PPC Campaigns Ad Text Ranking vs CTR

Transcription

1 PPC Campaigns Ad Text Ranking vs CTR The analysis of ad texts efficiency in PPC campaigns executed by Sembox agency. Lodz, Poland; July 2010 r.

2 Content Main Conclusions... 3 About Sembox... 6 The relation between ad text ranking and CTR... 7 How is CTR affected by ad text ranking? What CTR can the ad text achieve?... 13

3 Main Conclusions This document presents conclusions made while analyzing the performance of ad texts used in PPC campaigns of Sembox Clients. In particular, the correlation between ad text ranking and CTR was a subject of detailed analysis, with the other campaign settings remaining unchanged. The detailed information on research methodology is included at the end of this document. The key conclusions of this research are: There is a significant correlation between CTR and ad text ranking of the particular ad text the average CTR at 11 th spot is ca. 1% and increases to achieve a CTR of 8% at the top place. The performance of the ad text at spots 7-9 is very similar (1,5 2,2%). It is probably due to relatively low exposure of the ad among other ad texts being presented at the same time. The performance of the ad text at spots 1-6 depends strongly on ad text ranking and we can see a significant (from 0,5% up to 2,5%) improvement between following spots of the ad text. Pic.1. The correlation between average CTR and ad text ranking.

4 For a sample of ad texts meeting the qualitative criteria there was a more detailed research done and the conclusions were the following: The ad text shift from 11 th1 to 10 th spot (bar no. 10 at the chart below) brings the relative drop of CTR by 6,5% - it is probably connected with moving the ad text from the last (utmost) spot to a middle one which is simply less exposed. The ad text shift at 8 th and 9 th spot (ie. from 9 th to 8 th and from 10 th to 9 th ) brings insignificant changes in CTR because of reasons provided at the previous page. The ad text shift in spot range of 3-7 (ie. from 4 th to 3 rd, from 5 th to 4 th, etc.) brings a substantial difference in CTR on average by 33-39% which means that it may be reasonable to obtain the highest possible ad text ranking in this range that will result in a larger volume of clicks (visits) at the campaign landing page. The ad text shift from 3 rd to 2 nd spot and from 2 nd to 1 st spot (bars no. 2 & 1 at the chart below) results in insignificant change in CTR 17,3% and 8,2% accordingly which proves a comparable exposure of ad texts at top spots. Pic.2. The relative % change of CTR between adjoining spots of the same ad text. 1 The analysis took into consideration ad texts distributed both above and next to organic search results. Therefore the maximum number of ads presented at the same time is 11.

5 Reversing the conclusions presented at the previous page we can say that: A sample ad text that has a CTR of 1% at 11 th spot will be 7 times more effective when distributed at the top spot the average growth of CTR for all analyzed ad texts was equal to 707,6%. The increase in ad text performance can be more significant and depends on base efficiency of ads the sample of ad texts that were significantly more efficient than 1% at 11 th spot proved to achieve even 9 times higher CTR at the top spot. Pic.3. A simulation of CTR of the ad text that has a base CTR of 1% at 11 th spot.

6 About Sembox Sembox Sp z o.o. is the SEM agency providing PPC advertising services to its Clients. Sembox has been launched in 2009 as a part of bluerank Group one of the first Polish search engine marketing agencies that has been operating since 2005, delivering high quality services to leading international and Polish corporate clients. Sembox focuses on planning and execution of PPC advertising to SMB sector in Poland. The expert advice and know-how is provided by Bluerank. Contact data Sembox Sp. z o.o. Wólczańska 53 street, Łódź, Poland phone: WWW:

7 The relation between ad text ranking and CTR Almost everyone who is involved in PPC campaign management is aware that ad text ranking influences campaign effectiveness. The click-through ratio (CTR) is higher if the ad text is more exposed (ie. closer to the top of the page) to user s eyes. We tried to calculate the strength of this relation in our research. In order to do this we analyzed the average daily rankings of ad texts used in campaigns over several months (the detailed methodology of the research is described in the last part of this document). The following groups of ad text were analyzed: all texts that had any number of views / clicks (marked as 0 / 0 segment), ad texts that had at least 200 views and 10 clicks ( 200 / 10 segment), ad texts that had at least 1000 views and 20 clicks ( 1000 / 20 segment), ad texts that had at least 1000 views and 100 clicks ( 1000 / 100 segment). We would expect to observe significant differences in effectiveness of ad texts belonging to the most general segment ( 0 / 0 ) because of the fact that a lot of texts had statistically insignificant results (to few impressions or clicks) and the best performing ad texts from 1000 / 100 segment which should have been the most valuable from the statistical point of view.

