Right, so I recently had a fascinating chat with Gracie, a real whizz when it comes to user onboarding. We were chewing the fat about how AI is completely revolutionising the whole experience, moving way beyond those generic ‘Welcome to Our Platform!’ emails. Gracie’s been knee-deep in implementing hyper-personalised onboarding journeys, and I was keen to pick her brains.
“The key,” Gracie started, swirling the ice in her water, “is understanding that every user is unique. They’re coming to your platform with different goals, different levels of experience, and different learning preferences. A blanket approach simply doesn’t cut it anymore.” She’s spot on, of course. So, how do we move beyond the blanket?
Step 1: Data is King (and Queen!)
It all starts with data collection. We’re not talking anything intrusive here, just smart tracking of user behaviour during signup and initial platform use. Gracie explained that they look at things like:
- Signup Form Insights: What fields are they filling out? Which options are they choosing? This gives immediate clues about their intentions.
- First Actions: What’s the first thing they do after logging in? Do they immediately explore a specific feature? This indicates areas of interest.
- Navigation Patterns: Where are they clicking? Which pages are they spending the most time on? This highlights potential pain points and areas of curiosity.
They use a combination of tools for this – things like Google Analytics, Mixpanel, and their own internal tracking systems. “The important thing,” Gracie stressed, “is to integrate this data into your CRM or email marketing platform so you can act on it.” Makes sense.
Step 2: AI-Powered Segmentation
This is where the magic happens. Once you have the data, you can use AI to segment users into distinct groups based on their behaviour and inferred needs. Gracie’s team uses machine learning algorithms to identify patterns and automatically assign users to relevant segments.
For example, they might have a segment for:
- ‘Beginner Explorers’: Users who seem overwhelmed and are clicking around without a clear direction.
- ‘Feature Focused’: Users who immediately dive into a specific feature, suggesting a particular need.
- ‘Power Users in Training’: Users who are actively exploring advanced functionalities.
“The beauty of AI,” Gracie said, “is that it can identify these segments much more accurately and efficiently than we ever could manually. It also adapts as user behaviour changes.” Think about using something like Tensorflow, PyTorch or Scikit-learn using Python, and then train it on your current user data. After this, you could feed in all new user data and automatically segment them. It means it is a very fast and effective way to segment users.
Step 3: Dynamic Content Insertion and Personalised Recommendations
Now, with those segments defined, you can start crafting hyper-personalised onboarding emails. This involves using dynamic content insertion to tailor the email content based on the user’s segment. Gracie gave me some cracking examples:
- ‘Beginner Explorers’: Receive emails with simplified tutorials, step-by-step guides, and friendly encouragement. Content may be in video format.
- ‘Feature Focused’: Get emails highlighting advanced features related to their area of interest and case studies of users achieving success with those features. The content could be a webinar recording or a detailed textual explanation.
- ‘Power Users in Training’: Receive emails promoting advanced training resources, developer documentation, and opportunities to connect with other advanced users.
They also include personalised product recommendations within onboarding emails, based on the user’s initial actions and inferred needs. “If someone is exploring our project management feature,” Gracie explained, “we might recommend integrations with popular task management tools.” I noted that this provides tangible value and keeps the user engaged.
Step 4: Optimisation and Iteration
The job doesn’t end with sending the emails. Gracie’s team continuously monitors the performance of their onboarding emails and uses A/B testing to optimise them. They track metrics like:
- Open Rates
- Click-Through Rates
- Conversion Rates (e.g., upgrading to a paid plan)
- Feature Adoption
“We’re constantly tweaking our emails based on what’s working and what’s not,” Gracie said. “It’s an iterative process. The beauty of this is that you will continue to improve as you gain more user data.”
So, to bring it all together, the core principles of hyper-personalised onboarding are: using all available data, making use of AI to intelligently segment users and then tailoring content to them in a way that matches their learning style. From here you use A/B testing to continue improvement and maintain that level of optimisation. This approach is the complete opposite to a ‘one size fits all’ approach but you will see a much better level of conversion by being highly relevant to the target user.
