Why Every Business Needs a Personalization Engine
The things we buy express who we are, from the clothes we wear to how we decorate our homes. But how do retailers speak to each unique individual customer while running a large, general online shop that has to appeal to as many people as possible? The answer lies in a cutting-edge technology: the personalization engine.
Personalization is the process of creating a relevant, individualized interaction between two parties to improve the experience and engagement of the recipient. The marketing industry has been a forerunner in launching and using personalization tools, from email campaigns driven by cutting-edge CRM software to online ads based on a customer’s recent browsing history. Most online retailers use personalized campaigns, but very few have successfully created truly personalized shopping experiences for their customers.
Fortunately, as AI technology becomes more accessible, it’s not only possible to create a personalized experience for your loyal customers – it’s highly recommended. A personalization engine can transform the way ecommerce brands engage with their customers for good.
How Does a Personalization Engine Impact the Shopping Experience?
In brick-and-mortar stores, sales executives can ask customers questions to better understand their preferences and guide them to the most relevant products based on their descriptions. They can read customer’s facial cues, persuade them with samples, and ultimately lead them to make an informed decision about an in-store product.
However, when a customer shops online, those interactions don’t exist. The online store might have been exactly what the customer is looking for, in stock and ready for purchase… but isn’t able to recommend it to them.
A personalization engine can change all that. By dynamically presenting clients with content, recommendations, and special offers that are uniquely tailored to each and every one of them, ecommerce sites can provide the best possible service to each customer, without human intervention. They can even make special offers based on data like their browsing behavior, demographics, and purchase history.
Targeting and personalization is nothing new. Retailers and other businesses have always tried to target different audience segments with their communications and promotions. However, since the pandemic, there has been a real cultural shift towards hyper-personalization. Customers are far likelier to seek out shopping experiences that aren’t just targeted but hyper-personalized to them. By using a personalization engine, you can use customer behavioral data to provide dynamic, personalized experiences to every customer, not just a broad segment of your target market.
Let’s suppose that ten customers recently bought athleisure clothing from your site and received a marketing prompt to buy a pair of black running shoes. It might appeal to two out of the ten shoppers, but the other eight already own a pair of running shoes or simply prefer a pink pair over the recommended black. A personalization engine would know which customers have already bought running shoes, what shoe style they prefer, and which customers would prefer pairing their athleisure wear with some everyday sneakers or pumps based on the information collected about them.
In other words, the approach is far more likely to result in a conversion and an upsell than sending a semi-personalized message based on a single action (e.g., buying a set of athleisure wear).
What Is a Personalization Engine?
A personalization engine is an algorithm-based system that uses machine learning and data analytics to create a unique and highly individualized shopping experience for customers.
Personalization engines have become increasingly popular in the fashion industry as they allow retailers to understand their customers better and provide more personalized recommendations. They collect and analyze customer data such as purchase history, browsing behavior, and demographics to offer tailored product suggestions. This approach benefits the customers by providing them with a more enjoyable shopping experience and helps retailers increase their revenue by encouraging customers to make more purchases.
With the help of machine learning and data analytics, the personalization engine analyzes a customer’s purchase history and browsing behavior to understand their preferences and style. The engine then uses this information to offer product recommendations tailored to their individual tastes and requirements. By doing so, retailers can provide a shopping experience that feels more personal and engaging to customers, ultimately resulting in greater customer satisfaction and loyalty.
Is Personalization Right For Your Business?
Personalization is a great strategy for businesses that want to boost customer satisfaction, build brand loyalty, and improve sales performance. However, there are a few factors you need to consider before making a decision, including:
Your Customer Base
The first thing to consider is the nature of your customer base. Adopting a personalization strategy will be highly beneficial if you have a large and diverse customer base (e.g., in an online shopping environment). The right personalization engine will provide a tailored customer experience to each individual, adding enormous value and boosting your average order values through better recommendations. If your customer base is small or fairly homogeneous, on the other hand, personalization may not be as critical to your business.
Data Availability
Personalization relies heavily on customer data such as purchase history, browsing behavior, and demographics. You must consider whether you have access to the data required to implement a personalization strategy. If your customer data is limited or incomplete, it may be challenging to implement a successful personalization strategy.
Competitive Landscape
The level of personalization you require will largely depend on your industry and competitive landscape. If your main competitors are adopting personalization strategies, you must adopt a similar strategy to remain competitive. Of course, if personalization isn’t common in your industry, launching personalized shopping experiences will give your business a competitive edge and differentiate your brand from competitors. While only 15% of retailers have already implemented a personalization tool, 95% of retail CEOs say creating a personalized shopping experience is a strategic priority for their business. Retailers are about to enter the era of personalized recommendations and must be prepared to meet their customers’ sky-high expectations.
Long-term goals
Finally, consider your long-term goals and whether a personalization strategy aligns with them. Personalization has been known to improve customer satisfaction, build brand loyalty, and increase sales performance in the short term. It will require ongoing investment over time to remain relevant, and you’ll need to work with the right partner to ensure your strategy pays off in the long term.
The Benefits of a Personalization Engine
A personalization engine can greatly impact your bottom line, depending on how it’s used. Here are just a few ways businesses have been leveraging personalization engines to improve their sales and customer relations:
Increased Customer Satisfaction
Personalization allows companies to better meet their customers’ unique needs and preferences, creating a far more engaging and enjoyable experience. The personalization engine analyzes customer data such as purchase history, browsing behavior, and demographics to offer tailored product recommendations to each individual shopper. Instead of scrolling through pages of irrelevant goods, customers are presented with relevant products that match their preferences and interests. They feel an instant affinity and connection with the brand.
