Here's why...
"RPC" stands for "Revenue Per Click" (i.e., Sales divided by Clicks) and the bidding methodology is quite simple:
๐ป๐๐๐๐๐ ๐ช๐ท๐ช = ๐น๐ท๐ช ร ๐ป๐๐๐๐๐ ๐จ๐ช๐ถ๐บ%
With this strategy we align our "Ad Cost" with our "Ad Sales" on a click-by-click basis, which ensures we hit our Target ACOS.
I don't care how good your "ranking" is or that you have "100% Top-of-Search Impression Share."
If you spend more than you make, you're going bankrupt.
The objective of RPC is to maximize ๐จ๐๐ก๐๐จ ๐ซ๐ค๐ก๐ช๐ข๐ within our pre-determined ACOS restraints. I'm also convinced that Total Product Sales & Total Keyword Conversions play a much larger role in Amazon's algorithm than just Top of Search placements.
You can still bid aggressively and rank with RPC. You only need to set a ๐ต๐ถ๐ด๐ต๐ฒ๐ฟ ๐ง๐ฎ๐ฟ๐ด๐ฒ๐ ๐๐๐ข๐ฆ for ranking keywords.
I disagree with those who try to rank by sending bids to Mars with absolutely no calculation.
Even with a ranking strategy, we should have SOME kind of Target ACOS. You can have 100% Target ACOS, sure, but there should be some level of efficiency.
Think of it this wayโฆ would you rather have:
Ten (10) orders @ 200% ACOS
Twenty (20) orders @ 100% ACOS?
Even with a โhigh ACOS ranking strategy,โ there are still ways to rank efficiently.
Using RPC in a ranking strategy with a defined ACOS target will stretch your budget further, net more sales, and rank more efficiently compared to just closing your eyes and hitting "apply" on a $10 bid (even my dog can do that).
I hear this all the time, and I used to think it was true -- until I learned from my mistakes.
There are two primary reasons why reducing bids will increase ACOS:
๐ฌ๐ผ๐ ๐น๐ผ๐๐ ๐ง๐ผ๐ฝ ๐ผ๐ณ ๐ฆ๐ฒ๐ฎ๐ฟ๐ฐ๐ต. If you only decrease your bids WITHOUT increasing campaign bidding adjustments for Top of Search, you will destroy your ads by forcing them to worse performing placements (e.g., Product Pages).
Combining Placement Bidding Adjustments with Keyword RPC Bidding solves this problem (later this week I'll make a whole post about Placement Bidding, so be sure to follow ).
๐ฌ๐ผ๐ ๐น๐ผ๐๐ ๐ฐ๐ผ๐ป๐๐ฒ๐ฟ๐๐ถ๐ป๐ด ๐๐ฒ๐ฎ๐ฟ๐ฐ๐ต ๐๐ฒ๐ฟ๐บ๐. This is likely to happen with broad/phrase/auto targeting. Maybe 90% of your sales were coming from a higher CPC search term while 90% of your spend was going to another lower CPC search term. When you reduced your bid, you effectively removed yourself from the better search term that was driving all the sales.
Proper keyword harvesting & negative keyword management solves this. RPC still king.
How do you calculate the bid for a new keyword?
This is where RPC thrives (and other methods fail).
Traditional methods say to start with Amazon's "Suggested Bid," or perhaps if you found the keyword in your search term reports, use the CPC of the converting search term.
A couple problems arise here:
๐๐บ๐ฎ๐๐ผ๐ป'๐ "๐ฆ๐๐ด๐ด๐ฒ๐๐๐ฒ๐ฑ ๐๐ถ๐ฑ" is based on auction market price, and rarely aligns with your business goals or individual product performance. I've seen some suggested bids that are WAY above what we can afford and would kill us if we went with them.
๐๐ผ๐ป๐๐ฒ๐ฟ๐๐ถ๐ป๐ด ๐ฆ๐ฒ๐ฎ๐ฟ๐ฐ๐ต ๐ง๐ฒ๐ฟ๐บ ๐๐ฃ๐ isn't good enough (at least not for me). Too many factors could set the CPC either too low or too high.
For example, I've had terms that randomly convert with $0.02 CPC (who knows how that happened, but I don't want my bid to be that low when our average is $1).
