Publishers' Life After Cookies Webinar
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How should publishers handle the slow death of 3rd party cookies? What do they need to do to leverage their first party data? How can machine learning / artificial intelligence help? Learn in our webinar.
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Publishers' Life After Cookies Webinar
- 1. Publishers’ Life After Cookies
- 2. You’re viewing slides from DataSentcis’ webinar. Go to: to play the webinar recording for free. h tt ps://webinar.getresponse.com/yJQf5/webinar-whats-a ft er-cookies
- 8. SITUATION
- 12. PUBLISHERS Understand their conten t Have relationships with their reader s Know their reader s Are responsible to their reader s CAN TAKE ADVANTAGE OF 3RD PARTY COOKIES’ END
- 13. SOLUTIONS
- 15. e Can support all the functions that 3PCs d o In some aspects better than 3PCs X Can be seen as violating privac y X Not supported by some vendors (namely Google ) X Not available for all traf fi c Trying to keep the status quo
- 16. NEXT-GEN IDS Determinis ti c IDs / logins Probabilis ti c universal IDs 1st party cookie-based IDs
- 17. DETERMINISTIC IDS / LOGINS Very good persistency cross-site and cross-device capabilitie s Can be paired to advertisers’ CRM X Only available for small portion of user s X Can be considered asi privacy violation when widely broadcasted User e-mail address or other persistent personal id can be used as base for iden ti ty. Example: Universal ID 2.0
- 18. PROBABILISTIC IDS Wider coverage of user base than login id s Enables cross-site identi fi cation X Not 100 % accurat e X Not available for all traf fi c X Can be considered as privacy violation when not fully disclosed Iden ti fying the user by analysing behaviour or other signals. Example: ID5
- 19. 1ST PARTY IDS Wide coverage of traf fi c Easy implementatio n Very good for large sites with many page views / user X No cross-site identi fi catio n X Can be restricted by browsers Randomly-generated IDs stored in 1st party cookies.
- 20. ?
- 21. CONTEXTUAL TARGETING 100 % privacy complian t No restrictions on browser side X May have lower performanc e X May be more dif fi cult to implement properl y X Not applicable for all content
- 22. ?
- 23. PRIVACY SANDOBX – FLOC Can be a useful signal for behavioural targeting X Publisher do not control i t X May cause data leakage for publishers with high-value asset s X Questionable from privacy-perspectiv e X Not available for all users The browser segments user to cohorts with similar online behaviour and makes the cohort-id available via an API.
- 30. SUMMARY The ad tech landscape is changing . New opportunities for publishers to leverage 1st party data are emerging . AI / machine learning help to extract value.
- 31. WHAT CAN YOU DO NOW Establish ID strategy . Build a data lake to collect your data . Build ML models to analyse your audience and content data . Activate your data through ad technologies. We are here to help. Build the tech-stack and key competence!
- 33. 1 © 2021 DataSentics. All rights reserved. MODERN PUBLISHER ARCHITECTURE Publisher‘s data platform ALGORITHMS DATALAKE STORAGE RESULTS: ID1; BUYING-CAR 0.2; … ID2; BUYING-CAR 0.6; … ID3; BUYING-CAR 0.0; … ID4; BUYING-CAR 0.9; … … MANAGER (UI) Machine learning / AI Automated update (API) Automated data extract (API) Personalized Ad/content is displayed to user … Or similar IN YOUR CLOUD, FULL CONTROL, TRANSPARENT RAW DATA FROM YOUR AD TECH PERSONALIZED ADS ALGORITHMS AI-DRIVEN SEGMENTS & LOOKALIKES ADSERVER, DMP, SSP, WEB ANALYTICS, … Or similar „SEED“ DATA FROM BRANDS 1st party data onboarding of clients (hashed emails, …) CRM / TRANSACTIONS (registrations, subscribers, ….) Or similar Automated update (API) ADSERVER, DMP, SSP, WEB ANALYTICS, … CONTENT (article body, headline, topics, labels, …)
- 34. 2 © 2021 DataSentics. All rights reserved. How big is your internal data team? - Just few people creating reports - Up to 5 people, mostly reporting and DMP „clicking“ - We have own AI/ML team
- 35. WEBSITE, APPS BEHAVIOURAL DATA – user level web interaction table Food for ML/AI From Tools like… Adobe analytics, Mixpanel, Webtrekk… or similar
- 36. 4 WHEN WHO WHAT WHERE DEVICE GEO INTERACTIONS DURATION HOW MUCH AD BEHAVIOURAL DATA From Tools like… WHICH ADVERTISER?
