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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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. 

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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. 

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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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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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Doubleclick ID Alternatives for my Doubleclick Campaign Manager (DCM) logs?

tl;dr DoubleClick logs are used today by marketers for verification, attribution modeling, and other analysis beyond what is available in standard DCM dashboards.  

Log-based analytics require a device or user identifier, so DoubleClick’s removal of the DoubleClick ID represents a disruption of the status quo for log-based analytics solutions.  

Fortunately, DCM logs are not the only source of log-level data, or even the best.  Brands and agencies increasingly use tracking pixels from measurement vendors that have access to deterministic IDs as a replacement for ad server logs and to support more advanced analysis. Skip to the end if you are just looking for a list of recommendations.

How important are logs in digital advertising?

What Happened

Google’s announcement last Friday that DoubleClick is removing the Doubleclick ID from its logs resulted in panic in many corners of the digital advertising world.  What is the DoubleClick ID? For that matter, what are logs and why do people use them? Confused as to what the big deal is?

Here are the answers:

Beginning on May 25, DCM will stop populating the hashed UserID field (which stores the DoubleClick cookie ID and mobile device IDs) in DoubleClick Campaign Manager and DoubleClick Bid Manager (DBM) logs for impressions, clicks and website activities associated with users in the European Union. DoubleClick intends to apply these changes globally, and will announce timing for non-EU countries later this year.

What this Means for Advertisers

DoubleClick, like most adtech platforms, provides reporting dashboards to monitor performance KPIs.  While dashboards provide a good summary on performance, they can’t answer more granular questions that marketers want of their data.  That’s why many marketers ingest logs from their ad servers and DSPs. These logs are broken out into impression logs, click logs and site activity logs.

In order to perform custom analytics with these logs, the logs need to share a common identifier, so that the marketer can tie together recorded impressions from multiple sources (DCM, DSP, etc.) that belong to the same person, as well as clicks and site actions from that person.  

That common identifier is generally the cookie ID or, in the case of mobile app ads, mobile device ID.  DoubleClick currently has a field in all of their logs called UserID that stores a hashed version of the DoubleClick cookie ID or the mobile device ID tied to an impression, a click or a site action.

By removing this field from their logs, DoubleClick is effectively ending their support for ad server logs that are used for analytics, verification, measurement, or attribution modeling. Without the UserID field, marketers can no longer tie together impressions, clicks and site actions. For example, if you were previously filtering suspicious traffic based on frequency of engagement, you will no longer be able to do so (because each row becomes unique without a deduplicating identifier).

The alternative proposed by Google is for marketers to pay to use the dashboard found in the Google Ads Data Hub.  The big issue with this approach is that the marketer has to trust Google to grade their own homework, making the marketing standard “trust, but verify” approach all but impossible.

As a result, brands and agencies using DoubleClick logs will no longer be able to independently:

  • Verify frequency by cookie or person
  • Count total ad exposure by person
  • Analyze true reach of media placements and campaigns
  • Compare reach and duplication by media placement and campaign
  • Attribute or de-duplicate conversions and clicks
  • Report on user conversion rates
  • Identify unique site traffic

What’s the Back Story

This announcement is part of two trends in the market – GDPR as a pretext for raising the walls of walled gardens, and the shift from logs to trackers to collect data for custom analytics.  

First, Google is saying that the upcoming EU law, GDPR, is forcing them to do this, something many pundits have questioned. Walled gardens are continuing to grow taller, and increasingly are leveraging privacy concerns as the pretext for doing so. Media sellers are also now further pushing their own measurement and attribution solutions in a bid to grade their own homework and prevent cross-platform comparison.  

Google has built a more full-featured measurement and attribution product that is currently in pilot with selected large brands known as Google Attribution 360, part of Google Ads Data Hub.  The announcement to remove the DoubleClick ID from logs is connected strategically to the broader release of Attribution 360 later this year. In fact, Google Ads Data Hub was even plugged in the email to agencies informing them of this change.