Sometimes a term converts with a $3 CPC but only has 1 click and 1 sale, so the ACOS seems good. However, if you actively bid with a CPC that's 3x above your average, you'll likely overshoot your Target ACOS by end of week.
One final example:
What if the search term has 5 orders but the ACOS is too high?
Some people negate those converting search terms (missed sales opportunity) while others harvest the keyword with the same CPC (leading to higher ACOS and inefficient spend).
It's simple:
If there's enough data on a search term (i.e., at least 1 order and a good amount of clicks), we use RPC to harvest the keyword with an efficient bid.
If there's ๐ฏ๐ฐ๐ต enough data (e.g., brand new keyword with no history), we can use "Anticipated RPC."
Anticipated RPC is calculating how many sales your product generates per click by looking at Average Order Value and Conversion Rate. It goes like this:
๐๐ง๐ญ๐ข๐๐ข๐ฉ๐๐ญ๐๐ ๐๐๐ = ๐๐๐ ร ๐๐๐%
For example, if you have a product that sells for $10 and has a Conversion Rate of 10%, then $10 * 10% = $๐ญ ๐ฅ๐ฒ๐๐ฒ๐ป๐๐ฒ ๐ฃ๐ฒ๐ฟ ๐๐น๐ถ๐ฐ๐ธ.
This can be our starting bid for any new keywords which have no historical data. If the keyword performs similar to our average, it will hit the Target ACOS on the day it gets its first order.
But what if that keyword doesn't convert?
You might be asking, "Stephen, how can this strategy work when the keyword has ๐๐ ๐๐๐๐๐๐๐??"
We have a simple, yet creative solution for that
We once again use the ๐๐ป๐๐ถ๐ฐ๐ถ๐ฝ๐ฎ๐๐ฒ๐ฑ ๐ฅ๐ฃ๐, but this time we add an additional variable to the equation: current keyword clicks.
It's beautifully simple how it works -- with ๐ฒ๐ฎ๐ฐ๐ต ๐ฎ๐ฑ๐ฑ๐ถ๐๐ถ๐ผ๐ป๐ฎ๐น ๐ป๐ผ๐ป-๐ฐ๐ผ๐ป๐๐ฒ๐ฟ๐๐ถ๐ป๐ด ๐ฐ๐น๐ถ๐ฐ๐ธ, we reduce the Anticipated RPC. This allows us to "step down" our bids incrementally without archiving/negating the keyword outright.
Why is that better?
Because it still gives the keyword the OPPORTUNITY to convert without the fear of overspending.
This method is superior to instant negation because oftentimes the "high spend, non-converting" keywords are relevant, only the spend is too high because the CPC is too high.
So here's what the logic looks like:
๐๐๐ซ๐ ๐๐ญ ๐๐๐ = ๐๐๐ / (๐๐๐ฒ๐ฐ๐จ๐ซ๐ ๐๐ฅ๐ข๐๐ค๐ฌ + (๐/๐๐๐)) ร ๐๐๐ซ๐ ๐๐ญ ๐๐๐๐
Now that's a lot of PEMDAS, so let's break it down.
The major change here is that instead of multiplying by conversion rate, we divide by the inverse of CVR (i.e., 1/CVR). We do this to find our "average clicks-to-conversion," which I abbreviate as "aCTC." This is how many clicks it takes on average to get a sale.
We then add the current amount of non-converting clicks.
As the total number of non-converting clicks increases, our ๐๐ป๐๐ถ๐ฐ๐ถ๐ฝ๐ฎ๐๐ฒ๐ฑ ๐ฅ๐ฃ๐ ๐ด๐ผ๐ฒ๐ ๐ฑ๐ผ๐๐ป, and so our bids are reduced in a step-down manner. The bids continue to be reduced until either one of the following happens:
The keyword converts at the right CPC and hits the Target ACOS
The bid drops so low that the keyword loses visibility and is effectively paused
In this way, we can slowly phase out an underperforming keyword while still giving it the chance to win a sale. I find this method to be far superior to the traditional "decrease by X%" method (where the "X" is an arbitrary value).
I hope you're beginning to see the power of RPC.
It's the most logically sound, mathematically-based method I have found for managing investment levels, ranking, and profitability.