Beyond the Basics: Advanced Ecommerce Personalization with AWS

Personalization has become a crucial part of marketing today. Some people see it as platform optimization, while others view it as one of the activities to boost sales.

In simple terms, personalization happens when a company makes its platform dynamic, allowing it to change based on visiting users. 

For example, when you open a popular website like Amazon and show an interest in buying a smartphone, Amazon will adjust its homepage to list smartphones and related items for you, rather than showing unrelated products.

Let's understand this with examples like Facebook, Instagram, or Netflix. These platforms show you content you are likely interested in. 

These companies measure your viewing history and habits to create a personalized feed, and this happens in real-time. 

According to McKinsey's report, personalization can reduce customer retention costs by more than 50%. For example, if you send emails with personalized subject lines to your customer, then it can make emails 26% more likely to be opened. 

E-commerce personalization helps businesses connect with their customers better, leading to more engagement and improved loyalty.

What is E-commerce Personalization?

E-commerce personalization is a process in which a brand transforms its online platform from a one-size-fits-all approach into a dynamic platform that adapts according to the visitors. Let's understand this with an example. Imagine you own an e-commerce store, and one group of visitors is interested in buying a smartphone while another group is interested in fashion.

Now, if you provide both groups with the same homepage, one group might need to put in extra effort to find items of their interest. In such cases, you can record users' browsing history and events to develop a personalized platform that is different for each user.

This not only enhances the user experience but also significantly impacts sales and helps with user retention to a great extent.
Today, shoppers crave experiences that reflect their unique tastes. E-commerce platforms that provide this personal touch, combined with omnichannel personalization. 

Omnichannel Personalization ensures that the tailored experience extends across various touchpoints—whether it's through a website, mobile app, email, or in-store interactions. By integrating personalization across all channels, businesses create a cohesive and engaging shopping experience.

E-Commerce Personalization With AWS

In today's world, data is the most important asset, but many businesses either face infrastructure limitations or lack the technology to utilize it properly. AWS offers a wide range of services from data storage to complex simulations that can cater to a business's needs.

For example, you can secure your data in S3, and through Redshift and Kinesis services, you can obtain advanced analysis and valuable insights. By using these tools, you can accurately analyze data to create a personalized platform.

By providing relevant information and recommendations, you can not only keep customers engaged on your platform but also boost your sales. We can divide this into different aspects. 

1.1. Basic personalization has Limitations

Personalization has come a long way. Basic personalization has some limits, like grouping customers by their demographics, past purchases, and browsing habits. This gives only a small part of the picture. But with AWS services, you can take personalization to a higher level.

These services help you get better insights, so you can offer more relevant and tailored experiences.

1.2. Advanced Customer Profiling with AWS

So here, advanced personalization means developing a platform that can analyze customer activities in real-time and make changes on the platform instantly. For example, when a customer adds something to their cart, you can show related products on the checkout page.

By tracking their real-time actions, you can offer personalized recommendations.

To achieve this, you can use Amazon Personalize, SageMaker, and RedShift to easily profile customers. You can even go beyond this by combining and analyzing data from social media, website interactions, and IoT devices. This extra information will help you create even more advanced personalization.

You can analyze all this data in real-time by using AWS Lambda and Kinesis. These tools allow you to continuously track customer behavior and quickly build product recommendations and marketing campaigns.

Additionally, you can create predictive models using Amazon SageMaker, which can help predict customer preferences, churn risks, and purchase intent. By combining all these services, you can build a next-gen e-commerce platform in the cloud.

1.3. Hyper-Personalization Through AI and ML & Recommendation Engine

Additionally, you can use artificial intelligence to greatly speed up this process and cut costs. For instance, Amazon Comprehend has built-in AI capabilities that can easily analyze your product reviews, social media comments, and customer support interactions.

Using artificial intelligence for building recommendations is also a smart choice. By integrating AI, you can make your recommendation engine even more powerful.

However, personalization isn’t just about product recommendations; it’s about creating a journey where the customer sees only relevant products and services, rather than having to manually search through different sections.

Dynamic pricing can also be a very effective strategy. By analyzing customer purchase behavior, you can offer different pricing options. For this, you can once again utilize AWS Lambda services.

