If I had to recap this article in two sentences it will be as follows:
Targeting is cake, not frosting.
Blaming “targeting” for a poor targeting choice is a little like blaming “driving” for a car wreck.
McConnell wants to really focused on audience definition, audience delivery, and time if we really have to blame something.
Let me review the 3 before we get to ask your POV,
Audience definition is the well-established research about the brand
Audience delivery is usually not measured except as gross reach, which Reach is a quantifiable part without qualifiable attribute.
Time understanding the optimal “when” given a long purchase cycle etc
The Sensei’s note:
In my professional opinion, Targeting is the mechanics of relevant and intelligent reach which when completed right can lead to substantial results. It includes more than the different level of Audience segmentation (1st, 3rd party data, affinities, lifestyles, psychographics, etc.) geo, time, channel, etc.
Here’s a couple of my recommendations if you are listening today and are not confident about the way your audience targeting is implemented. Follow these steps:
- Go back and QA your set up: Make sure the audience segments selected are from trusted data partners. You can always reach out to each directly and ask them to explain how the data is captured and segmented.
- Don’t be afraid to remove targeting that is not working:
- If you see a higher CTR in the overnight hours coming from Internet Explorer or an outdated version of browsers, block those hours and monitor closely the following days.
- You can always partner with a DoubleVerify or a Moat or a Peer39 to help filter the fraudulent concern right away, and them move towards optimizing the actual audience segments.
According to Oli Gardner, Co-founder of Unbounce, there are 3 levels of Marketing IQ, which each have their own version of how lead gen is measured.
He talked about how implementing High IQ marketing strategy with one of his campaign where he optimized micro metrics like Spam emails, fake emails, branded emails.
Let’s go over the 3 micro metrics and how he optimize for success.
Spam emails he implemented a Captcha or honeypot to prevent bots, Fake emails which are entered by humans, he added a simple statement: “Enter the email address you’d like us to send the course link to” and the fake emails dropped from 7.9% – 5% a 35% improvement.
The final micro metric, the branded email which are business emails and the ultimate goal, he changed the label from “enter email address” to enter business email”, the number of branded emails went up by 60%.
Amy you posted about this on LinkedIn sharing your Point of View, why don’t you go ahead and take the lead here? Can you let our listeners know what’s happening?
Amy’s Post on Linkedin can be found here
Google is getting rid of the average position metrics, Google Ads is strongly encouraging to start using the transitioned metrics introduced last year and define as follow for to refresh anyone’s memory:
- Impr. (Absolute Top) %: This is what most people think of as position one. The metric shows the percent of your ad impressions that are shown as the very first ad above the organic search results.
- Impr. (Top) %: The percent of your ad impressions that are shown anywhere above the organic search results.
- Search (Absolute Top) Impression Share(IS): The impressions you’ve received in the absolute top location above the organic results divided by the estimated number of impressions you were eligible to receive in the top location.
- Search (Top) IS: The impressions you’ve received in the top locations above the organic search results compared to the estimated number of impressions you were eligible to receive in the top location.
Other Ginny Marvin ressources on this topic:
Advertising Research Foundation (ARF).
It looks like consumers are less likely to share personal information such as first and last name, home address, spouse names. Etc. Most of the surveyed adults priced their personal information from $10- $20.
Q: how much would you sell your data for?
What really surprised me is that Sullivan pointed out how most of consumers do not see the value in sharing data to improve personalization of advertising message. Some of which may be created with the misconception of how the data is being tracked and with terms like first-party data, data storage, etc.
Send us your thoughts, feedback, comments HERE