Is Beatgrid’s single-source measurement the answer to audience fragmentation?
Measurement systems have struggled to keep pace with audience fragmentation, but one company that believes it has the solution for single-source, cross-media exposure and outcomes measurement is Beatgrid.
The adtech vendor claims its consented, mobile app-based panel avoids data fusions and provides independent verification of incremental channel reach and also incremental effectiveness.
Clients typically use the measurement solution for cross-media reach and frequency, brand lift and direct outcomes attribution.
Importantly, these insights are based on the same person-level exposure dataset, provided via the mobile app, which uses audio-based content recognition.
Outcomes are a key part of the offer
A majority of client campaigns combine exposure and brand lift. Beatgrid’s co-founder Daniel Tjondronegoro (pictured) believes this is necessary to separate the contributions each channel makes to campaign effectiveness.
His argument is that as media plans become more complex, aggregated brand studies that rely on claimed exposures and perception are less reliable.
Beatgrid’s measurement solution provides proof of exposure, followed by a brand survey of exposed viewers (and non-exposed control groups), where required.
“Through the same [measurement] app, we can measure location, to see if someone went to a quick serve restaurant after seeing their ad,” Tjondronegoro adds.
Tracking new activity on mobile apps
Mobile phone-based activity can also be tracked with permission. “We can show whether there is new activity on certain apps.
“If a betting app is advertising on TV, we can track whether someone starts using it more, or uses it for the first time.”
Beatgrid measures ad exposure across broadcast linear TV, BVOD, AVOD, SVOD, FAST, other CTV, social video (including YouTube, Meta and TikTok), retail media video, radio, digital audio and OOH.
In-home and out-of-home media consumption is covered. Video viewing is tracked across television sets and multiscreen devices.
Panelists are incentivised with points rewards that are converted to gift cards or cash. They are rewarded for both passive monitoring and active surveys, which is the foundation for establishing single-source datasets.
Ad exposure is identified at channel and creative level, and Tjondronegoro claims the system can cope with mass-scale creative versioning.
Incremental reach (per channel) is a key metric, while Tjondronegoro notes: “Frequency management is crucial for cost efficiencies but also avoiding ad overloads that hurt brand perception.
“We track cross-media frequency very accurately, and we can help demonstrate optimum frequency.”
This understanding of optimum frequency is underpinned by the outcomes measurement.
Some advertisers, aiming to influence a weekly supermarket shop, may seek reach above all else, but others, with more complex messaging, may optimise for frequency.
One question is how many exposures you should seek on each channel or platform, like linear TV, or YouTube, or TikTok, Tjondronegoro suggests.
Should you use TV to make a brand top of mind, and then start the social campaign? Or start social earlier? This is the kind of effectiveness insight that Beatgrid can help with.
When it comes to brand lift, surveys can be triggered immediately to an exposed viewer, or the system can wait until that user reaches a frequency threshold across all platforms or on a particular channel/platform.
Demographically matched control groups
Control groups are created from users who are a demographic match to the exposed group, but known, via the passive monitoring, to have missed the ads.
Tjondronegoro says a solution like Beatgrid’s will outlive the rise of AI and joint-industry cross media measurement solutions.
On AI insights and planning, he says: “AI can only feed off fresh human data, and we are in a strong position to provide the insights it needs.”
Earlier this year, Tjondronegoro claimed that “as media agencies turn themselves into end-to-end marketing operating systems, they can only be fuelled by high-quality data from independent outcomes measurement.
“As more decisions are made inside unified agency platforms, AI agents recommend actions that are harder to interrogate externally, and outcome claims become tightly coupled to the system that made the decisions.”
He predicted that 2026 will be the year when advertisers demand independent, outcomes-based validation.
Addressing large-scale, advertiser-backed cross-media measurement initiatives like Origin and Aquila, he says, will help with de-duplicated delivery but will not show you whether a campaign worked.
He advises buyers to calibrate cross-media delivery with these solutions, but validate impact with the deterministic, single-source outcomes measurement his company provides.
“Then feed our outcome learnings back into the planning to refine channel allocations.”
He also advises using Beatgrid in parallel to verify incremental reach and optimal frequency.