Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Capabilities of 'Comprehensive Analysis' of digital ad campaigns

208 views

Published on

newage. is the digital marketing agency that applies an innovative approach to the online media campaigns analysis. Our proprietary technology of ‘Comprehensive Analysis’ (includes Post View analysis and User ID matching) enables us to get a 360-degree view of the real media effect of your campaigns and feel the gap in understanding of long term effects of media activities.

Published in: Data & Analytics
  • Be the first to comment

  • Be the first to like this

Capabilities of 'Comprehensive Analysis' of digital ad campaigns

  1. 1. CAPABILITIES OF COMPREHENSIVE ANALYSIS
  2. 2. Analysis and Reporting Media metrics • Impressions • CPM, vCPM • Reach (reach of target audience) • Frequency • CPU • CTR • Traffic metrics Post-Click actions • Visits • Bounce rate • Session duration • % of new users • Conversion rate • Desired actions Post-view actions • Visits • Conversion rate • Visibility of target pages • Time to desired action • Analysis of placements • Analysis of creative ads Quality control • Viewability • Targets check • Frequency-check • Bot-check report • Traffic-check report • Url-report • Visual check Agile-approach COMPREHENSIVE ANALYSIS THE WAY WE SEE IT ECOSYSTEM OF COMPREHENSIVE ANALYSIS
  3. 3. COMPREHENSIVE APPROACH TO DISPLAY ADVERTISING Demand generation Now we can track online behavior using cookies-matching and user-id
  4. 4. Source of data: data of third party measurement provider, agency expertise Post-view cookies-matching Post-click 22% - 88% of all conversions are post-view Are you sure that you are not losing data and making the right conclusions? Post-view user-id IMPORTANCE OF POST-VIEW ANALYSIS
  5. 5. TOOLS FOR CAMPAIGN OPTIMIZATION ● Finding the optimal frequency ● Analysis of creatives efficiency ● Estimation of media effect lifetime ● Optimization of ad platforms / targeting ● Building of a primary attribution card 1 2 3 4 5
  6. 6. Finding the optimal frequency What is the optimal frequency of the campaign? Having the data of the ‘Comprehensive Analysis’, it is possible to understand what number of users visited advertiser’s website at each frequency
  7. 7. Client: job search website TА: job seekers Period: March 2018 Goal: submission of CV Conclusion: 5-6 ad impressions per user per campaign is border frequency in terms of the efficiency of traffic generation. We use this as input data for planning. Campaign coverage (views) СРU Post-view visits Cost of Post-view visit 0.55 $ 0,034 $ x2 0,041 $ x3 0,050 $ x4 0,048 $ x5 0,047 $ x8 0,050 $ x12 0,055 $ x17 0,060 $ x27 0,075 $ Data source: data of third party measurement provider, agency expertise, | Сalculation formula: Cost of post-view visit=Campaign Coverage*CPU/Post-view visits EFFECTIVENESS DEPENDING ON FREQUENCYFrequency
  8. 8. Campaign coverage Post-view visits Cost of Post-view visit 1 1 0.21 $ 2 2 0.24 $ 3 3 0.29 $ 4 4 0.23 $ 5-6 5-6 0.36 $ 7-9 7-9 0.47 $ 10-14 10-14 0.64 $ 15-19 15-19 0.88 $ 20-34 20-34 1.62 $ Client: online retail TА: 25-45 Period: November 2018 Goal: drive traffic to the website Conclusion: given the client's activity and budget, the optimal frequency for the campaign was 4 impressions per unique user per month. Further frequency build-up is inefficient. Frequency EFFECTIVENESS DEPENDING ON FREQUENCY Data source: data of third party measurement provider, agency expertise, | Сalculation formula: Cost of post-view visit=Campaign Coverage*CPU/Post-view visits
  9. 9. Client: retail, office supplies (launching new brand) TА: Internet users with children Period: July-August 2018 Goal: boost of sales, increase brand awareness Conclusion: due to low level of brand awareness, it was advised to the client to run "noisy" campaigns with high frequency. Campaign coverage (views) СРU Post-view visits Cost of Post-view visit 0.67 $ 2.25 $ 1.34 $ 2.82 $ 2.01 $ 3.57 $ 2.67 $ 2.65 $ 3.38 $ 2.13 $ 5.38 $ 1.95 $ 8.74 $ 1.99 $ 11.45 $ 1.72 $ 18.18 $ 1.99 $ 28.2 $ 3.57 $ 42.41 $ 4.56 $ 58.6 $ 3.61 $ 67.3 $ 3.32 $ Frequency EFFECTIVENESS DEPENDING ON FREQUENCY Optimalfrequency Data source: data of third party measurement provider, agency expertise, | Сalculation formula: Cost of post-view visit=Campaign Coverage*CPU/post-view visits
  10. 10. Creatives efficiency Which creatives perform better than others? Relying on the data of the ‘Comprehensive Analysis’, we can track how the user behaved after seeing a particular ad creative.
  11. 11. Conclusion: in this campaign, the banner performed better than the video, satisfying the demand that was already created. Banner, that mentioned high salary, drove more traffic to the website (by 24%). Video Banners Data source: data of third party measurement provider CREATIVES EFFICIENCY Views to Visits - 3.9% Visits to Conversion - 1.4% Views to Visits - 5.2% Visits to Conversion - 1.2% Views to Visits - 4.2% Visits to Conversion - 1.2%
  12. 12. Client: online retail TА: 25-45 Period: November 2018 Goal: drive traffic to the website Conclusion: do not expect that the user will remember the specific item. If it is important to promote a particular product, direct your visitors to respective landing pages appeared on the main page of the website CVR to website visits 0,9% CVR to website visits 1% CVR to website visits 1% CVR to website visits 1,3% Data source: data of third party measurement provider CREATIVES EFFICIENCY
