Online shopping is fundamentally a personal experience. When you shop online as a consumer, you’re typically either looking for something to meet your specific needs right now (like when you’re trying to find something to help you clean the grout in your shower) or you’re looking for something that meets your specific preferences (like when you’re browsing a shoe sale for something that catches your eye).

With that in mind, every e-commerce site’s biggest goal should be to help a shopper find what she’s looking for — something that addresses her current needs or fits her specific tastes and preferences — as quickly as possible, much like a sales associate would do in a physical store.

Invaluable, the world’s leading online marketplace for fine art, antiques and collectibles, has this goal. It knows that fine art and antique collectors have sophisticated and highly individualized tastes. Some seek to build an intimate collection of unique pieces spanning several artists or movements, while others are interested in extremely specific, one-of-a-kind pieces. Invaluable knows that it in order to provide a good experience and keep collectors engaged, it has to surface the most relevant items to each person to help them easily find that perfect piece that matches their individual tastes.

The Challenge

While it’s easy to say that you’ll surface the most relevant items to each person, it’s much more difficult to put it into practice. Invaluable needed to be able to deliver individualized recommendations for specific items, categories, auctions or auction houses across their website, mobile app and email channels. And since Invaluable’s items are auctioned rapidly, it was critical that the company identify items each collector may be interested in — even if they had never viewed those specific items before — because any item a collector liked in the past will likely not be available for long.

Several years ago, Invaluable leveraged many different solutions to do this. However, these solutions had to be managed independently and they kept highly important and actionable data siloed — preventing Invaluable from creating a complete picture of each individual person.

What Invaluable needed was a single platform that could pull together all customer data in one place to deliver personalized experiences across channels.

The Solution

With Evergage, Invaluable can identify not just which specific items a collector is interested in, but what that interest says about her preferences for styles, categories, auction houses, artists and more — in order to recommend other items she may like across channels.

For example, it delivers an individualized MyInvaluable page to each collector that displays a collection of items, artists, auctions, categories and blog articles catered to each person’s tastes. This image below depicts a section of the page recommending specific items that a collector may like. In this case, the collector has primarily shown an interest in pop art pieces.

1-to-1 experiences

Invaluable also carries the same individualized experiences into its email campaigns. For example, its batch emails are tailored to each individual’s preferences at open time, rather than at send time, to ensure the content is as up-to-date as possible (so items that have already been sold will not be recommended, for example). In the image below, the recipient has demonstrated her interest in a specific carving. By swapping out static email recommendations for dynamic recommendations that are updated at open time, Invaluable has seen a 21% increase in email clickthroughs.

1-to-1 experiences

Personalized triggered emails are also sent based on a visitor’s actions to ensure they are timed appropriately. For example, visitors who have shown an interest in specific pieces recently, but abandoned the site before making a bid, may receive a triggered email encouraging them to return to the site.

Remarkably, these personalized recommendations in email, together with those presented on the website, have driven 12% of Invaluable’s monthly revenues.

Final Thoughts

Online product recommendations have been around for a long time, so you may think that you don’t need to think too much about them. But their effectiveness depends entirely on the data and algorithms powering them. To deliver truly relevant recommendations to each person, you need to have a good understanding of who each person is and what he or she is interested in. That means you need to bring your data together in one place, analyze it to understand what it says about a person, and then act on it to automatically select the most relevant products for each individual – all in milliseconds.

Essentially, you need a robust personalization and customer data platform. Request a demo today to learn more about how Evergage can be that platform for you, and read the full case study to learn more about Invaluable’s story.