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LVIMA DPD 2015 - Conversant

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LVIMA DPD 2015 - Conversant

  1. 1. © 2014, Conversant, Inc. All rights reserved. PRESENTED BY July 27, 2015 A NEW STANDARD FOR DATA: IDENTIFYING AND REACHING THE “ALWAYS ON” INDIVIDUAL IN A MULTI-DEVICE WORLD Matthew Weisbecker
  2. 2. © 2014, Conversant, Inc. All rights reserved. 6.8B people on the planet. How many have a cellphone? 4B PEOPLE HAVE CELLPHONES ?
  3. 3. © 2014, Conversant, Inc. All rights reserved. How many people have a toothbrush? 3.5B PEOPLE HAVE TOOTHBRUSHES ?
  4. 4. © 2014, Conversant, Inc. All rights reserved. There are more cellphones in the world than PCs. How many more? ? 5X MORE CELLPHONES
  5. 5. © 2014, Conversant, Inc. All rights reserved. What percentage of Americans use only mobile to access the internet? ? 25% USE MOBILE ONLY
  6. 6. © 2014, Conversant, Inc. All rights reserved. THE “ALWAYS ON” INDIVIDUAL 5+HOURS PER DAY SPENT ON DIGITAL 60%TIME SPENT ON MOBILE/TABLET VS. PC 67%START SHOPPING ON ONE DEVICE AND CONTINUE ON ANOTHER 75%USE SMARTPHONES WHILE SHOPPING Source: eMarketer, Think Insights by Google, Nielsen, 2014 6
  7. 7. © 2014, Conversant, Inc. All rights reserved. 7 WATCHED 3 TESLA VIDEOS SEARCHED FOR SHOW TICKETS SEARCHED FOR TIARAS 90+ MINS/DAY ON CELEBRITY GOSSIP APPS RESEARCHED COSMETIC INGREDIENTS BROWSED HOCKEY EQUIPMENT
  8. 8. © 2014, Conversant, Inc. All rights reserved.
  9. 9. © 2014, Conversant, Inc. All rights reserved. 9 WHO I AM WHAT I CARE ABOUT WHAT I BUY WHAT I WATCH HOW I CONNECT WHERE I HAVE BEEN
  10. 10. © 2015, Conversant, Inc. All rights reserved.10 ALL THE PIECES TO THE PUZZLE
  11. 11. © 2015, Conversant, Inc. All rights reserved.11 WAYS TO CONSTRUCT A PROFILE @ PII Login/ Registration Cookies/ Device IDs Privacy Concerns Platform Limited Accuracy Issues E.g. Experian E.g. Facebook E.g. DSPs
  12. 12. © 2015, Conversant, Inc. All rights reserved.12 VERIFIED INDIVIDUALS Individual Profile ID #99999 2 Online Data Transaction IDs, registration data and email opens hard link devices to individual @$ Online Purchase TXNID# 12345 Confirmation Email TXNID# 12345 Device Matched Device Matched Behavior on each device paired to individual 3 + browsing, search, video, shopping, purchase, etc. + app usage, location, download, purchase, etc. + demographic, home ownership, political affiliation, etc. Offline Data Name, address, email and transactions basis of individual profiles 1 Credit Card File (Name, address, etc.) TXNID# 12345 Individual ID #99999 (includes TXN ID# 12345) 3P Anonymization Partner Strips PII Creates Individual ID #99999 Example
  13. 13. © 2014, Conversant, Inc. All rights reserved. EDUCATION PROFESSIONALS 4,17XX,455 D E S K T O P S 1,654,0XX2 MOBILE X10,506 TABLETS Defining the Audience: This audience includes users whose occupation is in the education field based on offline name and address based sources. 24,986,512 DESKTOPS 15,161,826 MOBILE 7,130,734 TABLETS REACHING 10M CONSUMERS (4.7 Average Devices)RETAIL BEHAVIOR o 5.5x more likely to be in-market craft materials o 2.5x more likely to be in-market for entertainment BROWSING BEHAVIOR o 10x more likely to be on education enrichment sites o 3.7x more likely to be on arts and crafts sites SOCIAL o 32% have recent Facebook activity in the last 7 days W H A T I B U Y W H A T I C A R E A B O U T LIFE EVENTS o 85% are female o 15% are male W H O I A M DEVICE DATA o 78% have an iPhone o 2.2x more likely to own a Mac Desktop H O W I C O N N E C T BUSINESS DATA o 7x more likely to be on the school board o 3x more likely to be health and fitness teachers *Consumers seen in the last 30 days
