Retailers Biggest Fear? Survey Says Site Downtime and Poor CX
A recent report from Lucidworks surveyed retailers to gain insight into how e-commerce companies with $100 million or more in revenue power site performance, including product discoverability, customer experience, and personalization.
Understanding shopper intent requires an enormous amount of tuning, tweaking, and data combing. Retailers put endless pressure on themselves to create the perfect shopping experiences for consumers since they know customers will punish brands that don’t.
Research shows that customers who use search are ready to buy, but that 80 percent of those searches fail because sites rely on simple keyword search. Providing greater relevancy requires brands to analyze what people are searching for, and then optimize synonym lists, business rules, ontologies, field weights, and countless other aspects of their search configuration. Read on to see how your search stacks up and learn best practices in e-commerce performance.
Know Your Customer From First Visit to Final Purchase
Almost half of retailers (47 percent) say their add-to-cart (ATC) percentage is between 11 percent and 15 percent, with a quarter of retailers (28 percent) averaging an ATC of 5 percent to 10 percent. Forty-two percent of retailers have a clickthrough-rate (CTR) of 16 percent to 25 percent, with 31 percent of respondents saying their average is above that.
Sixty percent of shoppers visit a site up to four times before making a purchase, with 40 percent making five visits or more before they buy. For the 67 percent of retailers that are collecting customer feedback signals, each of these visits, as well as ATC and CTR, are an opportunity to better understand shopper intent and boost the chance of an upsell or cross-sell.
Incorporate Different Data Sources to Refine Search
Retailers are leveraging data from different sources to get a more holistic view of their customers. Loyalty systems are by far the most common data source brands utilize as part of their stack at 76 percent, with point-of-sale (POS) data at a distant second (59 percent).
Geographic information system (GIS) technology is tied for third at 40 percent. If you’re not incorporating GIS tech, your website could be promoting a snow shovel to a customer in Miami, or a lawnmower to a Minnesotan in the dead of winter. Pushing products without knowing the context and behavior of shoppers could be causing them to click elsewhere.
Prepare Site Performance for Peak Demand Periods
Site performance, product findability, personalized recommendations and more all impact whether a consumer returns later, purchases or abandons their search completely. These factors are especially critical during high-volume shopping periods, including Black Friday and the holidays. Almost three-quarters (73 percent) of retailer respondents say downtime, degraded site performance and poor customer experience, collectively, is their top worry during peak demand periods.
Keep in mind that 40 percent of potential customers will bounce if it takes longer than three seconds for the site to load. Reach out to your vendors to make sure site performance, including page-loading speed, can handle the influx of holiday shoppers.
Don’t Let Outdated Product Catalogs Cost You Sales
Modern technology allows retailers to update their product catalog in about 30 minutes. However, more than half (53 percent) of retailers report that they require up to 24 hours or more to make a new catalog item available to be sold online. Legacy infrastructure could be one of the causes of longer lead times, creating missed opportunities for time-sensitive trends.
Adopt AI Tools to Understand Customer Intent
Retailers aren’t usually technology experts. However, with new developments in artificial intelligence (AI) and machine learning (ML), it’s gotten easier to quickly improve site performance without being a search expert. Retailers are adopting AI-powered tools at a relatively high rate, but still have room to improve on creating hyperpersonalized experiences and understanding customer intent. Many of these steps are still being done manually. Not surprisingly, larger retailers, those doing more than $400 million in revenue, are leading the way in adopting AI-based systems.
Retailers say documentation classification (i.e., assigning an item to a specific category to make it more easily discoverable) is currently the most common usage of AI and ML (59 percent), with product recommendations trailing by only a small margin at 56 percent. Natural language processing (NLP) comes in third (52 percent), with retailers working to improve the customer experience by better detecting key phrases and terms.
In today’s always-connected shopping environment, online and in-store sales are heavily influenced by search performance and product discoverability. Retailers’ ability to deliver relevant search results, personalized recommendations, and real-time response will be what puts them ahead of the pack in the long term.
Download the full report today to see how your search and customer experience stacks up.
Diane Burley is vice president of content for Lucidworks, the leading search AI company.
Diane Burley is VP Content for Lucidworks, the leading search AI company. A former journalist and multi-media executive, she has been a content officer for technology companies. As a storyteller, Diane helps executives in all industries understand technology’s role in solving many of the challenges they face today. In her off-hours, she is a court-appointed advocate for a foster teen.