E-Commerce Personalization with AWS [with Example]

Let's explore how an e-commerce owner can shape a personalized shopping experience with AWS. 

When a customer visits an e-commerce platform, they may perform a variety of actions (also called events).

Events are important as they reflects customers intent. By analyzing these events, you can fine-tune the shopping experience. For example, if a customer keeps browsing electronics, it's a clear sign they're interested, even if they have yet to make a purchase.

At the same time, AWS's AI/ML services let you offer real-time recommendations by building an architecture that picks up patterns.

An Example of Personalizing E-Commerce with AWS

Suppose you own a restaurant business and want to build a personalized experience for your customers. Here's how you can do it.
Start with collecting data. AWS offers a powerful tool—Amazon Kinesis Data Streams – for collecting data.

Here's how you can leverage it: When a customer visits your online store and performs actions (or events happen). Amazon Kinesis can capture these events. It can capture millions and billions of events. This service further can be connected with AWS Lambda.

As a result, you can continuously monitor the Kinesis Data Streams for new events in real-time with AWS Lambda service.
For example, a customer places an order, and you want offer a best deal available. First, Amazon Kinesis will capture the events in real time. Let's say the customer adds a product to their cart. By capturing this information and putting AWS Lambda to work, you can offer the best deal to your customer.

In this scenario, AWS Lambda will read the events from Amazon Kinesis Data Streams and match them based on the items in the cart. The Lambda function then processes these events and retrieves your current promotions from Amazon DynamoDB.

To speed up response times and enhance the customer experience, you can cache recent or popular promotions. Amazon DynamoDB DAX helps with this by storing frequently accessed promotions or items in its cache.

And what if the customer adds the product to the cart but doesn't check out? In this case, you can use Amazon Pinpoint. Amazon Pinpoint is a marketing communication service that is used to run scheduled campaigns. By using this service, you can send reminders to customers through phone, SMS, in-app notifications, or email.

Furthermore, you can send them user-specific offers like "free goodies" with their new order. You can send these promotions over email.
You can also measure how well your campaigns are performing. For this, you can store data in Amazon S3 and analyze it using Amazon Athena. You can run SQL queries on the S3 data using Athena. It's serverless, so there's no need to manage infrastructure. 

In Amazon QuickSight, you have several options for creating visualizations. One approach is to use S3 as a data lake and load the data into SPICE (Super-fast, Parallel, In-memory Calculation Engine) to enhance ecommerce performance. Alternatively, you can connect directly to the data source, though importing data into SPICE typically results in faster visualizations.

Once your data is in SPICE, you can explore QuickSight's dashboard. You'll find various charts and tables, plus options like drill-downs and filters for more interactive features.

Challenges and Considerations

While advanced personalization offers significant benefits, businesses must address several challenges and considerations. Data privacy and security are crucial when handling large amounts of customer data.

AWS provides security services like Amazon GuardDuty, AWS WAF, and Amazon KMS to protect sensitive information.
Another challenge is technical complexity. It requires a skilled data science and engineering team to implement advanced personalization. To ease this, consider using AWS managed services and pre-trained models.

Over-Personalization can overwhelm customers with too much customization. Finding the right balance is key to ensuring personalization remains effective and not intrusive.

Best Practices

1.Use Reliable Data

Start with accurate, consistent, and accessible data. Good data is crucial for creating personalized experiences that work well. Without it, even the best systems won't be effective.

2. Set Clear Goals

Decide what you want to achieve with personalization, like boosting sales or improving customer satisfaction. Clear goals help you focus and make sure your efforts align with your business objectives.

3. Test and Improve

Personalization should be continuously tested and refined. Regularly check different methods, analyze performance, and adjust based on what you learn. This helps you stay updated with customer preferences and improve your strategies.

4. Enhance Customer Experience

Ensure that personalization makes the customer experience better and not overwhelming.  Develop a platform that is easy to sue and smooth to interact. 

5. Build a Skilled Data Team

Invest in a talented data science team to create and manage your personalization strategies. They can turn complex data into useful insights and ensure your efforts are based on solid analysis and technology.

Role of AWS in E-commerce: A Deeper Look

E-commerce giants face significant challenges with their large product catalogs, millions of customers, and high-traffic websites. Cloud computing, especially with AWS, has changed how they tackle these issues.

