29 Ecommerce Personalization Stats Every Marketer Should Know for 2021

Mind-blowing personalization stats to show you how every business can easily collect consumer data and personalize their marketing. 

Tina Donati
March 29, 2021

How surreal would it be if every website you landed on automatically changed its content and product offerings to perfectly match your interests and preferences? Oh, wait—this is already possible for ecommerce brands with personalization. 

Advanced ecommerce personalization is desired by customers. In fact, 91% of consumers are more likely to shop with brands that provide relevant offers and recommendations. 

So, why doesn’t every brand optimize for personalized shopping experiences? Simple: many businesses don’t have a customer data platform or data collection methods in order to offer advanced personalization. Don’t worry—that’s why I’m here. 

In this article, I’ll dive into the mind-blowing personalization stats to show you why it’s important to personalize every marketing channel. I’ll share several personalization examples, and I’ll show you how every business can easily collect consumer data and leverage it for customized shopping experiences. 

Ready to get personal? 😉  

Let’s go! 


What is personalization and why do customers want it? 

Ecommerce personalization is about using customer data to segment buyers into specific groups with different needs and wants. These data-driven segments are built from browsing behavior, purchase history, demographic data, intent data and other key customer insights.

For each buyer segment, the goal is to share relevant, actionable and exciting content and products that enhance their shopping experience. This makes shopping with your brand more efficient, enjoyable and rewarding. 

There’s no doubt that personalization is the start to a healthy, long-term customer-business relationship. Let’s take a look at some statistics to emphasize the power of personalization.


Graphic showing the different channels you can send a message to customers on


Customers get frustrated without personalized experiences


Customers are willing to share data

  • More than 50% of consumers say they'd share personal information about products they like to get personalized discounts.
  • 83% of consumers say they'd share their data to create a more a personalized experience. 
  • 64% of consumers are fine with businesses saving their purchase history and preferences in order to receive personalized experiences.


More businesses are personalizing


Personalization has a positive return for businesses

  • 80% of consumers are more likely to make a purchase from a brand that provides personalized experiences. 
  • When customers receive personalized ads based on the websites they visit, the revenue of the product grows by 38%.
  • Personalized shopping cart recommendations influenced 92% of shoppers online to buy products. 


Customers enjoy personalized Messenger AI conversations

  • 69% of consumers prefer chatbots because of their ability to provide quick replies to simple questions. 
  • 6 in 10 marketers say Messenger AI can deliver personalized attention to website visitors by being more conversational. 
  • Facebook Messenger AI starts an individualized, one-on-one conversation with customers, reaching 80%+ open rates and 30%+ click-through rates. 


Facebook Messenger sample conversations with Mavi Jeans and Marco Marco Underwear


Customers are happy with mobile engagement if it's personalized

  • 41% of customers say they don't mind if businesses use their purchase history to send personalized SMS offers.
  • 51% of consumers are actually interested in texting with brands they love.
  • 76% of loyalty members prefer to receive personalized updates from their favorite brands via SMS. 


Personalized email marketing directly impacts engagement and revenue

  • Personalized emails deliver 6X higher transaction rates.
  • 82% of marketers have reported an increase in open rates through email personalization.
  • Personalized email marketing generates a median ROI of 122%.


Subject line from meundies with product recommendation


Creating personalized website experiences drives more conversions

  • Nearly 60% of people want personalized promotions and offers as they browse your website.
  • A targeted pop-up can increase sign-ups by 333%.
  • 59% of customers say personalized interactions based on data is very important to winning their business.

Example of Sephora's "just arrived" section on their website


Social media ads drive more revenue when personalized

  • 72% of consumers in 2019 only engaged with marketing messages that were customized.
  • 63% of customers say they don't like when brands use generic ad blasting repeatedly. They want personalized ads. 
  • 88% of U.S. marketers reported seeing measurable improvements due to personalization, with more than half reporting a lift greater than 10%.


Example of Spongelle's paid ad to promote its quiz


I know I just listed a ton of stats, but do you see the importance of personalization? It leads to better engagement rates, more conversions and increased customer retention. Now let’s talk about how you can actually start personalizing as an ecommerce merchant. 


By the way, we’ve got a free 400+ page playbook about personalization for ecommerce marketers. This shares trends, tips, tricks and tools to personalize the entire customer journey. If you’re interested, you can download it here:

Get the Personalization Playbook


How to create personalized experiences: Data collection methods

One of the biggest barriers to personalization is businesses that don’t have access to data-collection tools. The reality is any business can benefit from learning more about their customers, and there are tools suitable for all business sizes, too.

