The ultimate metric on which to to base decisions regarding the redistribution of your advertising budget is Return-On-Ad-Spend, or ROAS, which necessitates the activation of conversion tracking and the input of conversion values. However, a recent survey by a leading PPC agency found that approximately 50% of SMB advertisers were not tracking their conversions. What’s even more striking, the lion’s share of account holders who did activate conversion tracking set their conversion value to $1 which is the default setting in Google AdWords. Such wrong entries result in the wrong ROAS values which in turn may lead to the wrong decisions and harm your bottom line.   

Below, we would like to illustrate by means of a simple numerical example, the importance of setting the right conversion values versus failing to specify them or posting the wrong ones. Our PPC hero is a plumber who created 2 accounts to market his services. His Google account is geo-targeted at a suburban residential area while his Yahoo account is aimed at a newly built housing estate. A conversion, or order, through the Google account brings him $250 in profits while through Yahoo only $80. These numbers represent his corresponding conversion values. His advertising budget is approximately $100 per week. 

The rows in the below table are colored in red, blue or green. The colors symbolize 3 basic scenarios: he initially set the wrong data (red), set no data (blue), or set the right data (green), relative to his corresponding conversion values.

Legend:   the wrong entries, missing entries, the right entries

In the above table, performance numbers are in normal font while input data is in bold and calculated values in italics. The columns are as follows: Account, Clicks, Average CPC, Number of Conversions, Conversion Value, Total Value of Conversions (Number of Conversions * Conversion Value), and ROAS.

Above the partition line (xxx…) are the “past” week’s data and beneath it the “next” week’s values. The partition line itself symbolizes the process of decision making.

Below the partition line, we entered the right conversion values for each color, so that the profitability of the decision could be measured. “Next” week’s data are calculated based on the reasonable working assumption that CTR as well as Conversion Rate remain unchanged and the weekly budget can be depleted.  

RED SCENARIO: The lowest red row is the result of the decision that the advertiser redistributed all its funds to Yahoo since after the first week the red Yahoo ROAS seemed to be the higher one. (0.17)

BLUE SCENARIO: The upper 2 blue rows are incomplete because this is the scenario in which the advertiser did not post his conversion values, as a result of which the Total and ROAS columns could not be calculated. Accordingly, no decision was made after the first week. Hence advertising went on as in the first week, just that we collapsed the 2 accounts into one G+Y row.

GREEN SCENARIO: The lowest green row is a result of the decision that the advertiser redistributed all his funds to Google since after the first week the green Google ROAS was the higher one (35.71).

FINDING: If the neutral “blue” scenario (G+Y) is taken as the basis for comparison, you may conclude that the wrong “red” decision resulted in a very huge 54% drop in ROAS while the right “green” one in a 19% increase.

CONCLUSION: All in all, if you fail to specify your conversion value you will probably miss out on improvements, while entering unrealistic data may lead to conclusions causing huge losses. Well, have you ever thought of setting your conversion value?

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