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Defining E-Commerce Personalization and How Every Online Business Can Benefit From It

In a digital world, being personal has never been easy— at least until the concept of e-commerce personalization came along. Now there are best practices for creating a personalized shopping experience, and these practices lead to an ideal shopping environment for your customers. 

If you own an online store, you know all too well the challenges of connecting with your shoppers. Sure, you try multiple ideas for connecting, such as frequent social media posts or clever email marketing campaigns, but it’s still hard to measure the results of engagement. 

E-commerce personalization allows you to use the data you receive on a regular basis, and use it to create a much more personal online shopping experience. For your shoppers, this means the digital world can become almost as personal for them as walking into a physical store.

Let’s explore this concept further.

What is e-commerce personalization?

Admittedly, there are a wide variety of terms and definitions to memorize when you run an online store, and e-commerce personalization may not be a familiar one. But the concept is straightforward — an online store owner can create individualized shopper experiences, based on browning history, data, insights, and demographics.

Think of this personalization technique as a way to create a unique shopping experience for individuals or groups of shoppers that visit your site. 

By incorporating e-commerce personalization techniques into your overall strategy as a business owner, you can increase your conversion rates, lower your cart abandonment rate, and increase your average-order-value. Or your goal may be tied to email marketing, such as collecting a wide range of email addresses or communicating an important company update. 

With online attention spans becoming shorter by the minute, e-commerce personalization offers a way to capture your shopper’s attention. What does your shopper get in return? Your shopper receives messages tailored to their needs, and motivates them to move further along the customer journey. 

Consider this statistic: on average, 71% of consumers express some level of frustration when their shopping experience is impersonal. By providing a personalized experience, your shopper is less likely to experience frustration.

Your shopper has likely shopped at a brick and mortar store in the past. When you physically walk into a store, a well-trained store associate offers multiple ways of helping, including:

  • Recommending a product
  • Helping find a specific product throughout the store
  • Giving opinions from other shoppers
  • Help with payment methods and options
  • Advice on how to use the product

But store associates don’t exist in the online world, so the need for e-commerce personalization is becoming more important, as shoppers need help navigating through a variety of product choices.

Using personal data

E-commerce personalization relies solely on data. Since you can’t meet with your shopper face-to-face in an online world, then you have to rely on the next best thing. 

But data is a broad term. So let’s break it up into the types of data, to understand what you can use to provide a more personalized shopping experience. Let’s look at how the following is used to reign in the data and use it to yours and the shopper’s advantage, including:

Demographic information

Demographic information should be used for personalization for a more personalized shopping experience. Demographics include information regarding gender, age, ethnicity, income level, and location. Location is determined from the IP address registered to either the website or mobile device the shopper is using. 

Using specific demographic information allows you to geo-target your shopper. For instance, if you’re an e-commerce store that focuses on outdoor products, you can use the shopper’s location to recommend specific outdoor products that are favorites in their city. Let’s say a particular backpack or stainless steel tumbler are best sellers in their location. Not only does this give your shopper ideas for products, but creates opportunities for you to cross-sell or upsell.

But demographics are only the tip of the iceberg. With so much personal data available to online store owners, there is greater opportunity for e-commerce personalization than ever before. Here are other examples of personal data you can use to customize the shopping experience for your shopper:

  • Type of device
  • Time of day
  • Weather
  • Location
  • Employment
  • Income level

As you can see, some of these demographics are highly personal, but using this information allows you to tailor the messages for your shoppers. For example if there’s an upcoming holiday in the country they’re shopping from. 

Behavior

Your shopper’s actions, or behaviors, offer multiple clues on where they are on their customer journey. Not only does it provide information on their past experiences, but it also points you in the direction for their future purchases. 

What kind of data provides you a snapshot of your shopper’s behavior? Consider the following data points and how it can be used for an individualized experience:

  • First-time site visitor
  • Previous site visitor
  • Past purchases
  • Past email interactions
  • Recently viewed products and categories
  • Items from abandoned carts
  • Loyalty program member

This type of data might change the way you market to your shoppers. For example, if your shopper recently purchased from you, you could add a note above the product with a tag of “previously purchased on X_date.” This serves as both a reminder to the shopper and encourages them to continue looking within that same category.

