Providing your customers with the personal touch makes them happy and, in this day and age where competition for a customer is fierce, it must be seen as an out-and-out fundamental. Consumers demand that brands know their own, unique wants, desires, and behaviors. But personalization at scale has historically been a difficult concept to execute. The solution lies in artificial intelligence (AI) which is proficient in transforming the customer experience approach of businesses.
The Power of Personalization
But, before we go into how AI fuels personalization at scale, let us first understand why personalization is crucial:
Better Customer Support: High ticket volume is one of the most stressful situations an agent can face, and smaller departments often struggle to manage it. In sales, however—when customers feel rewarded rather than punished for their loyalty—they’re more likely to be satisfied with your products or services at baseline.
Enhanced Customer Loyalty: Satisfyingly self-tailored customer experiences create emotional bonds, which results in improved long-term client loyalty.
Improved Conversion Rates: Personalized products and suggestions typically lead to more successful sales.
Improved Brand Perception — Companies that excel in personalization are viewed as more innovative and customer-focused.
The Challenge of Scale
Despite the obvious benefits of personalization, becoming and scaling to a personalized merchant when you have millions of customers is exceedingly difficult.
The Scale of Data: Ingestion and consumption of terabytes if not petabytes worth of customer data in real time.
Complication: A piecing together elaborate patterns and preferences that pulse through our diverse customer base.
Velocity — The ability to deliver relevant 1:1 experiences as soon as you have an interaction with the customer
Consistency: How to create constant brand experiences while catering to interactions.
Enter the game-changer known as artificial intelligence.
How AI Enables Personalization at Scale
This improvement is driven by Artificial Intelligence, most notably the use of machine learning and deep learning algorithms to process large volumes of data for analysis and prediction. AI is changing the personalization landscape The fields that AI can improve in terms of customization
1. Advanced Customer Segmentation
AI has access to massive data sets and this can help in developing extremely fine-grained customer segments. Rather than looking at large, general audiences from the outside in today’s business can learn about customers based on behavior patterns and preferences — even emotions. Doing so can also help in micro-segmentation, which is more targeted and personalized.
2. Real-Time Decisioning
AI-enabled systems would need to make a real-time decision on how best the experience can be personalized. Be that picking up the right product recommendation or selecting an email subject line, AI is capable of doing it in real-time — when a customer writes to you.
3. Predictive Analytics
Just as AI can be used to predict outcomes of sports games by analyzing past historical data and current behavior trends, it will also tell us what customers are likely to do in the future. Consequently, to proactively tailor experiences to anticipate customer demands before such demand is even voiced out.
4. Natural Language Processing (NLP)
With the help of AI-powered NLP, chatbots and virtual assistants can now analyze and respond to customer queries conversationally. Simply put, this puts personalized customer service at scale — 24/7.
5. Dynamic Content Generation
AI can provide content that is created and curated based on the preferences of individuals. AI technology has turned the classic idea of “newsletters” on its head, creating a unique platform that changes based on each consumer.
Real-World Applications
Now, I’m going to give some real-life examples of how businesses are using AI for doing personalization at scale:
E-commerce Recommendations
Using machine learning, Amazon has a recommendation engine that compares what you appear to be buying and the products people have bought about those items. No human at Amazon would be able to reach this level of personalization and relevance.
Streaming Services
Using AI, Netflix analyses what and when users watch movies to make a personalized homepage for them as well as suggest content.【Netflix】 This, in turn, makes the user experience better and also more time to watch LCV on YouTube leading to higher overall retention.
Financial Services
Artificial intelligence (AI) is being incorporated by banks to provide customized financial advice and product suggestions that are tailored to an individual’s spending style, life stage as well as his/her aspirations. They, instead, will turn generic banking into a personalized financial partnership.
Healthcare
To truly personalize treatment plans based on patient data, genetic information, and the most recent (artificial intelligence-enabled) medical research. A high level of personalization has the potential to greatly increase patient outcomes.
Implementing AI-Driven Personalization: Best Practices
AI holds huge potential, but there is much to think about when putting it in place effectively:
Clean and High-Quality Data: Your AI model is only as good as the data it receives. Make sure that your data is precise, detailed, and sourced legally.
Value Adding: Do not personalize just for the heck of it. Each personalized touchpoint must bring real value to the overall customer experience.
Transparency: At a high level, you need to make sure that your customers understand how their data is being used. Offer controls and opt-out mechanisms to create trust.
AI + Human Insight: Even at scale, AI is nothing without human creativity and empathy. Avoid AI to replace human decision-making.
Test, Test, and More Testing: AI models should be tested ad nauseam. For your personalization strategies, you should test frequently and revise based on what works.
The Future of AI-Driven Personalization
With the advancement in AI technology, we could see more refined personalization functionality:
Analyzing facial expressions, tone of voice, etc: Personalize based on emotional state Emotion AI.
Creating an immersive, personalized experience in a digital environment Augmented and Virtual Reality
IoT (Internet Of Things) Integration: using data from connected devices to inform personalized experiences both in the physical and digital worlds.
Conclusion
Personalized shopping on a large scale is no longer something that the future holds: thanks to AI, it’s happened today. Using machine learning, predictive analytics, and other AI capabilities organizations can potentially offer personalized experiences at a scale of millions. Those who crack this will not just ride the new customer experience wave but in fact, commence setting up a new benchmark for the AI-driven future of customers.