5 AI-Driven Strategies for Higher Ecommerce Conversions

Imagine spending countless hours and resources designing and optimizing your website, only to find that you’re attracting thousands of visitors daily but with few converting into loyal customers. It's a frustrating situation that can leave you feeling defeated.

Thankfully, there's a game-changer: artificial intelligence (AI).

In this blog post, we'll dive deep into the world of AI-driven strategies to boost your website's conversion rates. From deep personalization to dynamic re-ranking, we'll explore five different techniques that will help you increase engagement, enhance customer experience, and ultimately drive higher conversions.

Conversion rates - What works for ecommerce businesses

Conversion rates are the ultimate litmus test for ecommerce business. What do they reveal?

Conversion rates measure the percentage of visitors who take a desired action, such as making a purchase or filling out a form. Conversion rate metrics provide a clear picture of how well your website is performing in terms of turning visitors into customers. The higher the conversion rate, the more successful the business is.

However, achieving high conversion rates can be a challenging task, with various factors influencing the outcome. One of the most crucial factors is website design, which should be visually appealing, easy to navigate, and optimized for mobile devices.

User experience is another crucial factor that influences conversion rates. Ensuring that customers can quickly and easily find what they're looking for, with minimal friction during the checkout process, can significantly impact conversion rates.

5 Artificial Intelligence-driven strategies for higher conversions

Five AI driven strategies for higher conversion rates are stated below.

1. Deep personalization.
2. Dynamic re-ranking.
3. Synonym detection and handling in search results.
4. Offer visual search.
5. AI-powered customer service.

Let's understand each of them.

1. Deep personalization

Personalization is a powerful way to engage with customers and drive conversions – 90% of marketers believe that personalization is a significant driver of profitability.

AI-powered personalization uses machine learning algorithms to analyze customer behavior, preferences, and purchase history to recommend relevant products and content. 

By taking into consideration the user's profile and tailoring search results based on their individual needs, AI searches provide accurate and relevant results that are more likely to result in a purchase.

With AI-driven personalization, your search engine will take into account your customers’ past behavior and preferences. For instance, it can recognize that a customer named Jade has a Great Dane dog named Max and that she tends to buy toys and treats for him. Based on this information, the search engine will show results that are more relevant to Jade's needs. For example, it might show results for dog toys that are designed for larger breeds like Max or toys that are made of durable materials to withstand his enthusiastic chewing. The search results might also include dog treats that are specifically formulated for Max's size.

2. Dynamic re-ranking

Dynamic re-ranking is an approach that involves rearranging the order of products on category pages and search results based on customer behavior and preferences. 

The process starts with the collection of customer data, such as search queries, browsing behavior, purchase history, and other relevant metrics. This data is then fed into an AI algorithm, which uses machine learning models to identify patterns and make predictions about what products a particular customer might be interested in.

Based on these predictions, the algorithm dynamically adjusts the product rankings on category pages and search results to show the most relevant products first. For example, if a customer frequently purchases running shoes, the algorithm may prioritize displaying running shoes at the top of the search results when that customer searches for "athletic shoes."

The effectiveness of dynamic re-ranking depends on the quality and quantity of customer data that is fed into the algorithm. It also requires a robust machine learning model that can accurately predict customer behavior and preferences.

3. Synonym detection and handling in search results

Customers use different keywords and synonyms to search for products online. AI-powered search engines can detect and handle synonyms, ensuring that customers find what they're looking for, even if they use different search terms. This is especially important if you are operating in a market with multiple languages, as synonyms can be very different across languages. 

One way to accomplish this is through manual tagging. This involves tagging each piece of content on your website with relevant keywords. This helps search engines know what your content is about and match it with relevant queries. 

Another, more effective way is by using AI and natural language processing (NLP) to analyze the context of each word or phrase in your query and identify potential synonyms and related terms based on that context. By using this technique, businesses can improve their search accuracy, reduce bounce rates, and increase conversions.

4. Offer visual search 

Let's say a customer sees a pair of shoes that they like on the street or on social media, but they don't know the brand or where to find them. 

With visual search, they can simply take a photo of the shoes and upload it to the ecommerce site's search bar (or mobile application). AI-powered search engines can analyze the image and suggest the same or similar products that the customer can purchase.

By offering visual search, businesses can provide a seamless and convenient experience for customers, increasing engagement and ultimately, conversion rates.

5. AI-powered customer service

AI-powered customer service leverages technology such as chatbots and virtual assistants to provide instant and personalized support to customers. 

These technologies utilize NLP to understand customer queries and provide relevant responses, which can result in faster resolution times and increased customer satisfaction. For instance, automating customer service tasks such as providing answers to frequently asked questions or taking care of simple enquiries can free up time for human agents to focus on more complex issues. This can lead to shorter wait times and improved overall efficiency.

Here are some benefits of automating customer service using AI:

• Faster resolutions: Users don't have to wait before speaking to a customer executive. No matter how many users you have, you'll never run out of support agents.

• Personalization: Bots can learn recommendation preferences over time, providing more personalized search results and recommendations

Conclusion

By using AI-driven strategies you can improve customer engagement and satisfaction, and ultimately, drive higher conversions for your online store. 

One of the best ways to leverage AI for higher conversions is to use a search and discovery platform like Zevi. Zevi's AI-powered search engine provides personalized and accurate search results, dynamic re-ranking, synonym detection, and visual search. 

Zevi's platform is designed to help businesses improve their customer experience, increase engagement, and drive higher conversion rates.

Don't get left behind, embrace the power of AI – book a demo today.