Second, this announcement is a reaction to the trend of measurement and attribution vendors disrupting the importance of ad server logs, making Google’s decision seemingly reasonable.

Marketers are increasingly relying on vendors to improve their accuracy through features that are not a part of the traditional ad server log. Specifically, savvy marketers want (a) cross-device graphs and (b) the ability to perform causal attribution modeling. Neither of these goals are unlocked by DCM logs today, leading to the emergence of an ecosystem of measurement platforms, each with their own trackers tied to a cross-device graph for data collection. Of course, one such vendor is Google, whose Attribution 360 offering has both of these advanced features.

As such, DoubleClick’s announcement simply represents a formal passing of the torch in responsibilities from the ad server to the measurement provider for those marketers who have already reduced their dependence on DCM logs.

Recommendations

Brands and agencies need to identify vendors who can provide tracking and measurement capabilities (full disclosure – Thunder Experience Cloud is one such vendor). This change needs to occur before current dashboards built off of DCM logs become disrupted.  

If you are evaluating vendors to address this change, we recommend the following as requirements:

  • Ability to source data from impression trackers rather than logs
  • Visibility across all ad exchanges (several vendors are classified as DMPs by Google and thus blocked from tracking impressions on AdX)
  • Can provide the following categories of metrics:
    • Frequency by person and total ad exposure by person
    • True reach and overlap of media placements and campaigns
    • Attribution using any configurable attribution model, both position-based and algorithmic
  • Media agnostic (be wary of solutions that grade their own homework)
  • Independent of any arbitrage of audience data segments that are evaluated by their measurement product

In addition, some “nice to haves” include:

  • Backed by a deterministic people-based graph
  • Can provide reliable logs with interoperable customer ID to other identified vendors within the brand’s adtech stack if requested
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Panel discussion at OMMA Programmatic –  Can Robots Fix Programmatic Creative?

Thunder CEO Victor Wong had the pleasure of sitting in on a panel about programmatic creative at this year’s OMMA Programmatic event.

“Less than 1/3rd of online users today feel that internet advertising is relevant to them.

“Through programmatic creative and using data, if we can bring that up to 50%, that’s going to lead to hugely impactful outcomes for our clients and hopefully cut down on ad blocking and improve the way people perceive advertising in the future,” said Andrew Sandoval, Director, Biddable Media at The Media Kitchen in an opening statement.

Watch the video recording:

Below is a summary version of the main takeaways from the talk.

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What is the difference between dynamic creative and data-driven creative?

dynamic creative vs data-driven creative

Dynamic creatives are ads that can change content on the fly at any time.

Data-driven creatives use information about a customer to inform creative messaging.

Thus, a creative can be dynamic and data-driven if the same creative puts content in the ad that can be changed at any time, AND the content was chosen is based on data.

A creative may be dynamic but not data-driven if it simply changes content without regard to who the targeted user is.

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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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Where Next? Finding Flite Alternatives and Competitors After the CMP Shutdown

Flite alternatives and competitors

Snap’s acquisition of Flite last December led to all Flite ads going dark, leaving some advertisers scrambling to evaluate Flite alternatives and competitors. Although Flite’s website remains online, the creative management platform (CMP) has closed its doors for good.

Ad tech is often considered an area that is oversaturated with similar technologies, and many view Flite’s exit as a positive step for the industry overall. 

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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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Programmatic Creative vs. Dynamic Creative Optimization (DCO)

programmatic creative vs. dynamic creative optimization

This post is continuously updated to reflect how programmatic creative and dynamic creative optimization (DCO) are evolving.

When people think of the relationship of programmatic creative vs. DCO, a common misunderstanding is that dynamic creative optimization and programmatic creative are different technologies.

One term is actually a subset of the other. DCO is a form of programmatic creative.

While DCO falls under the programmatic creative umbrella, but it’s not the only way to build creatives that activate the 6+ billion dollars of data in contained in programmatic media.

To illustrate this idea, let’s start with a definition of programmatic creative.

