Finding the secret to ideal customer satisfaction is a customer success manager’s pot of gold at the end of a rainbow — elusive at best and maybe impossible in reality.
The Irish folklore of a pot of gold being hidden at the end of a rainbow has often been used as a parable to share the dangers of chasing something that is impossible to find; after all, a rainbow is actually just a light illusion that is really a circle.
Archeologists, however, proved that idiom to be at least partially wrong. Discover Magazine reported that a volunteer archeologist found 41 gold coins in a field in Germany that are likely the origin of the famous phrase. The coins — known as regenbogenschüsselchen or “rainbow cups” in English — are curved like small bowls instead of the flat coins we have today. The coins in this excavation were likely minted over 2,000 years ago. The theory is that gold coins like these were likely buried for safe keeping. After a field was plowed and rainstorm — both common in springtime — it would have been easy to spot these highly reflective gold coins that seemed to sit at the end of a rainbow.
Perhaps finding a pot of gold at the end of a rainbow wasn’t impossible, as long as you knew what to look for.
Likewise, finding the secret to customer satisfaction can be difficult — unless you know what to look for.
Built In Colorado caught up with Auror Senior CSM Zach Dalzell to learn how his team achieves perfect customer satisfaction.
Auror is a retail crime intelligence platform.
What key metrics or indicators does Auror use to identify potential churn among customers, and how do you leverage this data to proactively prevent churn?
At Auror, our enterprise-focused customer success team takes a data-driven, human-supported approach to churn prevention. We focus on three key areas: ensuring quality data entry into our machine learning models, being the voice of our users and aligning our work with stakeholders’ objectives.
The concept “better data in, better data out” for ML models is a key focus for our team. We closely monitor data entry by our users, and when we notice low-quality data from specific groups, we reach out and partner with local leaders to improve data quality.
Traditional churn metrics like net promoter score help us stay connected to end users’ experiences. For NPS, we schedule 15-minute sessions with respondents to hear their feedback firsthand, enabling us to share insights with our product team as the “voice of the user.”
Finally, we maintain regular check-ins with customer stakeholders to monitor leadership sentiment. This “soft” metric ensures our efforts align with each customer’s desired outcomes. When we have clean data to power our ML tools and we hear directly from stakeholders that we’re meeting their goals, we know we’re in a strong position to prevent churn.
“We maintain regular check-ins with customer stakeholders to monitor leadership sentiment. This ‘soft’ metric ensures our efforts align with each customer’s desired outcomes.”
Can you provide an example of a successful churn prevention initiative or strategy implemented by Auror, and what impact it had on customer retention and business performance?
Implementing bi-monthly engagement syncs with key stakeholders has played a central role in preventing churn by demonstrating our commitment to partnership. We start these calls with a review of how organizations are leveraging our tool, followed by working sessions to improve low-performing metrics and celebrate top users.
An honest assessment of platform utilization highlights positive outcomes and aligns stakeholders with how we can help their teams maximize Auror. These sessions also reinforce our product-led identity. We review upcoming releases, plan educational content to support new tool rollouts and highlight features directly influenced by their input. This personalized approach has helped position us as “different from other vendors” and “true partners” to our clients. As a result, these engagement syncs, paired with other strategies, have enabled us to maintain zero enterprise churn in North America.