There are wider benefits too. When a business understands what its customers’ unique needs and preferences are, they use them to create more impactful marketing campaigns, unique shopping experiences, and highly targeted recommendations. AI-powered styling tools can even recommend outfits for special occasions and provide advice based on customer cues.
The end result? A far more satisfying and rewarding shopping experience for your customers.
Enhanced Brand Loyalty and Customer Retention
Getting customers to visit your online store is great, but you want them to make a purchase – and to keep making them over time. Brands can use personalization to strengthen their relationship with their customers by providing consistently better experiences. Forbes once called personalization the “Holy Grail of loyalty”.
Customers are shown far more relevant and engaging product recommendations, which increases the amount of time they spend browsing and shopping. Brands can hone into the factors that determine whether or not a window shopper converts to a paying customer and what motivates them to keep adding products to their carts.
Personalization engines improve customer retention rates by encouraging customers to return to their website and make additional purchases through targeted recommendations and improved marketing messaging.
Increased Sales
When customers are consistently provided with personalized product recommendations that match their interests and needs, they are far likelier to make a purchase, which can lead to increased conversion rates and improved sales performance.
Personalization engines have been known to increase the average order value by encouraging customers to add additional items to their shopping carts. The engine can show customers products they may not have seen (but will probably want to buy) based on their interests, either on the website, in their social media feeds, or with highly targeted marketing campaigns and communication.
Your personalization engine will continuously analyze customer data to find out which emotional appeals, graphics, and other details increase conversions. If done manually, this type of data would require months of costly and time-consuming A/B testing. With the right personalization tools, analysis is instant.
Improved Inventory Management
When it comes to it, personalization is all about data. What are people looking at? What are they buying? How much are they buying? What items simply don’t hold their interest? Having this data and insight into your customer behavior and preferences in hand doesn’t just mean that a business can provide a better shopping experience. The information can be used to make improved data-driven decisions behind the scenes as well, including what type of inventory to buy and how much to buy.
Online stores can identify which products are most popular among certain customer segments and adjust their inventory accordingly, which reduces overstocking and understocking and boosts profitability.
Continuous Improvement and Innovation
We already know that personalization is a powerful driver of customer loyalty and engagement. When customers are served with communication or products that resonate with them, they are far more likely to engage and take action.
One of the key benefits of using a personalization engine is that it becomes more effective over time – each recurring interaction creates even more data that businesses can use to design even more relevant experiences, generating long-term customer lifetime value and loyalty.
You can set up your personalization engine to analyze customer behavior and set up relevant content to improve their on-site experience. For example, if customers consistently drop off during the checkout process, you could use AI to interject with a chat window offering support during this step. The more you know, the more improvements you can make.
Improved Understanding of the Target Audience
The right personalization tools will provide useful insights into your customer data and the products they like. The information can be used to inform future product development and marketing strategies, which can help retailers to stay ahead of the competition and boost profitability.
Knowing more about your audience makes it far easier to break your audience into segments and approach them with slogans and stories that resonate with them, improving the effectiveness of your communications.
Improved Customer Journey
Not everyone arrives at a sale in the same way. Customers can vary in the way they find a site, navigate the site when they land and what they do before they decide to make a purchase. A personalization engine can speak to each customer at every important touch point on their journey – even for first-time customers.
The personalization engine will start collecting behavioral data from the first click and combine it with other relevant information to take a client on a highly personal and relevant journey from the very beginning.
Great inclusivity
Retailers can use their personalization technology in a number of creative ways. Some fashion retailers are using virtual dressing rooms to display products on models of different sizes, ethnicities, and ages to create a more inclusive and holistic experience. It may seem simple, but using more relatable models has been known to improve conversion rates by 200%.
What Are the Challenges of Personalization Engines (and How to Overcome Them)?
Mega-retailers like Amazon have perfected the art of personalization at every step of the customer journey, but personalization doesn’t just belong to the biggest market players anymore. You don’t need their scale (or bank balance) to implement a personalization engine for your retail store, but there are a few challenges you may face along the way.
Data management
Like all AI-driven technologies, personalization engines are only as good as the data that powers them. There are usually two issues with data: poor quality data and simply having too much data. Retailers that want to implement personalization engines effectively need to work with a partner that can help extract, classify, analyze, and manage the magnitude of information they have available to achieve the best possible result.
Tools and technology enablement
The technology used should provide simple and easy access to AI and machine learning technology that can crunch a large volume of data and enable personalized shopping experiences. The technology should also have the ability to scale alongside the retailer to ensure a consistent experience for all customers.
Depth of understanding
Customers are very specific about what they are looking for. If a customer is looking for a black bucket hat with a paisley interior and a drawstring and the site can only accommodate searches for black and hat, the online retailer misses out on very important information and indicators of customer preferences.
The best approach is to use AI to accurately extract attributes from the image and the text to enhance the data on the retailer’s site. This only leads to improved product discovery but also enables the retailer to capture and capitalize on these attributes in the finest detail.
This data can then be used in real-time as AI will look at individual preferences at a granular level and recreate relevant recommendations at every click.
Conclusion
A personalization engine enables retailers to provide a highly individualized and dynamic shopping experience for each and every customer. By tapping into the data that customers naturally generate, a personalization engine can offer tailored product suggestions that fully align with each customer’s preferences and style.
This strategy not only boosts customer satisfaction, builds brand loyalty, and improves sales performance but will create even more opportunities for improvement and personalization with each recommendation.
With so many retailers competing for a slice of the ecommerce space, personalization is becoming a must-have for businesses of all sizes that want to differentiate their brands and gain a competitive edge.
Choosing the right product personalisation engine for your ecommerce store might be tricky, so we offer a free consultation with no strings attached. Feel free to send us a message to learn more.
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