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?