  13. 13. Client: foods and beverages TА: online-users Period: Mart 2016 Goal: increase in % of visits and conversion Conclusions: a banner with a specific price tag attracted much more users, with a higher conversion rate. Data source: data of third party measurement provider CREATIVES EFFICIENCY 0,6% 1,5%Website Visit > 3,5% 4,1%Visits to Conversion >
  14. 14. The duration of the media effect How long does the user remember your message? Based on the data of ‘Comprehensive Analysis’, we can make conclusions regarding users reaction to the ad campaign after certain time
  15. 15. Client: online retail TА: online-buyers Period: Mart 2017 Goal: drive traffic to the website Conclusions: The main media effect is concentrated within 1-3 days. It is necessary to use the appropriate weekly and daily restrictions in planning Source of data: data of third party measurement provider, agency expertise MEDIA EFFECT The share of users visiting the website after seeing the ad (daily distribution)
  16. 16. Source of data: data of third party measurement provider, agency expertise Post-click Post-view Conclusions: The main media effect was concentrated within the first 2 days and lasted up to 7-8 days MEDIA EFFECT Client: job search website TА: job seekers Period: March 2018 Goal: submission of CV Number of users visiting the website after seeing the ad (daily distribution)
  17. 17. Optimization of ad platforms / targeting What ad platforms/targeting perform the best? Based on data of the ‘Comprehensive Analysis’, it is easy for us to identify what platforms and targetings show best performance and prioritize accordingly while campaign is still running
  18. 18. Client: job search website TА: job seekers Period: March 2018 Goal: submission of CV Conclusions: differences in ad platforms / targeting are enormous, it is critically important to check performance by platform and TA as often as possible. Upon completion of the campaign, the cost of the conversion was optimised and went down by 34% for banner ads and by 52% for video ads. Branding 3-5% Website visits 3-9% Video 3-31% Banner Source of data: data of third party measurement provider OPTIMIZATION OF AD PLATFORMS / TARGETING
  19. 19. Client: web browser TА: online-users Period: December 2018 Goal: increase of market share Conclusion: digging into the reasons for such a profound difference in the websites performance, we realized that ad view frequency and the quality of the audience have crucial importance Video 0,1-0,3% Yandex Inventory 0,3-1,2% Banners 0,1-0,5% OPTIMIZATION OF AD PLATFORMS / TARGETING Source of data: data of third party measurement provider Visitstowebsite
  20. 20. Client: car brand TА: potential buyers Period: April 2018 Goal: drive website visits / downloads of price list Conclusions: An extensive initial planning allows to significantly optimize the campaign / Breakdown by specific audience categories didn’t work well, while identifying of the best performing ad placements yielded great results. Auto EnthusiastsCoverage + Target Audience Buyers Retargeting Source of data: data of third party measurement provider, agency expertise OPTIMIZATION OF PLATFORMS / TARGETING Visitstowebsite
  21. 21. Building a primary attribution card Usually, the users don’t make a purchase immediately after seeing the ad, so you need to build a customer journey map to understand via which channel the users that were exposed to the ad are coming to the website? Having the data of the ‘Comprehensive Analysis’, we are able to understand through which traffic channels users who saw the ad are visiting the advertiser’s website. Moreover, we can tell what was the user’s path to purchase and order of exposure to the ads.
  22. 22. Split of the traffic from media placements by three channels Распределение трафика Client: online retail TА: smartphone owners Period: September 2018 Goal: drive traffic to website Conclusions: looking at the users who were exposed to the ad campaign and visited advertiser’s website after some time, we can see that 23% of all media traffic returned through organic search Source of data: data of third party measurement provider, agency expertise CUSTOMER JOURNEY MAP OtherOrganiсPai d
  23. 23. Video Client: employment site TА: job seekers Period: March 2018 Goal: submission of CV Conclusions: analysing ad placements by share of users who visited the advertiser’s website through paid channels, it is easy to see which placements are more cost effective providing opportunities for optimisation Source of data: data of third party measurement provider, agency expertise CUSTOMER JOURNEY MAP BrandingBanners %of"paid"traffic
  24. 24. Client: shopping club TА: online-buyers Period: September-October 2018 Goal: boost registrations/purchases Conclusion: naturally, the difference in shares of organic traffic is also very significant. Eventually, optimization depends on the goals of the campaign and client’s paid search optimisation activities Source of data: data of third party measurement provider, agency expertise CUSTOMER JOURNEY MAP %oforganictraffic
  25. 25. DATA COLLECTION AND Q&A COMPREHENSIVE ANALYSIS CAMPAIGN OPTIMIZATION Post- view Post- click We have enough data and tools to address the issues described above. Our approach helps to optimize advertising campaigns in many ways and directly impact business results of our customers Collect the data, analyze it and draw the right conclusions – this is digital! EVALUATION OF RESULTS
  26. 26. THANK YOU

×