  14. 14. © 2015, Conversant, Inc. All rights reserved.14 Customer List Customer List Single DMP for display / mobile BlueKai LiveRamp / Axciom / etc. DSP or DMP Media Delivery Media Delivery o Offline-based profiles with scale result in higher match rates (80%+ vs 30-55%) o Fewer stages with user syncs means a larger pool is retained for messaging o Unified individual profiles in Conversant DMP enable cross device messaging and tracking MATCHING AND REACH
  15. 15. © 2015, Conversant, Inc. All rights reserved.15 Key Findings • Of the entire 79,129 conversions, 34% occurred on a channel other than the last messaged channel • Of the 29,435 Smartphone/Tablet attributed conversions, 90% occurred on a device other than the last messaged channel • In practice, the 34% of “cross-channel” conversions would either be misrepresented in a cookie-based report or missed altogether CONVERSION CHANNEL Last Messaged Device (Pre-Conversion) PC Tablet Smartphone All Channel Conversions DELIVERY PC 49,107 122 465 49,694 Smartphone 20,221 1,700 823 22,743 Tablet 5,168 99 1,425 6,692 Total 74,495 1,921 2,713 79,129 ATTRIBUTION CONVERSION REPORTING
  16. 16. © 2015, Conversant, Inc. All rights reserved.16 DATA DONE RIGHT  Profiles Built Around Known Individuals - Not Cookies  Transactional Deterministic Match To Link Devices - Not Guesswork  Single Customer View Across Display and Mobile – No Householding  Richer Customer Insights – Combine Offline and Online Data  Attribution and Measurement – Optimize and Learn  A Platform That Can Deliver Scale – Driving Reach and High Match Rates
  17. 17. © 2015, Conversant, Inc. All rights reserved.17 Thank You!
  18. 18. © 2015, Conversant, Inc. All rights reserved.18 CONVERSANT CASE STUDIES
  19. 19. © 2014, Conversant, Inc. All rights reserved.19 MOBILE BRAND BUILDER AUTOMOTIVE THE PROGRAM RESULTED IN $5.76M NEW REVENUE C A S E S T U D Y: M O B I L E B R A N D B U I L D E R Client: Buick Lacrosse Objective: Increase brand awareness and purchase intent for the Buick LaCrosse Solution: Conversant built a custom captivate smartphone unit to provide unique touchpoints for interaction with the Buick brand in the form of an attention-grabbing game. • 17% lift in likelihood to recommend • 3.9% average CTR • 2.7 minutes average interaction time for those who engaged with the ad • 21% lift in brand awareness 33% Lift in purchase intent
  20. 20. © 2014, Conversant, Inc. All rights reserved. DRIVING MOBILE ENGAGEMENT FOR A NEW TV SERIES PREMIERE 20 CAMPAIGN OBJECTIVE A leading TV network approached Conversant to introduce a new reality show across mobile devices. The goals included building brand awareness, driving video views and driving viewership within the target audience of males, ages 18-49 with a HHI of $75,000+ and college degree. o Leveraged proprietary & 3rd party data to create a custom mobile audience centered around male targets, ages 18-49 with a HHI of $75,000+ and college degree/higher education o Custom HD Video Trailers across smartphones and iPad inventory o Custom Full-Screen Video Ad Boosters aimed at driving engagement and ultimately increasing viewership WHAT WE DID DID IT WORK? The 6 week campaign yielded the following results: o 2.23% CTR o 67,000+ Add to Calendar, Twitter and Facebook actions o 10 Billion impressions served o 28,000 hours of brand exposure CASE STUDY: MOBILE VIDEO 2.23% CTR Mobile Video Booster 0.89% CTR Facebook Button 1.14% CTR Add-to-Calendar Button
