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In 2021, consumers became very aware of data privacy, especially as it is related to their rights regarding personal information gathered as they browse the internet and interact with websites. All companies, but especially ecommerce companies, are facing new challenges as consumers push inquiries into exactly what information is being kept from their shopping and browsing histories.
Fortunately, artificial intelligence (AI) can help in a way that both satisfies data privacy advocates and makes ecommerce more efficient.
About consumer data privacy laws
Consumer data privacy on the internet first got some teeth in 2016 when the EU passed the General Data Protection Regulation (GDPR), though it did not become fully effective until 2018. The GDPR protects the data privacy of EU citizens; it applies to any company doing business in the EU and is enforced with heavy fines. Privacy advocates pushed for this legislation after it became clear that major internet companies, like Google and Facebook (now Meta), had collected massive volumes of personal data without informing people and were using the data in a variety of ways, without transparency.
Similar regulations have followed in the U.S., led by the California Consumer Privacy Act (CCPA) and the California Privacy Rights Act (CPRA), which expanded the CCPA. Other states, like Virginia and Colorado, have followed suit.
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The result is that companies doing business on the internet now face a bewildering set of consumer data privacy laws. While these laws may be confusing, the cost of non-compliance is significant, both financially and in potential damage to a company’s reputation.
Using ecommerce data while remaining compliant
The good news is that ecommerce companies can implement very effective online merchandising and efficient site searches without storing a consumer’s sensitive personal information. AI-based on-site search platforms don’t need to know the age, gender, location, earnings, or marital status. They learn a consumer’s habits by analyzing purchase history, browsing history and search history or via a combination of this information.
The AI analysis supports a streamlined search process and delivers targeted, relevant search results to customers. It uses each customer’s browsing and shopping habits but also understands context and user intent, so it can take the guesswork out of e-merchandising.
AI website search technology can be applied to any industry, creating a more engaging search experience for customers. Each interaction is directed toward helping ecommerce visitors quickly discover products that fit their requirements or match their needs. It works by dynamically curating both search results and category pages for each online visitor based on their unique search, browsing, and purchase history. Every visitor gets a personalized view of the website’s products.
Leveraging artificial intelligence
New AI software solutions are improving online merchandising’s effectiveness in influencing purchase behavior. Natural language processing is a branch of AI used by search engines to understand the text people type in when they make a search. Semantic query understanding is an AI function that then helps the search engine understand the intent of the query. When these processes are combined with data from past searching, browsing and buying, they drive search results that are accurate and relevant. Sensitive personal information isn’t used, or even helpful.
The AI algorithms also use collected sales outcomes to optimize product rankings and displays on web pages. Customer searches are tracked, along with resulting actions, like add-to-cart, sharing, purchase and ratings. As more and more of these searches and actions are captured, AI uses the data to automatically re-rank results and put the highest converting items first, managing some of the complexities that are an inherent part of ecommerce.
Avoid data privacy law violations with AI
The AI approach also helps companies comply with consumer data privacy regulations. There is simply no need to retain sensitive personal data. All the issues related to consumer permissions and use transparency go away, as is the risk of fines for statutory violations.
Joe Ayyoub is the Chief Revenue Officer of Search.io.
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