Home CE Retail The Power of Personalized Online Shopping

The Power of Personalized Online Shopping

personalized technology being used by a consumer

The latest trend data from GfK Consumer Life shows that over half of global consumers like the idea of technology that “knows” them — can make recommendations based on their wants and needs. At a time when concerns about privacy when online shopping are also on the rise, why would so many shoppers embrace algorithms and other targeting techniques – sometimes labeled as intrusive and even “creepy”? 

The answer may lie in another data point — that over one quarter of consumers say they “feel overwhelmed with information” when making a major purchase. While today’s shoppers may be the savviest ever, with dozens of ways to research and buy products, this access can come at a price — a sense of overload for people who already have too much to think about. 

Personalization of e-commerce content can save consumers precious time and annoying hassles — and it has huge upsides for sellers. Merchant World reports that nearly 35 percent of Amazon’s sales come from personalized shopping recommendations based on a user’s past purchases. But what does it take to offer a truly personalized shopping experience online? Are e-commerce sites ready to deliver all of the convenience that buyers crave? 

A person doing online shopping through their phone.

From Simple to Sophisticated 

According to Forrester, 53 percent of digital experience delivery professionals say that they lack the right technology to personalize experiences. Online retailers who fall into this category will find themselves at a severe competitive disadvantage in the modern e-commerce space. But there is good news: The many flavors of personalization give retailers a host of options, with some being elaborate and others fairly simple to execute.  

E-commerce personalization mainly refers to the curated display of online content based on past customer data to ease the purchase journey. The data used may include shopper demographics, purchase intent, browsing history, preferences, previous purchases, cart history, and device usage. All of these can provide insights that simplify the shopper’s experience and possibly boost retailer revenue, sometimes with a minimum of effort. 

Some of the most common personalization tools are based on a user’s purchase history. We often see this in personalized home pages when we do our online shopping, where products we have viewed or purchased show up on the landing pages we click on. This flavor of personalization is easiest to implement.  

The Shopify online shopping site app.

Utilizing purchase history can be as simple as showing previous purchases, related products, merchandised products, or product recommendations based on algorithms. For example, when a printer is purchased, recommendations would be ink, paper, and extended warranties.  

The difficulty comes in with associating products on a SKU or series basis. This is where a highly normalized data set with accessories can be invaluable to a reseller. A normalized data set has product data details in a uniform order for all the products within a category, regardless of brand. Data providers such as GfK offer highly normalized data sets with accessories that can be used for this purpose.  

Channel partners can manually create these relationships, of course, but the task is large; a single product can have dozens or more accessories — simply showing these add-ons increases sales and conversions. The ability to leverage connections between products is the power to drive revenue. 

A Curated Option 

Purchase and search history by curated preferences is an extension of purchase-based personalization. Preferences can be defined by direct questions to buyers or by deductions made from purchase and search history. A deduction would be that a buyer from a legal office who purchases a printer would be interested in buying legal-sized paper and labels. Although not a direct accessory to the printer, paper selections displayed during a printer buyer’s search would likely increase sales.  

Deductions can also be made based on other related consumer purchases in specific categories and choices that they make in tandem. For example, law office customers may purchase many of the same items — creating a legal customer profile. Using specific types of profiles can take data in from many customers in similar businesses and create useful insights for resellers. The number of potential profiles is endless, and every search or purchase adds to the data set.  

Sophistication At Scale 

On the more sophisticated end of personalization is Amazon, which records and leverages every move made by a shopper. Amazon maps these actions carefully, studies the decisions made or not made, and integrates “people who viewed this bought that” data. The Amazon network data drives proprietary algorithms that dynamically provide shoppers a very curated journey based on their seemingly “casual” web interactions. Examples can be as simple as “buyers of running shoes tend to buy health food” or much more complex.  

An algorithm page showing what personalized online shopping settings can be set on a website.

Companies like Amazon and Walmart amass huge amounts of data and can run what are known as A:B tests. The same data or products are shown to a specific segment of buyers, and then a variable is introduced, and the results tracked. Using our legal office example: Half of the buyers within a legal office profile can be offered a promotion upon making a specific search. The promotion may be for a case of legal paper as the first search result. The retailer can then track the results, and know if the average cart size increased or decreased for the trial group compared to the reference group.  

Resellers of nearly all sizes can automate these A:B tests and perform many in a short amount of time. The test can be multivariate, which can speed the results, as well as the resulting changes to search or merchandising. The variables are not only product- or price-based; they can be region, by time, by external events, or even by influencers and promotions. The results can be built upon to continually optimize sales and conversions. Examples may be to show different brands that help drive margins of a case of legal paper in the example above.  

The truth is that you don’t need to be Amazon to take advantage of personalization. All retailers can use similar concepts and techniques to increase sales and margins. Here are a few essential steps for your journey: 

  1. Establish your goals — Are you just driving revenue? Trying to grow a specific product line or category? Knowing where you want to go in the end is key.  
  1. Take the customer’s viewpoint — What would make your users’ site experience better? Think beyond today’s revenue — consider the loyalty and stickiness you will build through great CX (customer experience). 
  1. Partner with your platform provider — Big Commerce, Magento, Shopify, and WooCommerce all offer personalization options that are inexpensive and can be easy to set up. 
  1. Check your product data — Does it allow for product associations and relationships? Normalized product catalogs such as GfK’s provide this functionality, in addition to delivering content for millions of products. 
  1.  Focus on continuous improvement — Once you have launched, keep checking your results and adjusting accordingly. Personalization is an iterative process, not a one-off. Think of all the ways it will benefit your business in the months and years ahead! 

Today, personalization is not just for ecomm giants with deep pockets; you can do much more with less – and the first step is deciding that now is your time to make a splash with this potent tactic. 

Lloyd Wood is Director of Sales at GfK Etilize, the world’s largest aggregator of content for e-commerce. He can be reached at Lloyd.wood@gfk.com.