Choosing the right bidding strategy is critical for programmatic TV advertising campaigns. While manual and rule-based options offer control, AI-powered bidding delivers real-time optimization, budget efficiency, and measurable business outcomes.
Connected TV (CTV) has cemented its place as one of the most effective channels for performance-driven marketers. But while CTV gives brands the opportunity to reach engaged audiences on the biggest screen in the home, there’s one critical factor that determines how effective a campaign will be: your bidding strategy.
Just like in search or display, the way you bid in programmatic TV advertising can mean the difference between wasted impressions and measurable business outcomes. But with multiple options — from manual bids to AI-powered strategies — many marketers are asking the same question: what’s the best bidding strategy for programmatic TV ads?
Let’s break it down.
Real-time bidding is the backbone of programmatic advertising. Every time a streaming viewer presses play, an instantaneous auction occurs behind the scenes. Advertisers compete to serve their ad, and the highest bidder (within set parameters) wins the impression.
This all happens in milliseconds, across thousands of auctions per second. On CTV, that means your ad could win placement in premium streaming content, reaching the exact audience you’ve defined.
But simply bidding more doesn’t guarantee success. To drive ROI, you need the right strategy for balancing cost, competitiveness, and outcomes.
With simple bidding, the bidder continuously bids across all available inventory to maximize exposure. By bidding on every impression opportunity, this strategy ensures broad reach across placements. You must set a max CPM, which controls spend and allows you to balance exposure with cost efficiency.
Best for: Advertisers who want to:
AI transforms real-time bidding from reactive to predictive. Instead of treating all impressions equally, machine learning models analyze millions of data points in real time (e.g. audience behavior, content context, device type, and historical performance) to determine which impressions are most likely to drive business outcomes. This approach helps you win the right impressions at the right cost.
Best for: Marketers who want AI to continuously optimize delivery for a key objective — whether that cost per outcome, cost per impression, ROAS, or brand engagement. When opting to use Intelligent Bidding, you can select the most important KPI for your campaign.
Plus, AI-powered bidding has several advantages:
CTV has many unique strengths, such as premium content, household-level targeting, and high engagement. But this also creates complexity: auction prices can fluctuate minute by minute, viewers jump between apps and devices, and inventory quality varies widely.
The good news is that AI thrives in this environment. By learning which audiences convert, which placements perform, and which creative resonates, AI bidding continuously optimizes campaigns in ways humans simply can’t replicate at scale.
In fact, AI-powered bidding can reduce cost-per-acquisition by up to 30%. For CTV specifically, platforms like tvScientific bring this efficiency to performance marketers by combining smart bidding with transparent reporting, so you see exactly where your ads ran and what outcomes they delivered.
At tvScientific, advertisers can choose how they want to optimize their campaigns, whether the goal is efficiency, scale, or measurable outcomes.
While we no longer offer simple bidding, our intelligent bidding system uses machine learning to dynamically optimize bids in real time. Marketers can choose to optimize for:
These strategies give marketers flexibility to test, learn, and optimize. Whether you’re focused on awareness, efficiency, or performance, you can choose the approach that best supports your objectives.
As the industry shifts toward a privacy-first, post-cookie world, bidding strategies must evolve. Contextual signals, first-party data, and outcome-based optimization will become even more important in programmatic TV.
The best bidding strategies will balance three things:
So, what’s the best bidding strategy for programmatic TV ads?
While a manual approach may work in limited scenarios, AI-powered bidding is the clear choice for marketers who want to drive measurable outcomes at scale. It ensures every impression is evaluated not just on cost, but on the likelihood of driving business value.
At tvScientific, we’ve built bidding technology that goes beyond clicks, optimizing every campaign for the outcomes that matter most to your business. With full transparency and guaranteed performance, we make sure your programmatic TV dollars work smarter, not harder.
Ready to take control of your CTV bidding strategy? Get in touch with us to see how tvScientific can help.
What is the difference between simple bidding and intelligent bidding? Simple bidding continuously bids across all available inventory to maximize exposure, giving advertisers full control over bid prices and pacing. However, it’s reactive and requires hands-on management. Intelligent Bidding, on the other hand, uses AI and machine learning to analyze millions of data points in real time — automatically optimizing bids toward the impressions most likely to drive your key objectives, such as cost per outcome, ROAS, or brand engagement.
Which bidding strategy is best for performance marketers? AI-powered bidding is the top choice for marketers focused on measurable outcomes like conversions, revenue, or sign-ups. It continuously learns and adjusts bids to deliver the highest-value impressions at the right cost.
Can AI bidding reduce costs compared to traditional methods? Yes. By focusing spend on impressions that are most likely to drive outcomes, AI-powered bidding can reduce cost-per-acquisition by up to 30% while improving campaign performance.
How does tvScientific support different bidding goals? tvScientific offers multiple strategies, including intelligent bidding that optimizes for Cost per Outcome, ROAS, CPM, and Brand Engagement, giving marketers the flexibility to prioritize awareness, efficiency, or performance. For those who want guaranteed performance, the Guaranteed Outcomes (GO) program ensures results against a declared cost-per-outcome.
How should advertisers prepare for the future of programmatic CTV? Marketers should prioritize precision, agility, and transparency. Leveraging first-party data, contextual signals, and outcome-based optimization will become increasingly important in a privacy-first, post-cookie world.