Popups and overlays are another useful tool when using behavior for a personalized experience. A popup is useful when you’re trying to grab the shopper’s attention. This example from GlassesUSA shows how a popup is used to get a shopper to join the email and newsletter list.  

Or an overlay is often used for offering discounts because your site visitor is brand-new and you want to encourage them to purchase with an additional discount. 

Segmentation

Another tactic for personalization is to segment your data. This is where you “lump” together your shopper’s data that share a common feature and allows you to focus your marketing efforts as well as create something more personal. 

Segmenting data not only allows you to digest massive amounts of information, but it gives you endless combinations for you to tailor your marketing campaigns. Here are the multiple ways you can segment your shoppers:

  • First-time site visitors
  • Mobile-device users
  • Price-point
  • Viewed certain categories of products, for example, camping supplies or school supplies

Continuing with the mattress theme, this is an example of how Puffy used the information as a first-time visitor to offer a discount and entice visitors to sign up for their newsletters. 

Segmenting is a simpler way to add more personalized shopping experiences for a broader range of customers.

Traffic sources

The source of traffic for your site holds a large key to information about your shopper. As you know, there are numerous avenues for your shopper to find you as they’re searching and browsing online. How you’ve captured their attention can be used to provide a better experience for them.

Traffic sources range from search to ads, and your shoppers can come from any one of these:

  • Organic search
  • Paid ads, such as Facebook and Google ads
  • Pinterest
  • Instagram
  • Other social media platforms
  • Amazon

Once you know where your shopper came from, you can tailor their experience further. For example, if your visitor came to you through a Pinterest pin, you could create a coupon for “Exclusive 10% off for Pinterest followers” or something similar.

Incorporating product recommendations and related products

For online stores, one of the most personalized aspects of shopping is to make product recommendations to your shopper. But anticipating what product your shopper needs and what they may like can be a little tricky. What kind of data do you need in order to make the proper product recommendations?

You would need to gather data on your shopper’s preferred brand, price points, location, and product pages they visit on your site. With this information in hand, you can offer more targeted product recommendations that eventually result in a cross-sell or upsell. 

Cross-selling and upselling

Cross-selling is a term used when you recommend a product or service that compliments what your shopper is looking for. If your shopper is browsing for a camping grill, then cross-selling kitchen supplies for cooking on a campfire would be appropriate. 

Up-selling is when you offer information to your shopper and encourage them to consider a more expensive product, but it’s the same product category they’ve already shown interest in. Again, with the camping grill example, if your shopper is browning a $300 version, but using the data your site would show the $400 version, and the additional features your shopper gets when they step up to a higher price-point.

Data is how you determine the opportunities for cross-selling and up-selling. Plus it creates the personal experience for your shopper. It’s showing them products they might not have realized they “needed” in their life or how a particular product can solve a problem for them. 

More e-commerce personalization examples

Using data and incorporating related product information and related products are a few examples of a personalized experience for your online shopper. But there are other methods you can use to create a more personal environment.

Payment methods and installment plans

Let’s face it, money is one of the most personal matters for your shopper. Each shopper you have has a unique circumstance surrounding money — both in how they earn it and how they spend it. So it’s not surprising that money, currency, and payment methods can lead to a more personalized experience.  

If you sell products in more than one country, using your shopper’s geo-location allows your site to automatically switch to the appropriate currency. This removes any guesswork for your shopper and is one less barrier to a complete purchase. 

Adding installment plans, such as Splitit, is another tactic for providing greater e-commerce personalization. The right installment plan provides the ultimate personal experience for payment without the additional hassle of paperwork and applications. Your shopper chooses the amount per month that fits into their budget, using their existing credit card, which has multiple benefits for both you and the shopper.

