GDPR vs California Consumer Privacy Act (CaCPA) Detailed Comparison

GDPR v. California Privacy Laws

If you’re a large digital marketer, ad platform, or agency that reaches any consumer in the EU or California, you will need to soon comply with both GDPR which went into effect in May 2018 and the new California Consumer Privacy Act (also known as CCPA or CaCPA) which will go into effect January 2020. While GDPR is generally seen as more stringent than CaCPA, there are still some nuanced differences and compliance with one doesn’t mean compliance with the other.

In Part I of this series, Thunder summarized the key differences and similarities between the two sets of laws.

In this Part II of the series, Thunder has provided a detailed breakdown for digital marketers, agencies and ad platforms comparing GDPR and California Consumer Privacy Act (known as: CCPA or CaCPA for short) to make sure they are compliant with both:

Jurisdiction

GDPR: Applies to data collection of persons in the EU (whether the company is based there or not)

CaCPA: Applies to data collection of California residents (whether the company is based there or not)

Personal Data

GDPR: Any information relating to an identified or identifiable natural person.

CaCPA: Any data that “identifies, relates to, describes, is capable of being associated with, or could reasonably be linked, directly or indirectly, with particular consumer or household.” A “consumer” is a California resident as defined by tax code. The “personal data” definition is developed through examples, exclusions and cross-references to other laws. Data subject to HIPAA is exempted from CaCPA but data subject to FCRA, and GLBA is excluded only to the extent those statutes conflict with the CaCPA.

Data Subject

GDPR: An identified or identifiable natural person. An identifiable natural person is one who can be identified, directly or indirectly, in particular by reference to an identifier such as a name, an identification number, location data, an online identifier or to one or more factors specific to the physical, physiological, genetic, mental, economic, cultural or social identity of that natural person.

CaCPA: A California resident as defined under California tax law.

Data Controller

GDPRThe natural or legal person, public authority, agency or other body which, alone or jointly with others, determines the purposes and means of the processing of personal data; where the purposes and means of such processing are determined by Union or member state law, the controller or the specific criteria for its nomination may be provided for by Union or member state law.

CaCPA: For-profit controllers that meet ONE of the following thresholds: (1) Annual gross revenue over $25M; (2) Buys/sells or receives/shares for “commercial purposes” the data of 50,000 California residents; or (3) Derives 50% of revenue from “selling” personal data of California residents. If a controller qualifies under the thresholds, parent companies and subsidiaries in the same corporate group operating under the same brand also qualify.

Processor

GDPR: A natural or legal person, public authority, agency or other body that processes personal data on behalf of a controller. The GDPR also defines a “third party” as a natural or legal person, public authority, agency or body other than the data subject, controller, processor, and persons who, under the direct authority of the controller or processor, is authorized to process personal data.

CaCPA: A “service provider” is a for profit entity that acts as a processor to a “business” and that receives the data for “business purposes” under a written contract containing certain provisions. The CaCPA uses the term “third party” to refer to entities that are neither business nor service providers.

Sensitive Data

GDPR: Per Article 9: Processing of personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, or trade union membership, and the processing of genetic data, biometric data for the purpose of uniquely identifying a natural person, data concerning health or data concerning a natural person’s sex life or sexual orientation is prohibited.

CaCPA: Sensitive data is not addressed.

Transfers of Personal Data

GDPR: Any transfer of personal data that are undergoing processing or are intended for processing after transfer to a third country or to an international organization shall take place only if the controller and processor comply with the conditions set forth in Articles 44-50. Transfers on the basis of an adequacy decision and methods such as Binding Corporate Rules, Contract Clauses, etc. or in the case of EU-US transfer, the Privacy Shield.

CaCPA: Cross-border data transfers are not restricted. All transfers to “service providers” require a written agreement containing certain provisions (that is, there is the CaCPA equivalent to Article 28 of the GDPR).

Data Portability

GDPR: Per Article 20, the data subject has the right to receive the personal data concerning him or her, which he or she has provided to a controller, in a structured, commonly used, and machine-readable format and have the right to transmit that data to another controller without hindrance from the controller to which the personal data has been provided.

CaCPA: There is a limited recognition of this right under the CaCPA. Cal. Civ. Code Section 1798.100 provides that data subjects that exercise their right to access, must receive the data “by mail or electronically and if provided electronically, the information shall be in a portable and, to the extent technically feasible, in a readily useable format that allows the consumer to transit this information to another entity without hindrance.” There is a related and somewhat contradictory provision on this under Cal. Civ. Code Sec. 1798.130(a)(2).

Consent

GDPR: Opt-in approach requiring informed, freely given, and unambiguous consent

CaCPA: Opt-out approach (for data being sold to 3rd-parties) that doesn’t require consent for adults; however users can ask that their data be deleted

Penalties

GDPR: Under Article 83: • Up to 10 000 000 EUR, or in the case of an undertaking, up to 2 percent of the total worldwide annual turnover of the preceding financial year, whichever is higher for infringements of obligations such as controllers and processors, the certification body, and the monitoring body. • Up to 20 000 000 EUR, or in the case of an undertaking, up to 4 percent of the total worldwide annual turnover of the preceding financial year, whichever is higher for infringements of obligations such as principles of processing, conditions for consent, data subject’s rights, transfer beyond EU, etc. • Under Article 84, each member state can lay down the rules on other penalties applicable to infringements of the GDPR in particular for infringements that are not subject to Article 83, and can take all measures necessary to ensure that they are implemented.

