Our approach.

Creating a view of the target audience 

The content strategy began with empathizing with the target audience. We needed to ask the right questions and built a view of the customer demographics and psychographics (what they might be in to). We built customer avatars (or personas) upon these initial hypotheses.  

Crafting scripts that effectively speak to that audience 

Firstly, successful paid ads on TikTok look and feel native to the platform, we achieved this by sourcing and directing UGC-style creators. And secondly, ads that perform well are crafted with the following formula:   

Hook > pain point > product > call to action.  

All within 15-30 seconds max. 

We aimed to identify the strongest motivation for downloading a sleeping app. We wrote targeted hooks addressing each pain point and ran distinct ads during different time frames.  

We then tested those hooks (including those which worked well for competitors), to see which resonated best, and naturally, quickly offering the product as the solution. The Simba sleep app would help users get the perfect night’s sleep through scientific education, and encouragement of healthy sleeping habits. 

The results so far

The tests identified a winning formula reflected in the CPI, with the top-performing ad content encouraging organic engagement via likes and comments, bolstering the ads performance.  

As we closed in our winning formula, we saw a 69% decrease in our average CPIs from December to April. And our top performing ad ran at a very comfortable cost per install of £1.17.  

Figures aside, the real success in the engagement lay in helping the client understand their target audience and inform their product strategy with an abundance of opportunities to utilize those findings well into the future.  

Of course, we don’t stop optimizing once we understand our winning formula. Our strategy continued with two objectives: To simultaneously sharpen the best performing ads via A/B testing with isolated changes to drive the best possible CPI, whilst, continuously testing new hypothesis, features, and USPs, so Simba Sleep could learn as much as possible about what attracts users to their app—whilst maintaining favourable costs.