Blog and Article Sharing Corner
Edit: This article has been published as a Knowledge Base article for Adobe Media Optimizer and can be viewed here 
Smart Bulk Actions feature of AMO Social
In this article, we will discuss about using the bulk actions feature of AMO Social mainly cloning of Facebook ad sets using which you can create or clone 1000s of Facebook campaigns, ad sets and ads with just click of a few buttons and the Formulaic bid changes.
You can create new Facebook ad sets by cloning the settings from existing ad sets. You can optionally include clones of all of the ads in the existing ad sets, and either apply all of the existing labels to the ad sets/ads or change the labels.
There are 2 options to either clone the ad sets in the same campaign or create a new one. The new ad sets are created in the same campaigns as the existing ad sets, but you have the option to create new campaigns for them. When you clone the selected ads, they have the same settings as the existing ads, including the same ad group names, but naming conventions can further be tailored.
Clone Ad Set/Campaign
- From the main menu, click Social > Campaign Management > Facebook, and then click the Ad Sets tab.
- Filter out the list to include specific ad sets by selecting the check box that you want to clone.
- As shown in the below toolbar screenshot, click Bulk Actions.
- A Bulk Edit window will open, where you can choose the following:
- Clone Ad Set/Campaign
- Create new campaigns
- Formulaic bid change
- Budgets
- Change status
- Labels
- Follow these steps to clone or create new campaigns
- Specify whether or not to change the status of the source campaigns: Do not change, Pause, Delete, or Activate.
- Specify the status of the new campaigns: Pause, Delete, or Activate.
- Specify the naming conventions for the new campaigns:
- Append original name with “-clone” — To specify the naming conventions to be used for new or cloned ad sets/ ads.
- Append “Time/date stamp” — To append the time and date at which the new campaigns are created.
- Creating or Choosing Labels
- Add new label(s) - To create new labels to assign to the new ad sets, select the check box and then enter the new label names.
- Add existing label(s) - To assign existing labels to the new ad sets, select the check box and then enter the existing label names.
- Inherit labels from source adsets/campaigns - To remove inherited labels from the new ad sets, select the check box next to Remove label(s) and then enter the inherited label names to remove.
- Preview or apply the changes
- To immediately post the new ad sets and ads to Facebook, click apply.
- If there will be any errors, they are visible under Social > Campaign Management by moving the slider on the upper right from Live to Staged.
- To just preview and not to post the changes to Facebook, please click Preview. The staged view will be displayed.
- When you are previewing unposted ad sets in the staged environment you can also do any of the following changes:
i.Edit the ad set settings orad settingsif necessary.
ii.Post thead setsoradsto the social network.
- If any ad sets or ads under them cannot be posted, the" Post Status" column for that ad set or ad indicates the error.
Formulaic bid changes
Follow the same first 4 steps which we discussed above to access this option and then follow the below steps:
- The currency, optimization goal and billing event will automatically be displayed for the selected ad sets.
- Choose from the below 2 options
- Enable Facebook Auto Bid – This option allows Facebook to set bids automatically. With this option, the ad set budget must be at least 5 USD, and you won’t enter a bid. Facebook will bid as low as possible while making sure to spend the ad set budget in the specified time.
- Action - If you will uncheck the auto bid functionality, action feature will be enabled and it can be used to increase or decrease the current bids for the selected ad sets by x% or x$ as defined by the user. Furthermore, you can also set threshold levels for bids or set all ad sets bids to a particular amount.
Using bulk actions feature of AMO not only saves time when we have to create and push thousands of ad sets and ads, with settings which are similar or different, but also helps us in automating naming conventions to use for our campaigns, changing or adding new labels, updating the status of the campaigns and automating bids for thousands of ad sets and ads in one go, which otherwise would have taken 3 or 4x extra time in any other user interface such as Power Editor.
Use of dynamic parameters in AMO Social
Dynamic parameters are the best way to track and automate when building ads in AMO social. Utilizing the dynamic parameter functionality, you can give automatic naming conventions to all the ad sets and ads which you are creating picking/from the assets already uploaded in the AMO.
For example, if we need to build a campaign with 10 different ad sets having 50 ads. It is easy to create 50 ads in one go, but can be quite painful to create or change names of 50 ads which are different in terms of creative as well as changing names of ad sets which differ in details such as age and gender targeting etc.