CaCPA: No private right of action for most provisions with the AG of California taking the role of DPA and being able to impose civil penalties up to $7,500 for each violation with no maximum cap. Violators may avoid prosecution by curing alleged violations within 30 days of notification. For certain data breaches there is private right of action with statutory damages set between $100 and $750 per data subject per incident with a requirement to notify the AG before filing a lawsuit and refraining from pursuing the action if the AG office prosecutes within six months of the notification.

Thunder’s Role

Thunder Experience Cloud enables the advertising ecosystem to balance consumer interests in privacy with commercial interests in data-driven advertising. Thunder helps ad platforms prevent data leakage, consumers protect privacy, and advertisers obtain transparency through its anonymized people-based measurement solution. Ask us how to protect consumer data while supporting data-driven advertising if you’re interested to learn more.

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Webinar: Surviving the Doubleclick ID Loss

Alongside Adweek and Neustar, Thunder engaged in a webinar on the topic of the upcoming Doubleclick ID loss in 2019 and how to prepare for it if you’re a data-driven marketer. Learn what sort of advertiser needs to consider switching to an open ID and who is better off sticking with Google’s ID. Watch the full presentation and discussion below:

More on the Ads Data Hub series

  1. What is Google’s Ads Data Hub and is it right for me?
  2. How does Google’s Ads Data Hub Affect My Data Management Platform (DMP)?
  3. How does Google’s Ads Data Hub Affect My Analytics?

 

 

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Neustar and Thunder join forces to deliver better customer experiences, powered by people-based intelligence

SAN FRANCISCO, Aug. 28, 2018 (GLOBE NEWSWIRE) — Thunder Experience Cloud, the leader in people-based ad serving, and Neustar Marketing Solutions (a division of Neustar, Inc.), the leading unified marketing intelligence platform for marketers, today announced the integration of Thunder’s people-based ad server with the Neustar Identity Data Management Platform (IDMP) and the Neustar MarketShare solution. The partnership will enable brands and agencies to quickly customize ad creatives to each customer, as well as measure performance for real-time optimization.

Thunder’s dynamic creative optimization (DCO) solution is a people-based, dynamic ad server that enables advertisers to factor in data signals such as CRM, weather, device type, time, media exposure, and now, audience data from large Data Management Platforms (DMP) like Neustar.

Customers of Neustar and Thunder will be able to target creative messaging for individual, real people and audience segments across digital channels such as display, video and mobile. By synchronizing people IDs on the open web, they can achieve a higher level of personalization, consistency and accuracy, eliminating irrelevant or redundant advertising.

In addition, Thunder’s people-based Experience Measurement solution tracks the performance of ads from exposure to viewer to conversion to allow for a high level of optimization. From there, joint customers can quickly and easily activate media by person tracked on the open web through the Neustar IDMP. This people-based data set will also be integrated within the Neustar IDMP and the Neustar MarketShare solution.

“Advertisers must be able to have a clear view of how their marketing performs across channels – which creatives and messages are being shown to whom, when and where. Neustar is dedicated to giving the industry access to independent and accurate media exposure data, ensuring brands and agencies have the tools they need for personalized, measurable experiences at scale,” said Steve Silvers, General Manager, IDMP, Neustar.

“There is no excuse for a bad ad,” added Victor Wong, CEO of Thunder. “This integration is another step toward ensuring every ad meets the highest standard of relevancy, frequency and impact, ultimately creating a better customer experience.”

About Thunder:
Thunder solves bad ads. Thunder Experience Cloud enables enterprises to produce, personalize, and track their ads cross-channel to achieve the right consistency, relevancy and frequency. Consumers maintain privacy, publishers safeguard data, and brands gain transparency through Thunder for a better ad experience for all.  To learn more visit: https://www.makethunder.com/

About Neustar Marketing Solutions
Neustar, Inc. helps companies grow and guard their business in a connected world. Neustar Marketing Solutions provides the world’s largest brands with the marketing intelligence needed to drive more profitable programs and to create truly connected customer experiences. Through a portfolio of solutions underpinned by the Neustar OneID® system of trusted identity and through a privacy by design approach, we enhance brands’ CRM and digital audiences, enable advanced segmentation and modeling, and provide measurement and analytics all tied to a persistent identity key. Neustar’s position as a neutral information services provider, and as a partner to Google, Facebook and Amazon, provides marketers access to the most comprehensive customer intelligence and marketing analytics in the industry. More information is available at www.marketing.neustar.

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How does Google’s Ads Data Hub Affect My Data Management Platform (DMP)? (Part II of the Ads Data Hub series)

Note: We provided an overview of Ads Data hub in Part 1. In this post, we look at how Ads Data Hub will impact DMP’s in general.

Data management platforms (DMPs) power the marketer’s ability to track, segment, and target audiences across programmatic media. Leading DMP solutions include Salesforce DMP (previously known as Krux), Neustar IDMP, Oracle BlueKai and Adobe Audience Manager

If you weren’t paying close attention, you may not realize that the changes Google have announced have blown a hole in your DMP.

