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Conversion Rate Optimization In Paid Search: Why Click Through Rate Matters

One might find it strange to talk about click-through rate (CTR) optimization when talking about conversion rate optimization, since these indicators do not initially seem related. Yet, while these metrics are not always correlated, they sometimes – and actually often – are.

However, a high click-through rate does not assure a high conversion rate. The two can even have an inverse relationship: an ad copy geared towards curiosity clicks will result in fewer conversions, percentage-wise, than an ad copy geared towards qualified clicks.

Keeping An Eye On CTR Helps Maintain Conversion Volume

Focusing on conversion rate optimization and neglecting CTR will keep you from scaling up your paid search program. You need to maintain a high traffic volume to maximize the number of conversion opportunities. If you don’t do so, you’ll end up with great conversion rates but low conversion volume overall.

A better way to go about it is to maximize the conversion rate within a certain CTR range, thereby keeping a good rank at a decent cost per click and maintaining traffic volume.

Even excluding the effect of CTR on Quality Score (and thus CPC), it is important to find the right balance between an appealing ad copy which generates lots of clicks, and a more conversion-oriented ad copy which generates fewer clicks at a higher conversion rate. The Quality Score factor makes it even more important to optimize the CTR as it helps mitigate the average cost per click and lowers the cost per acquisition (CPA) as a result.

The best performing ad copies are rarely those with the highest CTR or the highest conversion rates, but typically somewhere in the middle for both metrics. They are appealing without being deceptive or too generic. Best-performing ad copies usually have a strong CTR and an ok conversion rate – as opposed to an ok CTR and a strong conversion rate – because of the Quality Score factor and its consequences on CPC.

Beyond CTR & Conversion Rate: Maximizing Profit Margin

In the following chart (inspired from actual data) ad #1 has the lowest CTR and the highest conversion rate, while ad #10 has the highest CTR and the lowest conversion rate. Again, these metrics do not always have an inverse relationship, but it is the case very often.

If you are still unconvinced, you can give it a try for yourself with two ads in rotation – the first one clearly geared towards curiosity clicks, the second one clearly geared towards qualified clicks – and this logic should be verified.To get back to our sample data below, it is worth noting that neither ads #1 nor #10 are the best-performing ones overall.

If you look at the conversion volume, ad #6 is doing the best without having the strongest CTR, nor the strongest conversion rate.

If you look at the CPA, ad #8 has the lowest CPA. Ultimately, ad #6 performs best with respect to the effective profit margin.

In a nutshell, one should keep an eye on the CTR when testing ad copies in order to maintain decent traffic volume and maximize overall profit margin. The right balance might take time to find, but the important thing to keep in mind is that the best ads in terms of CTR or conversion rate are most likely not the best-performing ads out there. There is a middle ground where profit margin can be maximized.

Also, while Quality Score is only available at the keyword level (and unfortunately not at the ad level) it does make sense to monitor this metric when testing multiple ad copies geared toward qualified clicks rather than curiosity clicks.

Google engineers designed their paid search algorithm in such a way that the inverse relationship between CTR and CPC forces search marketers into coming up with ads which don’t necessarily generate the most revenue per visit, but the most clicks. It is mostly about relevance to the end users, Google says – where relevance is defined based on clicks, whatever their engagement level is.

Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.

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