  21. 21. © 2014, Conversant, Inc. All rights reserved. OFFLINE AND ONLINE CONVERSIONS CASE STUDY 21 CAMPAIGN OBJECTIVE A leading wireless carrier wanted to drive online and in- store carrier switches via Mobile advertising Goals were to drive offer awareness and in-store/online visits/conversions . THE STRATEGY The Mobile Campaign: Leveraged proprietary & 3rd party data to create & target a custom mobile audience centered around: • Customers of competitive carriers • Proprietary behavioral characteristic • Projecting national store visits and brand impacts based upon PLACED validated 3rd party panel data MEASUREMENT The 3 week campaign yielded the following results: • 387K stores visits with a store conversion rate of 0.47% that was directly measured from our matched group • Efficient cost per store visit of $0.26 • PLACED’s Telecomm average cost per store visit was 74% more efficient than the norm • Drove 6.22% lift leading to 23,000 incremental store visits in saturated telecomm market where lift is only seen 60-70% of the time. CASE STUDY: MOBILE MAX EXPOSURE 387K Store Visits 26₵ Cost/Retail Visit $1.19 Telecomm Industry Norm vs.
  22. 22. © 2014, Conversant, Inc. All rights reserved.22 CONVERSANT REMARKETING MAJOR DEPARTMENT STORE C A S E S T U D Y Program Dates: 2012-Ongoing Problem: Marketer identified existing remarketing solution optimizing to clickers did not generate incremental revenue at scale. Conversant Solution: • Doubled reach compared to prior remarketing solution • Cross-device, dynamic messaging strategy with variety of messaging including multi- product, Lifestyle, Promo, and Co-op treatments. • Demonstrated incremental revenue by providing marketer validation files of messaged test/control purchases 14.1M UNIQUES MESSAGED 20+% INCREMENTALITY 504K ONLINE MESSAGED PURCHASES $20+M INCREMENTAL REVENUE THE PROGRAM RESULTED IN
  23. 23. © 2014, Conversant, Inc. All rights reserved.23 CROSS-DEVICE BRAND BUILDER ENTERTAINMENT C A S E S T U D Y Client: Leading entertainment company Objective: A leading movie production company with a new movie release wanted to increase awareness and engagement of the movie trailer and drive traffic to the movie’s website. Solution: Conversant used its extensive cross-device media reach across mobile web, in-app and display to deliver a cross-device video campaigns targeting 18-35 year old males who are likely to purchase computer programs, TVs, video games, event and movie tickets. . THE PROGRAM RESULTED IN 50% LIFT IN CTR COMPARED TO DISPLAY ONLY 1.24x Lift in VCR 1.01% 1.52% Display Only Mobile & Display
  24. 24. © 2014, Conversant, Inc. All rights reserved.24 Conversant Private Exchange
  25. 25. © 2014, Conversant, Inc. All rights reserved. What programmatic media means to Conversant: Automated buying of Conversant offering through a Deal ID. CONVERSANT DATA & TARGETING UNIQUE REACH OUTSTANDING AD QUALITY PROGRAMMATIC BUYING SIMPLICITY & EFFICIENCY PREMIUM INVENTORY CROSS-DEVICE IDENTIFICATION EXCHANGE coming soon CONVERSANT HAS MADE IT EASY FOR PROGRAMMATIC BUYERS TO ACCESS OUR UNIQUE OFFERING
  26. 26. © 2014, Conversant, Inc. All rights reserved. HOW IT WORKS: BUYER PATH CONVERSANT PRIVATE EXCHANGE VIDEO CROSS-DEVICE DISPLAY MOBILE SUPPLY SIDE PLATFORMS (SSP) Your DSP