 

Two major capabilities are affected by the pending DoubleClick ID removal from logs and push toward using Google’s Ads Data Hub: (1) segmentation and (2) frequency capping.

First, marketers currently use DMPs to create new audience segments based on media exposure. A DMP can keep track of media exposure if its own tags/pixels can run with the ad, but on many publisher inventory such as Google’s Ad Exchange, DMPs are banned from running their code. These publishers are worried about data leakage, which happens when the DMP pixels proprietary audiences on media (such as sports lovers on ESPN.com) and purchased these users elsewhere without paying the publisher.

Historically, the DMP could still get a record of media exposure from the ad server such as DoubleClick, which would share data on who saw the ads running. Using DoubeClick’s data, the marketer could then still segment audiences within the DMP based on who saw the ad, who converted, etc.

Now that Google has discontinued the sharing of logs with IDs, DMPs are no longer able to see media exposure on either inventories on which they are explicitly banned and or inventories where they are allowed to operate but that Google’s DoubleClick ad server is used by the advertiser. If DMPs are to continue to be useful to the marketer, they will need a new source of data.

Second, some marketers use DMPs to create frequency caps across media platforms. By getting their pixel/code to run with an ad, or by ingesting ad serving logs, DMPs can count impressions exposed to a particular user ID and then send a signal to platforms like DSPs to stop buying a user after a certain amount of exposure. However, without log level data, DMPs will not be able to count frequency for inventory in which they are banned, leading to less accurate frequency measurement and therefore less precise frequency capping.

How do I keep my DMP running at full performance?

Marketers who have invested in a DMP and want to keep its capabilities at full power would be advised to either buy more digital media that allow DMP tracking or find an alternative ad tracking or serving solution that can data transfer log files to the DMP. A combination of these two strategies would allow a brand to continue using its DMP to its fullest by giving the DMP the complete picture of ad exposure tied to person.

If you want to add an independent ad tracker to your DoubleClick stack or to keep powering your DMP with data, talk to Thunder about our Experience Measurement solution. 

More on the Ads Data Hub series

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What is Google’s Ads Data Hub and is it right for me? (Part I of the Ads Data Hub series)

What happened to DoubleClick?

Most marketers today use DoubleClick Campaign Manager (DCM) as their primary ad server for delivering ads and tracking ad exposure to conversion. The largest advertiser and most sophisticated advertisers relied on DCM data to do analytics, attribution, and media activation.

These advertisers would “data transfer” log-level data (the raw data for each impression rather than the aggregate data that hides user-level and impression-level information) to their data management platform, data lakes, and vendors that do analytics or attribution modeling.

 

In April, Google announced it will no longer allow data transfer of DoubleClick log-level data with IDs. This decision effectively destroyed most of the value of the log-level data exported from DCM because advertisers wouldn’t know who saw the ads but only how often an ad in total was served. DoubleClick could be used only to verify that the total amount of impressions bought were actually delivered but all the other powerful use cases like analytics, attribution, and data management would no longer be possible with DoubleClick data.

In June, Google announced it was sunsetting DoubleClick as a brand and folding everything under Google’s brand.

R.I.P. DoubleClick.

Enter Google Ads Data Hub

At the same time, Google pushed forward its own solution to this new problem for marketers — Ads Data Hub. This product is essentially a data warehouse where ad exposure data is housed and can be connected to Google’s own solutions for attribution, analytics, and data management.

One new benefit is access to the Google ID, which is a powerful cross-device ID that uses data from users logging into Google services like Android, Maps, YouTube, etc. Previously, DoubleClick was only tracking and sharing a cookie-based DoubleClick ID, which neither connected cross-device ad exposure and conversion nor reconciled multiple IDs to the same person. For many advertisers doing log-level data analysis and activation, this new ID is a big upgrade because it provides more accurate measurement.

One major downside is that this data cannot leave Ads Data Hub. Consequently, you cannot do independent verification of Google’s attribution or analytics modeling. If Google says Google performs better than its competitors, you will have to trust Google at its word. In the past, you would at least have the raw data to apply your own attribution model if you so wanted, or to re-run Google’s calculations to verify its accuracy (since big companies are not infallible).

By extension, outside ad tech providers (such as DMPs, MTA, etc.) who may be best in-class will have a much harder time working with Google solutions. As a result, you will be dependent on Google.

To do matching of off-Google data such as other ad exposure or conversions that happen offline, Ads Data Hub now requires you to upload and store your customer data in the Google Cloud. In that environment, it can be matched with Google’s ID and tracking so you can build a Google-powered point of view of the consumer journey.

In a way, Ads Data Hub is for those who trust but don’t need to verify. It is a good solution for advertisers who today spend the vast majority (75%+) of their ad budget with Google because ultimately if their advertising isn’t working, no matter what Google says about how it is performing, it would be ultimately accountable for the results. You wouldn’t need to verify calculations to know if your ad budget is wasted.

What else can I do?

