Strategic recommendations in ecommerce account for more than 30% of revenue today. Every ecommerce brand seeks ways to earn their customers’ trust and bring in more sales than the previous year.
The secret is well-curated recommendations. They work directly to increase sales by making product discovery friction-free and helping to increase the average order value. The result is a booming business that you can future-proof with the right strategies in place.
In this article, we’ll cover:
Let’s dive right in!
As customers, we know how nice it feels when a brand shows they care about our investment and trust. From that perspective, there are a lot of ways brands can show they value their customers and want to ensure every shopping experience is as seamless as possible.
With AI, the simplest way to execute this now is to curate and display personalized recommendations on the shopper’s screen. Emotional bonds between customers and the brand of their choice go a long way in promoting loyalty, future-proofing your brand, and creating a positive image in the market against competitors.
When they choose to share their data with you, with information like their shopping history, likes, preferences, and wishlist of items, it becomes your responsibility to respond to them. By analyzing this data and accurately understanding their choices, your recommendations can help reduce decision fatigue and enhance their shopping from discovery to purchase.
Artificial intelligence can single-handedly skyrocket your business growth when used correctly.
With ViSenze-powered solutions, you can differentiate your brand and offer personalized suggestions. AI can be the ‘x’ factor that separates smart recommendations from generic ones—AI automatically tailors your display to every unique shopper.
Looking more deeply into ViSenze’s offered solutions, here’s a brief rundown of the six recommendation engines we employ to ensure every customer feels special when shopping from your brand online.
Each engine contributes to increasing sales by targeting specific shopper needs and behaviors. By investing in AI technology, you not only improve conversion rates and average order value but also move to gain a higher market share and become the go-to brand in your industry.
Upselling and cross-selling are long established as two of the most efficient ways to increase the average basket size and keep your inventory in high demand without active marketing efforts.
Customers who like your brand want to learn more about what you have to offer, and encouraging them to explore products they might not have purchased before helps you lead them to an enjoyable shopping spree with ease.
Higher-value items or additional products might not be on their shopping list, but your display can make them look like the perfect add-on for their existing cart.
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Product recommendations are not a way to squeeze extra money out of existing customers using some tactic. Instead, this vetted strategy builds trust between the customer and you.
When customers know their data is being stored privately and used exclusively to improve their shopping experience, they are inclined to continue desiring tailored displays. Online shopping with high-quality and accurate recommendations immediately establishes your brand as trustworthy.
In ecommerce, trust correlates directly with repeat business and increased sales.
As one of India’s leading fashion platforms in the e-commerce sector, Myntra offers a catalog of 6000+ brands, and helping customers find the perfect fit is their top priority. Gen-Z customers demand instant gratification, which was an opportunity for the brand to support them with visual search and intelligent recommendations.
Myntra leverages ViSenze’s Discovery Suite to power its ‘View Similar’ carousel to curate a collection of similar items based on visual attributes like style and color. This also supports better conversion when certain products are out of stock, increasing user revenue.
For driving complementary product recommendations, Myntra’s ‘Shop the Look’ leverages ViSenze to automatically showcase more products from the model images supporting AOV growth. This led to Myntra’s image search traffic growing by 35% over the last 12 months. Read the entire case study here.
Zalora is a leading online fashion and lifestyle brand in Asia, with over 41 million monthly visits and an impressive catalog of 3,000 fashion brands. With such a large inventory, it became difficult for them to maintain display transparency and ensure that the right customers viewed the most suitable products.
With ViSenze, they changed that as they introduced the Discovery Suite. This enabled Zalora to start smart tagging and ensure each product had the correct tags to be shown to customers who have shown a preference for similar items before. The Smart Recommendations feature also improved product discovery and kept their inventory in check as more customers found newer products to buy.
Seemingly simple, this change helped the company improve its engagement rate by 10% and the AOV by 15% after working with ViSenze. Read the entire case study here.
Now, you know more about recommendation engines and might even consider utilizing them to help your business grow. We get it; integrating a new strategy can be overwhelming and confusing. Here is a set of tips to help you get started with the first step:
You don’t want to overwhelm the customer with choices and options, often leading to cart abandonment. Instead, limit your recommendations to a few web pages and a handful of products each time. This lets the customer feel like they are in control of their decisions. It also allows each of your products to appear high-quality and sought-after.
To power up your product discovery, book a demo with Visenze today. Join the world’s top retailers who trust us to drive success.