It's A Metric!: First Time Impression Ratio
Today’s metric is one I just learned about: First Time Impression Ratio (FTIR)
According to Meta, FTIR is:
The percentage of your daily impressions that comes from people seeing your ad set for the first time.
FTIR = Reach / Impressions
The lower your FTIR, the higher your frequency.
This matters because you can’t survive on “moment of conversion” traffic alone. Such a small sliver of any platform’s user base is in-market for your given offer at any one moment that you should run campaigns to gain brand awareness (this is why you need both brand and performance marketing (and yes, smaller budgets can put these considerations on hold)).
Attention is gold.
A member of the Foxwell Digital community uncovered an interesting FTIR trend:
a dramatic decline from approximately 60-70% to 10-25% over the past 6-12 months [as of March 2024].
This drop suggests a saturation point where the same audiences are being reached repeatedly, leading to what can be termed as ‘audience fatigue,’ rather than just ad fatigue.
The root causes identified include a lack of creative differentiation, reduced influencer marketing budgets, and underinvestment in emerging platforms
A metric on its own isn’t very helpful, but First Time Impression Rate + Frequency could be a useful combo in your budget allocation and performance analysis arsenal when auditing your social accounts.
Disguised as a post about a Substack feature is a reminder that:
- Most new platform features are attempts at moat building
- You don’t have to use every bell & whistle
- You can treat social media as a public journal that you repurpose elsewhere later
Are you trying to find a solution for a problem you haven’t created yet?
A hypothesis is useless without a test.
Pick a measuring stick and get going. Iterate over time.
You can’t have a return on investment if all you’ve invested in is planning out how to measure ROI.
via the Louder Than Words podcast
Saturday Marketing Links | 031624
AI Prompt Engineering Is Dead / Long live AI prompt engineering
According to one research team, no human should manually optimize prompts ever again.
There is an alternative to the trial-and-error-style prompt engineering that yielded such inconsistent results: Ask the language model to devise its own optimal prompt.
this automatically generated prompt did better than the best prompt found through trial-and-error. And, the process was much faster
The optimal prompts the algorithm spit out were so bizarre, no human is likely to have ever come up with them.
The centaur approach is usually better than all human or all AI (at least for a while).
Which makes sense since the two types of “brains” function differently. It’s about finding the optimal combination of the two, not one directing the other.
Speaking of…
Of top-notch algorithms and zoned-out humans
A low-grade algorithm and a switched-on human make better decisions together than a top-notch algorithm with a zoned-out human. And when the algorithm is top-notch, a zoned-out human turns out to be what you get.
…
rather than thinking of the machine as a replacement for the human, the most interesting questions focus on the sometimes-fraught collaboration between the two.
Gold, bitcoin and stocks hit record highs this week. Then came inflation data
investors shrugged off a higher-than-expected 3.2% annual rise in consumer prices and cheered a cooldown in some categories like food prices.
…
US wholesale inflation rose 1.6% for the 12 months ended in February, its fastest clip in months, due to a spike in energy prices.
…
Markets expect the central bank to hold rates steady this month and begin cutting in June or July
Consumer prices climbed 3.2% in February as 2% goal remains elusive
The 12-month inflation rate has been stuck between 3% and 4% since June, hovering just above the Federal Reserve’s official 2% target