- 37. TRANSACTION BEHAVIOURAL DATA (REGISTRATIONS, SUBCRIBES, CANCELATIONS…) From Tools like… CRM, DWH, INTERNAL DB
- 38. 1) CREATING 360° BEHAVIOUR JOURNEYS Customer (up to) 360° behaviour / journeys WEB & CONTENT INTERACTIONS AD INTERACTIONS REGISTRATIONS/ SUBSCRIPTIONS
- 39. 2) DERIVING THEIR AI-DRIVEN ATTRIBUTES FROM 360° BEHAVIOUR JOURNEYS Football Cars Cars Cars Football Football Cars Fashion Football Fashion Fashion Fashion +Fashion Customer123 Customer124 Customer125 Customer126 … Football Football Football Football +Football +Cars x AI Our product = 160+ algorithms & framework to build more Geo / demo • Age • Gender • Address / permanent residence • Location at a time of filling out the form Life stages • Planning a wedding • Recently divorced • Baby birth • Student • Family • Retired Lifestyle • Hipsters • Commuting to work • Travel a lot • Tech savvy • Luxury fashion • Foodies / coffee lovers • Apple / Android • Chrome / Safari / other browsers • Expensive / cheap device Interests • Technologies • Politics • Books and literature • Cars • Home and garden • Financial products • Sports • Travel Digital maturity • High/mid/low • Early adopter Digital behaviour • Online (web, social media, e- mail etc.) activity • Digital ptb models • Product browsing • Web content browsing • Time and day of visit • Number and type of devices Funnel stage • First-time visitor (later returned) • One-off visitor (never came back) • Engaged visitor • Existing customer • Regular noc-client visitor Income & Wealth • High income • Low income • Maternity leave • Investor • Manager Purchase intentions • Searching for a car • Buying a house • Seeking flights • Getting car insurance Call to action preferences • E2E Digital • Inbound call • Branch visit + YOUR CUSTOM ONE
- 40. 3) SCALING INSIGHT FROM SELECTED JOURNEYS (E.G. 5 %) TO ENTIRE BASE BY ML/AI SEED AUDIENCE (e.g. CLICKED ON „SAMSUNG S21“ ) PROB TO CONVERT (0.6) PROB TO CONVERT (0.01) Machine Learning model = rules & weights to calculate similarity score <0.5 interested in footbal + 2x more visiting from iphone + reading at least 5x in a night…. „Doing lookalike“ (Scoring each user by ML-model) = calculatinig similarity score = probability
- 41. 9 © 2021 DataSentics. All rights reserved. How many audiences you define „manually“ by clicking in DMP? - We do not create own audiences (outsourced, 3rd party) - Most of them, and it work perfectly fine - Most of them, but performance is not good and we have „mess“ in our DMP - We are using own models to do it automatically
- 42. 10 © 2021 DataSentics. All rights reserved. MILLIONS OF USERS 1000+ NUMBERS OF AI- DRIVEN SEGMENTS
- 43. DATA-DRIVEN MEDIA PLANING & TARGET GROUP EXPLORATION = SEXY FOR BRANDS („DATA-DRIVEN RESEARCH“) = NO BLACKBOX = 1ST PARTY DATA BASED
- 44. 12 © 2021 DataSentics. All rights reserved. „CRM CUSTOM AUDIENCE“ FOR PUBLISHERS (NOT ONLY FOR GAFA!) Building lookalike audiences/personas based on CRM data „seeds“ of the client (eq. of Custom Audiences in Facebook/Google Ads) 100 % Privacy Ready All the data are hashed and not retraceable back Better performance by leveraging non-cookie data Minimum blockers DataSentics can help on all sides of the market
- 45. 13 © 2021 DataSentics. All rights reserved. Are you able to extrapolate SocDemo, Age, … of registered users to anomymous visitors? - Not at all - Partially, but we are struggling with DMP blackbox lookalikes (not enough data) - Yes we are easily doing it via DMP - Yes we are doing it with our internal Data team