Another solution is to add independent ad serving and/or tracking in addition to or in replacement of Google. By doing so, you can still generate log-level data for Google-sold media but it will not be tied to a Google ID. Instead, you will be using your own ID or a vendor’s cross-device ID to understand who saw what ad when, where, and how often.

This approach is best suited for large advertisers who want best in class ad tech solutions to work together, and who cannot spend all their money on a single media platform to achieve their desired results. Typically brands large enough to afford data lakes, independent attribution providers, and data management platforms are the ones who will have the most to lose by moving to Ads Data Hub.

If you already realize you want to take a trust, but verify approach in your ads, talk to Thunder about our Experience Measurement solution. 

More on the Ads Data Hub series

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What CMO’s Say About Ad Experiences

Marc Pritchard famously said “It is time for marketers and tech companies to solve the problem of annoying ads and make the ad experience better for consumers.”

What do his peers think? The CMO Club has partnered with Thunder to publish a “Guide to Solving Bad Ad Experiences,” which includes a survey of over 80 CMOs and an interview with the CMO of Farmers Insurance on the impact of bad ads and how people-based marketing can fix them.

Some key findings include:
  • 74% of CMOs consider brand loyalty as most negatively affected by bad ads
  • 55%+ of CMOs consider frequency and relevancy as the top factors in bad ads
  • 78% of CMOs consider it “inexcusable” to serve ads for products the customer already bought from them
  • 71% of CMOs consider frequency capping important for ad experience but 60% aren’t confident in even their frequency counting!

Click here to download the full research report.

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What is a CMP?

CMP is the hot adtech acronym of 2018. There are actually two meanings to this term: (1) Creative Management Platform and (2) Consent Management Platform. Here’s an overview of both these products and why you may need one.

Creative Management Platform

Introduced in 2016 by Thunder, the CMP acronym original stood for “creative management platform,” a tool for producing and trafficking ad creatives. Rather than just a general purpose creative editor like Adobe Photoshop or Animate, which are applications built for a single designer to use by him or herself, CMPs are meant for an enterprise that has a scale issue with creative.

Many brands, agencies and publishers are increasingly needing to build ads in different sizes and versions for different audiences and media formats. Consequently, creative production demands have grown exponentially while most creative organizations can only scale linearly in their capability by adding more designers and programmers. Because traditional creative editors were built for highly advanced users, a creative bottleneck formed as demand went up and not enough talent or payroll existed to fill the void.

Creative Management Platforms radically simplified ad production by providing easier interfaces and automated production tasks like re-sizing. Forrester began recognizing CMPs in 2017 as part of their broader creative ad tech research which has been timed with the rise in enterprise demand for new marketing creative technologies.

Consent Management Platform

Introduced in 2018, the new CMP acronym stands for “consent management platform.” The European privacy laws known as GDPR required publishers and marketers to obtain explicit consent for certain tracking and targeting data. As a result, a new category of tools emerged to specifically help these enterprises collect and keep track of user consent.

The CMP then feeds that consent information tied to an ID to other selected partners in the digital advertising supply chain. As a result, every party in a publisher’s supply chain understands what data they may use and for what.

Which CMP do I need?

It depends if you’re looking to solve a creative problem or a data privacy problem. Talk to Thunder if you need help with your data-driven creative problems or digital creative production problems. Check out these consent management vendors if you’re looking to solve a privacy preference problem.

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Why Marketers Need More Than One DSP – Understanding The Risks

The average advertiser uses 3 DSPs.  Part #1 of this series examined the reasons digital advertisers make use of multiple DSPs in their programmatic bidding.  Of course, the use of multiple DSPs also creates its own challenges. So in Part #2 below, we look at the challenges created around frequency and bidding against oneself by using multiple DSPs, and how the smart marketer overcomes these challenges.

Don’t multiple DSPs just bid against each other for the same inventory?

When advertisers think of using multiple DSPs to bid on inventory, the most common concern that comes to mind is that the inventory between the DSPs will overlap, and the DSPs will be bidding against each other.  In other words, the advertiser will be bidding against itself, thus inflating its bids and artificially driving up media costs.

And in a world of 2nd price auctions, marketers can see why this is a scary prospect.  We discussed in detail how bidding worked in Part #1 of this series, but here’s a brief summary:

First, DSPs conduct internal auctions and then sends the winning bid to an exchange or SSP for a subsequent auction.  These DSP internal auctions are conducted on a 2nd price basis, which means that an advertiser bidding $25 for an impression will really only bid $5 in the SSP auction if the 2nd highest bid in the DSP’s internal auction was $5.  

What does this mean if the same advertiser had multiple DSPs? Well, if the 2nd highest bid for the same impression in the advertiser’s other DSP was $10, then now the SSP is choosing between bids of $10 and $5 from the same advertiser.  And if the 3rd price in the other DSP was $4, then the advertiser would have cleared the SSP auction at $4 if it had only used the first DSP.

This scenario is certainly possible, but marketers have increasingly overlooked this concern for two reasons. These reasons both stem from the rise of header bidding.

