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What are the Challenges of Measuring Marketing Effectiveness?

There are many challenges to measuring marketing effectiveness. Factors include:

  • Types of Data Available: The type, richness and quality of data vary widely from channel to channel. For example, with programmatic display advertising, marketers can get user-level and impression-level data to track the user all the way to a conversion, regardless of whether a conversion occurs or not. However on TV, marketers would only get reporting of when their ads were flighted on air. On Facebook, marketers collect rich aggregate data reporting about their targeted audience, but can obtain almost no user-level data.
  • Frequency of Data: Some media channels offer data on a real-time basis, whereas others only offer data post-campaign and reporting may only be delivered weekly or monthly.
  • Attribution and Incrementality Methods: Not all attribution models and incrementality studies are created equal. Depending on the type of methodologies used, the channels under test and a host of other factors can lead to limited inputs for a media measurement framework. Gauging the contributions of each media channel, tactic, or audience without an always-on test and control experimentation practice in place is very difficult to execute in an apples to apples way.

For years marketers have been searching for the holy grail of media measurement, one that could address the challenges stated above. A single framework that ingests all online & offline data and automatically generates reports and insights to guide budget reallocation decisions in real-time with no friction. At one time we thought MTA was the answer to this desired state, however it failed to fulfill its promise due to many factors like – the collapse of the third-party cookie, identity resolution gaps, severe data reconciliation issues and perhaps the biggest blindspot of all, no access to the walled gardens. For all intents and purposes MTA is no longer a viable exercise.

The types, frequency and availability of user-level data limits the universe of advanced measurement techniques that can be used to measure marketing effectiveness. The types of decisions that the measurement informs also plays a big role in how useful marketing measurement itself is. Marketers looking to make tactical decisions, like optimizing between creative A vs creative B running on a specific audience within a specific media channel, can use data made available by that channel.

There are advanced measurement methods available that can answer the cross-channel attribution problem statement but are not subject to the limitations of MTA. For more strategic decisions, like budget allocation across multiple media tactics based on incremental sales and incremental ROI, you would have to use advanced marketing measurement techniques such as incrementality measurement to get to an answer. For other big strategic questions, like the impact of weather, competition, interest rates, or government policy on sales would need to apply a marketing measurement technique like MMM (Marketing Mix Modeling) for long-term planning.

Here are additional resources for reference:

Author

Madan Bharadwaj - Cofounder & CTO

Expert in advertising measurement, attribution and analytics

 

Multi-touch attribution is more challenging today due to limited tracking options, identity and cross-device resolution hurdles, data leakage and the massive amount of time it takes to implement.

 

What is cross-platform attribution (or cross-channel attribution) and why is it difficult?

The goal of cross-platform attribution in marketing is to gain clarity on the interplay and contribution of influence that each channel/tactic/campaign has on driving conversions over and above baseline sales.

It’s a task that has proved to be very difficult for many reasons including but not limited to:

  • Walled gardens are typically inaccessible to third-party tracking of impressions
  • Identity resolution across media platforms is quite low
  • Cross-device tracking is difficult and match rates are extremely low
  • Instrumenting a tracking infrastructure by a third party measurement provider has proved to be fraught with breakage and data leakage
  • It is extremely time consuming to implement without the help of a partner

Video: Landing a source of truth cross-channel media reporting dashboard

 

 

What are some cross-channel attribution tools?

MTA – collects individual, or user-level data, for trackable addressable media and conversion events in order to determine the impact of each media event to the desired conversion at the customer level. By summing the impact of each addressable media touchpoint on each customers’ likelihood to convert, MTA quantifies the total media channel lift provided by addressable media. MTA does not account for the impact of non-addressable media, and furthermore much addressable media is either non-trackable or lost due to the innumerable challenges of tracking data at the user level.

Incrementality Measurement – Incrementality in marketing refers to the incremental benefit produced per unit of input stimulation. Incrementality is the lift in desired outcome (awareness, web visits, conversion, subscriptions, revenue, profitability) provided by marketing activity.

Incrementality in marketing is especially needed for channels where ad impressions such as display, Facebook, social, or even TV are hard to measure. To measure incrementality, the audience is broken out into test groups (exposed to the ads) and a control group (suppressed from seeing the ads).

MMM – MMM is a top down (aggregate marketing data) and very artistic statistical exercise where one or more models (e.g. econometric, multi-linear regression) are leveraged to extract key information and insights by deriving information from multiple sources of marketing, economic, weather and financial data. MMM is also a high-touch consultative approach that is very manual with little to no automated data inputs, whereas MTA and Incrementality, when deployed properly, is a very automated approach leveraging preconfigured connectors that extract the required marketing data, across many channels, on regular cadence. (It’s important to note that MTA can take 6 months or more to deploy, whereas Incrementality can be up and running with reporting in 4-6 weeks.) See this article for more on why always-on automated experimentation is the future of marketing measurement.

Author

Trevor Testwuide - CEO

Expert in business strategy and marketing measurement.

 

Multi-touch attribution is more challenging today due to limited tracking options, identity and cross-device resolution hurdles, data leakage and the massive amount of time it takes to implement.