- 46. 14 © 2021 DataSentics. All rights reserved. MODERN PUBLISHER ARCHITECTURE Publisher‘s data platform ALGORITHMS DATALAKE STORAGE RESULTS: ID1; BUYING-CAR 0.2; … ID2; BUYING-CAR 0.6; … ID3; BUYING-CAR 0.0; … ID4; BUYING-CAR 0.9; … … MANAGER (UI) Machine learning / AI Automated update (API) Automated data extract (API) Personalized Ad/content is displayed to user … Or similar IN YOUR CLOUD, FULL CONTROL, TRANSPARENT RAW DATA FROM YOUR AD TECH PERSONALIZED ADS ALGORITHMS AI-DRIVEN SEGMENTS & LOOKALIKES ADSERVER, DMP, SSP, WEB ANALYTICS, … Or similar „SEED“ DATA FROM BRANDS 1st party data onboarding of clients (hashed emails, …) CRM / TRANSACTIONS (registrations, subscribers, ….) Or similar Automated update (API) ADSERVER, DMP, SSP, WEB ANALYTICS, … CONTENT (article body, headline, topics, labels, …)
- 47. 15 © 2021 DataSentics. All rights reserved. LET‘S FIGHT WALLED GARDENS TOGETHER WITH THE SAME AI/ML WEAPONS LET US ACCELERATE YOUR DATA TEAMS Data platform in your cloud (incl. Data collection pipelines setup, ETL, basic CICD/Git, and connectors to APIs for export…) Prebuild AI-AUDIENCES & UI (incl. 160+ interests algorithms for English/German/Czech, socio demographics, income) Managed services & Reselling (incl. Helping with campaign design, execution, evaluation, communication with your sales/account team) ACCELERATING YOUR TEAM, NOT REPLACING Your data analysts are contributors (upskilling, learning from ours, etc.) SAVING COSTS & TIME TO DEVELOP FROM SCRATCH We deliver 160+ prebuild algorithms already as a product SAVING COSTS OF DATA PREP FOR EACH CAMPAIGN We deliver UI to use the segmentation & automate audience exploration process
- 48. Artificial Intelligence & Cloud Data Engineering
- 49. 17 © 2021 DataSentics. All rights reserved. Consulting topics: - 3rd aprty cookies - meidalky… - přímý prodej reklam… - VOD - business /demand generation …. Free trial topics: Ad monetization Web perosnalization (using 1st party segments) Proposition: Personalization for publishers Data platform UI Prebuild segments Managed service All incluvice 360 stragtegic partner
- 50. Today‘s Agenda 1. Introductions // 5 min 2. About DataSentics & How we work // 5 min 3. How we understand the market situation (Publishing industry) // 5 min 4. Deep dive into Adpicker // 15-25 min 1. Optimal utilization of behavioural user data 2. Personalized advertising in a post 3rd-party cookie world 3. Integration of paid content and advertising into an optimally monetized user experience 5. Business model & Discussion // 5+ min
- 51. Making data science and machine learning have a real impact on organizations: optimize and automate the thousands/millions of small decisions you do everyday Gold partner & Partner of the Year 2020 Professional partner 4th fastest growing in CE Rising stars award Partners & Awards: Selected Customers: The Family 10+ product owners 50+ Machine learning /AI /Data science specialists 30+ Software engineering Cloud specialists 15+ 360° Campaign specialists DataSentics PX Personalization for Banking and Insurance DS Innovate AI/ML driven innovations & startups DS TechScale Platforms for AI applications DS InRetail Improving the customer shopping experience Adpicker Ad Innovations and managed services
