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Top 10 eCommerce KPIs to track in 2022
Any business owner should know which are the best eCommerce KPIs. That's why we put together a list of the top 10 KPIs you should follow, so that you...
We are living in the era of AI. If you were to scroll through your feed, every few minutes the word „AI” pops up.
AI this, AI that - And as an eCommerce business owner, you start to wonder how you can use AI technology to your advantage, such as enhancing various aspects of your online retail operations.
There is a way to leverage algorithms, machine learning, and data analytics to automate and optimize your eCommerce shop, ultimately leading to improved customer experiences and increased sales.
What is AI in eCommerce?
Before jumping to conclusions, let’s clarify what is AI in eCommerce.
Bear with me – it might seem like a foreign language, but we will try to put it as simple as possible: AI in eCommerce relies on a combination of machine learning, natural language processing, and computer vision factors to make sense of data and provide actionable insights.
All these 3 elements combined, help the AI understand what's going on in the online shop and thus lead to helpful suggestions. The core working principles involve data collection (e.g.: products viewed, products added to the cart, boxes clicked), training algorithms, making predictions, and continuous learning. There are always new products added in an online shop and new clients clicking around, so the algorithm is always trained with new sets of data.
As more data is processed, AI systems become better at identifying patterns and trends, contributing to the overall efficiency of the eCommerce shop.
So, what can these AI-powered tools do for your online shop? At Aqurate, we put together a list of 10 AI tools that can help grow your eCommerce shop.10 AI tools for eCommerce
1. Site Search Engine
Filter and sort results: Help users quickly find products in the online shop by entering keywords, product names, or even SKU numbers to locate items. Users can filter the results based on price range, brand, color, and other preferred attributes.Autocomplete and suggestions: Intelligent suggestions help users by predicting and completing their search queries. This not only speeds up the search process but also assists users in refining their queries for more accurate results.
Handle misspellings and synonyms: This ensures that even if users make typos or use different terms, they still receive relevant results, improving the chances of successful product discovery.
➡️ Examples of providers: Algolia, Bloomreach
As per a research study, approximately 30-60% of total revenue on eCommerce sites is generated by visitors who utilize the search function. Despite this significant potential, only 15% of companies allocate dedicated resources to optimize it.
2. Product Recommendation Engine
A personalized product recommendation engine displays widgets with up-sell, cross-sell, and substitute products to website visitors, on the product, home, and cart page. This helps online shops increase their sales and conversion rate, as it encourages users to grow their average order value (AOV) by looking at substitute or complimentary products.
➡️ Examples of providers: Aqurate, Recombee, Dynamic Yield
The best example from the eCommerce field is Amazon, which uses item-to-item collaborative filtering for its recommendation engine. In comparison to content-based filtering, collaborative filtering uses the experience of other users to create product recommendations.
And for those of you who did not know, Amazon is also credited with pioneering this approach after the company published the article, Recommendations: Item-to-Item Collaborative Filtering, in year 2003.
eCommerce shops can use the same technology as Amazon to increase the average order value of website users, as well as their website conversion rate. See for yourself how TheHome, a Home&Deco online shop managed this!
Read more about How to choose the right product recommendations engine →
3. Dynamic Pricing
Dynamic pricing helps eCommerce shops by introducing a responsive and adaptive approach to pricing strategies. In this dynamic model, prices are not static but instead fluctuate in response to various factors such as demand, inventory levels, competitor pricing, and even consumer behavior. This real-time adjustment enables eCommerce businesses to optimize their pricing structures, ensuring they stay competitive and maximize revenue.
➡️ Examples of providers: dynamicpricing.ai, quicklizard.de
"Dynamic pricing is highly beneficial when you have a fixed quantity of perishable inventory, such as airline tickets, and what customers are willing to pay varies."
4. AI Chatbot
A lot of online shops have a chat box displayed on the website which is managed by the employee responsible for customer support. This role can now be passed on to AI-powered chatbots, which are meant to handle customer inquiries, provide instant support, and improve response times, thus enhancing customer satisfaction.
