How to Scale from $0 to $3k/day

How to Scale

  1. Track the net profit (royalties – ad spend) of the series you’re advertising daily or weekly (tracking template + walkthough:
  2. Calculate your revenue per sale (sellthrough) and revenue per borrow (readthrough) for the series.
  3. The Amazon Ads automatically report sales and page reads; for non-Amazon Ads (e.g., Facebook Ads) use individual attribution links for each ad to track the sales and page reads (Amazon Attribution walkthrough:
  4. Use cost per unit (cost per unit = CPC / conversion) to analyze whether your ads are working by comparing the cost per unit to your revenue per sale and revenue per borrow. What’s working is dependent on your strategy (whether you’re running the ads as a loss leader, at breakeven, or aiming for direct profitability). Focus more of your ad spend on the ads / Amazon Ad targets that have the best cost per unit. Turn off ads / targets that aren’t effective. (How to Analyze Your Ads’ Profitability class:
    • You can analyze the cost per unit weekly when you do your net profit tracking (item #1 on this list), or you can do this analysis when you’re adding / refining new keywords + targets (Amazon Ads) / testing new ads (Facebook Ads).
    • Note: Instead of cost per unit, I generally use revenue and profit per click to analyze the Amazon Ads’ profitability, since this allows me to dial in specific bids for each keyword, ASIN, etc. This is covered in detail in Scaling Mastery Pro.
  5. Focus on one ad platform at a time to get good. It generally takes a year to get good at using an ad platform if you’re learning them one at a time. Then you can add the other one in.
    • Test 40 Facebook Ads a month for a year. Test each ad for 30 – 100 clicks to get enough data to analyze what’s working (make sure you use attribution links). You can set a rule to automatically turn off the ads after they hit a certain click threshold. You’ll be good at Facebook Ads in a year.
      • This will cost $400 – $1200/mo (at a cost of $0.30 per click).
    • Test 50 – 100 Amazon Ad keywords or ASINs a month for a year. Get 20 – 30+ clicks on each keyword or ASIN to gather enough data to see what’s working. These clicks don’t all have to be in the same month; they can accumulate over time. You’ll be good at Amazon Ads in a year.
      • This will cost $1000 – $3000/mo (at a cost of $1 per click).
    • You can add new keywords / targets or new creatives once a week (e.g., 10 new creatives/wk on Facebook, 12 – 25 new keywords/wk on Amazon).
    • Scale back the number of ads / keywords you’re testing each month if your ad budget is smaller. Then scale up the budget gradually by reinvesting some of your profits as you find winners. Don’t scale back the number of clicks; unreliable data is not useful, either for analysis or for learning.
  6. For backlist, scale up vertically until you hit the equilibrium point, which is where additional ad dollars reduce your overall profitability. This tends to be around $50 – $100 for most series that work with ads. Most books don’t work with ads, however. And some can be scaled to $200, $300, or even $500+/day.
    • Equilibrium point example: at $100 in ad spend you might be making $50 profit, then at $125, you’re making $40. So $100 would be the equilibrium point here; you’d scale back the spend to this number and wouldn’t push things further.
  7. Then you can scale horizontally to other ad platforms, series, and regions to continue increasing spend.
  8. For launches / situations where you’re getting algorithmic visibility, then you have an x-factor in the algos that can massively amplify the effectiveness of your ad dollars. If you’re seeing a lot more net profit then you’d expect based on your profitability analysis (watch the class listed under #4 for more details), then you can potentially scale more aggressively than what the analysis would suggest in a backlist scenario (where you were getting minimal or no algorithmic help).

That’s it. This is a constant game of tracking and testing, with the goal of, over time, investing more of your ad dollars in your winners and less in your losers.