Your product’s most powerful feature might not be what it does, but how well it knows your users.
In the age of endless SaaS options, users aren’t just looking for functionality. They crave an experience that feels like it was built just for them. While this used to be more of a “nice to have” or a strong point of differentiation for products, it’s now evolved into a core expectation for all products. With personalization tactics in place, you have higher user satisfaction and retention. Without them, your users may be blind to your product’s value.
However, personalizing every aspect of a product can feel like chasing an impossible goal.
Challenges of personalizing the core product
When you think of product personalization, you probably think of a fully dynamic interface that can adapt to a wide range of user identities, needs, desires, etc. This is often far more complicated than anticipated, though.
Achieving meaningful (not hokey) personalization requires deep integration of user data, behavior tracking, and advanced algorithms to tailor everything from content layouts to interactive features.
Common challenges that arise are:
Data overload
Collecting and processing the necessary data to create meaningful personalization at the UI level can be overwhelming. Users generate a massive amount of behavioral and interaction data, which needs to be stored, processed, and applied appropriately. Often, in pursuit of collecting as much data as possible on users, a “frankenstack” of data tools is assembled, which leads to breaks in communication between tools, errors, and inconsistencies.
Fragmentation
Personalization can sometimes go too far in attempting to account for a wide range of user needs. Balancing customization without making the product too complex or inconsistent for broader audiences can become a major challenge.
Heavy workload
Even if you were able to identify the perfect strategies to account for all of your users, scaling these personalization efforts requires a heavy lift for your engineering and product teams. When you attempt to build custom features for several different audiences, the workload can balloon to something that becomes insurmountable.
AI can help, though
Thanks to the acceleration of AI technologies in the past couple of years, scaling personalization efforts has become much more achievable. AI-driven personalization takes some of the grunt work off of your team and shifts it to technology.
Advancements in machine learning and generative AI allow SaaS companies to create predictive models that can understand user needs in real time. This helps to offer tailored experiences without constant manual intervention.
One example of this in popular culture is Netflix and Spotify. They use AI to curate personalized content recommendations based on users’ viewing/listening history. SaaS companies can similarly implement AI-driven dashboard or suggestions features that are driven by product usage patterns. This level of real-time personalization is likely to become table stakes for the industry.
Steps to implement product personalization
If you’re looking to implement more personalization in your product, there are several key steps you can take to jumpstart the strategy.
User segmentation
It may not always be possible to segment on an individual basis, so identifying key user segments is critical. You can segment users based on behavior, preferences, demographics, or any other criteria that is relevant to the way that your users interact with and experience your product. This helps you to deliver content and features that cater specifically to each group. For example, you could have different paths for enterprise users versus small businesses, or marketers versus sales leaders.
Behavior tracking
When you monitor user interactions, you get a better understanding of the relevant patterns of use and pain points. Using tools like Google Analytics, Mixpanel, or Heap, you can gather information on where users spend the most time, which features they frequently use, and where they encounter friction.
You can use behavior tracking to inform the segments we mentioned above, to set off triggers, or to gather information for ongoing product development. So, for example, you could create segments of power users to deliver notifications on new advanced features. Or, you could notice that when users get to a certain point in the experience, they typically drop off quickly, so you set a trigger to deliver a helpful interactive tutorial as soon as they land on the page.
Preference settings
Sometimes, the best solution is the simplest. Instead of trying to make inferences about your users and the experience they want, you can allow them to manually adjust their experience. For example, you can let them choose which notifications they receive, how their dashboards are displayed, or which features show up for them.
An email marketing platform, for instance, could offer a basic and advanced mode, letting users toggle between simplified and more robust options depending on their level of expertise. Salesforce and Google Analytics are also two examples of SaaS companies that let users customize their views based on specific needs
Being able to make these decisions themselves is sometimes more effective than more dynamic personalization, so long as you make the settings easy to access and understand, since it provides more of a sense of control.
An easier and arguable more effective strategy: Personalizing the assistance layer
While strategies to implement more core product personalization are more accessible than ever, you can eliminate the need to implement such in-depth personalization if you shift your focus to personalized assistance. Focusing on personalized user assistance, including education and support, is a more practical and impactful approach.
Personalizing the assistance layer in your product is like giving your users a map to navigate even the most complicated products with ease. This allows you to keep more of the core features of your product uniform and only adapt the way that you guide your users through the product.
When you use cutting-edge user assistance tools like Command AI, you can implement the following personalized assistance strategies:
Tailored help articles
Instead of showing a generic list of articles in a help center, use AI or behavior tracking to display articles that are relevant to each user’s recent activities. For example, if a user has been exploring advanced features, show them guides related to those features.
Personalized onboarding flows
New users often need guidance on getting started, so providing personalized onboarding flows is one of the most valuable strategies you can enact.
By tracking their behavior during the first few sessions, you can adapt onboarding flows to their specific needs. For instance, if a user skips certain tutorial steps, the system could infer they have advanced knowledge and adjust future guidance accordingly.
Custom tooltips based on user behavior
If a user is frequently navigating to the same feature, you could trigger tooltips that offer suggestions for advanced uses of that feature. This helps users discover new functionality they may not be aware of, enhancing their overall experience.
Behavior-based notifications
For instance, in a project management tool like Asana or Trello, personalized notifications can help users based on their current tasks or collaboration patterns. These could include reminders, suggestions for overdue tasks, or advice on using certain features more effectively.
The future of product personalization
The future of product personalization lies in balance.
SaaS companies must strike a balance between providing an easy-to-use, general-purpose product while meeting the growing expectation for personalized experiences. AI-powered personalization will continue to grow in popularity, especially for user education, support, and notifications, which offer significant value with less technical complexity than fully personalized UI changes.
By focusing on personalizing user education and support, SaaS companies can meet user demands more practically and efficiently while delivering a superior product experience.
