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    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 personalized 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.

    benefits of personalization

    🔍  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.


    Covid-19 has triggered an interesting cultural reset, when it comes to consumer attitudes towards shopping, and new habits are likely to have formed. Consumers are likely to be seeking out a personalized experience more and more. As Pam Danziger, luxury retail expert and author, shared in a conversation on steering retail companies through the pandemic,

    Coming out of this crisis, we're going to see even more distinction between the idea of going shopping as an experience and actually having to buy something…the shopping experience and buying have become disintermediated.

    Read this next: The State of Commerce Experience 2021 [Analyst Study]

     

    Designing Personalized Experiences in eCommerce

    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. 

    Site search, browsing data, product recommendations, landing pages, and all other interaction points should work cohesively to build a complete picture of each visitor across their journey.

    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.
     

    designing personalized user experiences in ecommerce

    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. 

     

     

    The Key Differences Between B2B and B2C Personalization

    Studies found that 73% of B2B buyers want personalized experiences, similar to the B2C-like customer experience. Yet, the Forrester/Bloomreach study found that just 22% of B2B customers say their most recent online experience was completely personalized to them.

    b2b personalization

    Personalization remains a strategy that most B2B marketers are interested in pursuing this year. But for many, the simple fact is that personalization is a challenge.

    Here are a few reasons: 

    • Multi-Layered Persona: It’s not easy to personalize to a single individual, but it gets complex in B2B when you factor in vertical, account, department and application.
       
    • Extremely Diverse Customer Base: When the customer base is diverse from the researcher, to the technician, to the customer service rep, providing the right information without having to wade through thousands of SKUs and other data that is irrelevant to their job is much more complex.
       
    • Complex Product Catalog: While a knowledgeable salesperson can navigate through an unwieldy catalog, B2B buyers often require personalized & funnel-based catalog on different education levels.

    In short, B2B companies require contextual targeting which is based on understanding of industry, accounts and use cases as well as an understanding of products. 

    So, opting-in for an intelligent personalization solution with AI and ML capabilities play an important role. 

     

    The Role of AI in eCommerce Personalization

    Advancements in technology, especially the increasing accessibility of artificial intelligence (AI)/machine learning, has been a major driver of personalization. 

    Machines can crunch data quickly, enabling real time optimizations and scalability. Companies can utilize the collected and processed data to recommend personalized products to every customer in real time and thus design an individual, user-oriented shopping experience.

     Adding intelligence to the user experience can 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.

    For organization who rely heavily on content, intelligence can help direct the creation of that content by identifying gaps in information that visitors are searching for. Perhaps a financial company sees a rise in visitors searching for information around automating investments - information like this can help content creators prioritize the rising topics their actual customers are interested in. Through natural language processing and machine learning these trending topics can be identified quickly, without the hours of manpower that would be required to read through thousands of search terms and pull out trends.

     

    eCommerce Personalization Technologies and Tactics

    A major issue that digital business faces when discussing personalization is that there is no single tactic that defines it, and each class of technology comes with limitations.

    And there’s no single tactic that defines personalization.

    It’s not as simple as “We ran an A/B test, and now we are personalized.” 

    There’s a whole spectrum of technologies involved and creating your personalization roadmap means making your own unique recipe of how much, or how little, you will rely on each one.

    The below table contains some of the most common tactics used in both B2C and B2B eCommerce and each one of these technologies is on the spectrum of personalization. The way forward is to combine each of these technologies to build a comprehensive intelligence around user intent.

    To get your visitors to their goal of the moment you need to understand them and tailor your experience across every level these technologies offers.

    personalization technologies tactics softwares

    Real time personalization requires noticing how a visitor’s behavior differs or aligns with their typical behavior, identifying their current goal through their own behavior and the behavior of similar users, and using insights across all levels of technologies to help them accomplish this goal.

     

    [Personalization Tactic #1]: Understanding Audience: 

    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.

