Competitive ad intelligence has never been short on data. Marketers can already see where competitors advertise, how much they spend, and which creatives they run. What’s been missing is context—the intent behind those campaigns. BIScience, the company behind the ad intelligence platform AdClarity, thinks it has the answer.
The company this week announced Ad Objective Intelligence, a new AI-driven capability that automatically classifies competitor campaigns based on their primary goal: brand building or performance. The feature is designed to help marketers understand not just what rivals are doing, but why they’re doing it—and what that signals about broader strategy shifts.
It’s a deceptively simple distinction with outsized implications. A brand-awareness push requires very different creative, channels, and expectations than a performance-driven campaign. Yet in most competitive monitoring tools, both appear as undifferentiated “spend.”
From Spend Tracking to Strategic Insight
AdClarity’s new capability aims to close that gap by labeling campaigns according to objective, allowing teams to benchmark apples to apples. Instead of reacting blindly to a spike in competitor activity, marketers can see whether rivals are investing in long-term brand equity or chasing short-term conversions.
That distinction matters more than ever. According to BIScience data, brand awareness accounted for 40% of share of voice (SOV) in the U.S. over the past year, while performance campaigns made up the remaining 60%. The mix, however, varies widely by industry.
Health brands lean most heavily toward awareness, with Insurance and Investing not far behind. On the other end of the spectrum, Marketplaces and Digital Games skew strongly toward performance‑focused advertising. For marketers operating in these categories, misreading competitor intent can lead to costly overreactions—or missed opportunities.
In practical terms, Ad Objective Intelligence lets teams identify when a competitor shifts from “always‑on” awareness into promotion mode, or when sustained performance spend hints at a new growth push. That kind of signal can inform everything from media allocation to creative testing and messaging strategy.
Why This Matters Now
The launch lands at a time when marketing teams are under pressure to do more with less. Rising media costs, fragmented channels, and increased scrutiny on ROI have made strategic clarity a necessity rather than a luxury.
Traditionally, competitive intelligence tools have excelled at surface‑level visibility: impressions, formats, publishers, timelines. What they haven’t done well is interpretation. By layering objective classification on top of existing data, BIScience is betting that marketers want fewer dashboards—and more answers.
This also reflects a broader trend in ad tech toward decision intelligence, where AI doesn’t just collect data but actively frames it in a way that supports planning and forecasting. Rival platforms in the competitive intelligence space have focused on creative analysis or channel tracking, but few have tackled campaign intent at scale.
Avoiding the “Copycat” Trap
One of the quieter benefits of objective‑based classification is cultural. Without understanding intent, teams often feel compelled to mirror competitor activity, even when it doesn’t align with their own goals. A rival’s aggressive spend can trigger panic, leading to reactive budget shifts that undermine long‑term strategy.
By clarifying whether a competitor is building brand or chasing conversions, AdClarity gives teams permission to not react—or to respond in a more targeted way. It also helps agencies pressure‑test their recommendations against real market behavior, rather than assumptions.
“Understanding competitors’ and industry ad intent transforms a marketing budget from a gamble into a strategic asset,” said Dorit Kaplan, VP of Product and Strategy at BIScience. “By moving from a reactive to a proactive position, you stop chasing the market and start leading it.”
The Bigger Picture
As AI continues to reshape marketing analytics, features like Ad Objective Intelligence point toward a future where competitive insight is less about volume and more about meaning. Knowing that a competitor is spending heavily is table stakes. Knowing why they’re spending—and what that implies about their priorities—is where the advantage lies.
For brands navigating increasingly crowded digital markets, that difference could determine whether ad intelligence is merely informative—or genuinely strategic.
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