Anyone who has recently been involved with any form of Google Ads activity will probably be sick of hearing all about smart bidding, and little robots coming to steal your job. On the face of it, smart bidding is a fairly terrifying prospect for seasoned PPC’ers, a bid that is fully controlled by an unseen algorithm. On paper a recent grad with the ability to google can set-up a smart bidding strategy and potentially get better results than his seniors who’ve been sweating over gigs of data. The jury is still out on smart bidding as a whole, here at Katté & Co. it has at times delivered sheer brilliance in terms of results; at others pure frustration and angry phone calls. However, this is not a piece on Smart Bidding, rather a piece on how we can Bid Smarter; looking at some common errors and oversights displayed by those new and old to the industry.

Error #1 Ignoring KPIs

This point may be contentious; but CTR FOR ADS DOES NOT MATTER.

There, I said it…

Now before you burn me at the stake consider this, you have an A/B test for a client who’s KPI is CPA. You have two Ad Sets and write up a long self-promoting email on how ad set 1 has a much better CTR and therefore has the best messaging to use going forward. But wait a minute… did you review CPA? The point being that there are numerous scenarios where CTR does not lead to better CPA (why would it?). Say for example you have an ad made up of multiple call to actions vs. an informative ad that has product price, description and delivery price. About 90% of the time your descriptive ad will have a lower CTR; why? Because it pre-qualifies users by giving them a preview of what the page contains. Why is this a good thing? Because pre-qualified users are more likely to convert after clicking, this means less wasted spend on users who bounce off, better efficiency and (hopefully) happier clients. Ditch the CTR analysis unless you are working on a brand awareness piece, stick to the KPIs.

Error #2 Ignoring Significance

We (the industry as a whole) seem to be pretty terrible at considering statistics. Which is a bit frightening when in reality it should underpin every optimisation that we do. There are numerous complex schemas you could go into to help analyse performance but the most common error by far is ignoring significance. What is significance (oh dear) you ask? Essentially significance means something didn’t happen by chance. In PPC significance is often forgotten, with demographics/audiences etc. being proclaimed as best performers whilst only generating a handful of conversions. The issue with this is that a couple of conversions can change whether the dimension you are looking at is good or bad, these can be due to chance and not the actual impact said dimensions are having on your traffic. Google significance tests, put in numbers, and optimise properly.

Error #3 ‘Dumb’ Bid Changes

This is a scenario that everyone is often all too guilty of, you have an account which needs to spend more, you’ve filtered for your best performing keywords, you’ve stuck your pinky in the air, and increased bids for these keywords by 20%. Yes you’ve pushed well performing keywords, but this is a dumb change, what will new CPCs be? Did you push enough/not enough? Will some keywords now be inefficient? There is rudimentary fix for this. In general most clients have either a ROAS or CPA target. There is a very simple formula for working out target CPC for both:

CPA:
Target CPC = CVR * Target CPA

ROAS:
Target CPC = (Revenue/Click)/Target ROAS

With the above information in hand (you can even add them as custom columns in Google Ads!), it is a fairly straightforward task to apply a few simple formula in your spreadsheet software of choice to work out the difference between your current CPC’s and those that you should target in order to make more representative bid changes. This method is not foolproof, and generally assumes that CVR will not change despite your search/shopping bid (test it, it generally doesn’t); however it easily beats the method of changing bids in bulk with no consideration for more granular performance differences.

 

Hopefully the above insights into some common optimisation errors are of use, and give you some insight in how to bid and optimise smarter. Any super common errors you think we missed or errors more heinous (gasp) then the ones above? Let us know!