Boost your e-commerce with AI Recommendation engines. Increase the content personalization with AWS Personalize.

Boost your e-commerce with AI Recommendation engines. Increase the content personalization with AWS Personalize. 

Leading technical trends are bringing customer experiences to new levels of personalization. Advances in machine learning and artificial intelligence provide unprecedented opportunities for brands to: analyze data in real-time, predict consumer behavior and create remarkable e-commerce experiences. 

The merging of big data and e-commerce is advancing at accelerated rates. That meeting of the minds helps businesses draw conclusions from past interests and engagement; to understand what is not yet in the scope of their interests, and make recommendations. 

This predictive personalization has major implications for businesses and the ability to convert interest into a sale. According to Researchscape, this type of recommendation technology increases consumer engagement by 73 percent

Let’s Get Real (Time) Personal

Intelligent algorithms use data to perfect themselves; and help brands build trust to create helpful relationships for consumers.  

A leading example of this technology that is currently in-practice is Amazon Personalize.  The system allows developers to add individualized recommendations to applications for e-commerce clients. Moreover, the ability to combine real-time consumer activity with an existing user profile helps Amazon Personalize begin to make recommendations. 

Advances in technology for personalized onsite content, emails and offers help brands achieve the holy grail of marketing: relevancy. In addition, the use of personalized data creates opportunities to bundle the information for consumers, such as ‘frequently bought together’ recommendations. These bundle suggestions are effective with 44 percent of consumers. 

Solidifying Consumer-Brand Connections 

Machine learning is not just for big brands. It is an essential building block for any e-commerce company; one that leverages the power of your existing digital footprint. According to Infosys, 25 percent of consumers say that personalization ‘significantly influences’ their buying decisions. Businesses of all sizes need to pay attention to this business dynamic.

While companies such as Netflix and Cadbury are building AI and machine learning use cases, small to medium sized companies need to take advantage of the emerging best practices as outcomes to stand out on the e-commerce landscape. From social media marketing and engagement to custom website content, AI recommendations are increasing engagement and trust. This is the technology that enables Netflix to customize the user experience to never show the exact same rows on the home page – ever. 
Behavior Metrics Boosts e-Commerce

Traditional marketing metrics are minimized by the power of behavior as a key metric. This science of personalization rests with behavior – past and real-time – to customize experiences for individuals. Marketers now have the tools to individualize experiences, right down to the content and design that is shown to people, and help consumers discover additional interests. 

As machine learning and AI continue to evolve, brands will be able to:

  • Better understand the behavior and intent of their customers
  • Create a universal customer view to drive a seamless customer experience across digital channels
  • Increase conversational commerce with chatbots and other machine learning technologies

For the broader business community, we know the inclusion of recommendation technology is how brands can – and should – compete better and build strong digital relationships with consumers.  

Businesses that embrace AI and machine learning now will strengthen e-commerce goals and improve the customer experience by being relevant, and guiding their journey toward a purchase.

Interested in boosting your e-commerce metrics? Learn how our teams leverage the power of AI and machine learning to help achieve business goals.


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