- Dynamic Parameters can be used for Ad Set Names and Ad Names both
- Access them just by entering “{ “ (bracket) while typing the name of your AdSet or Ad
- Dynamic Parameters automatically append naming conventions from 12 different parameters and pick them including image name, placement, gender and device
Stage 1: AMO Bulk Ad Creation Workflow
Following are the dynamic parameters which are available in AMO for use in ad sets and ads names:
- {ef_adtype}
- {ef_agemax}
- {ef_agemin}
- {ef_country}
- {ef_date}
- {ef_time}
- {ef_fbcampaign}
- {ef_gender}
- {ef_image}
- {ef_placement}
- {ef_label}
- {ef_region}
Stage 2: After using this functionality for campaign creation following are the results as seen in Facebook Power Editor:
We can clearly see that AMO automatically appends related naming conventions for use by picking it from assets defined earlier in stage 1. In the above example we chose dynamic parameters – {ef_gender}, {ef_agemin} and {ef_agemax} for ad set, and {ef_image} for ads in the below screenshot.
This automation activity saves a lot of time and enhances productivity. In our example above, we can save around 10 - 15 minutes if we have to create 1 campaign – 5 ad sets – 50 ads.
The Blog Post below is from Cici DeWaal, Social Advertising Manager at Adobe
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15 Years of Defining Programmatic
Programmatic ad buying growth continues to explode. The online advertising ecosystem can be complex to navigate but for those that have embraced it programmatic simplifies the online ad buying, management and optimization process.
Looking back on how the industry has evolved, offline direct marketing tactics and principles have been applied to online ad technology and have now come full circle connecting the offline and online worlds. Because of these changes advertisers can now track and target audiences, and measure performance results across channels on and offline.
How did we get here? Looking back 15 years.
For today’s internet based businesses, online advertising channels like search and display are top channels used to acquire new customers. However, that wasn’t the case for us back in 2000. During the dot-com boom and crash, I was managing direct marketing programs for new customer acquisition at the “first online grocer,” HomeGrocer.com (Amazon was an investor, and it was later acquired by Webvan). We tested various direct marketing channels at HomeGrocer.com. Interestingly, we found that direct mail was the most efficient channel for us to profitably acquire new customers at scale (~$20M annual spend).
A lot has changed since the peak of the internet bubble in 2000 for advertisers. Here is a snap shot of today’s common direct marketing channels as they were used 15 years ago.
- Display – The first click-based banners were sold on HotWired.com in 1994. In 2000, display buying was done primarily through direct placements. Yahoo, AOL and MSN were the big portals around. Advertising.com, the ad network, came around in 2000 and was acquired by AOL in 2004.
- Search – Overture and Google were just getting started in 2000 with the auction-based, pay per click (PPC) model. Google launched AdWords in 2000, began offering PPC in 2002 and went public in 2004.
- Social – Facebook didn’t exist in 2000 and was founded in 2004 the same year they ran their first ads.
- Email – The perception on email marketing was low due to poor performance and offshore spammers clogging up inboxes with non-relevant content. The Can SPAM Act of 2003 helped to legitimize email marketing with clear opt-in and opt-out requirements.
- Direct Mail – Direct mail was a scalable and effective direct marketing channel. From magazine subscriber files to those compiled from warranty registration cards and phone books, advertisers had access to hundreds of marketing lists to test for performance (and all appended with demographic data). Database marketing was popular and allowed an advertiser to efficiently manage their prospect lists and direct mail communications.
With the growth of the internet and access to more audience data, the industry has progressed. Search, social and display channels have had tremendous growth and are now primary direct marketing channels for many businesses. Today we have a lot more options for online advertising.
Advertising 15 years later
Advertisers now have access to massive amounts of audience data, everything from online site activity and web analytics data to offline customer data, and 3rd party data. Offline CRM data and email marketing data can now be linked to programmatic ad buying platforms. Audience targeting can be done more efficiently now than ever before.
Today advertisers have access to advanced advertising technology platforms to help them manage and optimize their online advertising campaigns. Everything from search bid optimization, display ad buying and audience management, to site optimization and marketing automation tools.
All channels have shifted to programmatic (or automated) ad buying with a focus on audience-based buying. In display, audiences can be reached at the impression level through real-time bidding. Facebook enables social advertisers to reach custom, website and search retargeting audiences. In search, advertiser can now target audiences for their campaigns via RLSAs (Retargeting Lists for Search Ads).
Display Advertising 15 Years Later
For display advertising channels specifically, the industry has changed completely.
Ad exchanges revolutionized the industry. The ad exchange allows a publisher to sell their ad inventory in an auction environment, and an advertiser to bid on ad inventory in real time. The auction determines the fair price for the user impression. This process is similar to the stock market with buyers and sellers, but with display ads instead of stock.
Demand side platforms (DSPs) permit advertisers to plug into the ad exchanges to bid in real time on their key audiences at the user impression level. The DSP optimizes for the advertisers performance objective. The advertiser can bid what they believe to be the right price for each impression based on the available data they have about that user.
