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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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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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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Thunder Unveils Experience Cloud, Appoints BJ Fox as VP of Engineering

thunder creative management platform press

San Francisco, CA – (Feb 21, 2018) – Thunder, the original and leading Creative Management Platform (CMP), today announces it has expanded its offering to three enterprise products: In addition to its Creative Management Platform, Thunder now also offers Dynamic Creative Optimization and Experience Measurement. In addition, the company has added industry veteran BJ Fox to manage and scale product development. Fox brings over 20 years of experience across Internet-based software companies, ranging from startups to large enterprise companies.

The Thunder Experience Cloud is comprised of:

  • Creative Management Platform (CMP)
    • Thunder’s CMP enables users to produce brand experiences across channels and traffic them to the appropriate media platforms.
  • Dynamic Creative Optimization (DCO)
    • Thunder’s DCO personalizes and optimizes brand experiences to increase conversions and media efficiency.
  • Experience Measurement
    • Tracks and measures a brand’s customer lifetime experience, decreasing media waste and improving understanding of how ads work through creative, media and exposure data.

“We are excited to bring BJ on board as we roll out the Thunder Experience Cloud,” said Victor Wong, CEO of Thunder. “His experience in building and managing large engineering teams will be a major asset as we take our platform to the next level of scale and innovation.”

In his new role, Fox will be responsible for overseeing and growing the product development team for Thunder, which expects to grow headcount by 25% in the coming months alone.

Previously, Fox was vice president of engineering at Getjar, a late stage venture-backed mobile ad network that sold to Sungy Mobile before working at Glympse, the popular consumer app for location sharing where he built out the company’s enterprise offerings for Fortune 100 customers and partners. Prior to that, Fox was director of software development at Microsoft, where he held key roles in Windows Azure, Research, and Xbox, managing a team across three continents while driving the initial launch of Windows Azure. He also served as chief architect of Signio, an angel-funded payment startup that was purchased by VeriSign in 2000 for $820M. Most recently, he was vice president of engineering at Xevo, a connected car platform for the auto industry.

Fox said, “Thunder has long been an industry leader; the first Creative Management Platform, it is now paving the way for true people-based marketing with Experience Measurement. I have tremendous respect for Victor and am thrilled to join his team of boundary-pushing thinkers and innovators.”

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 Experience Cloud enables brands to personalize, optimize, and connect ad experiences cross-channel for people-based marketing. Leading brands such as Anheuser-Busch and McCormick rely on Thunder for its creative management platform, dynamic creative optimization and experience measurement to increase conversions and decrease media waste.

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Press Contact:
Cassady Nordeen
Blast PR on behalf of Thunder
Cassady@blastpr.com

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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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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 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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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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Thunder January Press & News Roundup

thunder creative management platform press

To achieve a better ROI from their data-driven ad technologies, brands and advertisers need to leverage the audience data from their DMP, strategize creatively around it, and execute that strategy across different audiences. Victor Wong offers Thalamus his take on the current challenges and future of the programmatic creative revolution.

Though automating marketing functions typically improves efficiency and performance for digital campaigns, human intervention still plays a vital role in its success. Learn why marketers should avoid forgoing human touch entirely within programmatic advertising in the $200M automation mistake that could happen to your brand.

January is a time of reflection and prediction. In Marketing, By the Numbers, Rob Lennon offers his thoughts on the proliferation of ad blocking and what we can do to combat it.

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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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