You’re right – calculating marginal CPCs can be tricky. One option would be to adjust your keyword bids methodically, and take a note of click volumes. If enough data is collected for different CPC levels, you could have a fairly good understanding of the click volume at say $0.65, the click volume at $0.95 and the click volume at $1.15, and hence work out your marginal CPCs.

This obviously assumes that there are no external fluctuations in click costs (which of course there are – think seasonality, days of week, times of day, competition), so to improve accuracy you might want to take advantage of bid adjustments using Google’s ad scheduling. Set different hours in the day (and week) to as many different bid levels as you can (20%, 50%, 85%, 160% etc), then run an hourly report and plot your cost per click prices for each hour against your click volumes for that hour. This should reduce external bias and help improve the accuracy of your marginal CPC calculations considerably.

Another (quicker but less reliable) option is to use Google’s Bid Simulator to get an idea of how click volumes change as cost per click prices change, although I would tend to be very cautious using such data as its typically normalised across a large number of different advertisers.

Hope this helps!

Alan

I thought that this was an excellent demonstration of economic theory which has been apllied to PPC expertly.

I would like to take this a stage further and conduct your analysis with one of my clients.

My question to you is:

How do you accurately calculate the marginal CPC when you work out the figures for real as I am struggling.

Best,
Richard

@ Tom

You’re right – the model does become more practical and beneficial to both parties when targets are regularly set and long-term goals take priority over short-termism, although as you point out, this does require a open dialogue between client and agency and a clear understanding of the client’s long-term strategy.

Nice comment about low spend levels – there is definitely a minimum amount of effort required to build and maintain a successful PPC campaign, so a minimum spend will be needed to make it worthwhile for the agency.

@ Justin

Again, you’re right – performance metrics such as cost per sale and ROI definitely improve the percentage of spend model, since they encourage the agency to maximise the client’s sales subject to a profitable cost structure.

Any performance-related pricing model, however, requires a good understanding of marginal costs and revenue at different spend levels (in order to efficiently set targets), which is easier said than done – especially if the client is relatively new to online marketing and conversion performance data is scarce.

Interesting point too about the value of simplicity. Creating an intricate pricing model can be extremely time consuming, expensive and distracting for all concerned, so it may be in the client’s (and agency’s) best interests to go a simpler model, even if it means some loss in potential profit.

This works particularly well, and i think is a fair model as you mentioned in your post it sometimes does not accurately reflect the level of work required to achieve targets but over a longer working relationship period it evens out.

The other main option of charging a flat management fee per month is clearly suicide for the client; no incentive for the agency to do any better than hit a specific agreed CPS/ROI target and sit on that with minimal workload as there’s no incentive to do any better. The only way this would work is to add an override into the mix for performance over and above what is expected. THis can still lead to grey areas however.

Lastly, consider that the markup % of spend model is the same as most other media out there (TV, DM, Radio etc) and is something that can be easily understood by every client, budgeted for and fit into existing client finance models and payment terms.

I am completely with you in that the % spend model , when applied incorrectly (and often it is) is divisive and leads to the problems you’ve described.

There are instances, however when the model can work very well indeed – that is, when a client’s marketing goals are achivable within the threshold limits of the marginal CPC/RPC. In such cases both sides are equally incentivised to maxmise performance. The difficulty is, of course, calculating this tipping point – which can usually only arrived by through an open and clear communication between both parties. This is the problem many agencies/clients make – avoiding this step in the hope of ‘gaming’ the commercials for short-term profit maximisation. There then also needs to be a pre-determined negotiation point at which commercials are renegotiated, ensuring that interests are realigned.

Another consideration is that the %spend model does not work well when spend levels are so low as to not adequately reward an agency for working at developing a campaign.

Often this position can result in a impasse where both parties, influenced by short-termism, are unwilling to invest the time or money needed to that the required effort to the detriment of fulfilling the long-term potential of a campaign.

Keep the good stuff coming, Al!

T

Heck of an analysis.

Very thorough and well researched and I don’t mean to belittle it when I say that I can’t believe anyone pays to have someone else run a PPC Campaign for them.

I know this is mypotic and there are many business people with legit businesses that don’t know much of anything about the internet, or PPC, or web sites, or SEO or any of it.

I once had a Broker that paid huge bucks to a PPC reseller who did not much more than come up with all the main primary KWs and recommended he pay $5 a click.

Probably they were on the % of spend model. LOL!

Good work on this though. RM

Thanks for you comment!

You’re right – sometime maximizing volume becomes a larger priority for clients than maximizing profit, at least in the short-run, which can make analysis all the more complicated.

But I think in the long-run, assuming the client understands their cost and revenue structure accurately, and assuming it’s possible to accurately attribute all the revenue generated from paid search at every touch point (which are big assumptions), there will undoubtedly be a optimum point which would make the client the most profit, which will inevitably be at a lower click volume than the optimum point which will make the agency the most profit.

But you are right – adding growth as a business objective (rather than just profit maximization), as well as short and long-term motivations does complicate the model considerably.

@ George

You’re right – observed, or reported, revenue is generally a pessimistic measure of actual paid search revenue, which can make profit maximizing decisions extremely difficult.

Interesting point too about short and long-terms goals. Guess my analysis was based more on maximizing short-term profit, which as you point out, is often unrealistic for many businesses.

I think if the article had more of a long-term focus, we would see the point of ‘compromise’ closer to that of ‘maximum client profit’, as keeping existing clients happy will always be more profitable for the agency (and client) in the long-run.

Guess that’s the problem with economic modeling – over-simplify and it becomes unrealistic, over-complicate and you lose clarity. Glad you enjoyed it though!

I look forward to reading your posts.

I’d make three minor points based on our experiences at RKG:

First, there’s a distinction to be made between “observed revenue” and “actual revenue”. Because of cookie breakage (dropping cookies, which is rare, and shopping and buying on different machines, which is much more common), spillover to the call center, javascript blindness for those who rely on it, and the like, we often don’t see all the revenue driven. Driving to observed profit maximization may not maximize actual profits.

Second, immediate profit maximization isn’t always the best plan. Lifetime value considerations and even some “brand-building” thoughts make many of our clients believe that breakeven (observed, or even factoring in that tracking drop off) is the right target to maximize their long-term benefit. Short-term profit maximization can lead to a business death spiral over the long-term.

Third, we rarely find ourselves in the position of determining what the advertisers target should be. Sometimes they ask us to help them think through all this stuff, but oftentimes they know the metric they want us to hit, and we’re evaluated by how large we can grow the program within that target.

All that said, I think any pricing model can be gamed by agencies who put their short-term revenues first, and their clients interests second. We think the shrewd agency recognizes that pursuing the clients interests first and last is what builds a profitable business in the long run. Client churn is costly and requires huge marketing investments to continually replace the alienated. Not only does “doing right by your clients” allow you to sleep better at night, it turns out to be a good business decision as well.

Thanks for the call out! I love any blog post that uses graphs smartly and references marginal analysis!