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60% of Shoppers Visit Sites Up To 4 Times Before Conversion, So Make Their Journey Smooth Featured

  • Written by  Bryan Wassel
60% of Shoppers Visit Sites Up To 4 Times Before Conversion, So Make Their Journey Smooth

Convenience is possibly the biggest advantage e-Commerce has to offer shoppers, so it makes sense that factors causing inconvenience are the top three pain points identified by retailers: downtime, degraded site performance and a poor customer experience. These disruptive issues were collectively cited as the biggest worry for 73% of respondents to the 2019 Retail Benchmark Survey by Lucidworks and Retail TouchPoints, titled: Online Retailers Struggle With Performance, Targeted Personalization And Product Availability. Inconvenience also was a common thread behind the other top concerns: stockouts (69%), undiscoverable products (49%) and checkout slowdowns (48%).

Convenience also needs to be consistent over the multiple site visits that, according to the study, typically precede an online purchase:

  • 24% of shoppers make one to two visits before making a purchase;
  • 36% make three to four visits;
  • 22% make five visits; and
  • 18% make more than five visits.

The key to maintaining the shopper’s interest and stoking their intent to buy during this process is to understand the shopper and what they’re looking to buy, according to Diane Burley, VP of Content at Lucidworks. That begins with retailers taking into account the price point of the item and how that can affect customer behavior, then combining that information that with consumer insights to refine their strategy.

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“If something is a lower price point and it's taking them five, six, seven times to come back, maybe you need to ask yourself why that's happening,” said Burley in an interview with Retail TouchPoints. “You can send alerts to tell people this is waiting in your cart, but maybe they're waiting because they're traveling — you don't really know the reason why. If they're coming back five or six times and it's a higher-priced product, I think you can make some assumptions that maybe this has to do with budgeting and saving up, so maybe offering a time-sensitive promotional discount will encourage a purchase.”

Retailers can refine these types of outreach by looking at feedback signals, according to Burley. For example, are they still searching for similar products? In that case, the item in their cart may be a second choice and they may need an incentive, or help finding similar products, before pulling the trigger. Do they have a history of placing items in a basket and then waiting to make a purchase? If so, there may be no need for further action, but if it’s unusual behavior, retailers should look for ways to encourage the sale.

Feedback Signals Should Come From As Many Sources As Possible

Careful understanding of feedback signals also is important when it comes to providing personalization, and more than two thirds (68%) of retailers collect them for further analysis. This process is the key to turning cohort analysis, such as providing recommendations based on similar customers’ activites (which 69% of retailers offer), into true hyperpersonalization.

The consumer data used for personalization can come from a slew of sources. For instance, 76% of retailers utilize loyalty data, giving them easy access to past purchases and preferences, while 40% of retailers use Geographic Information System (GIS) technology, which helps ensure search results match the local weather, not to mention sports teams.

“You want to really bring in as many different types of data sources as possible,” said Burley. “Any one of these can give you some good indicators or some good ideas, but it's not necessarily going to give you that truly, uniquely personal experience. So if I know your history, I see what you're typing in and what you're not typing in, what you're clicking on and what you're not clicking on and what you buy and what you don’t buy, I can factor that in with what other people in your cohort might be doing and get a much better picture.”

Personalization applies to search as well, and retailers express confidence in their ability to understand shoppers’ query intents: the average retailer grades their capabilities at 4 on a scale of 1 to 5. However, there is still plenty of room for improvement: only 46% of retailers use anomaly detection, which is vital in getting ahead of trends and making sure both product stock and campaigns are being prepared accordingly.

The First Step Is Getting Search Right

Strong search functionality is a prerequisite for personalization — after all, a shopper won’t care what you present them with if it’s not relevant to what they want in the first place. This area represents a potential product management challenge, particularly with new product launches. While modern e-Commerce management tools let retailers have their entire index up and running from scratch in as little as 30 minutes, 53% reported that it takes them up to 24 hours or more to make a new catalog item available to be sold online.

This challenge was actually more common among companies with $400 million or more in revenue, at 54%. In comparison, only 39% of retailers with revenue between $200 and $399 million and 38% of retailers with revenue between $100 and $199 million need up to 24 hours to index items.

"Big companies are still struggling with the size of their product catalogs and the amount of time it takes for them to get their information even findable,” said Burley. “That's a fundamental problem right there. If your product information is not being indexed for up to 24 hours, or in 8% of cases even longer than 24 hours, that means you've got product ready to sell and yet you haven't even taken it out of the warehouse, for want of better way of describing it. Until that search engine index knows that that product is readily available, your shoppers can’t see it.”

As might be expected, offering accurate, up-to-date search results is an important sales driver: research shows that when a web site search is used, conversion rates average 4.63% compared to 2.77%. Ensuring that every search brings up relevant results requires a scalable engine that can make sure every item is available no matter how large a product portfolio grows. Applying that same level of dedication to personalization can keep a customer in your ecosystem no matter how many visits they make before making a purchase.

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