How to deal with this?

[sumaiyakhatun26]

The easier it is for the algorithm to learn who is the ideal target group to whom the next ads should be displayed. However, if this scale is lacking, the algorithm fails. And it can be avoided, especially in the case of small businesses.


Up until now, we have been solving this issue using manual control. We have been closely watching every złoty, selecting target groups very carefully and implementing changes just as quickly. And we have learned something from this. However, if marketing and sales automation in the form in which it is to be introduced really does come fully, it may turn out to be very problematic.

These are of course my assumptions, I am not the person responsible for the Google Performance Max algorithm or the Facebook and Instagram algorithms. However, I can tell you about it based on my experience working with various external tools.

There are many external tools that are created to help large advertisers get more out of china rcs data paid ads. For example, on Facebook or Instagram for online stores.

And I often hear the question from smaller or start-up stores whether they should invest in such tools to gain an advantage over other advertisers.

What do I answer then?

As someone who has tested many such tools – on a smaller and larger scale – I always say no. These tools help a lot, but only when they have a lot of data at the starting point. For example, information about hundreds of purchases per week, and not individual purchases per week or month, as is the case with start-up stores.

Without data, the algorithm that governs an external tool cannot help us. The question is, will the algorithm of Facebook, Instagram or Google fall into a similar trap?

I don't know. I do have some concerns, though, and I'd like to express them. I hope they turn out to be wrong in the end, but for now, everything I see makes me full of these concerns.