First, for all the bids that are inflated due to the use of multiple DSPs, there are as many bids that a single-DSP marketer that will lose in a header bidding world without using multiple DSPs. As was explained in Part #1 of this series, precisely because SSPs conduct 2nd price auctions, an advertiser can win an exchange’s auction, but lose the unified auction to an exchange that had a higher 2nd price that was lower than the advertiser’s actual bid price.  So, if the advertiser’s main goal is to reach its audience, then it will want to use more DSPs (and win more internal auctions). This inevitably translates to more exchanges submitting the advertiser’s winning 2nd price bid to the header bidding unified auctions, and more wins overall.  

Is this bidding against oneself?  Perhaps, but with header bidding, this is often required to simply win enough auctions to achieve desired scale.

Second, header bidding is bringing about a seismic shift in real-time bidding from 2nd price auctions to 1st price auctions within SSPs and exchanges in order to eliminate this scenario in the first place.  Since header bidding unified auctions select the highest price submitted by participating SSPs and exchanges, SSPs and exchanges are incentivized to maximize the chance of winning the auction, which means submitting the bid with the highest price. In practice, they follow 1st price auctions and submit the winner with their 1st price bid, rather than the 2nd price.  Many SSPs, such as Pubmatic and OpenX, are now following this practice for precisely this reason. Once SSPs and exchanges are using 1st price auctions, the risk of inflating one’s bid goes away as long as an advertiser bids the same amount for the same category of inventory across their multiple DSPs.

How to control frequency with multiple DSPs?

A more serious challenge raised by the use of multiple DSPs than inflating bid prices is the loss of control over ad frequency.  And here, this challenge remains largely underserved, even if the demand for solutions continue to grow among large advertisers.

The main reasons why managing frequency of ads served to individuals matters are (i) to limit the frequency of ad serving to individuals in order to reduce waste, and (ii) to avoid burnout and negative brand associations from over-exposure.  We have all seen bad ad experiences where a brand bombards us with the same ads. So when using a single DSP, advertiser often follow the best practices of capping frequency by day (otherwise known as pacing) and by month, campaign duration or user’s lifetime (to limit the overall exposure to a brand’s advertising).  

However, when using multiple DSPs, frequency capping becomes impossible to accomplish on the DSP level (since the DSP’s don’t actually talk to each other). What solutions are there?

One solution is to control frequency capping on the ad server.  Doubleclick Campaign Manager supports frequency capping, but rather than suppress media buying (as a DSP would via frequency capping) DCM serves a blank ad. This solution is pretty unsatisfying to the advertiser, as it results in significant wasted media spend.  

DMPs, such as Adobe Audience Manager and Oracle BlueKai, claim to offer cross-DSP frequency capping, by tracking ad impressions and then suppressing users via existing integrations with DSPs.  It’s not uncommon to use a DMP to create suppression audiences, so this seems like a natural extension of this capability. Unfortunately, Google blocks DMPs from tracking impressions on GDN inventory.  Currently 14 DMPs are blocked by Google from tracking impressions in GDN. Since Google touches a significant portion of display inventory, frequency capping becomes much less useful without cooperation from the Google ecosystem.

We expect the use of multiple DSPs to be a growing trend for major advertisers that require scale given the evolving mechanics of real-time bidding auctions. Spurred on by this new trend, these same advertisers who need scale will also be the ones most concerned with solving for control over frequency. Stay tuned for solutions that emerge in the marketplace.

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Why Marketers Need More Than One DSP – Understanding Demand Side Platforms

The average advertiser uses 3 DSPs.  There are strong reasons for digital advertisers to make use of multiple DSPs in their programmatic bidding – if you have wondered why advertisers use multiple DSPs, then Part #1 of this explainer is for you.  

Of course, the use of multiple DSPs also creates its own challenges. So in Part #2, we will look at the challenges created around frequency and bidding against oneself by using multiple DSPs, and how the smart marketer overcomes these challenges.

Why do Marketers use Multiple DSPs?

The primary benefits to advertisers of using multiple DSPs are: (i) differentiated DSP features which are needed to execute each campaign, (ii) accessing DSP-specific audience data, and (iii) scaling out the reach of campaigns. Let’s deep dive into each reason.

Benefit #1: Competition among DSPs around Features and Take Rates

DSPs are differentiated in many ways.  One key area is their take rates – the percentage of media spend they charge advertisers.  Another is that DSPs vary in ease of use and level of support. For example, AppNexus has lower take rates than others, but also offers less hands-on support and a powerful but complicated API.  The Trade Desk and MediaMath, conversely, are well known for their customer education and easier-to-use interface. The targeting options they offer and the reporting and analytics available for media insights also vary between each platform.  

By employing multiple DSPs, trading desks also are able to pressure the DSPs to add features and lower take rates by moving spend across DSPs easily.  Most recently, some DSPs have agreed to increased transparency by revealing the fees charged by exchanges, and SSPs that provide the ad inventory. This is a great example of DSPs accommodating customer demands in a competitive environment.

Benefit #2: Audience Data

Many DSPs have unique sources of audience data.  DoubleClick Bid Manager, of course, brings data on users of Google Display Network sites to make targeting options available for AdX sites (most of AdX inventory is GDN) that are not available in other DSPs.  Amazon Audience Platform brings audience data unique to Amazon. MediaMath has a 2nd party data co-op called Helix that benefits many advertisers. Some DSPs, like AppNexus and The Trade Desk, offer IP-range targeting.  

