The next evolution of attribution is here.
Bi-Modal Attribution delivers channel incrementality and media mix analysis to provide the most comprehensive look at channel-level performance.
Twice the value. One Platform.
Advertising today is fundamentally different from when attribution was first created. Iterations on old attribution thinking don’t solve the complexities of today’s digital era.
Modern technology merits a novel approach and thinking to evaluating ad spend and channel effectiveness: Bi-Modal Attribution.
Our experiences as agency performance marketers and media buyers lead us to a unique insight – Ads deliver value in two ways, either reaching and converting a unique audience or lifting the conversion rate in a mix of media.
We designed a new method to evaluate ad contributions that shows both ways ads perform.
Channel incrementality shows the results from each ad channel that have not been influenced by other channels, and is additive to the campaign. This method allows you to see your most significant growth drivers, and with our proprietary metrics, you’ll be able to spend smarter. Channel Incrementality uncovers the real value each ad channel delivers independent of other ads.
Media Mix Lift
Accurately see how ads work in a media mix to drive results and how each ad channel lifts conversion rate. See how often your top media mixes occur, and the opportunities to optimize your ad spend towards the best media mix. Media mix lift identifies wasted ad spend and the ways you can deliver your campaign more efficiently.
Pillars of Bi-Modal Attribution
Today’s technology paired with the insight that ads deliver value in two ways, marketers have a choice of between seeing a complete view of attribution or only half of the equation. Bi-Modal Attribution doesn’t just process the data differently, it’s a new paradigm for viewing how ads drive results.
Bi-Modal Attribution starts with direct measurement of every impression, click, and engagement taken by users. BMA uses direct capture of log-level data for the most granular analyses available to marketers. By measuring 95%+ of every campaign, there’s no need for estimating to ‘fill in the gaps’.
With 95%+ of your campaign measured, Bi-Modal Attribution applies first-party data and multiple identity layers to match users across devices and ad channels. This process of cleaning and deduplication removes the need to reconcile platforms over-reporting with Google Analytics.
Typically, cleaned data represents 70-80% of your total campaign delivery for a clear understanding of who ads were served to and how those ads influenced action.
The new way of collecting and processing data means that Bi-Model Attribution doesn’t need to extrapolate from a small sample or model the performance of channels using API data.
The core analyses for digital channels use an algorithm that parses the data, without injecting estimation, so you can see your media mix and channel incrementality. Direct analysis of the log-level data is fundamental to producing data marketers can trust.
There are channels that can’t be measured, like broadcast radio and print. Different types of experiments are needed to calculate their contributions, which can be designed and executed with Mint Measure.
The real value of attribution is created in applying learnings and improving effectiveness throughout the campaign.
As former media planners, we care most about showing you the opportunities to optimize and giving you the tools to take action. Our understanding of how you work and the technologies you use day-to-day lets us deliver the insights you need most.
Bi-Modal Attribution’s new approach means it delivers results above and beyond single-output methodologies. It’s time for a new understanding of how channels work together and separately to produce results.