- 52. DataSentics PX ü Your partner for building modern AI-driven personalization in retail banking & insurance (joint-team cooperation) ü Persona 360 product suite (In your environment, transparent, full control, collaboration ready) 360° PERSONALIZED EXPERIENCE (CONNECTING THE DIGITAL & CRM USING ML/AI) Machine learning & AI Siloed data 180° GOLDEN RECORD OF CUST. Digital channels Classic CRM / core systems Digital marketing tools CRM/MA tools EXISTING CUSTOMERS ONLINE ADS (SEARCH & DISPLAY & SOCIAL) OWN WEBSITE & SALES INTERACTIONS MOBILE APP INTERACTIONS CLIENT ZONE, MY ACCOUNT & CHAT INTERACTIONS DETAILED TRANSACTIONAL DATA, NPS, CUSTOMER RESEARCH, GEO-DATA, TV, PARTNERS, VOICE, CHATS, REVIEWS… EMAILING / SMS / PUSH BRANCHES & SALES NETWORKS BASIC TRANSACTIONAL/ CLAIM HISTORY CALLCENTRUM DATA / CALL LOGS 360° CUSTOMER DATA MODEL & JOURNEYS … … … Partners & technologies: Selected Customers in Europe: Breaking silos between digital and CRM: changing the mindset of campaign teams by a new workflow, democratization of AI-insights across digital and offline Setup the deanonymization of „Cookie-style“ IDs from digital technologies vs. existing client IDs Personalization for existing customers: Enrich CRM by „softer“ lifestyle/need triggers using AI-models for detecting key behaviour changes in Digital channels Personalization for new customers: Microtargeting of Digital campaigns based on AI-identified key characteristics of the best existing customers NEW CUSTOMERS / ANONYMOUS
- 53. DataSentics inRetail Selected Customers: DS inRetail Products and Solutions ü Your partner for building modern AI-driven solutions in retail (joint-team cooperation) ü Several pre-build solutions (In your environment, transparent, full control, collaboration ready) ü Long-term experience from various retail clients (experience from both – online and offline world) Vision: Get closer to your customers both in digital and physical world Digital non-client & client behavior Classic client profile New opportunities Advisory powered e-commerce AI product targeting Personalized 360 experience Become a place where users get inspiration and choose their products (not on other sites, but on your e-shop) Cover the whole customer journey Producers want to get a closer relationship with their customers; retailers can help them. We help you personalize as banks do and monetize your loyalty and digital data We help you to get closer to your customers by targeting your products on all the physical levels –products on shelves, placement in stores, placement of your outlets
- 54. Persona-style audiences using 1st party data & lookalikes of registered profiles Transparent lookalikes of 100k+ registered/subscriber people to entire visitor base using tailored AI/ML algorithms. Enabling building of tailored data-driven audiences for key advertisers. 2nd largest Austrian Publisher Selected customer success stories from Ad industry „Persona-style“ audience management using ML/AI on top of Adserver raw data Automatically processing Billions of ad impressions. Behavioural profiling of cookies (interest, income, socio demographics, etc.) to enable smart Persona-style targeting for key clients and campaigns. Reselling for extra revenue to current customers. Rolled to 3 countries, so far: Austria (Vienna - iProspect), Czech Republic (Prague – Adexpres) SK (iprospect) Fan 360° and personalized campaigns for partners (media agency & publisher) Supporting business decisions/actions across CFG by Fan 360° profile data & insights. Personalized FRM campaigns (Email, SMS, Cityzens widgets, push…). Stitching data across multiple systems, teams living in separated silos. Feeding data/triggers to maximize value of marketing tools (e.g. SalesForce campaign, FB campaigns,…)
- 55. 23 © 2021 DataSentics. All rights reserved. HOW WE UNDERSTAND THE MARKET SITUATION?