➡️ Examples of providers: DRUID AI, moin.ai
"AI is revolutionizing e-Commerce and I'm stoked that DRUID is leading this trend with AI-driven customer service and contact center agent automations, shopping assistance and product recommendations powered by Generative AI. We're providing technology that’s innovating and benefiting businesses like Kmart, Carrefour, Auchan, eMag, but also their customers."
Raluca Tatarusanu, VP of Sales DRUID AI
5. Segmentation Tool
Segmentation tools categorize customers based on behavior, enabling targeted emails, marketing strategies, and personalized communication. Such tools allow you to improve your marketing strategies and target users with content that is relevant to their specific interests.
➡️ Examples of providers: trbo, Salesforce, Mailchimp, Klavyio
80% of people are more likely to do business with a brand that personalizes their experience with it. That is why it is important to segment your audience and send tailored marketing communications.
6. AI-Generated Product Descriptions
Gone are the days when you had to spend hours and hours creating and uploading descriptions for your products on the website. Thanks to AI, we can now create product descriptions quickly and in a variety of content styles. Some systems can adapt their writing style based on the target audience, or the brand's tone and voice; thus product description writing has never been easier.
➡️ Example of providers: Dyver.ai, Ahrefs
"Dyver leverages AI and automation to retrieve, normalize, categorize and enrich product data, while creating descriptions that ease the burden on product and marketing teams. This ensures market readiness, increased traffic, customer experience and cross-border scalability at unmatched speed and accuracy."
Octavian Dumitrescu, CEO Dyver.ai
7. AI-Generated Ad Creatives
If you are an eCommerce owner or marketer, you have probably already struggled with creating appealing ads for your products - especially when the ad visuals require the skill of a specialized person. Good news! There are tools out there that help businesses to customize and automate their ad creation.
➡️ Examples of providers: Creatopy, AdCreative.ai
“Creatopy helps eCommerce shops by seamlessly automating the creative process. With our tool, it's easy to generate ad creatives that resonate with your target audience, thus reducing creative development down to a few clicks."
Dan Oros, CEO Creatopy
8. AI SEO Tool
AI SEO tools help in identifying opportunities for improvement, uncovering valuable insights, and improving the optimization process. Such tools can assist in keyword research, content optimization, and link-building strategies, ensuring that product pages are not only search engine-friendly but also tailored to meet the evolving needs of users.
➡️ Examples of providers: Aysa.ai, Surfer AI
“Our platform harnesses advanced AI algorithms to conduct site audits, perform keyword research, execute backlink analysis, and carry out on-page optimizations. By embedding AI into every aspect of SEO, Aysa.ai delivers actions with precision, thus helping eCommerce shops save time.”
Marius Dosinescu, Aysa.ai
9. Predictive Analytics for Inventory Forecasting
Predictive Analytics for Inventory Forecasting can anticipate future demand patterns for products in an inventory. This approach goes beyond traditional methods by leveraging advanced algorithms to make accurate predictions, optimize stock levels, and ultimately prevent both overstock and stockouts.
➡️ Examples of providers: Netstock, o9 Solutions
Zara uses Predictive Analytics to understand customer preferences and anticipate fashion trends. This allows Zara to adjust its inventory rapidly, ensuring that stores are stocked with the latest fashion items that align with customer preferences.
10. Visual Search
By utilizing advanced machine learning algorithms, visual search systems can analyze and identify objects, colors, patterns, and shapes within images, enabling consumers to find similar or identical products within a retailer's inventory. This capability is particularly useful when a shopper sees an item they like in the real world, in a magazine, or on social media and wants to locate it online.
➡️ Example of tools: Canto, ViSenze
Visual search simplifies online shopping by letting users find products using images rather than keywords. It enhances the customer experience by streamlining searches, making it easier to discover desired items.
Conclusion
AI is here to stay, so we might as well make use of it! Even if it means trying out multiple tools to see which one is the best for your online shop, we recommend you stay up to date. In this day and age - who knows what can give you a competitive edge against other eCommerce shops?
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Create product pages that convert
Now that you have learned how AI tools can help take your eCommerce shop to the next level, take a look at how to create product pages that convert in this free eBook!