The right installment plan offers the online store multiple advantages, including:

  • Higher amount of qualified customers
  • Increased average-order-value
  • Increased conversions
  • Increased shopper loyalty

For shoppers, the advantages of an installment plan are as numerous as for a business, including:

  • Streamlined checkout experience
  • Flexible payment terms to fit their budget
  • No interest or additional fees
  • Ability to purchase a greater amount, possibly for a higher quality item
  • Overall improved customer experience

Email marketing

Using data and creating a personalized shopping experience aren’t only for websites. You can use specific data points to customize the messages and offers your online shopper receives via email. 

Email marketing takes skill, it’s more than simply stringing together a few sentences and hoping your shopper opens it to read it. An email marketing strategy is as detailed and coordinated as any other marketing plan you put together.

An email marketing campaign is an organized, scheduled series of email messages with a singular goal in mind. Your goal may be to launch a new product, introduce new customer service guidelines, educate your shoppers on your updated shipping policies — whatever goal you have for your business, an effective email marketing campaign can help you communicate this clearly to a shopper.

Personalizing emails can be the difference between an email that’s opened, read, and acted upon, versus an email that sits in someone’s inbox all day or gets deleted. Here are a few interesting statistics from Instapage to illustrate this point further:

The bottom line is, personalized emails result in increased engagement with the shopper, and in turn, the chance of success for your business goals is improved. 

Not sure what types of emails to send for a more personal touch? Think about the messages you receive in your inbox and what it takes to get you to pay attention. You could:

  • Send a special birthday message with an exclusive coupon
  • Send a coupon to entice your shopper to “come back” to their abandoned cart
  • Send an email reminding a shopper of what they were eyeing on your site 
  • Update a shopper on price changes on items they previously viewed

With a little planning and creativity, an email marketing campaign can become a tool for heightened e-commerce personalization and higher engagement levels with your shopper. The right email can take your shopper straight from their inbox to the shopping cart on your site, making the purchase more streamlined.

Personalization based on device

Mobile shopping has become the new norm. Worldwide, the average share of online shopping penetration is 52%, with areas like Indonesia reaching as high as 80%. Whether you’re ready or not, your shoppers want a seamless shopping experience on their mobile device, laptop, tablet, or a combination of all these devices.

When you know where your shoppers are purchasing from, you can personalize their experience based on their device. This type of personalization takes on a variety of forms, including:

  • Enhanced product pages for mobile viewing
  • Easy-to-read product information, no matter where your shopper is browsing
  • Synchronized desktop and mobile browsing history, so no matter where they log on from, your shopper sees their browsing history
  • Integrating social logons, where your shopper can sign on to your site and make a purchase by using their social media account (like through Facebook)
  • Create an app for enhanced and easy purchase experience

Creating a positive shopping experience via a smartphone ends up separating your online store from others. With statistics showing more shoppers turn to their smartphones for purchases, this is an area you want your online store to lead in.

Machine learning

Machine learning may sound like a futuristic concept, but in e-commerce, it’s being used to revolutionize the shopping experience for online shoppers. What exactly is this? Machine learning involves the use of algorithms to spot trends in massive amounts of data. This isn’t to be confused with Artificial Intelligence, or AI, which is technology that mimics human behavior.

Machine learning is important because it brings all the e-commerce personalization ideas together— it’s the glue that binds the massive amount of data at your fingertips. Machine learning is what’s used to create the personal shopping experience. 

Machine learning is used in multiple applications with your e-commerce store. It provides the insights for a number of important aspects of running your company. Each of these aspects contributes to the overall personalization of your site, such as: 

  • Inventory management: Machine learning allows you to spot trends with your supply and demand, and adjust your stock levels accordingly. When your stocking levels are improved, the customer experience is improved.
  • Better customer service: Machine learning involves technologies such as chat bots to help resolve customer service issues. Chat bots respond to customer requests right away and have become increasingly popular. The numbers continue to increase for use of chatbots, with 64% of surveyed users claiming it provides a useful customer function.
  • Cybersecurity: Machine learning can boost your fraud detection efforts. When a shopper feels more secure with their purchases, it creates a positive shopping environment.