8 As a result, we observed the following performance: Segment / Rank / 0 7,73 5,54 4,51 3,49 2,81 2,30 1,69 1,49 1,69 1,19 0, / 10 7,83 5,58 4,53 3,53 2,85 2,34 1,75 1,62 1,97 1,47 0, / 20 7,93 5,59 4,54 3,54 2,86 2,36 1,76 1,63 2,00 1,53 0, / 100 8,14 5,66 4,62 3,64 2,95 2,42 1,88 1,92 2,16 1,75 1,12 Tab.1. Relation between CTR and ad text ranking in various segments. The difference in performance of ad texts belonging to specific segments is insignificant at the same positions (e.g. 7,73% - 8,14% for the 1 st spot). What is more important, the CTR change trend across all rankings is very similar in all segments. This is presented at the chart below which visualizes figures shown in Table 1: Pic.4. Relation between CTR and ad text ranking in various segments. The detailed analysis of particular segments enabled us to identify exceptions which made the whole summary slightly inaccurate some segments contained ad texts which had achieved different performance results (varying from 2% to 11%). We believe this was particularly a result of: specifics of campaign subject, competitiveness number of ads exposed to the user at the same time, quality of ad texts of competitors and relative attractiveness of ads being subject of this research.

9 These are the main reasons why the average (absolute) value may not accurately express the differences of effectiveness of ad texts. That is also why we decided to conduct a more detailed analysis which is also described in the later part of this research.

10 How is CTR affected by ad text ranking? The general summary presented above was appended with analysis of trends for each ad text. This was executed in the following way: we calculated the relative change of CTR for ad texts on various placements meeting qualitative criteria (described at the end of the document) e.g. if the CTR rose to 5% from 4%, the calculated relative CTR change was equal to 25% and was then used for further calculations; we calculated the average relative CTR change of all ad texts belonging to one segment. The results of this operations within defined segments are presented in the table below: Group / Rank / 0 8,21 17,28 32,93 37,48 37,09 38,77 35,07 7,66 17,93-6, / 10 7,57 17,04 32,95 38,28 37,84 40,61 37,88 7,12 28,52-4, / 20 6,95 16,73 32,82 38,25 37,85 40,65 34,44 8,03 30,62-4, / 100 6,63 16,57 32,94 38,53 38,27 40,02 38,90 14,08 32,28-5,57 Tab.2. The relative CTR change (in %) between adjoining ad placements for the same ad text. Column 1 contains the relative CTR change of ad text between 1 st and 2 nd ad placement. Similarly, column 2 contains the relative CTR change of ad text between 2 nd and 3 rd ad placement, etc. The particularly interesting findings are: Column 10 (which shows performance differences between 10 th and 11 th ad placements) consists of negative values this proves that performance of ad text is higher for the lower placement which is utmost (last placement on the right side of the search engine results page) than for higher placement which is located directly above. The shift from 10 th to 9 th placement results in substantial performance growth which may be connected with the fact that the still default screen resolution used by majority of users 1024x768 gives the 9 th placement bonus of being the 1 st bottom visible ad text.

11 It is very interesting to see the insignificant growth of performance between 9 th and 8 th ad placements it may be related to moving the ad text to the middle part of the screen which is less exposed to users. The ad text surrounded by other ads is simply less eye-catching. The substantial relative changes where noticed for ad placements 3 to 8. Each shift up resulted in 30-40% of performance improvement. Finally, the shift by 3 placements brought 100% increase of performance! The dynamics of performance growth is less significant for top placed ads (placements 1-3). It means that the order of ads is of minor importance when they are maximally exposed to the user and users are almost equally interested in all three top ads.

12 The above-mentioned findings are presented on the chart below: Pic.5. The relative CTR change (in %) between adjoining ad placements for the same ad text.

