Hello readers! The first blog post of Spring is finally here.
Now that the days are longer and the weather is slowly getting warmer, you may be in the market for seasonal appropriate clothing - but perhaps since you've been bundled up in winter clothes for the past few months, you don't know the best online shopping destination. What do you do? Odds are, you turn to Google.
When you search for an item type, for instance "light sweaters," Google search returns with both paid ads and top SEO ranked pages, all of which often direct you to the same place: the product listing page (PLP).
This channel represents a big opportunity for retailers (just look at your own SEM spend that you make just to get customers here). It's the portion of the shopper's journey where customers don't know exactly what they want or actively search for the products they'll buy. These pages account for a significant amount of traffic due to search/SEO. The thing is, no technology or retailer has ever been able to optimize or improve the product listing page experience, so all PLP content is completely static.
The user experience of traditional product listing pages is consistently terrible, regardless of the retailer. Today, we're diving into the specific reasons why the modern product listing page experience is still so poor for customers, and what retailers can do to fix it.
1: Traditional PLP pages actually limit product discovery
The goal of any product listing page is to give customers a clear and simple path to the products they'll want to buy. It's the area of the user experience where customers have indicated interest in a certain product set, and are actively trying to narrow down to the products that they'll want to purchase.
The problem is that large e-commerce retailers have inventories that span thousands - if not millions - of unique items. Product listing pages default to displaying a pre-selected collection of trending/popular items, sale items, or best sellers at the top of the page, which is ultimately a static collection shown to each customer.
Essentially what this means is that there's no way for the retailer to recognize an individual user's specific interests and adapt to their preferences in this channel, or even to cater content to a particular segment or persona. Customers are limited to the same collection of goods as everyone else, and the long tail inventory within the rest of that category (which may be exactly what a particular customer is looking for) will never be automatically featured or may end up being buried on page 56.
There are a couple reasons why the PLP experience is limited to static displayed content: first, retailers who acquire customers through SEO and search often have difficulty recognizing users who arrive at the PLP stage. Even if you're a long-time customer at a particular site, entering at the PLP page means you'll be treated as a new user until you log in. Secondly, logging in and providing the retailer with your user history and preferences doesn't help - traditional PLP pages aren't able to incorporate user data quickly enough to accommodate and adapt to real time browsing behavior.
2: Manual processes are forced onto the customer
In most parts of the shopping experience, retailers actively serve content to their customers; whether it’s promotional banners on the homepage, personalized curated content on a landing page, or an e-mail with a collection of merchandised goods, the marketing team is doing the legwork to show customers what they think may be relevant. Even if the content completely misses the mark, it's produced by marketers and displayed freely, with zero effort placed on the consumer.
In product listing pages, retailers force their customers to search, filter, and scroll through thousands of products to narrow things down. Because there has never been a way to adapt content in real time, placing the extra effort on the customer to search and filter seems to be the only option.
This demonstrates a profound disconnect in retailers' ability to utilize customer information - customers browsing items in the PLP section are providing the most significant information about their current intent, but retailers can't leverage it to suggest the right items.
Ultimately, consumers just don't have the patience necessary to manually track things down. According to Jetlore's Consumer Survey Report, released earlier this month (access here), more than 40% of consumers lose interest after searching just 2 product listing pages because it's too much effort.
3: PLP pages have no memory
Another insight from Jetlore's Consumer Survey Report is that 86.4% of customers hate it when retail sites don't remember their information; customers expect a smooth shopping experience that adapts to the information they provide. Unfortunately, that's not possible with the current technologies powering PLP. It doesn't matter if you're arriving to a retailer for the first time or the thousandth - even with the most detailed user profile, the product listing page will feature the same static collection of content, and you'll have to sort and filter to find what you like.
If that's not annoying enough, the filters and selections you make on a traditional product listing page don't convert to other categories. If you're in the "pants" section and filtered "large" and "men's" products, the site can't remember those filters when you shop in a the “jackets” category. Instead, you have to search and filter all over again.
How to fix PLP
There's no denying that product listing pages are an important e-commerce channel; it’s the area that receives the most traffic, collects the most significant information regarding customer intent, and is the main channel for product discovery. The underlying problem with product listing page is that retailers are unable to leverage what they know about each customer in this channel, and adapt content while customers browse.
To fix product listing pages, retailers must invest in a system that can: recognize customers, and retain a detailed memory of customer information; quickly understand real-time impressions and learned behavior; understand what content is right for each individual at the time of interaction; and automatically surface the best individual products for each customer immediately.
Jetlore's Predictive Ranking™ product utilizes a patent pending "learning-to-rank" technology to do all of the above, and more. With our innovative AI, retailers can now leverage recently collected customer information to create a completely unique and relevant experience for each customer in the product listing page channel. To learn more about Predictive Ranking™ and how Jetlore revolutionizes PLP experiences, click here.
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