+10 %
Conversion Rate
+16 %
Revenue per Impression
+14 %
Adds to Cart
Bring more customers to your site—and make sure they convert while they’re there.
By improving SEO and SEM, Avatria Engage is proven to drive more traffic to your site.
Key Capabilities
Improve conversion by showing customers what they’re looking for with AI-optimized search, browse, and recommendations.
Key Capabilities
Whether you’re new to SAP Commerce or optimizing an existing site, Engage can be implemented within 30 days, saving months of development time and preventing problems before they arise.
The Challenge
Many sites experience reduced SEO values due to a few common problems:
Avatria’s Solution
Avatria’s Vanity URL capability gives business users the ability to solve these issues by providing full control over the structure of your URLs. This means you can automatically:
The Challenge
Any time a product family contains multiple options (such as size or color), most eCommerce sites will generate a unique URL for each variant. Unfortunately, this causes search engines to index each variant as a unique product, splitting the Page Rank of the product and causing it to show up lower in search results. This effect can be so severe that oftentimes a product will fall off the first page of results entirely, leading to a significant reduction in referral traffic from organic search.
Avatria’s Solution
To address this, Avatria Engage supports URL Canonicalization. This feature forces a search engine to treat related URLs as a single product, leading to higher page ranks and improved organic search placement.
The Challenge
For many sites, search engines are able to embed rich product data directly into the listing, such as the title, description, reviews, and more. This meaningful information, known as “Microdata,” can improve the likelihood that a user clicks on your link.
Avatria’s Solution
Avatria Engage has implemented Schema.org, a Microdata standard, into relevant eCommerce templates, ensuring that search engines can display attractive content in listings for all your pages.
The Challenge
Over 73% of shoppers never make it to the second page of products on category or search results pages. This means that getting the best possible products in front of the customer as soon as possible is crucial to conversion.
Unfortunately, many modern eCommerce platforms rely on simplistic product sorting capabilities, leaving top products buried below the first page, and requiring extensive manual merchandising effort to optimize product lists.
Avatria’s Solution
Fortunately, the solution is simple. Avatria Engage* uses machine learning to create personalized product lists in categories and search results. By studying shopping behavior, product data, and user demographics, Avatria Engage determines what the shopper is most likely to purchase, and pushes the best products to the top of the page.
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The Challenge
Product recommendation carousels are a staple of the modern eCommerce experience, and have been proven to dramatically increase Average Order Value. Unfortunately, many eCommerce platforms require an effort-intensive process to make these carousels effective, and make personalization virtually unmanageable.
Avatria’s Solution
Avatria Engage* uses machine learning to automatically generate personalized recommendations. With multiple carousel types available, such as “You May Also Like,” “Similar Products,” and “Most Popular,” cross-selling and upselling on SAP Commerce has never been easier. Avatria Engage makes it painless to display recommendations anywhere on your site.
*Powered by Convert Recommends
The Challenge
Most conversion optimization solutions operate as a black box, preventing business users from understanding why they work, and applying lessons to other parts of the business.
Avatria’s Solution
Avatria Engage* provides actionable business intelligence without needing a data science team. Advanced dashboards like Relevance Analysis, Key Metrics, and Anomaly Detection help you identify where your site needs help, and make it simple to track progress.
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