Data management platforms (DMPs) enable advertisers to consolidate audience data from various sources, identify and segment high value audiences, and activate those audiences for cross channel marketing on external ad targeting platforms like DSPs and site optimization platforms.
Dynamic creative optimization (DCO) allow advertisers to reach granular audiences with flexible ad creative that is personalized in real time to drive user engagement, conversions and integrated experiences.
Everything is in real time (or close to it). The entire real-time bidding process takes less than 100 milliseconds. When a user visits a website, before the ad appears, an ad call goes to an ad exchange which sends bid requests to participating demand-side platforms (DSPs). The DSPs in play then evaluate available data on that impression (audience, category, time of day, geo device, etc.) and send back bids based on what they know about the user and the likelihood they’ll convert for the advertiser. The ad exchange holds the auction and the highest bid wins. The ad served on the website was the highest bidder of the real time advertising auction. All this takes place in less than 100 milliseconds.
Real-Time Bidding Process
Are we coming full circle between the offline and online advertising worlds?
Many traditional offline direct marketing tactics and principles are still in practice and have been applied to ad tech and the online world.
In 2000, marketing databases were popular with offline direct marketers. These databases allowed for consolidation of various audiences down to individual user profiles, and expanding of audiences using 3rd party demographic, business attribute data and look-alike models. It gave the advertiser deeper insights into their audiences, enabling them to identify high value audience segments and deliver them to vendors for direct marketing channels. Does that sound like a Data Management Platform in the online world?
Direct mail letters were laser personalized with creative content (offer, message) based on the audience segment.Sound like Dynamic Creative in the online world?
We have come full circle and connected the offline and online advertising worlds by allowing advertisers to take their offline data (CRM, call center, POS), consolidate it with their online data (site visitors, web analytics) and use it for online targeting of ads.
Today marketers can meet their objectives more efficiently with Programmatic
Manual processes have given way to automated buying. CPM based selling models have moved to transparent pricing models. The massive amounts of online and offline data that is available to an advertiser can now be easily harnessed for ad targeting and optimization. Programmatic enables advertisers to buy more efficiently, reach more granular high value audiences, and as a result drive better performance.
Here is how Adobe views programmatic and some key characteristics of programmatic today.
Automated buying of ads across channels and devices
Many think of display advertising and real-time bidding (RTB) when they think of programmatic but it includes the automated buying of ads on any digital channel including Search and Social.
Data driven
Data powers programmatic ad buying. To gain the most from programmatic, it’s all about using and applying data. This includes online and offline data, and 1st, 2nd and 3rd party data. Data powers the following benefits of programmatic:
- Enables an advertiser to build and reach high value audiences
- Fuels performance optimizations
- Powers personalized dynamic experiences
- Drives automated ad buying decisions across channels and devices
Transparency
Advertisers have financial transparency into media costs by ad inventory source, and visibility into where their ads are running.
Advertising has come a long way
Today’s advertisers have access to integrated buy side tools – from audience management (DMP) to media buying (DSP) to dynamic creative optimization (DCO) – to help them most efficiently meet their online advertising objectives.
Programmatic ad spend continues to grow at a fast pace. According to IDC, global programmatic display spend will grow from $10B in 2014 to $70B in 2019. 60% of display transactions will be programmatic by 2019.
For advertisers that are embracing programmatic ad buying and leveraging their businesses audience data, the result is more efficient ad buying, better audience targeting across channels, and better performance results.
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Read the original blog post at - https://blogs.adobe.com/digitalmarketing/advertising/15-years-of-defining-programmatic/
The Blog Post below is from Pete Kluge, Group Product Marketing Manager for Adobe Media Optimizer
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Brilliant Advertising: Unlock the Power of Programmatic Advertising With the Right Creative
In 1976, Jhane Barnes designed a pair of pants that made men look so good that even John Lennon wanted a pair. Within two years, she bought a loom and, inspired by fractals — yes, fractals — became a force in the textile market. Fractals are comprised of one pattern that is repeated infinitely to create some of the most beautiful designs in nature. In 1992, to create beautiful fabric without having to spend years drawing the thousands of tiny details on her designs, Barnes applied the concept behind fractals to fashion.
She began by collaborating with mathematician Bill Jones (who specializes in software that creates patterns for wearing) and physicist and software developer Dana Cartwright (who translates Jones’s mathematics). The tools they created enabled Barnes to zoom in on nature’s fractals until she found an image that interested her. Then, she could set that image on repeat to create more intricate designs. Lastly, she swapped out background colors and weaves to add dimension and a feel to her fabrics that would resonate with her target consumer. In the process — though Jones’s and Cartwright’s software helped develop different design variations for target consumers — all the images derived from one design, helping Barnes retain her unique “Jhane” look.
Fractals Come to Advertising.