Marketers may be running different strategies with various campaigns, and leveraging multiple targeting options across DSPs empowers them to do so.

Benefit #3: Scale

Ultimately, the primary driver for using multiple DSPs may be the challenge of achieving scale in large budget campaigns with only a single DSP.  A trading desk may simply be unable to spend the budget for a target audience in a large campaign without using additional DSPs.

Why is that?  It’s complicated.  But the explanation below breaks it down.

First, bidding on multiple DSPs increases the odds of winning auctions.  

How?  There’s a couple reasons:

Each DSP conducts its own internal auction before submitting a winning bid to an exchange, which then conducts its own auction to decide which DSP wins.  An advertiser can lose an internal auction in one DSP (for example, DoubleClick Bid Manager), and win an auction in another DSP (say, AppNexus) for the same ad impression.  That’s because DSPs select winning bids not based on bid price alone, but also on the profile of the user and performance factors specific to each advertiser (whether the viewer is likely to click on the ad).  As such, one strategy some trading desks pursue to maximize their chances of winning is to intentionally add a smaller DSP to the mix because they will face less competition winning that DSP internal auction for this reason.

But even once an advertiser wins the DSP auction and the exchange auction, there is increasingly another auction that comes next that they might still not win – the header bidding unified auction.  Before header bidding, publishers would run an auction through a single exchange, and if the winning bid is rejected for some reason, it would run a subsequent auction through another exchange, all in a waterfall process.  With header bidding, publishers run a unified auction across multiple exchanges. Because the exchanges conduct 2nd price auctions (the advertiser pays the price of the 2nd highest bidder), an advertiser could win an exchange’s auction, but lose the unified auction to an exchange that had a higher 2nd price but lower than the advertiser’s actual bid price.  So, the more DSPs with the advertiser’s bid, the more exchanges will have the advertiser’s winning bid, the better chance the advertiser will win header bidding unified auctions.

Here’s an example auction to put this in illustration:

DSP A: The bids are: Advertiser A – $2.00, Advertiser B – $1.00, and Advertiser C – $0.50 -the winning bid is Advertiser A – $1.00 (price paid by Advertiser B)

DSP B: The bids are: Advertiser C – $1.50, Advertiser D – $1.25, and Advertiser E – $0.75 -the winning bid is Advertiser C – $1.25 (price paid by Advertiser D)

The Exchange would look at DSP A and B, and decide the winner to be Advertiser D paying $1.25.

Second, DSPs can’t always bid on every impression on behalf of every advertiser. The infrastructure demands on DSPs to bid on every auction are considerable even before header bidding became ubiquitous.  With the mass adoption of header bidding, a process which duplicates the auction across multiple exchanges at the same time, DSPs’ infrastructure demands become further compounded.

As a result, DSPs can’t always factor every advertiser line item in every internal auction.  There’s a lot of confusion around whether all DSPs can see and bid on all inventory. But that’s really the wrong way of thinking about it.  

In reality, even though DSPs have access to over 90% of the same inventory, they don’t necessarily use their sophisticated and resource-intensive algorithms to score and bid on every single impression they have access to.  They have to filter (partly for cost, partly for other performance factors). This process, of course, leads us back to the first reason advertisers gain scale from using multiple DSPs – you can lose the internal auction of one DSP because you weren’t included in the auction, and win the auction of another DSP, for the exact same impression.

So, there’s several benefits to advertisers from using multiple DSPs – scale, audience data and competition for your business.  In fact, this trend has somewhat altered the trend of in-housing digital advertising operations within brands. Supporting multiple DSPs would be a lot of work for a brand, and is generally handled by trading desks, both agency trading desks and independent trading desks.  

However, the use of multiple DSPs is not without its challenges, as we’ll learn in Part #2 of this blog series.

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How to Test Ad Creatives: Beginner’s Guide to Optimize Your Display Ad Tests

There are so many creative elements that digital marketers can test in their banner ads – from value propositions to taglines to images and styling – that it can be hard to know where to start.  

A/B testing your creatives take a couple weeks to conduct to get proper statistical significant, so it’s often difficult to test every possible creative variation.  So, how should a digital marketer get started with A/B testing their banner ads?

Thunder has conducted hundreds of A/B tests, and distilled our learnings into the best practices for designing creative tests.  When followed, these tips can reduce the amount of time required to optimize your creative!

What is Test Significance?

Before we begin, we should address a commonly misunderstood concept: test significance. Marketers with no background in statistics often miss a critical fact: your tests may tell you less than you think.  

The reason is simple: our testing approach basically surveys the opinions of a smaller group of people within our target population, and sometimes, these small groups don’t completely represent the true opinion of our target population. This can expose marketers to faulty decisions that are based on false positives, that is, tests in which the apparent winner is not the actual over-performer in the target population.  

Statisticians have overcome these sampling errors with “statistical significance” to correct for this type of error, and you should always ask your A/B test vendor how they control for sampling errors including false positives.  If our goal is to learn from our creative testing, then we must ensure that our outcomes are statistically significant!

