Overview
Every marketer knows the tension: customers expect relevance now, but data arrives late, fragmented, and stripped of intent. Spark New Zealand faced that exact challenge across its B2C and B2B portfolios and chose to solve it at the root.
By unifying consented first-party data in real time with Tealium, Spark transformed how it identifies intent, activates audiences, and converts demand. The result wasn’t just better campaigns – it was Spark’s strongest performance to date across identification, activation, and acquisition.
This is the story of how Spark moved from reactive marketing to confidence-driven marketing, where every message feels timely, personal, and psychologically aligned with customer intent.
The Challenge: Attention Is Scarce – and Relevance Is Earned
One of the key moments in telco is the launch of flagship devices. For Spark, these high-stakes moments, along with always-on portfolios and acquisition, were competing in an environment defined by:
- Fragmented data across CRM, web, media, and platforms
- Over-reliance on broad targeting and historical segments
- Media waste from low-intent or already-converted audiences
- Slower feedback loops between behaviour, decisioning, and activation
In simple terms: Spark had demand, but not always the signal clarity to act at the moment intent peaked.
For marketers, this creates friction. When signals are noisy, confidence drops. When confidence drops, personalisation becomes conservative.
Spark’s ambition was to reverse that psychology and market only when the customer was ready.
The Solution: A Unified First-Party Data Engine
Spark partnered with Tealium to build a real-time, consented first-party data foundation spanning B2C and B2B.
At the centre was a simple principle: intent compounds when signals connect.
What Spark implemented:
- Unified behavioural, CRM, and identity data across web, media, and marketing platforms
- Real-time audience building based on fresh behaviour, not static profiles
- Strong identity stitching to move customers from unknown → known
- Consistent suppression logic to remove friction, waste, and repetition
- Always-on activation across paid media and owned channels
This allowed Spark to replace guesswork with psychological certainty: when someone clicked, browsed, compared, or returned, Spark knew why, not just that.
How It Came to Life: Turning Intent into Momentum
Flagship Device Launches (iPhone 17 & Samsung Fold / Flip)
Rather than treating launches as awareness blasts, Spark treated them as decision moments.
High-intent audiences were built from real-time product engagement across Consumer and SME traffic, then activated precisely when motivation was highest.
- Launch emails reached customers already mentally primed to buy
- Paid media prioritised eligibility, tenure, and behavioural signals
- Suppression ensured Spark never “over-asked” already-converted users
The psychological shift was subtle but powerful: customers weren’t persuaded. They were assisted.
Always-On B2C Portfolios
Across Devices, Mobile, Broadband, and General Merchandise, Spark applied the same logic continuously:
- Detect intent early
- Reinforce confidence with relevance
- Remove distraction through suppression
This created sustained conversion lift even when media investment fluctuated, proving the value wasn’t spend-driven, but signal-driven.
B2B: Trust Before Conversion
For SME, Enterprise, and IoT, Spark wanted to focus on identity integrity and signal hygiene:
- Cleaner form and contact triggers
- Stronger deterministic ID matching
- More accurate ABM and suppression
The outcome was not just more leads, but better conversations, powered by confidence in the data behind every trigger.
The Results: Where Confidence Converts
Spark’s results demonstrate a consistent pattern: when relevance aligns with real-time intent, performance scales efficiently across channels.
Key Outcomes
- Delivered one of Spark’s strongest quarters to date across identification, activation and acquisition
- Up to 10× uplift in engagement rates during flagship device launches
- +23% increase in known customer identification (unknown → known)
- Consistent double-digit conversion uplift across core B2C portfolios
- +47% growth in B2B inbound signals QoQ, alongside improved signal quality
- ~5% QoQ uplift in B2B engagement across key business segments
Email Performance: Intent Meets Timing
- 4× higher click-through rates vs. benchmark
- 74.5% open rate (highest among recent sends)
- Highest email-to-sale conversion segment
- ~90% of engagement driven by high-intent CTAs
Paid Media Impact: Precision Scales
- Up to 10× YoY CTR uplift across paid channels
- Improved media efficiency and audience precision across all platforms
- Strongest digital launch performance to date across key device campaigns
Always-On Performance
- Devices: +29% conversion uplift
- Mobile Plans: +21% conversion uplift
- General Merchandise: +23% conversion uplift
Why It Worked: The Psychology of First-Party Data
Spark’s success wasn’t driven by more data, but by better use of real-time, consented first-party signals.
- Fresh behavioural data enabled timely and relevant engagement
- Suppression and audience governance reduced waste and improved customer experience
- Consistent cross-channel activation reinforced messaging and intent
- Real-time signals allowed Spark to act at the moment of highest customer interest
In practice, this meant moving from reactive campaigns to more precise, signal-led marketing.
What’s Next: From Smart Marketing to Autonomous Marketing
With a strong first-party data foundation in place, Spark is well positioned to continue evolving its marketing approach:
- Expanding real-time decisioning across channels
- Increasing automation while maintaining control and relevance
- Further integrating data, activation, and AI-driven use cases
The focus is not on doing more, but on delivering the right experience at the right moment, consistently at scale.