Hinweis der Redaktion

  • Open with trivia to get them thinking about how the world has truly gone mobile, and because of these we need to use data correctly to target effectively
  • Open with trivia to get them thinking about how the world has truly gone mobile, and because of these we need to use data correctly to target effectively

  • Open with trivia to get them thinking about how the world has truly gone mobile, and because of these we need to use data correctly to target effectively

  • Open with trivia to get them thinking about how the world has truly gone mobile, and because of these we need to use data correctly to target effectively

  • Todays consumer is Omni-channel, and always on.
    5 hours on digital, more time now spent on mobile tablet than all PC. Most are trading devices, we’re all mobile.

    Core issue; most digital marketing platforms are built on cookies alone. There are no cookies in mobile, Apple allows no 3rd party cookies in ios, oh, and by the way, cookies get constantly blown out.
  • We asked him what his browsing history looked like, and this is what we know with ONLY Scott’s browsing history:

    He watched three videos on the new Tesla model
    He searched for One Direction show tickets and tiaras
    He spent over 90 minutes/day on celebrity gossip apps
    And researched cosmetic ingredients
    He browsed hockey equipment

    With browsing behavior only, you MIGHT assume Scott is a terrorist cross-dressing boy-band fan BUT, <<Click>>
  • Let’s use a real-life example of why we need to see more sides of a person to truly understand them as a consumer. Conversant’s VP EC Mobile sales, Scott Dornblaser, graciously volunteered his recent browsing behavior to be tracked…..

    We asked him what his browsing history looked like, and this is what we know with ONLY Scott’s browsing history:

    He watched three videos on the new Tesla model
    He searched for One Direction show tickets and tiaras
    He spent over 90 minutes/day on celebrity gossip apps
    And researched cosmetic ingredients
    He browsed hockey equipment

    With browsing behavior only, you MIGHT assume Scott is a cross-dressing boy-band fan BUT, <<Click>> until we understand all six sides of him as a person, do we really understand him as a consumer.

    Through understanding all six sides we can see that he’s a father, that he is raising tween girls in the home but still finds time to play hockey with is friends. Until we understand Scott’s other five sides – His demographics, his purchase behavior, what he shares and his relationships with different brands, and how he connects across multiple devices are we able to reach him person-first through these richer consumer insights.


  • BUT, <<Click>> until we understand all six sides of him as a person, do we really understand him as a consumer.

    Through understanding all six sides we can see that he’s a father, that he is raising tween girls in the home but still finds time to play hockey with is friends. Until we understand Scott’s other five sides – His demographics, his purchase behavior, what he shares, watches, and how he connects across multiple devices are we able to reach him person-first through these richer consumer insights.



  • We invested over a billion dollars and united 5 industry leaders into a single company and platform that could deliver the breakthroughs necessary.

    The idea is to use the vast resources and data of this new company to deliver the best possible understanding of the customer, and then empower your campaign to reach and connect with them in the absolute best ways possible.

    We united all of our companies to do just that. NewCo has spent the last two years integrating everything to create a media solutions provider that can deliver better results for your campaigns. And deliver better results whether your challenges are around driving awareness, building consideration, or fulfilling demand.

    Let me show you specifically how we’ve improved what we can do for you.

