The problem every performance marketer knows
You've been here before. Another vendor pitches their "revolutionary AI solution" that will transform your ad campaigns, but a great demo and a nice UI don’t guarantee performance improvements.
Marketers have learned to be skeptical of AI claims, and for good reason. Despite high adoption, many report a “performance gap” as AI investments fail to deliver the growth promised.
That gap exists because much of today’s AI focus is misplaced. Using AI to create content and ads is one thing. Using it to improve how those ads perform in-market is another. The biggest opportunity isn’t in creation — it’s in optimization.
The real opportunity: Optimization technology built for outcomes
True performance gains don’t come from better-looking ads. They come from better decision-making at the moment an impression is available.
Performance gains happen in the optimization layer of an ad campaign, so tvScientific AI was built to ingest real-time conversion data, adapt targeting based on observed user behavior, and provide transparent attribution — all with the explicit goal of driving measurable business outcomes like sales and installs.
While many platforms still optimize primarily for reach and frequency, tvScientific’s patented AI continuously evaluates trade-offs between scale, audience, and frequency at the level of an individual bid request. These decisions happen at a frequency and speed and with a level of complexity that no human buyer could manage manually.
By handling this complexity in real time, our technology ensures ads are delivered when and where they are most likely to convert — not simply where inventory is easiest to buy. The result is an increase in performance.
What AI for Performance TV actually looks like
Our patented technology analyzes tens of thousands of variables in real time, including audiences, inventory, geographical data, and formats. For every impression, tvScientific AI makes four critical real-time decisions that human buyers cannot handle at scale:
- Which household is most likely to convert right now
- How much to bid on a specific impression
- Which creative is most likely to perform in the moment
- Whether to spend immediately or wait for a better opportunity
These decisions account for traditional factors like geography, audience, time of day, and content type, alongside performance-specific features such as frequency, campaign objective, and observed conversion behavior. Every impression is a learning event, so it’s continuously improving as data flows in.
The technical edge that makes performance possible
Real-time optimization at this level depends on one thing above all else: speed.
Because of this, tvScientific made a critical architectural choice by building our bidder in Zig, a C-like programming language that allows for manual memory management and highly efficient execution.
This technical approach allows bidding decisions to be made up to 10X faster than other platforms. Faster execution ties directly into performance, allowing the platform to run significantly more inferences per bid request than competitors. More inferences mean more options considered. More options mean better matches between impressions, creative, and high-intent households. And better matches translate into stronger ROI and lower cost per outcome.
Put simply:
Speed enables deeper decisioning. Deeper decisioning drives better performance.
This technical foundation gives tvScientific a greater ability to identify those rare, high-value moments when a viewer is most likely to convert — the moments that matter most to performance marketers.
The numbers don't lie: Real performance gains
Skepticism about AI is healthy. That’s why performance needs to be evaluated through real campaigns.
Point of Sale Customer: Head-to-Head AI vs. Manual Test
- Setup: 50/50 budget split between AI optimization and manual buying
- Results: TV drove 69% more app installs and 82% more purchases than would have occurred otherwise
- Why it worked: tvScientific AI identified high-converting households at scale that manual targeting could not capture using publisher and audience filters.
Financial Services Customer: Revert Test
- Setup: Already using tvScientific AI, temporarily switched back to manual buying
- Results: 160% drop in performance when tvScientific AI was turned off
- Key insight: Even well-tuned manual strategies can't compete with machine-speed optimization.
Home Goods Customer: Week One Performance
- Setup: New client launch with AI optimization from day one
- Results: Over 40% performance improvement within the first week, leading to three budget increases in a single weekend
- Takeaway: When AI is built correctly, performance impact is immediate.
Game-changing features performance marketers should know about
tvScientific continues to invest in features that extend its optimization advantage.
Smarter targeting through our patented Household Profile
Instead of relying on broad demographic segments, tvScientific’s Household Profile incorporates deeper household-level intelligence directly into the optimization process. This enables more accurate predictions about which households are most likely to convert.
In testing, this approach was approximately 20% more accurate at identifying buyers.
The bottom line: tvScientific AI prioritizes conversion likelihood, not just low-cost inventory.
AI pacing that prioritizes performance
Many platforms pace budgets evenly throughout the day to ensure full delivery, regardless of performance conditions.
tvScientific AI evaluates whether to bid immediately or wait for a stronger opportunity, allowing spend to concentrate around higher-performing moments — even during traditionally slower viewing periods.
The bottom line: Budget is allocated toward outcomes, not just completion.
The bottom line
Connected TV is growing fast and performance marketers are under increasing pressure to prove ROI. Performance TV can deliver reach and results, but only with buying decisions smart enough to optimize every impression.
The question is whether you’ll rely on static rules, or machine learning that gets smarter with every decision. Why not put your own performance data to the test? Contact us for a free demo.
