For a long time, eCommerce has been on the hunt for the holy grail of personalization - a consistent, cross-channel experience that adapts to customer needs and goals in real-time.
The good news for eCommerce is that these technologies have arrived.
The bad news is that the sheer amount of these technologies, which offer very different levels of personalization, means it’s unclear what designing personlized user experiences in eCommerce means and how you can achieve it.
What is eCommerce Personalization?
eCommerce Personalization is the process of delivering personal experiences on eCommerce sites by dynamically showing content, product recommendations and specific offers based on previous actions, browsing behavior, purchase history, demographics, and other personal data.
Personalization is increasingly important to merchants seeking to, not only engage shoppers, but also to increase repeat purchases, drive sales and increase conversion.
It comes in many different forms—from personalized product recommendations on a retailer’s homepage or product detail page, to cart-abandonment marketing emails to onboarding quizzes that provide a personalized showroom of items to consumers, among many other applications.
Benefits of Personalization in eCommerce [with stats]
Before the explosion of digital commerce, customers simply walked into stores and found a friendly clerk who helped them find what they wanted.
Pretty simple, right?
Unfortunately, that kind of personal customer attention remains exceedingly rare in the digital realm. Even in the “age of the customer,” retailers, brands, and B2B companies talk a great deal about the need to personalize the customer experience.
Let's take a look at benefits of personalization for eCommerce businesses.
🔍 Consider those ecommerce personalization stats:
Marketers see an average increase of 20% in sales when using personalized experiences. (Monetate)
80% of shoppers are more likely to buy from a company that offers personalized experiences. (Epsilon)
44% of consumers say that they will likely become repeat buyers after a personalized shopping experience with a particular company. (Segment)
77% of consumers have chosen, recommended, or paid more for a brand that provides a personalized service or experience. (Forrester)
However, in another Forrester survey 53% of digital experience delivery professionals said they lack the right technology to personalize experiences.
What an eCommerce Personalization Strategy Should Look Like
The heart of personalization is goal attainment.
Importantly, these goals should be customer driven.
It’s not about simply delivering what your business wants, but also about allowing every visitor to consume the experience how they prefer and helping them achieve their goals at each stage in their journey.
Think of a business you interact with online - your favorite store, your bank, a vacation booking site - and recall the variety of goals you’ve looked to accomplish there.
Your needs from a home goods store may be quite different during wedding season. You relied on your bank for a new set of information when buying a home, and your vacation preferences change depending on if you are traveling by yourself or with family.
Each visitor interacts with businesses in a multitude of ways and truly powerful personalization looks beyond who you are to what you are trying to achieve right now.
Of course, this is easier said than done. While personalization is an increasingly hot topic, most businesses are still in the early stages of understanding how to best utilize it.
When embarking on a new personalization strategy, or revamping an existing one, personalization boils down to 3 main questions:
👉 [Question 1]: Where should personalization occur in the user experience?
Look at all the channels and touchpoints your customers interact with. Where would a personalized element help the most? Product recommendations, inspirational content, location based services, site search, customer portals - map out each micro-moment that could benefit from a more contextual experience.
👉 [Question 2]: What information will be used?
What tools do you already have - CRM, marketing automation, A/B testing, transactional systems, - that offer a wealth of information? Take your map of where you’d like personalization to occur, decide which of your current tools could help support each micro-moment, and identify the gaps in data you need to fill to complete your vision.
👉 [Question 3]: How will you use technology and human insight to create this personalization?
Now comes the fun part. How are you going to bring all of your channels and data together to deliver this contextual experience at scale. This is the biggest question of the 3, and one we dive into in the following eCommerce personalization examples.
Understanding each customer’s need is the very essence of personalization. Satisfying that need takes a blend of the right technology and the knowledge of how to use it.
Whether it’s a new visitor or a familiar customer, you can assemble clues from how they entered your site to determine why they came to you. If you identify that intent immediately, you can shorten their customer journey and enhance their experience.
Did they come from an advertisement on social media? Did they look for a particular product or service on a search engine? Did they find you from a press article?
If you’re lucky enough to have a known visitor, that perhaps purchased something or filled out a form, you can display items or content that is related.
🔑 Do this:
If you’re a sports retailer and they have entered through a search engine with the term “bargain golf clubs,” your landing page could boost some clubs you have on sale along with other low-priced clubs to the top of the product grid.