    <<NEXT>>
  • There are three basic ways to construct a user profile: using PII, through login or registration data or by using cookies or device IDs
    PII-based profiles are typical for offline data, such as CRM databases
    Most online data is collected through cookies, device IDs or user login, although some use PII as well (for example: registrations requiring name and email address)
    Matching PII data from one source to PII data to another source is fairly straight forward, as long as the same PII appears in both databases
    Matching cookie data on the same device between multiple sources requires the cookies to be synced – basically pixels needs to fire when both data bases see the same user so they can build up a matching table for the two sets of cookies
    Matching device ID data on the same device is simple since IDFA/GAID is the same for all vendors on that device
    Cross device matching gets tricky in the online space and requires either probabilistic or deterministic matching between devices and cookies
    Offline to online matching is also tricky and requires either PII, some sort of cookie/device sync using a bit of data that exists both online and offline (like a unique user ID) or is done in a less accurate way using IP addresses
    Benefits: PII and login profiles offer persistent user IDs that are linked to an individual, and it is easy to match with other data collected using the same PII, while cookie and device IDs offer better privacy protection (if a login/registration profile anonymizes all PII, then it will offer similar privacy protection to cookie-based systems, otherwise the linked PII will put them in the same category as a PII-based system)
    Drawbacks:
    It is very tricky in terms of both regulation and PR to target users in a digital marketing campaign using any system that does not protect user privacy;
    Large publishers can skirt around this using login data and an aggressive privacy policy, but users need to be logged in for it to work and it is heavily reliant on publisher scale, so only a few large platforms like Facebook are practical to most advertisers;
    Also PII and registration/login systems often rely on users to input at least part of the PII data, and if that data is erroneous or false then is can make the data unusable;
    On the other hand, cookie and device ID-based profiles are not persistent (they can be deleted, blocked or changed) and are not based around the individual (each ID could be an individual, or a group could be one person) making it difficult to track users and get a complete picture of their behaviour;
    Offline to online match rates will generally be poor due to sync rate issues

  • Keyword: Accuracy
    Our profiles are base around verified individuals, not cookies, device IDs or algorithmically generated “people”, and we know they are actual human beings because they have transacted online or offline
    We use transaction IDs, registration data and email opens to connect the offline world with the online world, which allows us to hard match devices to verified individuals
    Most other digital marketing vendors try to do this the other way around, which has a negative impact on audience fidelity
  • Conversant’s unique way of constructing individual profiles for media targeting combined with our scale means that we are more efficient at onboarding offline data right from the beginning
    Conversant’s match rate with our offline data partners that provide recent, vetted user data is 80%+ - much higher than the 30-55% match rates boasted companies like LiveRamp
    BlueKai (on the Oracle website) even recommends that clients use multiple match vendors in order to try to increase the initial offline/online match rate, which shows how limited all of the 3rd party service providers are in reach
    Because our records are matched directly to profiles in our DMP, which is integrated with all major exchanges, the entirety of the on-boarded audience is available for media messaging
    With “stack” solutions, multiple databases need to sync users and users are lost every time a sync occurs. This creates a large amount of user leakage so only a small portion of the initial on-boarded audience is available for messaging
    For example: to get a PII-based customer list into BlueKai, companies will use a provider such as LiveRamp or Axciom to match those users to cookies and device IDs. Those match providers then need to sync those users with the users in BlueKai’s database. During this part of the process, 45%-65% of the audience is lost. Once the data is in BlueKai, it needs to then be pushed onto a media delivery platform in order for the users to be messaged. This could be a DSP, Conversant, or any other media delivery platform. This is yet another sync and even more of the audience is lost. By the time the list is at the stage where users can actually be messaged, there could be low double digits to single digit percentages of the original audience retained for targeting.
    Conversant owns our own bidder, so we do not need to sync with a media delivery platform in order to message users – they can be messaged directly with profiles from our DMP
    Any blind spots that BlueKai has becomes a pool of users we cannot target an audience that passes through the BlueKai platform
    Example: We have a huge amount of visibility into platforms that block 3rd party cookies because of our ability to place 1st party cookies on devices on a massive scale (for example, we have cookies on 70% of iOS devices.) A user with a new version of Firefox and an iOS device could be completely invisible to BlueKai because both of those platforms would block their cookies. Conversant, on the other hand, would have a 90% chance of having our 1st party cookie on at least one of the user’s devices (because we would have a 70% chance of a cookie on either platform – it’s a stats thing.) Since BlueKai can’t see that user, they will not be able to pass those records on to us, no matter how good our cookie sync rates are. When we on-board a list directly, however, we do see that user because we have our cookies matched directly to their PII-based profiles.
    This is also why so much offline data available through BlueKai is modeled – it’s the only way to achieve scale once user loss is factored in to the on-boarding process for that platform
    If Bluekai is recommending using multiple matching partners to get PII-based data into their system to get maximum coverage, then why wouldn’t you also want to send us the list as well so you have one more matching partner, with proven scale and a superior process, onboarding your list for messaging?

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