“When a measure becomes a target, it ceases to be a good measure.”

So states Goodhart’s Law. A wise warning about unintended consequences and the dangers of a narrow focus on optimising for a particular metric.

In our metric-rich world of PPC, there are plenty of these dangers lying in wait.

Here are four examples – from the most straightforward, to the least intuitive…

CPC

CPC looks like a reasonable-enough KPI.

  • Pay less per click…
  • Bring in more clicks for the same cost…
  • Generate more conversions for the same cost…
  • Win!

All things being equal, this makes perfect sense.

The trouble is, all things aren’t equal.

There is a reason why some auctions are more expensive than others.  It’s because higher-cost clicks are often higher-value clicks.

Low-quality inventory, such as Search Partners traffic and much of the Display Network, is often the cheapest.

Even within a particular keyword, the lowest-cost clicks don’t tend to be the most desirable (a serious issue for the Maximise Clicks Strategy…) because some of the eligible search terms will be more valuable (hence more hotly-contested, hence more expensive) than others…

Then within the set of auctions on a given search term, some devices / audiences / locations etc are more valuable than others… and so it goes on.

The quality vs cost balance can be favourable at any CPC… Sometimes it’s easier to find your way into the black with high CPCs; sometimes with low.

This is the problem with a focus on keeping CPCs low. It stems from a desire for cost-effectiveness, but limits the scope for it.

In this chart, if we stipulate that CPCs must stay under $2, we are no longer able to access much of the profitable zone

Impression Share

Impression Share metrics give a unique window onto unused potential

This is indispensable when you want to know how much more volume you could achieve either by raising budgets, or by bidding more aggressively.

But it is easy to overlook the limitations of what, exactly, Impression Share is evaluating.

I.S. is only interested in your precise, current setup.

It does a great job of taking into account your keyword selection (including negatives)… Audience and location targeting / device exclusions…

And in doing so, all of the results it shows have to come with the big, unspoken caveat, 

“This is how you are doing vs your potential, assuming you don’t make any significant changes” 

As soon as you alter your targeting, add any keywords, remove any exclusions etc… That ‘potential’ changes.

Another way of putting this, is that Impression Share is one of those fractional metrics that can easily give misleading results based on the denominator…

Impression Share = Impressions/Potential Impressions

Both ‘impressions’ and ‘potential impressions’ are apt to change, and both have an equal say in the output metric.

e.g.

• Campaign X has an unnecessary exclusion on all mobile traffic, and achieves 40% of potential impressions.

• We re-enable mobile traffic. Its impression count rises… but its potential impression count rises by a higher proportion.

Campaign X now achieves only 30% Impression Share, after we have expanded its scope and successfully increased its impression count.

This makes perfectly good sense within the logic of the metric, but not for the use of Impression Share as a target…. Because the target is a moving one.

CTR

We enter more controversial territory here, because a high CTR has real, direct benefits, not just from additional clicks, but also in Ad Rank, and therefore CPC.

So we generally want our ads to achieve a high CTR, for good reasons.

The counterpoint is that making an ad more widely appealing tends to improve its CTR, and in attracting those additional (less ‘filtered’ clicks) decreases conversion rate.

Hence you will often see lower conversion rate in conjunction with higher CTR. (Not always of course… but it’s a common pattern:

One way in which this dilemma crops up is with the decision over whether to include the price in an ad.

By showing the price, you (disproportionately) reduce clicks from users who a) don’t want to spend as much as you charge, and b) are looking for informational content rather than a commercial site.

So a lower proportion of people will remain willing to click on your ad (CTR down) but a higher proportion of those who are still willing to click, should be convertible (conversion rate up).

Conversion Rate

Hang on… Didn’t we just use conversion rate as the obvious ‘good’ that can get lost in pursuit of CTR?

Of course, conversion rate matters.

But there are times when a higher conversion rate not only stops being a worthy KPI but, conversely, starts pointing towards wasted spend.

These cases are important to spot, and to act on.

This is not a rare issue, but the clearest example I’ve seen was from a smaller advertiser, in the commercial cleaning space.

Along with high-quality leads, we were seeing quite a few enquiries from prospective cleaners.

There is a certain amount of filtering we can do with keyword selection, negatives, ad text and so on, but some traffic – and enquiries – from the ‘wrong’ kinds of user will always slip through. Too much, in this case.

By paying attention to the data over time, we learnt that a far higher proportion of the irrelevant enquiries were coming from mobile than desktop… so the higher conversion rate we were seeing on mobile was not the usual indicator of better performance.

(In practice, lead generation campaigns often see lower-quality enquiries – with a higher proportion of employment seekers – among the 18-24 band, so this is a good first place to look for ‘dud conversions’ in your campaigns.)

Ideally what we count as a conversion really is the desired outcome… but in practice (and especially in lead gen) there is usually some gap between the two. Finding and understanding those gaps gives you a powerful new lever.

So be prepared to review the meaning of conversions, conversion rates, and CPAs when you can pinpoint segments of traffic that tend towards driving unwanted conversions.

And then close that gap! 

Importing genuine leads is a technical step worth taking to help address this issue.

We also now have Conversion Value Rules for cases like the one above, which allow us to downweight or upweight the value of conversions coming from a particular device category, audience or location.

More intricate moulding of conversion value is also possible… 

But whatever we do to solidify our metrics, remember that they are always signposts rather than destinations. 

Optimising for any single metric will always come at a cost, and that cost will be less visible the more narrow our focus. 

Within reason, we like to be led by data in digital marketing… Just be sure that we’re never led blindly!

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