- 56. 24 © 2021 DataSentics. All rights reserved. ADVERTISING INDUSTRY EXPECTS UPSIDE DOWN CHANGES ! Privacy regulations (CMP, ePrivacy, 3rd Party cookies elimination done by browsers) ! Limited access to 3rd Party data after cookieless politics will be applied by browsers ! Identity management as the way how to recognize your user is extremely difficult (politics, motivation, unification with adtechs) ! Hard to fulfil targeting requirements of advertisers (complex Persona-based criteria such as Male 35-55, interested in buying a new car and having 2 kids)
- 57. 25 © 2021 DataSentics. All rights reserved. WALLED GARDENS WINS IF PUBLISHERS/AGENCIES WILL NOT DELIVER THREATS OPPORTUNITY ! Advertiser's spends move to Walled Gardens (Google and Facebook will benefits more because they are able to recognize registered users) Data – Welcome back to publishers! Third party SSPs/DSPs were making profit on your data, so far. And for free... Behavioural data will back in hands of each publisher. This will be extremely beneficial for mid and large- sized publishers. without targeting based on 3rd party cookies (Interests, SocDemo, Intents,…) Non Google/Facebook Ad spendings of Brands Brands are now looking for the alternatives!
- 58. 26 © 2021 DataSentics. All rights reserved. WALLED GARDENS WINS IF PUBLISHERS/AGENCIES WILL NOT DELIVER NOW MEDIA BUDGET SPLIT OF BIG BRANDS Ad Revenue & Direct deals Their own media & digital agencies You Facebook Google Deals (based on 3rd party audiences) YOUR OPPORTUNITY MEDIA BUDGET SPLIT OF BIG BRANDS Their own media & digital agencies You Facebook Google Vendor campaigns (listing on Alza, Mall…) Marketplaces Vendor campaigns (listing on Alza, Mall…) Ad Revenue & Direct deals
- 59. 27 © 2021 DataSentics. All rights reserved. BUSINESS OPPORTUNITY = 1ST PARTY DATA-DRIVEN DEALS WITH BRANDS Direct deals (based on 1st party data) NOW MEDIA BUDGET SPLIT OF BIG BRANDS Ad Revenue & Direct deals Their own media & digital agencies You Facebook Google Deals (based on 3rd party audiences) YOUR OPPORTUNITY MEDIA BUDGET SPLIT OF BIG BRANDS Their own media & digital agencies You Facebook Google Vendor campaigns (listing on Alza, Mall…) + YOUR NEW USP ++ EASY FOR ADVERTISERS ++ REACH / BIG ENOUGH ++ YOUR DATA = ASSET ++ AGENCIES CAN ONLY RESELL BY NEW MEDIA PROPOSITION (DATA-DRIVEN CAMPAIGN) Marketplaces Vendor campaigns (listing on Alza, Mall…) Ad Revenue & Direct deals New Ad Revenue
- 60. 28 © 2021 DataSentics. All rights reserved. NEW MEDIA PROPOSITION BASED ON 1ST PARTY DATA
- 61. Time consuming to „try“ manage it (e.g. 2h to maintain x 100 audiences.) BRANDS STILL WANT TARGETED CAMPAIGNS… (PERSONAS, …) Perf/Quality issues (wrong assumptions, not learning from data) Blackbox for advertisers (why this audience?) MEDIA AGENCIES ARE SELLING 3RD PARTY AUDIENCES... This „party“ is ending…
- 62. WEBSITE, APPS BEHAVIOURAL DATA – user level web interaction table Food for ML/AI From Tools like… Adobe analytics, Mixpanel, Webtrekk… or similar
- 63. 31 WHEN WHO WHAT WHERE DEVICE GEO INTERACTIONS DURATION HOW MUCH AD BEHAVIOURAL DATA From Tools like… WHICH ADVERTISER?
