"Not a single conversion ..." or tips on analyzing large contextual campaigns
Recently, we quite often come across an analysis of the effectiveness of contextual advertising of large online stores with many product categories. This post is devoted to only two simple tips that will help to more accurately assess the effectiveness of each contextual advertising campaign for such cases.
1. It is common for some contextual advertising specialists to compare the effectiveness of advertising for each product group according to its general indicators. For example, the now-loved conversion rate for this is used very often, a bit less often a comparison occurs at a price per goal (or purchase). In this case, in the reports there are conclusions of this type: “Conversion of campaign A 0.5%, the price for achieving the goal is 100 rubles; campaign conversion B 1%, the price for achieving the goal is 30 rubles. We recommend lowering the cost per click in Campaign A, and using the released budget in Campaign B. ” The conclusion is quite clear and, in general, correct. That's just what if campaign A advertises the sale of yachts, and campaign B - oars for inflatable boats? Products are in completely different price categories and in no case can they be compared in terms of conversion rates and price for achieving the goal.
An example, of course, is greatly exaggerated, but this does not change the essence. If several product groups are advertised, it is necessary for each of them to calculate the optimal price that you are willing to spend on attracting one buyer in this product category. For yachts, this price will of course be high, and for oars low. Further, these prices should be considered along with the results of the campaign and, based on the deviation of the desired price for the client from the real one, to draw conclusions about the redistribution of budgets between the campaigns and the change in CPCs.
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2. The second tip is also related to the characteristics of the product groups themselves. It is well known that different products have a different sales cycle. Therefore, for example, they buy cell phones quickly enough - if the price and delivery methods are arranged, and jewelry is often bought after consulting with the wife, friends of the wife or someone else. In the end, there is no difference for the store to buy now or a day later, but for the source of the conversion, the difference can be significant. A visitor can come to the site again to complete the purchase in any way convenient to him - from the browser bookmark, by searching for the store name, through the browser's address bar. At the same time, in reality, the “merit” of this sale can be attributed to the initial entrance to the site, which could occur, in particular, due to contextual advertising.
Thus, when comparing conversions and prices for achieving the goal of campaigns of various products (even if they are from the same price category), it is necessary to take into account products with “pent-up demand”, the indicators of which may be significantly worse than the rest. For this, the tool of multichannel sequences in Google Analytics, about which we have already written earlier, is perfect.
Consider an example:
In the “Associated Conversions” report, we reviewed the contextual advertising indicators in the context of campaigns. It is clearly seen that for the “Products for Children” category, the ratio of associated conversions to conversions by the last click is very different from the average. This means that it is for this group of products that the purchase after the return to the site is more characteristic. This may be the reason for the low conversion rate of this campaign, although in reality, in addition to the conversion on the last click, it led to significantly more associated conversions than other campaigns. This means that the effectiveness of this campaign is higher than what its conversion rate shows us.
1. It is common for some contextual advertising specialists to compare the effectiveness of advertising for each product group according to its general indicators. For example, the now-loved conversion rate for this is used very often, a bit less often a comparison occurs at a price per goal (or purchase). In this case, in the reports there are conclusions of this type: “Conversion of campaign A 0.5%, the price for achieving the goal is 100 rubles; campaign conversion B 1%, the price for achieving the goal is 30 rubles. We recommend lowering the cost per click in Campaign A, and using the released budget in Campaign B. ” The conclusion is quite clear and, in general, correct. That's just what if campaign A advertises the sale of yachts, and campaign B - oars for inflatable boats? Products are in completely different price categories and in no case can they be compared in terms of conversion rates and price for achieving the goal.
An example, of course, is greatly exaggerated, but this does not change the essence. If several product groups are advertised, it is necessary for each of them to calculate the optimal price that you are willing to spend on attracting one buyer in this product category. For yachts, this price will of course be high, and for oars low. Further, these prices should be considered along with the results of the campaign and, based on the deviation of the desired price for the client from the real one, to draw conclusions about the redistribution of budgets between the campaigns and the change in CPCs.
')
2. The second tip is also related to the characteristics of the product groups themselves. It is well known that different products have a different sales cycle. Therefore, for example, they buy cell phones quickly enough - if the price and delivery methods are arranged, and jewelry is often bought after consulting with the wife, friends of the wife or someone else. In the end, there is no difference for the store to buy now or a day later, but for the source of the conversion, the difference can be significant. A visitor can come to the site again to complete the purchase in any way convenient to him - from the browser bookmark, by searching for the store name, through the browser's address bar. At the same time, in reality, the “merit” of this sale can be attributed to the initial entrance to the site, which could occur, in particular, due to contextual advertising.
Thus, when comparing conversions and prices for achieving the goal of campaigns of various products (even if they are from the same price category), it is necessary to take into account products with “pent-up demand”, the indicators of which may be significantly worse than the rest. For this, the tool of multichannel sequences in Google Analytics, about which we have already written earlier, is perfect.
Consider an example:
In the “Associated Conversions” report, we reviewed the contextual advertising indicators in the context of campaigns. It is clearly seen that for the “Products for Children” category, the ratio of associated conversions to conversions by the last click is very different from the average. This means that it is for this group of products that the purchase after the return to the site is more characteristic. This may be the reason for the low conversion rate of this campaign, although in reality, in addition to the conversion on the last click, it led to significantly more associated conversions than other campaigns. This means that the effectiveness of this campaign is higher than what its conversion rate shows us.
Source: https://habr.com/ru/post/135940/
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