Budgets, Testing and Scaling for Black Friday – The BPM Method Mastermind Q&A Session


In a recent Q&A video call with The BPM Method clients, we had an an interesting discussion about avatars and scaling for Black Friday. Here are some questions from that session. 

Questions from this session: 

1.Is there a “good” percentage range that we should be working within for scaling up that doesn’t affect the algorithms but also doesn’t impact negatively on ROAS?

  • When scaling ads and not wanting to affect the algorithm, go for a 20-30% increase in budget per day. Beyond that, it can disrupt performance.   
  • Put the additional budget in the campaign level (using CBO) to spread that budget out between multiple ad sets and multiple ads.
  • You can scale more aggressively during times like Black Friday but this is an advanced strategy that carries high risk.

2.Do you retest avatars that have failed in the past when approaching a new advertising channel? Or use ones that have worked? We’re bootstrapped. 

  • For a bootstrapped business, every dollar matters. Take which avatar worked and test it in other platform/channels. Don’t over think it in terms of *having* to test everything. It’s about finding something that works, fast, and scaling it. 
  • Yes you’ll need back ups (ads, audiences, offers) but traction is more important than anything at the early stages.
  • Don’t forget that Black Friday is a buying frenzy period so act fast!

3. It seems using The Graduation Framework (from The BPM Method) on an unproven audience/ad costs upfront before getting something that works. How can I best use this spend?

  • Follow the phases below as you ask questions of the data. Yes it will cost to test and learn but The Graduation Testing Framework is designed with efficiency in mind – test fast, fail fast, learn fast.

                   Phase 1: Does the audience work?

                   Phase 2: Does the creative or messaging work?

                   Phase 3: Push more spend into what’s working!(I don’t spend too much on audiences/ads that haven’t been tested and shown to be working.)

Anything else you’d add to this?

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