- 64. TRANSACTION BEHAVIOURAL DATA (REGISTRATIONS, SUBCRIBES, CANCELATIONS…) From Tools like… CRM, DWH, INTERNAL DB
- 65. 1) CREATING 360° BEHAVIOUR JOURNEYS Customer (up to) 360° behaviour / journeys WEB INTERACTIONS AD INTERACTIONS REGISTRATIONS/ SUBSCRIPTIONS
- 66. 2) DERIVING THEIR AI-DRIVEN ATTRIBUTES FROM 360° BEHAVIOUR JOURNEYS Football Cars Cars Cars Football Football Cars Fashion Football Fashion Fashion Fashion +Fashion Customer123 Customer124 Customer125 Customer126 … Football Football Football Football +Football +Cars x MACHINE LEARNING Our product = 160+ algorithms & framework to build more Geo / demo • Age • Gender • Address / permanent residence • Location at a time of filling out the form Life stages • Planning a wedding • Recently divorced • Baby birth • Student • Family • Retired Lifestyle • Hipsters • Commuting to work • Travel a lot • Tech savvy • Luxury fashion • Foodies / coffee lovers • Apple / Android • Chrome / Safari / other browsers • Expensive / cheap device Interests • Technologies • Politics • Books and literature • Cars • Home and garden • Financial products • Sports • Travel Digital maturity • High/mid/low • Early adopter Digital behaviour • Online (web, social media, e-mail etc.) activity • Digital ptb models • Product browsing • Web content browsing • Time and day of visit • Number and type of devices Funnel stage • First-time visitor (later returned) • One-off visitor (never came back) • Engaged visitor • Existing customer • Regular noc-client visitor Income & Wealth • High income • Low income • Maternity leave • Investor • Manager Purchase intentions • Searching for a car • Buying a house • Seeking flights • Getting car insurance Call to action preferences • E2E Digital • Inbound call • Branch visit + YOUR CUSTOM ONE
- 67. 3) SCALING INSIGHT FROM SELECTED JOURNEYS (E.G. 5 %) TO ENTIRE BASE BY ML/AI SEED AUDIENCE (e.g. CLICKED ON „SAMSUNG S21“ ) PROB TO CONVERT (0.6) PROB TO CONVERT (0.01) Machine learning the insights (ML-model) Lookalike/Scoring (using ML-model)
- 68. DATA-DRIVEN MEDIA PLANING & TARGET GROUP EXPLORATION = SEXY FOR BRANDS („DATA-DRIVEN RESEARCH“) = NO BLACKBOX = 1ST PARTY DATA BASED
- 69. 37 © 2021 DataSentics. All rights reserved. EMAIL MATCHING, NO MORE 3RD PARTY COOKIES… Building lookalike audiences/personas based on CRM data „seeds“ of the client (eq. of Custom Audiences in Facebook/Google Ads) 100 % secure All the data are hashed and not retraceable back Enterprise ready This solution is working well together with sufficient amount of the customer's data Better performance by leveraging non-cookie data Less manual work by using AI to identify the selection criteria for audiences/personas Minimum blockers DataSentics will help the client to manipulate the data within his systems
