Personalization Strategy: Beginner's Guide

If you want to be successful, you must have a concrete customer strategy. It's the plan that shows you how to attract, engage, and keep your audience interested. However, things are changing now. Today's shoppers aren't just attracted by simple customer strategy; they want a personalized experience. So, it's time to embrace the era of personalization strategy.

Why do you need a personalization strategy?

Customers need a personalized shopping experience

Your customers want more than just one-size-fits-all experiences. They want things tailored to them, and if you're not doing that, you're setting yourself up for disappointment – or even worse, for them to walk away. Personalization lets merchants meet these changing expectations by offering relevant product suggestions, tailored content, and targeted offers based on each customer's unique interests and purchase history.

Competition needs

Most of your competitors have already boarded the personalization train, and they're reaping the benefits of increased customer satisfaction and loyalty. If you do not have a strategy for personalization in place, chances are you are leaving money on the table and losing ground. Enterprises are going to stand out with personalization, creating relevant experiences for customers at their buying intent. This difference can really be important when trying to win and retain customers in a highly competitive marketplace.

Precision marketing needs

Ecommerce merchants need to personalize their customer strategy for precision marketing to deliver the right messages to the right segment of customers. You will be better positioned to create relevant experiences for every customer when you look at what they do, like, and buy. Offers, product recommendations, and relevant communication will propel conversions and overall customer loyalty. Knowing exactly what your customers want and like will enable you to establish much better relationships with them, ensure their loyalty to your brand, and stand out from the competition.

Inventory management needs

Overstocking or understocking situations are a significant challenge for many ecommerce merchants, particularly during peak sales periods. A personalization strategy allows eCommerce merchants to gain valuable insights into the demand for specific products from different customer segments. This information is essential for optimizing inventory management and addressing inventory issues effectively.

Summary

Shoppers who are faced with a multitude of options related to their taste - like color, design, texture, and style - don’t know exactly what they want until they find something they like. Especially taste-based shoppers, enter a store hoping to discover something that matches their personal preferences. Taste-based shopping includes stores and item categories including but not limited to:

• Apparel
• Jewelry
• Beauty Products
• Arts & Entertainment

These eCommerce merchants should prioritize personalization strategy instead of purely customer strategy. A practical personalization strategy can understand what customers want and proactively surface those items, enabling customers to quickly find something that matches their taste.

Benefits of personalized shopping experience

The following are some benefits from true cases:

• Better customer experience: Shoppers can readily find products, deals, and inspirations that match their needs.
• Increased customer loyalty: A recent study shows that 88% of consumers consider trust as the most vital feature of a brand.
• Increase Return On Investment (ROI): The personalization technique when applied can result in up to eight times more return on investment compared to general marketing strategies.

What is a good personalization strategy?

An effective personalization strategy allows for the different needs, preferences, and behaviors of every individual customer to be responded to in an enriched way, with richness at every moment and loyalty. Apply this multi-dimensional approach to develop an effective personalization strategy:

Know your customers

Gather and study customer data from different approaches to understand their likes, habits, and needs better. This involves using CRM systems, analytics tools, and other tech to gain detailed customer profiles.

Segment customers strategically

Grouping customers into categories can be an effective strategy. Based on the commonalities among the groups, their behaviors, or their needs. This allows for more targeted personalization of efforts.

Personalize across multiple channels

Provide customers with the same great experience, consistently, no matter how they come to you: via email, on your website, through mobile apps, on social media, and in person. This way, keeping in touch with you is easy.

Use AI and machine learning

Use AI and machine learning to process data, identify trends, and predict customer behavior in even more sophisticated ways of customizing your offerings.

Personalized content and recommendations

You can personalize content, product recommendations, offers, and messaging to suit different customers and what they've done in the past.

Personalize the customer journey

Map out the customer journey and identify those key touchpoints that will have the most impact on personalization, such as onboarding, checkout, or support interactions.

Implement real-time personalization

Use tech that lets you tailor the customer experience in real time based on their behaviors and context.

Respect privacy and build trust

Be transparent about data collection and use, and give customers control over their data and personalization preferences.

Continuously test and optimize

Regularly test different personalization strategies and measure their impact on key metrics like conversion rates, customer satisfaction, and revenue.

Netflix: Digital personalization strategy example

Above we have already provided the key features of a good personalized strategy. Next, we will present the best practices that established those key features with a case study. Netflix is reputed for its advanced personalization mechanisms; below are detailed ways in which it utilizes personalization techniques with the customer:

• Personalized content recommendations: Netflix employs artificial intelligence and machine learning algorithms to analyze extensive user data, including viewing history, search behavior, ratings, and even the time of day users watch. Then they will provide personalized content recommendations. This guarantees that the content displayed to each user is highly engaging.
• Personalized user interface: According to each user’s viewing habits and specific preferences, the personalized Netflix homepage is produced. This includes personalized recommendations and even tailored artwork for showing thumbnails.
• Personalized notifications and updates: Netflix utilizes personalized notifications and updates to keep users informed about new releases, trending content, and recommendations tailored to their interests and viewing habits.
• Multi-dimensional content categorization: Netflix uses a complex system of "alt genres" to categorize content, allowing for highly specific recommendations based on nuanced user preferences
• Personalized language and subtitle preferences: Netflix allows users to set their preferred language and subtitle preferences, ensuring a personalized viewing experience.
• Personalized playback settings: Users can adjust playback settings, such as video quality, audio settings, and captions, to suit their preferences.
• Timing-based recommendations: It considers the time of day as well as the device used to recommend appropriately, suggests shorter content recommended at night, and shows that can easily be resumed on the phone.
• Personalized profiles: Netflix allows users to create multiple profiles within a single account, enabling personalized recommendations and viewing histories for each user or family member.
• Personalized email marketing: Netflix sends personalized emails to users highlighting new content that matches their interests, using engaging subject lines to increase engagement.

