Measuring the Challenge of Marketing Channels

Główne pojęcia

The author discusses the challenges of measuring hard-to-measure marketing channels and provides insights on how to approach this issue effectively.

Streszczenie

The content delves into the difficulties faced by marketers in measuring channels like PR, social media, and events due to changes in tracking methods. It highlights the shift from easily trackable digital efforts to a more complex attribution landscape. The author emphasizes the importance of understanding incrementality in marketing measurement and advocates for a return to 20th-century mentality for tracking success. Despite the limitations in tracking, it is still possible to measure these challenging channels through a strategic approach that focuses on brand interest and sales lift over time.

Statystyki

From ~1996-2016, the web had twenty years of highly-trackable digital efforts.
Three trends are now combining to spell doom for the world of tracking we used to know.
Some savvy analysts compensate by building ever more complex attribution and traffic modeling.
True measurement means measuring incrementality.
The rise of zero-click content on search, social, and content networks is impacting tracking efforts.

Cytaty

"True measurement means measuring incrementality."
"The rise of zero-click content on search, social, and content networks is impacting tracking efforts."
"Some savvy analysts compensate by building ever more complex attribution and traffic modeling."

Kluczowe wnioski z

How to Measure "Hard-to-Measure" Marketing Channels - SparkToro

by Rand Fishkin o sparktoro.com 10-12-2022

https://sparktoro.com/blog/how-to-measure-hard-to-measure-marketing-channels/

Głębsze pytania

How can businesses adapt their marketing strategies in response to the challenges posed by hard-to-measure channels?

In response to the challenges posed by hard-to-measure channels, businesses can adapt their marketing strategies by focusing on building first-party data. By encouraging visitors to voluntarily log-in and provide valuable information through expressed or implied preferences and behaviors, businesses can gather actionable insights without relying solely on trackable metrics. Additionally, investing in experimental periods for hard-to-measure tactics, monitoring competition that engages in similar activities, and showcasing results from small-scale investments can help sway stakeholders towards embracing un-attributable metrics.

What are some potential drawbacks of relying heavily on big tech ads for marketing attribution?

Relying heavily on big tech ads for marketing attribution comes with several potential drawbacks. One major drawback is the lack of true performance measurement when it comes to attributing conversions solely to these ads. Big tech platforms have access to extensive user behavior data which they use to predict user actions and show relevant ads; however, this may not always result in incremental sales as many users might have made purchases even without seeing the ad. This leads to inflated ad prices based on potentially unnecessary ad exposure rather than actual impact on conversions.

How can marketers strike a balance between embracing un-attributable metrics and proving value to stakeholders?

Marketers can strike a balance between embracing un-attributable metrics and proving value to stakeholders by adopting a combination of approaches. Firstly, they should focus on setting up benchmark measurements for key visit paths such as direct visits, branded search traffic, social referrals, etc., which are often associated with hard-to-measure activities. Secondly, investing in select high-potential techniques within hard-to-measure channels over an experimental period allows marketers to observe changes in conversion rates or other key metrics that indicate effectiveness. Finally, communicating transparently with stakeholders about the limitations of traditional attribution tracking while showcasing observed lift from these activities helps demonstrate value even without precise attribution data.