- 70. 38 © 2021 DataSentics. All rights reserved. MODERN PUBLISHER ARCHITECTURE Automated ALGORITHMS STORAGE / DATA PREPARATION RESULTS: COOKIE1; AFFINITY1 0.2 ; COOKIE2; AFFINITY1 0.6 ; COOKIE3; AFFINITY1 0.0 ; COOKIE4; AFFINITY1 0.9 ; … MANAGER (UI) Machine learning / AI Automated upload (API) Automated download (API) SSP/DMP/ADSERVER Personalized Ad/content is displayed to user … Or similar IN YOUR CLOUD, TRANSPARENT, FULL CONTROL USER INTERACTIONS (Ad impressions, clicks, urls,…) TARGETING/ PERSONALIZATION ALGORITHMS AI-DRIVEN SEGMENTATION (ALGOS) ACCELERATING YOUR TEAM Your data analysts are contributors (upskilling, learning from ours, etc.) SAVING COSTS & TIME TO DEVELOP FROM SCRATCH We deliver 160+ prebuild algorithms already as a product SAVING COSTS OF DATA PREP FOR EACH CAMPAIGN We deliver UI to use the segmentation & automate audience exploration process YOUR EXISTING WEB ANALYTICS & ADTECH TOOLS Or similar „SEED“ DATA FROM BRANDS
- 71. Select campaign goal „Seed“ (e.g. People who converted/purchesed…) Execute targeted campaign (export to ad tech) = YOUR NEW PROPOSITION FOR BRANDS WE COVER IT END TO END Or similar… Media plan / audience learned from data by AI (= Real personas) 1. 2. 3. Your existing tools Our Managed services (Campaign & Data specialists) Our Business network (demand for this service) (Dentsu, Asahi, CS, Moneta, Samsung, Microsoft, Koop, …) YOUR NEW USP (VS. PUBLISHERS, ALZA, MALL, …) HIGHER PERFORMING ADS (BRAND, PERF…) CAN BE USED TO GROW REGISTERED/SUBCRIBERS & MediaSentics agency (ex Adexpres experts) Our Product & platform (Adpicker) (Models, algorithms, …) „Reselling“ it -> via our business network 0.
- 72. 40 © 2021 DataSentics. All rights reserved. EXAMPLE OF BUSINESS CASE (YOUR PERSPECTIVE) 6 months commitment, 2 month notice period, All prices excl. VAT Revenue share only (incl. your Cloud Costs) Mixed (Project based) Data platform in your cloud (incl. Data collection pipelines setup, ETL, basic CICD/Git, and connectors to APIs for export…) Prebuild AI-AUDIENCES & UI (incl. 160+ interests algorithms for English/German/Czech, socio demographics, income) Managed services & Reselling (incl. Helping with campaign design, execution, evaluation, communication with your sales/account team) Included CPM / subscription fee CPM / subscription fee Included Total costs for XXX 000 CZK XXX 000 CZK (assuming XXX M Ad impressions affected) (minimum X0 000 CZK/ month) (minimum X0 000 CZK/ month) YourProfit (gross, before ad tech fees) 1 XXX 000 CZK 1 XXX 000 CZK (assuming markup 20+ CZK CPM) (before cloud Costs) Running costs for your cloud Revenue share only (excl. your Cloud Costs) Included CPM / subscription fee CPM / subscription fee Typically 1000 – 3000 EUR / Month 600 EUR / MD CPM / subscription fee 600 EUR / MD Typically 1000 – 3000 EUR / Month Minimal business risk (No upfront Costs for you) Reducing complexity (managed by us) Continuous development & upgrades $ $
- 73. 41 © 2021 DataSentics. All rights reserved. HOW TO START? BAU & ADJUST BASED ON MARKET INSIGHTS FROM PILOT SCALE TO MORE CUSTOMERS PILOT CUSTOMERS (FOR SELECTED CUSTOMERS) Time Complexity Business Goal: validate business potential of selling behavioural data (audiences) Pilot KPI: Ad Data revenue / market feedback BAU & ADJUST BASED ON MARKET INSIGHTS FROM PILOT ADD NEW DATA SOURCES / FEATURES AUTOMATE INITIAL SETUP (GET DATA & DEPLOY SEGMENTATIONS) Free of Charge 3-6 months
- 74. 42 © 2021 DataSentics. All rights reserved. You’re viewing slides from DataSentcis’ webinar. Go to: https://webinar.getresponse.com/yJQf5/webinar-whats-after-cookies to play the webinar recording for free.