Programmatic Creative Definition

Programmatic creative refers to the set of advertising technologies that add speed, scale, and automation to the creative process. This covers ad production, dynamic ads, and creative optimization.

Programmatic media has unlocked tremendous potential in how we tell stories in paid media online. The purpose of programmatic creative is to enable data and creativity to come together to tell brand stories in a more resonant and effective way than ever before.

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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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What is People-First Marketing?

what is people first marketing

People-first marketing is both an approach and a set of marketing strategies that focus on personalizing customer touchpoints across channels to drive engagement and maximize campaign performance.

The proliferation of digital channels, devices, and platforms have led to a vast shift in consumer behavior and expectations. Gone are the days where advertisers can mass send out generic marketing messages aimed at everyone–which in reality, cater to no one.

Consumers have gained more control over their own journey to purchase, which means brands and advertisers need to do a better job of identifying and reaching the right audience at the right moment. Understanding who your specific target audiences are, as well as their needs, wants, and pain points help put each customer at the forefront of your marketing strategy.

Targeting the right audience, however, is just one part of the equation.

Executing a people-first strategy also means understanding how to capture your audience’s attention with the right message. To activate the $6 billion dollars spent on targeting technologies like DSPs and DMPs, brands and advertisers need to focus on delivering a personalized message that captures their audience’s attention at the right time in their customer journey. Delivering a personalized creative is key to truly engaging consumers, instead of just marketing to them.

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7 Ingredients For The Perfect Programmatic Creative Management Platform

7 Key Ingredients For A Creative Management Platform

The main concepts of advertising have been around for over a century, but the emergence of programmatic creative and the creative management platform (CMP) is a phenomenon that is much newer.

A number of companies have seen incredible results from creative management platforms, including Anheuser-Busch, the biggest brewer in the world, and Intercontinental Hotels Group (IHG), the second-biggest hospitality company in the world.

Programmatic creative technologies combine well with programmatic buying, data management platforms (DMPs) and demand-side platforms (DSPs). In this ad tech stack arrangement, the CMP is the creative arm of a data-driven campaign strategy.

We’re going to explore seven ingredients that can make up the perfect creative management platform that aligns with your programmatic creative strategy. If you’re still learning about what a CMP is, check out the video below before you review the list.

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Video: Programmatic Creative vs. Dynamic Creative Optimization (DCO)

Programmatic creative refers to the set of ad technologies that enable data-informed, software-assisted creative executions. The purpose of programmatic creative is to unify data and creativity to drive hyper-relevant ads to each audience.

Dynamic Creative Optimization (DCO) falls under the programmatic umbrella, but is not the only way to solve creative problems for programmatic media. Both Dynamic Creative Optimization and Creative Management Platforms (CMPs) maximize the impact of the creative within programmatic and direct advertising through very different approaches.

In this video, learn how programmatic creative activates audience data through two main technologies: Dynamic Creative Optimization and Creative Management Platforms.

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Video: What is a Creative Management Platform (CMP)?

Creative Management Platforms (CMPs) are a class of programmatic creative technologies that enable digital marketers to tailor, test and optimize display and social ad campaigns.

Leveraging a CMP allows programmatic advertisers to create hyper-targeted ads at scale, dramatically amplifying the creative output of a team and the performance of each campaign.

In this video, learn more about the benefits of using a Creative Management Platform and how they compare to Dynamic Creative Optimization technologies (DCOs).

If you like this video, you might like this post: 7 Ingredients For The Perfect Creative Management Platform.

And if you want to learn more about programmatic creative, download our free eBook: The Essential Guide To Programmatic Creative Technologies.

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Video: Programmatic Display – 5 Creative Optimization Tactics to Drive Performance

A report published by Yahoo! in 2014 found that personalized ads are 54% more engaging and 45% more memorable compared to generalized creative.

To continuously drive higher programmatic display performance, leveraging the right creative optimization tactics will not only lead to more engaging ads that strongly appeal to your target audiences but also higher conversion rates.

Watch this video to learn 5 creative optimization strategies to maximize the ROI of your programmatic display campaigns.

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