Interview with Lauren Reiterman, Manager of CRM, Udacity
Ben Okeya (Customer Success Manager, Blueshift): Hi everyone, and welcome to our webinar: Unlocking Hyper-Personalization Using Data & AI.
Lauren Reiterman (Manager, CRM, Udacity): Thanks, Ben. I’m excited to share how we’re scaling personalization at Udacity using data and AI, and how others can apply these strategies too.
Why Personalization Matters
Personalization isn’t a luxury, it’s expected:
- 76% of customers say personalized content makes them more likely to buy
- 71% expect personalization
- The average attention span is just 8 seconds, so value must be delivered instantly
It all goes back to the golden rule: Treat people like people. Understand their needs, celebrate milestones, and help them overcome friction. Emotional connection drives loyalty, 62% of customers say they feel emotionally connected to the brands they buy from most.
The Four Pillars of a Personalization Strategy
1. Real-Time Data
To personalize well, you need:
- Behavioral data: clicks, purchases, on-site activity
- Zero-party data: user-declared preferences via surveys, forms, onboarding flows
- A unified customer profile
- A UX that encourages data collection through thoughtful touchpoints
At Udacity, we map each step in the student lifecycle, from anonymous visitor to enrolled alumni, and personalize outreach at each step using these data points.
2. Product Recommendations at Scale
AI-powered recommendations help us:
- Curate top programs by category (e.g., "Top Degrees in Data")
- Re-engage dormant users with fresh, relevant suggestions
- Populate newsletters and lifecycle messages automatically
The impact? Saves 10–15 hours/month and boosts engagement consistently.
3. Dynamic Content with Shared Assets and Liquid Syntax
In a single email template, we can:
- Change headers dynamically based on user persona
- Insert personalized course recs
- Show or hide blocks depending on past behaviors or attributes
One campaign now serves 4–6 customer types with a single setup.
4. Multi-Channel Orchestration: The Role of SMS
Email is core, but SMS excels at urgent, time-sensitive communication:
- Renewal reminders
- Download links
- Deadline-driven nudges
- Mentorship action items
We follow four rules: personalize, be relevant, offer clear CTAs, and respect timing. This has led to 3–8x increases in click rates.
A 5-Step Personalization Roadmap
- Map the Customer Lifecycle – Identify emotional high and low points
- Define MVP Segments – Focus on high-value personas first
- Audit Your Data – What attributes and events are tracked? Where are the gaps?
- Create a Content Strategy – Match message types to lifecycle stage and persona
- Execute with Campaign Journeys – Use automation and modular templates to scale
Q&A with Lauren Reiterman
Ben: What’s your favorite part about using Blueshift?
Lauren: Easy: unified profiles. I can see behavioral history, attributes, and engagement in one place. It’s a marketer’s command center. Plus, Blueshift’s customer service is the best of any vendor I’ve worked with.
Ben: You work with a global audience. How does geography affect engagement?
Lauren: Significantly. U.S. and Europe have higher email engagement. In India, SMS rules—but timing and compliance vary by country. Community is also more powerful in some regions than others.
Ben: How are you managing with fewer resources and bigger expectations?
Lauren: We run lean. One person can do a lot with the right tools. We say no to over-designed campaigns and focus on what drives impact—like AI recommendations, simple layouts, and reusable templates. Removing dependencies on other teams is huge.
Ben: Your 5-step action plan is great. How do you scale it across different student segments?
Lauren: Templatization. We reuse reference segments and templates, personalize based on 1–2 variables, and prioritize based on data availability and business value.
Ben: You saw a 32% lift from AI recommendations. What’s next with AI?
Lauren: Generative content is big—subject lines, product copy, segmentation. Next, I want to dive deeper into predictive lead scoring using behavioral data to prioritize users most likely to convert.
Ben: Favorite campaign?
Lauren: Two come to mind:
- A recurring newsletter using AI-generated course recommendations. Result: doubled syllabus downloads and 1.5x more purchases—with zero ongoing work.
- A personalized re-engagement flow for free course students. When we layered AI recommendations with survey-based headline personalization, we saw a 40% lift in engagement.
Ben: Incredible. Thanks for the insights, Lauren!
