Have you ever thought to yourself (or had a client say to you), if I triple my budget, I should see at least triple the results ... right?
Unfortunately NOT ... at least in most cases that have anything to do with search!
Plain and simple; any reputable search company will target the easiest and least expensive wins first where limited budgets are involved (or as I like to refer to it, the preverbial low hanging fruit). Let me explain using a very simple example.
Imagine you're a caveman or cavewomen, and you're obviously always hungry. You find an apple tree brimming with tasty ripe red apples.
Image courtesy: AmesWladorf
Where do you begin picking the apples from? Do you climb to the very top of the tree and risk life and limb, or do you first pick the apples that you can easily reach?
Obviously, you're going to pick those apples that require the least effort, and pose the least risk. This is the same fundamental principle as is followed by search experts, we start with the easiest wins first.
How many apples do you pick?
Essentially, what's your objective? Will 5 apples be enough? Will 10 apples be sufficient? Or do you require every single apple on the tree? This question becomes important because the more apples that are needed, the more risk, effort, and time that must go into picking those apples.
If you needed to pick only 10 apples, you'd likely pick 10 you could easily reach that are in close proximity to where you're standing.
Total time needed (eg) - 100 seconds or 10 seconds per apple
If you needed 20 apples, you'd need to pick 10 more in addition to the original 10. This would likely take slightly more time and now you'll have to move around a little. These next 10 apples may take 15 seconds per apple (150 seconds), versus only 100 seconds for the first 10.
If you needed 30 apples, you now might need to start climbing, which will take even more time, and increases the average time per apple picked. Beyond 30 apples, it takes progressively more time and effort for each additional 30 apples needed.
This is a well documented economic principle known as the "Law of Diminishing Returns". Essentially it means with the same levels of input (ie. time in our example), production or output progressively decreases. Consider picking the last 10 apples at the very top of the tree, and on branches that will not support the weight of a human or ladder. Those last 10 apples will require much more time and effort so the same 100 seconds of input would produce much less output (perhaps only 1 apple).
This is shown by the purple line in the graph above, while the green line shows the cummulative results/output. If results/output were constant (ie. 10 apples every 100 seconds), the green line would be straight across, and the purple line would be straight, though angled toward the upper right.
While simplified, this model precisely illustrates the challenge with scaling results from search. The more traffic and business that clients require, the more effort and work is required, and therefore the higher the cost per acquisition (CPA) or the lower the ROI (Return on Investment). Remember the CPA is relatively low (or ROI relatively high) for the initial 20 sales, but progressively increases (ROI decreases) as more and more sales are required.
In the instance of search (organic or paid), substitute keywords for apples. Some keywords are very uncompetitive and inexpensive to buy or achieve rankings for. However, the more results a client demands, the more expensive and competitive the keywords become, raising the overall average CPA.
So, the next time a client asks the question; why can't I triple my results by merely tripling my investment? Ask him if he's ever gone apple picking.
This is the first in a series of Monday posts called 'Search Economics', where I'll simplify stuffy economic prinicples into straight forward simple examples that relate to search in some way. Some of the other posts in the series will be:
1) Search Economics - The Concept of Arbitrage
2) Search Economics - Economies of Scale
3) Search Economics - Supply and Demand
4) Search Economics - Porter's Model
5) Search Economics - Maximizing Client Results