It helps them build a platform with limitless scalability. This is why big companies efficiently handle traffic spikes during busy times. Cloud infrastructure lets platforms quickly scale up to handle the load and then scale down when traffic drops.

Flexibility is also key. E-commerce is always changing with new products, marketing strategies, and customer preferences. Cloud-based systems allow businesses to adapt quickly, try new ideas, and launch features or services more easily.
Cloud is cheaper or expensive? Well, it depends from one company to another. However, it saves business owners from big upfront investments in hardware and maintenance. AWS, especially, uses a pay-as-you-go model, so businesses only pay for what they use. As a result, you can cut down on cost when a season sale is live.

Global Reach is vital for many ecommerce giants. They need to serve customers in different countries and regions. AWS  offers a global network of data centers so companies can deliver fast, low-latency experiences worldwide.
Data Management and Analytics are essential for improving ecommerce operations.

E-commerce generates lots of data, from customer behavior to inventory levels. Cloud-based services enable businesses to analyze data and improve operations.

Who is Using AWS Services? 

Here are some examples of e-commerce giants that rely heavily on AWS:

1. Amazon: As the owner of AWS, Amazon uses its cloud technology to support its huge e-commerce operation.
2. Walmart: Walmart invests in cloud technology, including AWS, to improve its online shopping and compete with Amazon.
3. eBay: eBay uses AWS to manage its global operations, including product listings, auctions, and payments. This helps keep its marketplace running smoothly.
4. Lyft: As a ride-sharing service, Lyft relies on real-time data processing and analysis to match riders with drivers efficiently.
5. Netflix: Netflix, the streaming giant, leverages AWS from content delivery and storage to recommendation engines.
6. Airbnb: Airbnb uses AWS to manage its global operations. AWS provides the tools and infrastructure to support Airbnb's rapid growth, from listing management and payment processing to customer support.

The Future of Personalization

Technology is growing rapidly, and so is personalization. New trends like augmented reality, virtual reality, and voice commerce are changing how we customize experiences. As these technologies develop, they offer fresh ways to engage with customers. Augmented reality (AR) lets people interact with digital elements in the real world. For example, with AR technology, customer can try product from their home virtually. 

On the other hand, virtual reality (VR) takes this a step further. Businesses can use VR to create unique experiences, like virtual tours or interactive product demonstrations.
Voice commerce is another exciting trend. With smart speakers and voice assistants, customers can shop by speaking commands. This way, they can search for products easily and quickly. 

AWS, or Amazon Web Services, provides the tools necessary for these advancements. AWS offers cloud computing services that support AR, VR, and voice commerce. This means businesses can use AWS to implement these technologies and personalize their offerings.

Advanced personalization through these technologies helps businesses connect more deeply with their customers. It also boosts sales by creating tailored experiences that meet individual needs and preferences.

Final Words: Measuring and Refining Personalization Efforts

In this blog, we have discussed how companies can leverage different AWS services to develop personalized experience. Personalization is crucial for any business to succeed. However, effective personalization needs ongoing monitoring and optimization.

It includes going over the strategies used to give a personal touch to the platform. AWS provides plenty of tools, from A/B testing to examine different approaches. For example, you can use AWS CloudFront routes traffic to different versions of your website or app for these tests.

For tracking there are so many options available. With these services, you can track Key Performance Indicators (KPIs).  To make it more effective, Incorporating Feedback Loops to refine your strategies. Use Amazon Comprehend to analyze customer reviews and support tickets for insights and improvements.

This process ensures that personalization stays effective and meets customer needs.In this article, we have walked you through a simple guide to building a personalized e-commerce experience by providing an example of how to develop it. Whether it is about e-commerce optimization and implementing AI/ML capabilities, AWS offers a wealth of services to handle unpredicted traffic surges and deliver personalized recommendations and services.

With many use cases that are transforming the e-commerce space, AWS is a top choice among the world's renowned e-commerce platforms. If you are looking to enhance your existing eCommerce platform, then look no further. As a leading AWS consulting agency, we offers AWS consulting and development services to help business innovate and solve their key challenges by using cloud.