How to Unlock Growth with Data-Driven Marketing: Expert Insights from Eran Friendinger
In today's fast-paced digital landscape, data is the lifeblood of successful marketing. But simply collecting data isn't enough. The real power lies in knowing how to interpret it, integrate it with your marketing strategies, and ultimately, use it to drive growth. On a recent episode of the Sticky Note Marketing Show, host Mary Czarnecki spoke with Eran Friendinger, co-founder and CTO of Voyantis, about how businesses can unlock user value through advanced data analytics and predictive growth strategies. This blog post summarizes their conversation, offering key takeaways and actionable insights for marketers looking to leverage data effectively.
Simply collecting data isn't enough.
Bridging the Gap Between Marketing and Tech
Eran's background as a software engineer with 15 years in marketing and growth gives him a unique perspective on the challenges businesses face. He explained that many companies struggle to connect the dots between technical insights and actionable marketing. His company, Voyantis, was born from this very challenge. At his previous company, Adiance, they built a predictive analytics platform, but realized that the crucial missing piece was helping customers activate those insights. Marketers often lack the technical resources needed to create automated loops based on their data. Voyantis aims to free marketers from this dependency, empowering them to leverage data for improved ROI.
The Power of Value-Based Bidding
Eran delved into the specifics of how Voyantis helps marketers, focusing on the concept of value-based bidding. He explained that traditional ad bidding often focuses on volume – the number of conversions. However, not all conversions are created equal. Some users might sign up and never return, while others become highly engaged, inviting team members and actively using the product. Value-based bidding, on the other hand, prioritizes the value of each user. Instead of just telling ad networks how many conversions you want, you tell them the value of those conversions. This allows the networks to optimize for high-value users, leading to a significant increase in efficiency and ROI. This is particularly transformative for e-commerce businesses, where understanding the value of each purchase (one shirt vs. seven shirts, for example) is crucial. Eran emphasized that for e-commerce, value-based bidding is often more effective than predictive models.
Predictive AI: When is it Necessary?
While value-based bidding can be implemented relatively easily, predictive AI plays a vital role in certain business models. Eran explained that businesses that take longer than seven days to drive a first purchase, or those focused on cultivating long-term customer relationships (even with quick initial purchases), benefit most from predictive AI. He used the example of Rappi, the DoorDash of Latin America. While ordering a pizza is a quick action, predicting the long-term value of that customer (will they become a regular customer? What types of food do they prefer?) requires predictive models. These models allow companies to identify high-value customers early on and tailor their marketing efforts accordingly.
Data Infrastructure and the Inevitability of Data Issues
Eran stressed the importance of having a solid data infrastructure in place. However, he also offered a crucial reminder: "Data will break." It's not a matter of if, but when. Therefore, businesses must build safeguards into their systems to protect themselves from data disruptions. This includes monitoring, alerting, and solutions to mitigate issues quickly. He advised that building a data-driven product requires a product team, not just a data scientist. It's an ongoing process of building, maintaining, and adapting to the ever-changing data landscape.
Key Takeaways for Marketers:
Connect Marketing and Tech: Bridge the gap between marketing and technical teams to effectively leverage data insights.
Embrace Value-Based Bidding: Prioritize user value over volume in your ad campaigns for increased efficiency and ROI.
Consider Predictive AI: Assess if your business model requires predictive models to identify and target high-value customers.
Build Robust Data Infrastructure: Invest in data infrastructure and implement safeguards to protect against inevitable data issues.
Focus on Long-Term Value: Don't just chase immediate conversions; focus on building long-term customer relationships.
By understanding these principles and implementing them effectively, businesses can unlock significant growth through data-driven marketing. The conversation with Eran Friendinger offered invaluable insights into this complex but crucial topic. Listen to the full podcast episode for more details and expert advice.
