The 'Bait and Switch' Media Model

Originally Published Autumn 2021

This is part 2 of our recent Organic TikTok vs Instagram Influencer vs Facebook Ads experiments

Part 1 can be found here



Based on the results of our original experiment we also decided to explore the deeper question: Was the problem with the Influencers or with the Platform (Think: Instagram)?

We measured the response to our influencers' activity on both TikTok and Instagram

... and the simple answer is it appears to be the platform

Our influencers were able to replicate the click through traffic generated by our ongoing organic TikTok experiments

The next question is why? Why can't the influencers replicate their followers behaviour on both Instagram & TikTok?

Could it be TikTok's content engagement algorithm has rendered the defacto social media follower count metric redundant?

Or, is the answer much simpler?


We modified the experiment and invested our creative energy and dollars into Instagram Advertising

Not surprisingly the CTR results - before we adjusted for bounce and bots - mirrored the organic reach of influencers on TikTok


and these numbers point to a deeper insight into the nature of user generated creative platforms


You see the bait and switch for these social media platforms is inflating organic creator engagement to accelerate user growth and then throttling organic reach for these creators at the expense of the paid advertising model they later introduce to monteize the platform


The only question is can the advertising model reach scale before the next 'disruptive/game changing' bait and switch platform gains traction among the creative community and you have to start paying the highest rating stars to keep the audience engaged


Today being an influencer on Instagram is tough.

It's much easier on TikTok, but for how much longer?


and what about the rise of social commerce as a revenue model for influencers?


Well to show you how difficult it is for Instagram creatives to monetize their reach here is a quick 'Rule of Thumb' calculator to help you translate influencer engagement rates into Cost per Click rates

It illustrates how engagement is a more accurate measure than reach when forecasting the ROI on influencer marketing

It also illustrates how difficult it is for the influencer to compete directly with the platform they have built their business on

Note:
a. Shares & Retweets can be added to the Comments count
b. You can add the cost of supplying the promotional merchandise to the influencer in the engagement fee to obtain a more accurate cost per click estimate
c. The average CPC for Facebook & Google for retail apparel advertising is between $0.50 to $0.90
d. The bounce rate of Influencer Traffic is signicantly lower than Facebook or Google Paid Traffic


Influencer Category




Influencer Metrics

Follower Count


Engagement Fee ($)


Ave. No. of Likes


Ave. No. of Comments

Campaign Forecast

Engagement Rate


Click Throughs Generated


CPM Rate
$

CPC Rate
$

Disclaimer

The use of these calculators, charts, visualisations, data or any information shall be at the user’s sole risk. Such use shall constitute a release and agreement to hold harmless, defend and indemnify Digital Partners from and against any liability (including but not limited to liability for special, indirect or consequential damages) in connection with such use. Such release from and indemnification against liability shall apply in contract, tort (including negligence of such party, whether active, passive, joint or concurrent), strict liability, or other theory of legal liability; provided, however, such release, limitation and indemnity provisions shall be effective to, and only to, the maximum extent, scope or amount allowable by law.

Questions of accuracy

Tymbals is an experiment in machine learning and statistical modelling of small data pools. Tymbals is still under development. It is still learning. Tymbals is Beta - i.e. Pre-release.

The probabilities and outputs (e.g. calculators, charts, visualisations) will evolve and change as the system ingests more data.

Tymbals is a probability model. The results generated by Tymbals are market estimates based on the cummulative value of the data within the distributed data pools.

Privacy

All data inputs are automatically added to the learning pool from which Tymbals models are generated.

If you do not want your data added the data pool do not use Tymbals



Copyright 2021 Digital Partners Pty Limited. All Rights Reserved