First, let me tell you about the two data types: qualitative and quantitative data. Then I'll share several data-collection tools.


The difference between qualitative and quantitative data

Qualitative data is also known as descriptive data. It is not based on numbers, but rather includes descriptions and opinions from your customers. Qualitative data is important because it complements numeric data, meaning it can explain the “why” for the trends you see in your numeric data. 

Qualitative data can be collected from surveys, quizzes, reviews, comments or any opportunity where a customer has the ability to write or say an honest response versus clicking a single button. 


Screenshot of Spongelle's quiz


On the other hand, quantitative data is based on numerical data. This type of data can range from how often one of your products is purchased, how many customers say they have oily skin or even how often a product is abandoned in a shopping cart. You can use it to uncover deep insights about what your audience is interested in and how your brand may be able to help them. 

However, having both types of insight can help you make powerful decisions when creating personalized customer experiences. So, let’s look at a few simple ways any brand can collect buyer profile data. 


Surveys and quizzes

With an ecommerce quiz or survey, you can ask customers questions and match them to the right products, recommendations or content. There are a variety of quiz types, such as gift finders, size finders and product matching. Any ecommerce business, no matter the industry, can benefit from an online quiz.

Considering 73% of marketers say combining traditional content marketing tactics with interactive content enhances the retention of their organization’s message, a quiz is a great way to engage visitors and drive them to make purchases. 

The questions you ask customers throughout the quiz tell you valuable information. You can learn so much about different groups of customers, such as their age, concerns, lifestyle, habits and contact information. You can also place pixels on quiz questions and results pages so you can easily sync quiz data to Facebook ads. 


Screenshot of BeautyBio's quiz


Website tracking

The way customers interact on your website can tell you a lot about them. In fact, customers create as many as 40 data points in one visit. Depending on who your website host is, you may have access to some of this website data. But, you should make sure you have an analytics software set up where you can see what customers click on and the journey they take. 

You can take this one step further by placing pixels on your site. This is so you can use cookies to track user behavior, make the most out of lead analytics and retarget those customers later with paid social ads.


Transactional data

Transactional data shares insight about customer’s purchase behavior. Checking a customer’s purchase history is always a good place to start when trying to understand their product preferences.

If it’s a product they’ve purchased more than once before, it’s likely they’ll purchase it again. Whether your transactional data comes from your web host or a third party, this data will give you insight into what products are purchased the most and by who. 

For example, if you have customers with oily skin that have purchased your moisturizer for that skin type, you can create a campaign for those customers in a few months to remind them to restock their moisturizer. 


Loyalty, subscription and registration data

Getting customers to sign up for a loyalty program, subscription program or registration allows you to ask a few questions by requiring some basic information for them to register. For the registration form, you’ll likely ask demographic data about the customer’s birthday, age, gender and location. But, you can also use this as an opportunity to sneak in a few other questions about their preferences, too. 

Keep in mind that asking too many questions can lead to a high bounce rate where customers won’t finish the registration. Find the right balance between asking an appropriate number of questions to keep customers engaged. 


Ivory ella loyalty program registration page


Segmenting your buyer profile data

Once you have your data-collection tools set up, you’ll start to see customer patterns. For example, you may notice one type of customer is more interested in a specific set of your products than other types. 

Your next step should be to organize the information you gather and strategize how you will take action with it.


5 types of data-collection segments

Every piece of data you collect about customers is different. Here are five different types of data collection: 

Demographic data includes age, gender, location or the source from which they discovered your brand.

Engagement data tells you how a customer is interacting with your business and the touchpoints they take. For example, you can segment customers by their quiz drop-off rate or the products they click on. 

Attitudinal data is what customers think about your business. Are they satisfied? This information can be collected by using the Shop Quiz to create a post-purchase survey. 

Qualitative data is what tells you about a customer’s preferences, pain points and motivations. This type of data shows you how your customers feel about your products and what the most popular solutions are. 

Descriptive data includes customer lifestyle habits and behaviors, family details, career details or any other information that helps you understand their habits and intents. 

Within each data bucket, you’ll notice customers that show similar behaviors. Organizing those like-minded customers into groups is how you build buyer profiles. 


What are buyer profiles?

A buyer profile is based on data and customer behavior. Unlike a buyer persona, which is a fictional representation of a customer, buyer profiles are created by learning about your actual customer base and their shopping patterns. Collecting data about a customer’s likes, dislikes, preferences, needs and more gives you a full profile about who that customer is and what they may need from your business. 


How do you organize buyer profiles?