If you’re an insurance company and someone is visiting via their mobile phone from a country out of your region, you could induce they are likely a client on vacation and show claim information on the homepage.
If you’re an electronics retailer and your visitor recently ordered a laptop, merchandisers may want to display some popular accessories for that computer, like a desktop porting station, an external memory drive, or a carrying case.
Combined with other information you may know about this customer, such as past purchases and recent browsing history, you can assemble a page that lists what the customer really wants and include content that helps them make a purchase decision.
You can virtually accompany your visitors while they browse your site, just as a car salesman might walk with a customer around a showroom.
All along the way, a good salesman picks up clues on what kind of car suits his customers, what color they like, what they can afford, and how soon they want the vehicle. Knowing the dealership’s inventory, he can then show them a car that matches their needs
You can take a very similar approach online and can even use a trick that car dealers can’t: you can remain invisible while you do it.
A key to making this work is to let machine learning process all that information and match it against your inventory in real time.
Not only can machine learning help guide individuals at blazingly fast speeds, but it can also offer options a human might have missed by recognizing patterns in the visitor’s past behavior or matching them with a segment of buyers that had similar characteristics.
Your system can even identify entirely new customer segments that your team overlooked.
🔑 Do this:
If a clothing retailer knows that customers will soon be looking for festival wear. They create a landing page and add in the products they believe festival goers will be hunting for.
The machine then gets to work, boosting items that are performing well, have more stock available, and align to the visitors preferences.
Additionally, content marketers might create targeted inspirational content around regional festivals and let the machine provide the right content based on IP locations.
Adding intelligence to the user experience can also provide real time assistance to users that simply isn’t possible manually.
For instance, say a transportation service has an app offering public transportation directions. Algorithms could determine, based travel speed, if the user is walking, biking, or driving, and recalculate the journey with the appropriate timings.
1:1 personalization requires rapid data aggregation and analysis, cross-channel deployment, and machine learning optimization.Marketers and merchandisers can use this deep level of data to provide 1:1 personalization through specific product recommendation.
Product Recommendations is a service that displays product recommendations for customers based on their browsing history.
You’ve likely seen prompts and recommended products on retail websites before. “You Might Like…” and “Others Also Purchased…” are common prompts on eCommerce websites that signal a product recommendations engine at work.
🔑 Do this:
For example, if you have a customer who looks at very high heels, then you might suggest shoes with stiletto heels and shoes with four or five-inch heels.
If a customer browses several Louboutin slingback heels, then Dynamic Categories might suggest Shoes by Christian Louboutin or Evening Wear Shoes by Christian Louboutin, and display products matching those categories.
How to Get Started
[Step 1] Understand where and how you want to personalize for your site visitors. This decision should also be made depending on where the most impact on revenue is to be had with personalization.
[Step 2] Do your research on the available eCommerce personalization technologies and tools out there, and decide on a few to get you started.
[Step 3] Assign enough resources to the project. Decide who will oversee this project and measure the gains.
[Step 4] Define a long term personalization strategy and optimization process.
[Step 5] Start to segment and personalize your site. See which areas of your site benefit most from personalization.
[Step 6] Continue to track and monitor the results of your strategy. Optimize the process where needed.
[Step 7] Once you're happy with the strategy, begin to scale across channels
eCommerce Personalization Examples: Boden, Albertsons and Torrid
Boden realised that personalising the customer journey was the key to their future success. However, the team was working with tools that required a lot of manual work and were therefore time consuming and slow to market for trading changes.
As part of the digital transformation project, they looked for a solution that would allow them to use their time more wisely and strategically.
With Bloomreach, Boden is now able to build a personalised experience for each of their visitors. The solution is powered by AI which eliminates the time consuming manual work and offers capabilities in A/B testing, slot based merchandising, 1:1 personalisation, segmentation, analytics and more.
To create compelling digital experiences for Torrid’s customers, their goal was ‘to offer a robust search engine that delivers customers refined and more precise results, allowing her to shop more efficiently.
As Torrid offers such a wide range of apparel (swimwear, shapewear, tops, dresses, jeans, etc.), as well as carrying licensed merchandise, it was a challenge for the company to return accurate search results to each visitor.
They found the Bloomreach tools checked off all her requirements. The AI-powered site search really allowed Torrid to scale. And paired with Salesforce Commerce Cloud, Sumaira was able to upgrade the search experience for customers.