There's a rising demand across industries for personalized experiences. In Software as a Service (SaaS), users often face generic, "one size fits all" product and service offerings, highlighting the pressing need for more personalized solutions.
To stand out in a saturated SaaS market, companies must leverage personalization. It not only differentiates their product but also bolsters user engagement and satisfaction. The demand for personalization extends to Customer Service and Support (CSS), which is pivotal in retaining loyal users and mitigating churn. Technological strides in AI and ML have ushered in the granular, data-driven personalization era. This trend is further emphasized in post-COVID, where a tailored digital experience has become paramount. Drawing from my hands-on experiences in leading customer success and support teams and insights from my clients, it's evident that personalization offers tangible advantages, from improved user satisfaction to robust business growth.
The Six Facets of Personalization
1. Explicit Personalization
Customization based on explicit inputs from users.
How It Works:
Self-Reported Personalization: Users directly provide information about their preferences, needs, or goals. Websites or applications may use questionnaires, profile settings, or preference selectors. For example, a news app might ask users about their favorite topics or regions and then prioritize that content in the feed. Netflix, for instance, asks subscribers about their preferred genres during onboarding, ensuring that their homepage is populated with relevant content from the get-go.
2. Behavioral Personalization
Customization strategies are derived from users' actions and behaviors.
How It Works:
Segmentation-Based Personalization: Users are categorized into groups or segments based on shared behaviors, demographics, or interests. For instance, an e-commerce site might group users as "frequent buyers of electronics" based on their purchase history and then show them electronics-related deals. Amazon, for instance, categorizes users into distinct segments (like "avid readers" or "tech enthusiasts") based on their purchase history, subsequently tailoring product recommendations.
Contextual Personalization: Systems detect a user's immediate context or action and offer relevant content or aids. TripAdvisor, a travel website, noticing that a user is searching for flights to a ski destination, might offer guides on ski resorts or equipment rentals in that area. Real-time Personalization: The system instantly reacts to a user's actions. If someone pauses on a product page for a while, a chatbot might pop up offering further details or a discount on that product. Online clothing retailers might use this approach, deploying chatbots that offer size guides if a user lingers on a product size chart.
3. Predictive Personalization
Projections about future user actions rooted in their historical data.
How It Works:
Analytical Predictive Personalization: The system assesses past interactions, buying habits, or viewed content to predict what the user might be interested in following. Music streaming services, like Spotify, often use this to suggest songs or artists based on a user's listening history.
4. Generative Personalization
Tapping into the prowess of Generative AI for bespoke user experiences.
How It Works:
Hyper-Personalization with Gen AI: Generative AI models assimilate vast datasets, making connections and generating outputs tailored to individual user behaviors or needs. For example, a project management tool might create a workflow template tailored to a team's unique project structure and goals. Or, an email marketing tool might utilize Generative AI to draft unique email content tailored to individual user engagement patterns, ensuring higher open rates.
5. Immersive Personalization
Using AR/VR technologies for a deep, interactive personal touch.
How It Works:
AR-guided Personalization: Augmented Reality overlays digital information in the real world. IKEA's AR app allows users to visualize how a piece of furniture looks in their actual living space, offering a personalized shopping experience. VR-embedded Personalization: Virtual Reality immerses users in a digital environment. Autodesk's VR capabilities allow architects and designers to virtually navigate their creations, receiving real-time AI feedback on design optimization. An architect might walk through a VR simulation of a building they're designing, with AI suggesting changes based on their interactions or preferences.
6. Hybrid Personalization
A combination of techniques from various personalization methods offers a multi-dimensional personalized experience.
How It Works:
Behavioral + Generative Personalization: The system observes user behavior and then uses Generative AI to craft a specific solution. For instance, if a user frequently struggles with a software feature, the AI might create a tutorial addressing their specific issues. Grammar-checking tools like Grammarly not only identify user writing patterns but, using Generative AI, suggest sentence structures that resonate with their unique style.
Predictive + Immersive Personalization: The system offers an immersive AR or VR tutorial by anticipating a user's needs. In gaming, if a player often struggles with a certain level, the game might use AR to superimpose helpful strategies or offer a VR mode for immersive training.
Conclusion
The tapestry of personalization today is rich and varied. By decoding these diverse categories, businesses and developers can curate experiences that resonate deeply, making users feel cherished and more inclined to engage. This level of detail doesn't just enhance user experience—it transforms it.
This is part 2 of a two-part series on SaaS Personalization. You can find part 1 here, https://lnkd.in/dBgEktZW. We welcome your experiences, insights, and views in the comments below. Also, don't forget to sign up for our weekly CCO Perspectives newsletter. 