    Thanks to digital experience platforms and machine learning you can take care of this at scale and ensure related content and products to your visitors.

     

    [Personalization Tactic #2]: Semantic Understanding for Personalized Search

    The relative rarity of personalized search is a huge missed opportunity, as visitors using search convert at a 1.8 times higher rate than the average visitor.

    The search box is the most important real estate on any site.

    Unfortunately, many of the search functions on sites today may hurt as much as they help because they focus on keywords instead of the meaning of those words in context. 

    Search can be messy. Spelling mistakes, use of broad terms, differences in how people describe the same product can make accurate search results a struggle.

    On a practical level, it’s the difference between dumb search and intelligent search. Most marketing platforms still search for words alone, which is a recipe for failure

    If a shopper searches for “budget black laptop” they probably want a black, low-cost computer. But a keyword search may instead deliver a page of low-cost black accessories for a laptop.

    By comparison, an intelligent, semantic search considers the words in context, just as a human sales clerk would.

    🔑  Do this:

    Intelligent search with semantic understanding capabilities is a huge advantage when it comes to happy customers. Brands, manufacturers, retailers and distributors need to bring their business into the search engine to create guided, merchandising-driven selling experiences on their own.

    Intelligent search solutions 

    • Offers a set of selling capabilities beyond the search box
    • Enables sellers to promote new products since a customer’s last visit
    • Helps in-store shoppers locate products on a kiosk
    • Can promote parts for already-purchased products, or products in the shopping cart

    This means sellers can deliver personalized experiences and recommendations to customers searching and browsing across landing pages – eliminating the need to combine disparate products from multiple software vendors.For example, if a user that has shown interest in female products (e.g. skirts, dresses, bikinis, etc.) and then searches for generic terms like “shorts”, “shirt”, “exercise shirt”, or “running shoes”, some site search technologies will give preference to female items as the user is more likely to be female.

    The experience of each user is personalized in regard to the preferences that they have shown in the past. This is what Semantic Search has as its main goal: making it easy for your users to find what they're looking for. 

    Read this next: Semantic Search Explained in 5 Minutes [blog]

     

    [Personalization Tactic #3]: Targeting & Profiling

    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.

     

    [Personalization Tactic #4]: 1:1 Personalization 

    1:1 personalization in eCommerce is powerful in situations where you have a rich set of data about customers and as a result of that it can significantly change the products you show to that individual. It requires rapid data aggregation and analysis, cross-channel deployment, and machine learning optimization. Due to a lack of data, 1:1 personalization can be challenging for a large majority of companies to do well. 

    With the right personalization solutions, marketers and merchandisers can use this deep level of data to provide 1:1 personalization through search, browse, layout and content.

     

    🔑  Do this:

    You can return accurate results for every visitor with relying on AI to ensure that your search is always learning and getting better. 

    You can deliver accurate product recommendations based on search behavior and 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. 

    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

     

    How eCommerce Companies Personalize The Experience

    boden ecommerce personalization

    Boden

    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.

    Read this next: Boden on Personalising Every Visitor’s Experience [Customer Success Story]

     

    Albertsons online grocery store

    Albertsons

    Albertsons’ online grocery store was struggling with poor search results - they weren’t very accurate and lacked relevance. This led to high bounce rates and lost revenue.

    Nearly 50% of their eCommerce turnover was attributed to search, so it made sense to improve the search experience first.

    They started using Bloomreach Experience Cloud (brX), which uses AI-driven algorithms to power customer search. It helped Albertson’s offer personalized search results and product recommendations.

    After implementation of brX, basket-building speed went up by over 25%.

    Read this next: Albertsons on Building an End-to-End Online Shopping Experience [Customer Success Story]

     

    Torrid

    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.

    Read this next: Torrid on Helping Customers Find What They Want [Customer Success Story]

     

    Busra Sahin

    Busra Sahin

    Busra is a Digital Marketing Manager specializing in web marketing, design, content marketing and SEO.                

    More blog posts by Busra Sahin

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