#1 Test Hypotheses, Not Ads

The first question to ask when designing a creative A/B test is this: What hypothesis do we want to test?  Common hypotheses to test include:

  • Value Proposition (ex: 10% off vs. $25 off)
  • Image (ex. red car vs. blue car)
  • Tagline (ex. “Just do it” vs. “Do it”)
  • Call to Action Text (ex. “Subscribe now!” vs. “Learn more”)
  • Single Frame vs Multi-Frame

Each test should allow you to answer a question, for example: “do my customers like 10% off, or do they like $25 off?”

Many creative tests make the mistake of testing creatives that were created independently of each other, and thus vary in more than one way.  The reason why these tests are ineffective is that the marketer can’t distill the test into a lesson to be applied to future creative design. The only learning from such a test is that the brand should shift traffic to the winning ad.  But no lessons for the next new ad result from such a test.

For example, the A/B test below is comparing different layouts, images, value propositions and CTA text all at the same time.  Let’s say Creative B wins. What have we learned? Not much, other than in this particular set of ads, Creative B outperforms Creative A.  But we don’t know why, and thus have learned nothing that we can apply to future ads.

A/B Test with No Hypothesis

 

By comparison, the following two A/B tests have specific hypotheses – “do red cars work better than blue cars?”  At the end of this test, we will learn that either red SUV’s or blue sports cars outperform the other, and can apply this learning to future creatives.

Hypothesis-Driven A/B Test: Car Type Drives Performance

 

In this next A/B test, the hypothesis is that the value proposition in the tagline drives performance.  A common first A/B test for a brand is to compare feature-based vs value-based taglines.

Hypothesis-Driven A/B Test: Value Proposition Drives Performance

 

#2 Test Large Changes before Small Changes

Large changes should be tested first because they generate larger differences in performance, so you want these learnings to be uncovered and applied first.  

Larger changes – such as value proposition and image – are also more likely to perform differently for different audience segments that small changes – like the background of the CTA button.  As such, by breaking out your A/B test results by audience segment, you can learn what tagline or image pop with particular segments, which can guide the design of a creative decision tree.

Large changes: Value Proposition, Brand Tagline, Image, Product Category, Price/Value vs Feature, Competitive Claims

Smaller changes: CTA text, CTA background, Styling and formatting, Multiframe vs Single Frame

Small changes are likely to drive small lift.  Only test this after testing bigger changes.

 

#3 Test multiple creative changes with Multivariate Test Design

Multivariate test designs (MVT) sound more complex than they are.  Multivariate tests simply allow you to run 2 or 3 A/B tests at the same time, using the same target population.  They are a statistically rigorous way to break Rule #1 above that says you should test a single change at a time.  In the case of MVT test design, you can more than one change by creating a separate creative for every combination of changes, and then learning from these tests.  

For example, if, as below, you are testing 2 changes – message and image – each of which have 2 variations, you have a 2×2 MVT test and need to create 4 ads.

Multivariate test that tests Image and Message at the same time

 

When the test is done, aggregate test results along each dimension to evaluate the results of each A/B test independently. If you have enough sample, you can even evaluate all the individual creatives against each other to look for particular interactions of message and image that drive performance.

To Summarize:

To drive more optimizations more quickly and generate demand and budget for more testing, following these simple tips:

  1. Test hypotheses that generate learnings for subsequent creative design
  2. Test large changes first and setting up multiple variate tests
  3. Test one change at a time, or set up a multivariate test framework

Happy testing!

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Digiday eBook: The ABC’s of People-Based Testing

Ad testing is meant to solve a very specific problem: Marketers are tired of launching their ads into a void, crossing their fingers and hoping for a boost in conversions. But, as Digiday reports in a new eBook, a number of widely used ad testing techniques dodge the question by failing to keep track of the individual on the other side of the screen.

As a result, people-based testing techniques are slowly but surely catching on, making it far easier for industry pros to identify real effectiveness and impact to put more media budget behind.  To learn more, check out Digiday’s Did Your Ad Work: The ABC’s of People-Based Testing.

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Fireside Chat with Wells Fargo on Customer-Centric Marketing

At a recent insider marketing event in Palo Alto, Thunder CEO Victor Wong sat down with Dane Hulquist, ‎SVP, Head of Media and Retail Channels at Wells Fargo, to talk about customer-centric marketing.

A key focus of the talk was how brands with multiple products often times end up competing as they overlap in targeting a customer, bid against themselves, and create inefficiencies. The interview below has been edited and condensed for clarity.

Hulquist spoke about Wells Fargo’s high-level cultural and strategic shift which was a move toward centralization to eliminate internal competition and focus on company goals.

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What is the difference between a CRM and DMP in cross-channel advertising?

Customer Relationship Management (CRM) systems and Data Management Platform (DMP) products are complementary and competing software for targeting people digitally.

A CRM tracks only your registered customers (prospects, loyal, and churned).

A DMP tracks unregistered and registered audiences of your digital media and advertising, which can be a larger set of user profiles than your CRM.

Both technologies are important to data-driven marketers looking to personalize advertising with unique ads to unique sets of targets via a creative solution like a creative management platform.

How do CRMs and DMPs work?