New trend: personalization strategy in the age of AI

Personalization strategies are changing in the AI age at breakneck speed—first and foremost in search and recommendation. Here's how:

AI-Powered search

• NLP: It is the capability of understanding human language. Artificial intelligence has scaled such great heights that it now understands and interprets the queries of customers with an accuracy never seen before. It deciphers context, intent, and even slang to give search results closer to the truth and relevance sought.
• Visual Search: This feature allows shoppers to upload pictures in their search for similar products. For fashion and home decor retailers, this is a huge opportunity.
• Voice Search Optimization: With the ever-increasing popularity of smart speakers, the need to optimize based on voice search is a necessity of any business. Artificial intelligence can effectively decode and respond to voice queries.

Personalized search results:

• Learning from Behavior: AI analyzes past search and purchase history to ensure that each user receives results that are tailored to their specific needs.
• Real-time Adaptation: Search results are subject to change based on the user's current browsing session, time of day, and even weather conditions.
• Semantic Search: Artificial intelligence is capable of understanding the meaning behind queries, which allows it to show results based on intent rather than just keywords.

Smart product recommendations:

• Collaborative Filtering: AI identifies patterns in customer behavior to recommend products based on similar users' preferences.
• Content-Based Filtering: Recommendations are made based on product attributes and user preferences.
• Hybrid Systems: Combining multiple recommendation strategies for more accurate suggestions.

Dynamic recommendation placement:

• Adaptive Positioning: AI determines the best location on the page to place recommendations for maximum impact.
• Cross-Sell and Upsell Optimization: Intelligent suggestions for complementary or upgraded products based on cart contents and browsing history.

Predictive analytics in search and recommendations:

• Anticipating Needs: AI predicts what a customer might search for or need next, offering proactive suggestions.
• Trend Forecasting: Recommendations adapt to emerging trends and seasonality.

Personalized category pages:

• Dynamic Sorting: Product listings change order based on individual user preferences and behavior.
• Custom Category Creation: AI generates personalized product categories tailored to each user's interests.

Contextual recommendations:

• Situational Awareness: Recommendations change based on the customer's current context (e.g., browsing for a gift vs. personal purchase).
• Device-Specific Suggestions: Different recommendations for mobile vs. desktop users.

Automated merchandising:

• AI-Driven Product Highlights: Automatically featuring products likely to interest specific customers.
• Smart Inventory Management: Recommendations adjust based on stock levels and profit margins.

Challenges in creating personalized shopping experience and how to overcome

When planning to implement personalization effectively in eCommerce, it is important to be aware of the challenges that may arise. With the appropriate approach and tools, success is achievable.

Privacy and regulations challenges

More so considering the growing emphasis on the concern for data privacy and new regulations like GDPR and CCPA, this can make personalization appear quite a dangerous strategy. To that respect, clarity in data collection and compliance with such regulations should be addressed by companies. More importantly, businesses should let customers know how their data is going to be used and give customers control over their data.

Clean data challenges

Incomplete or inaccurate customer data is the biggest challenge to personalization. At the heart of any personalization strategy is the creation of meaningful customer segments and accurate targeting of customers within them. That gets to the root of why investing in comprehensive data collection and management systems, regular cleaning and updating of databases, and using AI-powered tools that can fill data gaps is important for businesses.

Measurement challenges

It is not easy to measure how effective personalization efforts are. One cannot always establish a clear link between the improvement of metrics such as conversion rates or average order value and personalization. For this reason, businesses must clearly define KPIs and use sophisticated analysis tools to be able to trace back effectively the impact caused by personalization on the different touchpoints.

### Getting started challenges

Many businesses find it difficult to get started with personalization on their own. The process can be time-consuming, resource-intensive, and technically challenging. This is where solutions like AfterShip Personalization can make a significant difference. AfterShip offers an AI-powered product discovery platform that can help businesses overcome these challenges:

• Smarter search & browse: AfterShip Personalization uses multimodal AI and Large Language Model (LLM) intelligence to elevate the storefront search and browse experience. This includes visual search capabilities and personalized category pages, making it easier for customers to find relevant products.
• Product recommendations: With over 10 pre-built AI algorithms, AfterShip Personalization provides personalized product recommendations across all touchpoints, from product pages to post-purchase experiences.

• Product tagging: AfterShip's AI-powered automated tag extraction and prediction can enrich product data, boosting discoverability and improving website performance.
• Strategic merchandising: The platform offers flexible custom rules, advanced analytics, and built-in A/B testing to help businesses optimize their merchandising strategies.
• Easy integration: AfterShip Personalization integrates seamlessly with platforms like Shopify and offers full API support, making implementation straightforward even for businesses without extensive technical resources.

Conclusion

Don't let the complexities of personalization impede your online shop growth. Take the first step towards transforming your customer experience and increasing profitability. AfterShip Personalization provides a comprehensive, AI-powered solution that is straightforward to implement and produces tangible results. With features such as smart product recommendations, advanced search capabilities, and strategic merchandising tools, you can rapidly implement a personalized shopping experience for your customers.