Hyper-personalization has been a dream for a long time, and now generative AI is making it a reality.
Technological limitations have held it back, but with the power of artificial intelligence, real-time personalization is more achievable than ever. From a product manager perspective, I keep being impressed by the new capabilities that become possible as technology evolves.
Challenges of personalization
Personalization is a relatively complex process that involves:
- Data management: managing the large volume and variety of user-generated data, such as browsing history, preferences, and purchase patterns.
- Data privacy: accessing customer data, which can include personal information, ensuring data privacy and complying with regulations.
- Technology integration: choosing and integrating the right technology and tools that can support personalization, with capabilities such as data collection, analysis, segmentation, content creation, delivery, testing, and optimization.
- Balancing AI with human touch: striking a balance between AI-driven personalization and maintaining a human touch.
- Scalability and adaptability: implementing personalization strategies that can scale with the growth of the business and adapt to changing customer preferences.
- Limited resources and expertise: finding the resources and expertise to implement advanced personalization tools.
Traditional tools were often inadequate in handling the vast swaths of data necessary for accurate personalization. Ensuring real-time responses and personalization at scale was a pipe dream with legacy technologies. Unlike current AI systems, they couldn’t learn and evolve with changing consumer behavior.
Older systems were largely deterministic and couldn’t fill in the gaps in data with intuitive or creative solutions. This led to more of a one-size-fits-all approach than a tailored, personalized experience. Legacy tech also couldn’t be creative, unable to think outside the pre-programmed box. This lack of creativity and reasoning ability was a significant roadblock for delivering a truly hyper-personalized experience.
Generative AI as the missing key to unlock hyper-personalization
GenAI opens up new possibilities:
- Marketing campaigns: it crafts custom offers and shopping guides, making each campaign smarter with ongoing interactions. It also creates personalized emails and enables responsive chatbots for customer queries.
- Product creation: in the real estate industry, generative AI can help customers design their ideal home, find offers that fit their specific needs, or prepare their own offer to entice buyers.
- Customer experience: it can ensure consistent personalization across various channels, using algorithms to analyze data and generate content that matches individual user journeys.
- Content creation: generative AI can almost instantly write emails, articles, reports, and more, tailored to user preferences.
- User experiences: by analyzing vast data, generative AI tailors information and suggestions, enhancing engagement and fostering brand loyalty through personalized experiences.
- Content recommendations: it enhances recommendation systems by analyzing user behavior and preferences, offering personalized content suggestions.
- Consumer marketing: generative AI accelerates consumer marketing, enabling hyper-personalized campaigns at scale, significantly cutting down content design and customer targeting timeframes.
Plus, the ability of genAI to continuously learn and adapt to changing consumer behavior is a game-changer, ensuring that personalization remains a dynamic, ongoing process.
Technologies that can enable hyper-personalization in real estate
Large Language Models (LLMs):
Language models, like the GPT models that power ChatGPT, are powerful tools for hyper-personalization. They are trained on vast amounts of textual data which allows them to understand and generate human-like text based on the input they receive. When it comes to hyper-personalization, LLMs can be used for:
- Content personalization
- Customer support
- Behavioral analysis
- Predictive typing and search
Models that can generate images also enable new avenues of hyper-personalization. They can be applied for:
- Personalized avatars
- Customized product images
- Personalized advertising
- Visual recommendations
Both LLMs and text-to-image models provide a strong backbone for innovative hyper-personalization strategies, enabling a more nuanced and individualized user experience across all digital platforms. Through their ability to analyze, learn, and generate content, they bridge the gap between generic user interactions and a truly personalized digital experience.
Impact across industries
In retail, genAI can deliver a seamless shopping experience by predicting the needs of consumers, even before they articulate them. In healthcare, it's about personalizing patient care and treatment plans to ensure better health outcomes. In finance, it’s about offering bespoke financial solutions that resonate with individual circumstances and long-term goals. GenAI is versatile, and applicable to any industry, including real estate.
Using generative AI in the real estate industry:
Traditionally, the information associated with each real estate digital product concerning a user is quite basic. Typically it contains some elementary personal data, location, and historical interactions with that particular product. Conventional systems could only leverage this limited data, but users are far more nuanced and complex.
By incorporating an additional genAI module that interfaces with user-specific information, a system can generate significantly more personalized content. This enhancement enables a richer understanding and alignment with user preferences and interactions, going beyond the superficial level of engagement offered by legacy technology.
For a real estate platform, genAI could enable capabilities such as:
- Deep understanding of users: it can analyze user interactions across different listings, their preferences indicated through likes, shares, or saved listings, and even feedback or comments provided on various properties.
- Dynamic personalization: it can adapt to the changing preferences and circumstances of users in real-time. For instance, if a user recently started exploring listings with home offices, the system can dynamically adjust the recommendations to highlight properties with dedicated workspaces.
- Contextual recommendations: it can understand the context behind user interactions, and provide recommendations that are contextually relevant. For instance, if a user frequently browses listings near schools, the system could prioritize properties in family-friendly neighborhoods.
- Visual personalization: it can also generate or modify images to better match user preferences, such as showcasing how a space might look with different styles of furnishing or decor, thus providing a more immersive and personalized visual experience.
- Predictive analysis: it can analyze past interactions and other user-specific data to predict and anticipate user needs, often before the user explicitly states them. This predictive capability can be a game-changer in delivering a truly personalized user experience.
- Enhanced user engagement: it can offer more relevant and personalized content, making users more likely to engage with the platform, increasing the chances of successful transactions and fostering a long-term relationship between the platform and its users.
Through the integration of a genAI module, real estate platforms can transcend the limitations of classical personalization models, delivering a highly personalized and user-centric experience. This level of personalization can significantly enhance user satisfaction, platform engagement, and ultimately, business success in the competitive real estate market.
The hyper-personalized future of digital business is here, and those that acquire genAI-powered capabilities first will have an advantage over the competition. Artificial intelligence tools keep evolving, and the possibilities keep expanding. Now, it’s all about finding the right use case and designing a solution with a healthy cost-to-benefit ratio.
This particular challenge with real estate hyper-personalization came up during one of our AI Primer workshops. We facilitate them with companies to:
- Guide beginners through AI & GenAI use cases and help them with a strategy and best-in-class solutions
- Inspire GenAI-advanced teams with our helicopter view on challenges in their industries, and support them in prioritization
Happy to connect on LinkedIn or discuss on a call if there’s anything we can help you with.