Segment each buyer profile into a group of other like-minded people. For example, if you sell skincare products and notice a large group of customers struggle with oily skin, that’s a buyer profile segment with an opportunity to target a campaign about oily skin. 


Example of organizing data into buyer profiles based on skin type


Personalization in marketing campaigns

After creating your buyer profile segments and analyzing your data for patterns, decide how you will leverage your new customer knowledge for customized content. Remember, the goal is to tailor your marketing and target your campaigns to each individual buyer profile group. This is so they only receive content they’re actually interested in. 

Let me tell you how you can use your data for personalization next. 


1. Gain a better understanding of who your audience is

As an ecommerce merchant, it’s difficult to know every single customer that lands on your website and makes a purchase. With the proper data-collection tools, you can learn about every person that visits your store, understand more about their needs and see how your business can help them discover products they’re seeking or may be interested in. 

You may even discover an entirely new audience you didn’t know was visiting your store before. For example, Doe Lashes, a false eyelash brand, discovered with their ecommerce quiz an entire group of customers that had never even worse false lashes before. Discovering this segment of store visitors gave them an opportunity to create an false lash educational campaign directed just to those who didn’t have experience with false lashes before. 


Example of an email from Doe Lashes inviting customers to take their quiz


If you want to learn about Doe Lashes complete personalization strategy, download the full case study here:

Read Case Study


2. Improve your retargeting

Imagine how accurate your retargeting campaigns would be if they were based on real, collected data you have from customers? With buyer profile data, you can retarget your customer segments with paid ads that offer more specific and personalized product offerings and messaging. 

Create lookalike audiences in Facebook Ads Manager based on the data you collect or from your pixel. Here’s an example of a personalized customer journey flow based on Octane AI’s Shop Quiz and Facebook Messenger tools. This flow shows how you can take the data you collect from engaging with a customer via a Shop Quiz to send personalized recommendations and discount opportunities on email, SMS or Messenger.


Example of how Octane AI collects data and segments for ad campaigns


3. Prospect more profitable audiences and improve your messaging

What customers tend to spend more money at your store? Which ones have a higher lifetime value or higher AOV? By knowing who your customers are and where they spend their money, you can position your products and brand better towards them. If you find a certain group of customers have a higher conversion rate or average order value, prospecting similar audiences can mean a better return on your advertising investment. 

Tailor your content and messaging for each buyer profile group. This includes blog posts, videos and infographics. For example, Bailey’s CBD uses a quiz to discover their audience’s knowledge-level about CBD products for pets. After recommending products in the quiz results page, they also share blog content to educate those customers.


Screenshot of the cover of Bailey's CBD blog article about CBD for dogs


4. Make better predictions about your customers and purchasing patterns

One of the most interesting parts of analyzing your customer data is when you start to notice patterns. For instance, if you notice a group of customers have a higher conversion rate when they’re recommended a product from a quiz, you can send an invite for other like-minded customers to take your online quiz, too. 

Seeing these patterns can help you make better predictions about how you should position your products, where you should market them and where you should focus more of your company resources. 

Let’s look at a seasonal example to explain. During the winter season, customers tend to suffer more from dry skin because of the cold. Because of this, they’re more likely to purchase moisturizing products. With a bit of data to confirm the higher conversion rate on moisturizing products, you can position your messaging to help customers through the winter dry season and make sure you carry a larger stock of these products throughout the season.


5. Personalize your website experiences for different types of customers

You can use cookies to determine if a visitor is a previous customer, or use a login through your loyalty or brand registration program to make the website switch to a version more personalized to that customer.

Whether its pop-ups or product upsells, you can leverage your buyer profile data to personalize the website experience for your customers. You can create a “recommended products” section on your homepage that shows products you know are relevant to each visitor. Or, create unique pop-ups that offer exclusive opt-in content. 


Sample pop-up


Make sure to A/B test your pop-up copy, design and incentive (between percentage and dollars off) to maximize your conversion rate. Target each pop-up to specific website pages. For example, each product collection could have its own unique pop-up relevant to the collection. 


Get personal with your customers to create memorable shopping experiences

Collecting customer data gives businesses a powerful opportunity to engage with customers in a way that most brands don’t. Despite what it sounds like, collecting this information isn’t creepy, and most customers are willing to share some information in order to have a customized shopping experience. (90% of consumers are willing to share personal behavioral data with companies for a cheaper and easier experience.)

It’s just easier when businesses know what you like and recommend the right things, right? 

Get more personal with your customers today, and watch your engagement and revenue skyrocket like you’ve always dreamed of it doing. 🚀


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