13 What CTR can the ad text achieve? Knowing the relative CTR changes for specific ad texts we tried to answer the question raised above. It was rather surprising for us to find out that you can accurately estimate the effectiveness of ad text on specific placements. The table and the chart below contain estimations for a sample ad which is assumed to have a CTR of 1% at the 11 th place: Group / Rank / 0 7,08 6,54 5,58 4,19 3,05 2,23 1,60 1,19 1,10 0,94 1, / 10 8,15 7,58 6,48 4,87 3,52 2,56 1,82 1,32 1,23 0,96 1, / 20 8,03 7,51 6,43 4,84 3,50 2,54 1,81 1,34 1,24 0,95 1, / 100 8,77 8,23 7,06 5,31 3,83 2,77 1,98 1,42 1,25 0,94 1,00 Tab.3. The prognosis of CTR of particular ad text with a base CTR=1% at 11 th spot within defined segments. Pic.6. The prognosis of CTR of particular ad text with a base CTR=1% at 11 th spot within defined segments.

14 The presented values mean that the performance of the ad text is: 2x higher at 6 th spot (shift by 5 placements); 3x higher at 5 th spot (shift by 6 placements); 7x higher at the top spot (shift by 10 placements). For the purposes of comparison we made the same simulation for ad texts belonging to all segments analyzed in this research. The calculations confirmed that also the better performing ad texts (ie. the ones with a base CTR higher than 1%) would achieve similar results in CTR change. Using the same formula we can predict the effectiveness of ad text using any input data. The table below presents sample estimations for 5 different ads using random input data (highlighted with bold) based on CTR change pattern established for 0 / 0 segment: Text / Rank Ad Text 1 6,35 5,86 5,00 3,76 2,74 2,00 1,44 1,06 0,99 0,84 0,90 Ad Text 2 4,77 4,41 3,76 2,83 2,06 1,50 1,08 0,80 0,74 0,63 0,67 Ad Text 3 3,03 2,80 2,38 1,79 1,30 0,95 0,69 0,51 0,47 0,40 0,43 Ad Text 4 12,00 11,09 9,46 7,11 5,17 3,77 2,72 2,01 1,87 1,59 1,70 Ad Text 5 5,96 5,51 4,70 3,53 2,57 1,87 1,35 1,00 0,93 0,79 0,84 Tab.4. The prognosis of CTR for five different ads with random input data (base CTR).

15 The methodology of research The research was conducted on sample of 979 ad texts used in paid search campaign presented exclusively on Google search engine ranking pages (no partner & contextual network impressions). Ad texts came from more than unique 60 accounts containing campaigns of small & medium businesses operating in various industries and sectors. In order to ignore the influence of brand awareness, all ad texts that contained brand or were exposed to the branded keywords were excluded from the research. The statistical data used for calculations was collected between Aug 29 th, 2009 and Jul 26 th, During this period ad texts were viewed more than 13,3 million times and gathered ca. 630 thousand clicks. The research was focused on data analysis relating to Top11 placements and it is worth to remember that: Top3 placements may refer to ad exposure above organic search listings. In this case placements 4-11 are shown at the right side of the search engine ranking page; Placements 9-11 may refer to ad exposure at the search engine results page no.2 (ie. presenting organic entries 11-20) if ads at the 1 st search engine ranking page were placed exclusively at the right side (max 8 slots occupied). The statistical data provided by Google AdWords does not include this type of details to differentiate the true position of the ad. Having this information would definitely help to present more accurate and reliable conclusions. We were able to present findings of this research by using BlueReport the online tool that supports and enhances Google AdWords campaign reporting. Calculating the average CTR The average CTR was calculated as the weighted average of CTR of each ad text included in the specific segment. The number of impressions of the ad text was used as the weight more frequently viewed ads (that also have more statistically reliable results) have a more significant influence on the overall results. The calculation of CTR for specific placements of each ad text was based on daily statistics delivered by Google AdWords (available both through Google AdWords web interface and Google AdWords API).

16 Calculating CTR change in relation to occupied ranking The CTR change referring to occupied position were calculated in a relative way that was based on performance of lower (more distant from the top) placement. This means that if we saw a CTR of 4% and 5% for two adjoining placements (ie. X, X+1) we calculated the relative change as [ (5-4) / 4 ] x 100% = 25%. In addition to that we removed all data where at least one of the adjoining placements had insufficient views or clicks which enabled us not to rely on low quality and statistically invaluable information. The aggregated relative CTR change between neighbouring placements was calculated as weighted average of CTR change of the specific ad text and the sum of impressions of the ad text on neighbouring placements was used as the weight.