Paid Search Forecasting - How to arrive at a reasonable estimate?

Paid Search Forecasting comes into the picture on different occasions. When a prospective client comes up and asks you what kind of results you can produce given the ad spend or you might also be asked what kind of ad spend do you require to produce the results that the client expects.

Well you need you consider several aspects before you answer that question. At the very basic you need to need know the conversion rate (how many sales/leads they get per 100 visitors) and the cost per acquisition (how much they can spend to acquire one sale/lead). Effectively with this two numbers you can find out how much you can afford to spend per click. Also where available you would consider historic data, performance of other channels and overall ad spend limitations to arrive at a reasonable forecast.

The second scenario where forecasting comes into picture, typically happens when the client wants to either increase or decrease the ad spend and arrive at an optimum spend level. This is even more complicated than the first scenario because lot more parameters come into the picture like Ad Position, CTR, CPC, Keyword Set, Conversion Rate and you need to several combination of these parameters to arrive at a reasonable forecast. This is more of trial and error process which I am not going to go into right now.

However if you are looking to do a forecasting at the macro level, looks like the square root rule might help. While this method has its own pitfall, try it out for yourself if this is something that works for you. If you do not want to do all the work to figure out the square root rule, go get this free plug and play with your numbers spreadsheet.

And if you aren’t still satisfied with your forecasts and you are someone working on your forecasts weekly or monthly, here is an alternative. You might want to try the 7 day or 30 day exponential moving average, which might give you a reasonably close forecast.

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