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Thunder Taps Industry Veteran as Sales Director

Former Rocket Fuel Director John Huffman to Support Leading Programmatic Creative Company’s Expansion

San Francisco, CA – (May 22, 2017) – Thunder, the original and leading Creative Management Platform (CMP), has appointed seasoned digital advertising sales executive John Huffman as Sales Director. In his new role, Huffman will be based in Dallas, covering Texas and surrounding states in response to strong market demand for Thunder’s innovative solutions.

Huffman brings over 20 years of experience in digital media sales, maximizing revenue and margin growth for major players in the space, including Adobe, Quantcast, Rocket Fuel and Yahoo!. At Adobe, he grew his business sector from zero clients to over $4 million in revenue within 18 months. During his eight years at Yahoo!, he beat his quota 18 consecutive quarters and was consistently one of the top 5 revenue performers at the company — leading one customer to spend more than $44 million annually.

“I was immediately impressed with Thunder’s offering,” said Huffman. “The company is at the forefront of programmatic creative technology, offering incredible revenue building opportunities for advertisers and agencies. Today’s marketers need a fast, scalable way to cut through the noise and reach consumers with highly personalized messages across channels. Thunder is enabling them to do that in a way that’s never been possible before.”

“We are thrilled to have John on board,” said Victor Wong, CEO of Thunder. “John’s deep data expertise, long-standing industry relationships and proven track record of expanding territories and increasing revenue will be immensely valuable as Thunder continues its rapid growth.”

About Thunder:

Named one of Forbes’ 100 Most Promising Companies in America, Thunder powers ad creative personalization, decisioning and analytics for advertisers, agencies, and publishers across the globe.

Thunder is the original and leading Creative Management Platform. Thunder CMP customers include leading Fortune 1000 companies such as Anheuser-Busch and McCormick, and acclaimed agencies like J. Walter Thompson.

 

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Press Contact:

Cassady Nordeen

Blast PR on behalf of Thunder

Cassady@blastpr.com

 

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What Is Data-Driven Marketing? – Definition, Examples and Case Studies

How data-driven marketing evolved from 2000-2017

Data-driven marketing is the strategy of using customer information for optimal and targeted media buying and creative messaging. It is one of the most transformational changes in digital advertising that has every occurred.

The rising quality and quantity of marketing data have been followed by explosive growth in the technologies for creative production and automation. These burgeoning mar-tech and ad-tech sectors now enable personalization of every aspect of the marketing experience.

Data-driven decision-making is taking the answers to questions like who, when, where, what message, and making those answers actionable.

Usage and activation of data, often in an automated or semi-automated manner, allows for a significantly more optimized media and creative strategy. This people-first marketing strategy is more personalized. It has also been responsible for driving considerable ROIs for marketers.

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What is Programmatic Creative? – Definition and Tactics

Thunder Creative Management Platform (CMP) designer
Above: Design work being done in Thunder Creative Management Platform

This article is continuously updated to reflect how programmatic creative is evolving.

Programmatic creative enables data-informed, software-assisted creative executions that deliver on the promise of modern digital marketing.

The purpose of programmatic creative is to harness the data that we’re spending billions of dollars to leverage in advertising and activate it to create a more successful execution—one that captures attention and increases campaign results. Studies suggest optimized creative can routinely boost performance by 30-50%, often more.

So to attract eyeballs, programmatic creative is solving the production and creative management challenges in producing a large volume of ads, thereby enabling messages to be hyper-relevant. Rather than showing a generalized creative, these new technologies allow the experience to be specifically tailored and customized to the viewer.

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Video: What Data-Driven Creative Means For The Future Of Advertising

Though $6 billion is invested in targeting technologies like Demand Side Platforms (DSPs) and Data Management Platforms (DMPs), programmatic advertisers have not successfully delivered the right message for the right audience.

In order to build long-term relationships, drive brand loyalty and long-term advocacy, advertisers must provide personalized messages that truly resonate with customers.

In this video, learn about how your organization can achieve data-driven creative by activating both data and technology investments.

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What Data-Driven Creative Means For The Future Of Advertising

data-driven advertising future

With over $20 billion being spent globally in programmatic advertising, data-driven creative (or programmatic creative) poses a tremendous opportunity for marketers to reach and engage potential customers.

Though 30%, or $6 billion, of this programmatic spend is invested in targeting technologies like Demand-Side Platforms (DSPs) and Data Management Platforms (DMPs), brands and advertisers have not yet successfully delivered on the promise of the right message for the right audience.

In fact, according to research by AppNexus, up to 97% of programmatic campaigns lack a targeted creative for each audience segment.activate dsp dmp data

This means that once the ad has successfully reached their potential customers, a majority of creatives are generic and untailored. Brands and advertisers need to combat this $6 billion waste by activating their data and delivering personalized messages that truly resonate with customers.

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Define Programmatic Advertising – Concept Breakdown and Insider Tactics

Define Programmatic Advertising

Programmatic advertising has been one of the most transformative advancements in marketing. It has also been one of the biggest disruptors to the ad-powered internet.

Now a dominant way to sell and purchase media, programmatic advertising is expected to rise to encompass 58% of all ad spend on digital display this year. The US is the strongest programmatic market, accounting for 62% of all global programmatic ad spend.

But what exactly is programmatic?

Here’s how we define programmatic advertising.

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