As you can see, machine learning is another tool for e-commerce personalization and improving the overall experience on your website. Once you decide your main goals for your site, you can use machine learning to get you to your end-goal. Whether you call in third-party experts or dedicate your own resources to developing and using machine learning, look at it as a way to bring a more personalized shopping experience for your customers.

How to measure success of e-commerce personalization

With these various tactics for creating the personalized shopping experience, it’s equally important for an online store owner to have metrics to review. After all, you need numbers you can point to in order to determine what’s working and what isn’t. The success of e-commerce personalization can show through various metrics, including:

  • Conversion rate: The percentage of site visitors who take the desired action (purchases, registrations, memberships, downloads, newsletter sign ups).
  • Bounce rate: In email marketing, this refers to the number of emails that can’t reach the intended recipient. In e-commerce, bounce rate is the percentage of site visitors who leave your site after visiting only one single page.
  • Average number of page views per visit: This is the total number of page views on your site divided by the total number of visits during the same timeframe.
  • Add-to-cart rate: This is the percentage of site visitors that add at least one item to their shopping cart during a visit.
  • Cart abandonment rate: The number, or percentage, of abandoned shopping carts, compared to the number of completed purchases.
  • Revenue per visit: The total amount of money generated by each unique site visitor.
  • Average-order-value: The average amount spent on each order. AOV is based on the number of sales per order, not sales per customer.
  • Average session duration: The average amount of time a visitor spends on your site in one, single session.

Notice how each of these metrics is measurable. This is different from vanity metrics, such as the number of social media followers you have. These are metrics that reflect engagement from shoppers, and actually gives your business real results. 

Once you have your metrics determined, it’s time to start tracking. Compare the metrics before you implemented the e-commerce personalization strategy to a defined time period.  

And remember, if you’re not satisfied with the metrics you’re observing, you can always switch up your strategy. For instance, if you didn’t see much success with the overlay you added for a specific holiday, try changing the message or changing the time you use the overlay, like before a customer leaves versus when they first visit your site.

Create goals based on metrics

For personalization to work, it’s important to create goals on the metrics listed above. Once you define your most important goals, you can pinpoint which personalization tools to use and the data you need to collect to achieve it.

An example of this might be you want to improve your checkout page where your shopper has to make as few clicks as possible. To do this, you would need geo-data information to automatically identify your shopper’s currency. Then you would decide how you measure this success, such as through conversion rates or increased average-order-value. 

Personalization versus privacy

It’s hard to discuss e-commerce personalization, the use of personal data, and machine learning without giving thought to shopper’s privacy. It’s a fine line that can easily be crossed, and it’s up to you as a retailer to set the boundaries.

As a retailer, you must balance e-commerce personalization and product recommendations, with keeping your shoppers from feeling like their privacy was invaded. Plus, if you give them too personalized of an experience, there’s no room left for them to explore and discover your website and product offerings.

There’s no clear cut answer as to how much is too much data, and how much should be used versus remain private. But keep your shopper’s concerns in mind as you’re mining through the data and making recommendations. 

A Pew Research Study found that 79% of Americans are very concerned with how their data is being used by companies. Although most online shoppers understand their data is collected and used for marketing purposes, the waters are still murky on how much data is too much. It’s up to the individual online stores to determine how much data is collected and how much is used.

E-commerce personalization – a key to greater revenue and greater shopper loyalty

No matter how you choose to segment your data or the different tactics you use, shoppers now expect a more personalized experience — even in the digital world. This can be accomplished by using specific types of data and in turn, creating more personalized content through product recommendations, location-specific product offerings, email marketing campaigns, and other strategies. 

Once you identify which metrics you want to target and your online store’s goals, then you’re ready to fine-tune your shopper’s experience and create a more personalized shopping environment.

Sara Coleman (Content Contributor), December 17, 2020 Share this article

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