ATTRAQT : Product discovery now central to ecommerce merchandising

It's why product discovery solutions for retail really matter. Factors and numbers speak for themselves. Consumers are more likely to buy when they can find relevant products quickly, 54% will abandon a website if making a choice is too difficult, while 34% give up browsing after ten minutes. There is a small window of opportunity to capture shoppers online. Brands must be exceptional at it.

In an era of infinite abundance and availability via the Internet, tolerance for disappointment is pretty low. Choice paralysis is also extremely high, since consumers have an overwhelming number of products to choose from. Often shoppers have hundreds of search results to screen and filter. With more online stores and products available, it also becomes increasingly difficult to grab someone's attention. If a consumer cannot find what they're looking for quickly and easily - forget it.

With so much content, product information and social media feeds vying for people's time and attention, any tools that help consumers make sense of the shopping experience and guide them through the purchasing process in an intuitive and intelligent fashion are going to be invaluable.

Mastering the ability to help shoppers discover items that are of genuine interest to them has become a significant challenge for retailers. Offering shoppers tailored, personalized recommendations in ecommerce at scale is therefore the new battleground for brands. However, product discovery is one of the most underinvested aspects of the online customer experience.

For many companies, the dial has barely shifted over the last decade. Yet product discovery platforms now exist that bring the knowledge, expertise and profiling seen in expert sales assistants online. The enjoyment and entertainment of product exploration can now be mirrored in ecommerce, just like it is in store, but only with the right tools.

The search box is typically the first- place shoppers head to when they have an idea about what they're looking for. The ecommerce site search engine must therefore be fit for purpose. If it is powered by artificial intelligence it can offer fine-tuned product discovery results and recommendations based on machine learning. The search engine can then reference all customer journeys that have gone before and offer up the best results.

There are other issues that have arisen with product discovery too. Faced with too much choice online, shoppers are getting smarter at narrowing down their searches. They use more complex and detailed queries as if they were searching on Google. They also expect the retailer to answer these queries. These are difficult to answer unless the company has the right ecommerce site search engine. A poor search experience with countless zero returns on queries, or poor matches, means a loss of interest, product discovery, conversion and revenue.

Today's consumers also interact with brands across multiple touchpoints and prefer to follow their own path to purchase. Shopper journeys have therefore become more complex. Customers may come straight to a product page from a friend sharing a social media post, or from any myriad of other channels. It is also the case that, shoppers don't always know exactly what they're looking for. They may not have a specific product in mind, sometimes it's just an idea or a desire to shop. Browsing online for retail therapy is now as common as real life high and main street browsing.

To complicate matters further, with every visit, shopper intent can change, therefore low conversions online are a common problem. Just like someone who walks out of a bricks and mortar store after perusing the shelves but doesn't buy anything. Online, it takes on average three sessions before a customer converts; only 2% of shoppers convert via the web. It's a numbers game.

Gauging shopper intent at any point in the customer journey is therefore extremely critical. This can complicate a brand's product discovery strategy, but it also provides additional opportunities to engage with the customer with suggestions for the right product. Brands can prompt and entice with relevant content and offers at critical points in the shopper journey, albeit seamlessly.

All these issues and challenges can also be overcome with the right product discovery solutions for retail. Dynamic ecommerce merchandising is now possible. Data is the new oil in this process. Information on customer journeys is the great enabler. The more the better. It informs machine learning tools and artificial intelligence. It is the foundation of personalization in ecommerce.

A typical shopper experiences around 50 micro-moments - small, intent-driven shopper interactions with a brand - before purchasing. Each visit determines if a shopper stays on the journey or exits the site. This can all now be calibrated, understood and acted upon for each customer. The aim is to deliver a series of product discovery experiences that are connected, relevant and that inspire them to make the right choices, all the way through to a conversion.

Personalized recommendations go to the heart of this process. Customer data allows brands to map out all shopper journeys and therefore align products and collections to shopper intent, context and the needs of customers ensuring only the most relevant items are shown to those browsing on a brand's website. Parameters such as price range and the visual characteristics of a product matter.

Retailers can't leave anything to chance in this new era of product discovery that is both customer and data centric. No brand should let a good customer go to waste. We don't.