Interview with Kristina Paulos, Director of Marketing, CRM, Slickdeals
Joan Jenkins (CMO, Blueshift): Hello everyone, welcome to today's webinar on the art of retention: increasing loyalty and engagement with AI. I'm really happy to welcome our guest, Kristina Paulos, Director of Marketing CRM at Slickdeals.
Kristina Paulos (Director of Marketing, CRM, Slickdeals): Thanks, Joan. I’ll start by sharing some context. Slickdeals is the internet's largest deal-sharing platform. Every day, hundreds of deals are posted and voted on by our community of avid shoppers. The platform helps users discover and understand the best deals in real time.
My team focuses on optimizing the marketing components of the customer lifecycle, with retention being a major focus. Today, I’ll walk through some insights we’ve gained by using AI and predictive insights to improve retention.
Optimizing the Customer Lifecycle
Our retention strategy focuses on converting new users into daily users and maximizing LTV. We look at three stages:
- Onboarding
- Ongoing engagement
- Reactivation
Each is optimized through AI-powered, omnichannel personalization.
Custom Welcome Journeys
We start by customizing onboarding based on registration source:
- Mobile app signups: We send a welcome message through email, SMS, and push notifications, highlighting app features.
- Cashback rewards signups: We tailor messaging to focus on the benefits of cashback and, if needed, prompt users to install our browser extension.
This approach boosted retention across cohorts. We also use dynamic triggers to adapt messaging based on user engagement and behavior.
Real-Time Engagement with Predictive Scores
Post-onboarding, we use Blueshift’s predictive scores and engage-time optimization to measure engagement and adjust message frequency accordingly:
- Low engagement: Less frequent messages focused on reactivation.
- High engagement: Timely, relevant messaging.
This segmentation approach resulted in:
- 80% lift in engagement
- 20% decrease in user churn
Dynamic Segmentation in Action
The predictive scores automatically shift users between segments in real time. As engagement increases or decreases, so does message cadence. Results include:
- 26% increase in open/click engagement
- 32% increase in push click-through rates
Omnichannel Personalization
We use behavior data across all channels to inform strategy. For example:
- Shopping for Android phones:
- Push: Prompt to set up deal alerts
- Email: Highlights with visuals and tailored deals
- Push: Deal alerts when matches are found
On Prime Day, we sent coordinated messages across SMS, push, and email to maintain visibility without overwhelming the user.
AI-Powered Deal Recommendations
Our deals newsletter uses recommendation "recipes" that:
- Curate by category
- Personalize based on recent behavior
- Rank by popularity and recency
Results since implementing AI:
- Revenue tripled
- LTV grew by 65%
- Transactions doubled
Reactivation Campaigns
We use real-time data and recommendations to re-engage users:
- Abandoned browse:
- Reminder of viewed deals
- Alternative (similar) deals
- Complementary (related) deals
Different cohorts respond to different strategies, so we test continuously. For instance:
- Similar deals perform best early in the funnel
- Related deals work better for re-engagement later
Post-Purchase Recommendations
After a purchase, we send:
- Email: Related product suggestions
- Push: General prompts to explore relevant categories
Lapsed User Intervention
We identify waning interest and trigger:
- Messages with FOMO-driven language
- Nudges to explore fresh deals
Strategy Outcomes
- 65% increase in engagement
- 40% increase in retention
- 10% decrease in churn
- 34% revenue increase
- 65% growth in LTV
- 118% increase in transaction rates
Q&A with Kristina
Joan: What are the top industry changes that shaped your strategy?
Kristina: Channel expansion—especially push and SMS—and personalization. SMS, in particular, has the highest engagement rates.
Joan: How has AI changed your day-to-day?
Kristina: It’s become an everyday tool—from Alexa and Siri to ChatGPT. We use AI for copywriting, campaign ideas, and brainstorming. It’s like having another teammate.
Joan: Advice for marketers balancing acquisition and retention?
Kristina: Know your goals and customer value. Test cost-effective channels first. Scale what works to finance higher-cost acquisitions that yield better LTV.
Joan: What role does SMS play in your strategy?
Kristina: SMS is our highest-performing channel. We're looking at ways to use it for conversational marketing—managing alerts, adding/removing interests, etc. It’s all about making interactions seamless and personalized.
Joan: How do you collaborate cross-functionally?
Kristina: Constant collaboration. We work closely with product, engineering, business development, and design. Engineers integrate data and build triggers; product teams align roadmaps; and designers help us deliver beautiful messages.
Joan: Key benefits of Blueshift?
Kristina: Automation and data access have supercharged retention. Before Blueshift, we only had basic email. Now we have full lifecycle campaigns powered by AI and a unified data platform—all scalable by a small team.
Joan: Thank you, Kristina. Great insights for everyone. To our audience: thanks for joining us. If you have any questions, feel free to reach out!
