessary to detect and address any such content gaps.
While AI-driven content creation can generate large quantities of product descriptions at the touch of a button, it does not remove or replace the human element. However, human and machine intelligence can work together in harmony to produce high-quality product descriptions for ecommerce.