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Media Effectiveness Measurement Services

Analyse, test and optimise your channel effectiveness with incrementality testing and media mix modelling

Work with our combination of media planning and statistics consultants to gain a picture of your unique media mix. With our bespoke consultancy, you can gain a true picture of the influences on your sales beyond just your media buys — and well beyond what your ad platforms tell you.

How incrementality testing and media mix modelling helps your business

Through incremental testing, you can assess the real impact of your marketing campaigns, allowing you to estimate ROI and optimize budget allocation. Informed by these insights, you can develop more effective strategies and messaging for future campaigns.

Alternatively, media mix modelling helps us determine the optimal allocation of marketing spend across multiple channels, ensuring performance and efficient resource utilization.

Our media solutions team includes experts across digital analytics, web & app tagging, server-side implementations, data engineering, data science and Google Marketing Platform and Adobe Solutions, so can offer an end-to-end solution where your data is collected, processed, analysed and reported transparently.

Work with our Media Effectiveness team

Our analysts can offer a number of different data services which can be tailored to meet the unique needs, data availability and nuances of your business.

Understanding and bidding to value

First party customer analysis from your CRM/CDP which can support in lifetime value modelling and therefore support your media buyers in better bidding-to-value practices

Advertising platform incrementality testing

Design and implementation support of in-platform experiments to measure campaign or channel lift / effectiveness to determine their part in your future media mix, typically tested via controlled geographic exposure

Bespoke Media Mix Modelling (MMM)

Media mix modelling as a one-off or recurring study, to associate cause and effect of your media investments over time, with budget and ROAS modelling into the future to allow you to unlock investment opportunities

Understand your media effectiveness

Marketing mix modelling, or media mix modelling is the next level, modern, cookie-less form of macro media attribution.

Media Mix Modelling, especially when backed with incrementality lift testing, has been tipped as a “new gold standard for ad measurement in data-constrained online environments” (Harvard Business Review).

Impression’s Media Solutions team, along with our media colleagues will consult with you to understand your existing digital maturity, based on the actions you’re already taking. We’ll work with you to roadmap to an end state where you can run regularly refreshing media mix modelling, backed by an experimentation programme.

Our consultancy will span from your data monitoring, warehousing, preparation, validation, testing, modelling and then onto reporting and consultancy. Every project is different and we will always operate transparently with your media, marketing or data science teams, sharing the model throughout.

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Media Effectiveness FAQs

Multi-Touch Attribution Modelling or Media Mix Modelling?

Multi-touch attribution and media mix modelling both measure the impact various media channels have on business goals and in turn optimise the allocation of marketing resources. The key difference is that media mix models analyse media effectiveness through modelling relationships between media spend and target metrics such as revenue or conversions, whereas multi touch attribution models track and assign credit to multiple media channels based on “touchpoints” within the customer journey.

Key differences:

  • Data privacy restrictions: Media mix modelling doesn’t require customer journey data and hence is not influenced by online restrictions such as cookie bars. In recent years, tracking the customer journey has become increasingly difficult due to the decaying lifetime of the cookie as a result of the Intelligent Tracking Prevention (ITP) browser feature introduction in 2017.
  • Non-media factors: Multi-touch attribution models credit media channels (organic & paid) for the whole revenue. This means that any revenue generated or influenced by non-media factors such as seasonality, sales periods and competitor activity isn’t accounted for. On the other hand, media mix modelling can easily account for non-media factors provided relevant historical data is available.
  • Historical data: A media mix model typically requires 2-3 years of data to produce a reliable model. Obtaining good quality, complete historical data can sometimes be challenging. Multi-touch attribution on the other hand has no such requirement.


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Find out what we can do for your business

Want to maximise your media investment, through media mix modelling or incrementality testing? We’d love to hear from you.