Programmatic advertising began as an automated way to buy and sell ad inventory through exchanges that connected advertisers with publishers. Nowadays, it’s a common tactic for most advertisers. Last year, Chris Breikss, president and cofounder of 6S Marketing, tweeted something that intrigued marketers. He wrote that he was, “Learning about the Mandelbrot set, fractals, and self-similarity at the Programmatic Insight Summit.”
On the surface — like in fashion — the connection between fractals and programmatic advertising isn’t obvious. But, when the underlying concept of fractals is applied to programmatic advertising, it makes way for a revolutionary concept: scalable mass personalization. Similar to Barnes’s fractal designs, creatives can develop infinitely similar ads and then swap out ad components — images, copy, pricing — in real time to create ads that are sure to resonate with the target consumers who receive them.
Because of these new customizing capabilities, the implications of programmatic advertising have become far-reaching for brands that are striving to maintain a competitive edge. Enthusiasm has grown, as targeting capabilities have become more apparent, and in 2016, US programmatic digital-display ad spend topped $22 billion — comprising 67 percent of all digital-display ad spend in the US. Ultimately, programmatic isn’t about ads at all, but rather, giving each customer a personalized, holistic experience — even if there are thousands, or even millions, of individual consumers. And, as with Barnes’s designs, programmatic done well is the scalable melding of art, math, and science that enables brands to deliver on customers’ wants and needs.
Make the Switch to Programmatic Advertising.
Marketers now have a tool that empowers them to match ad execution to the needs of media while allowing them to optimize in real time, manage multichannel campaigns, and target consumers with personalized ads throughout their customer journeys — all the way through to purchase. Done well, programmatic saves time and money and improves engagement and conversion performance. Following are three steps to help you apply the power of today’s programmatic advertising to your brand.
1. Unlock the Beauty and Power of Programmatic — Break Down Organizational Silos.
In school, Barnes was never great in math. Nowadays, though, by collaborating with those who are, she is able to scale her design process and delight target consumers. Likewise, the divergent groups that make up the list of stakeholders for programmatic advertising are worlds apart, but their collaboration can achieve great impact.
The CMO understands the brand and the focus of products; the head of digital advertising combines analytics and creativity to implement marketing campaigns; media buyers make decisions on ads and budgets; creatives produce custom ads; and marketers develop relevant, integrated, compelling messages across channels. Planning and analytics — often the instigators of data-driven advertising — drive results from digital efforts. And, if they all succeed in working together, the ultimate result is smarter, more effective campaigns that better resonate with consumers. For this reason, brands are finding it’s well worth the effort to bring all these groups together.
To drive acquisitions of a premium credit card, the Royal Bank of Canada (RBC) wanted to reach Canadians who were interested in travel. The marketing team assembled a group that comprised the creative group that was handling production, the media-buying team, and data analysts who defined the test and established performance reports. Working in collaboration, they developed a matrix of various product-benefit messages that were tested against an awareness control message. In doing so, they came up with one message — no seat restrictions — that led to a vigorous performance uptick of 28 percent in conversions.
2. Bridge Art and Science for Spot-On Customer Experiences.
Now that you’ve broken down silos to enable a collaborative approach, the next step is to take the immense amount of data available across your organization and find meaning that allows you to build a complete picture of each customer’s wants and needs — the perfect melding of art and science — so you can then deliver on them with personalized experiences. Without data, creative insights come only from intuition. But, like a fractal — whose beauty is defined by simple, yet powerful, mathematics — successful programmatic creative is fueled by data.
Big Data can be the inspiration behind stories that connect you with the right prospects — the trick is finding a message that resonates. After all, the best creative in the world is meaningless if it doesn’t serve a purpose; and creative that triggers emotion, but doesn’t increase engagement, doesn’t achieve the marketing goal. The solution is to identify the variables that impact results. In other words, if you’re going to send a personalized ad, test to learn which variables — including product, description, price, image, offer, location, dates, deadlines, and whatever else you can come up with — have the greatest impact.
L’Oréal sought to build a campaign over the summer to showcase two sunscreen products — one sunscreen for women and another for children. To create relevant ads for each segment, the company used audience-targeting lists to reach women both with and without children. By swapping out the images and copy, L’Oréal targeted the right consumers in real-time with creative that was personalized to drive engagement and conversion.
3. Embrace the Similar.
For most marketers, customizing multiple versions of one campaign, serving up real-time ads with strong creative, and making adjustments based on consumer reactions is challenging. For programmatic success, marketers and creatives must create simple, powerful pieces of content with modular elements that can be adapted to create the ads they want. Templated creative reduces development time, as you only need to produce the key assets that power creatives.
The ability to quickly make changes can be a factor in deciding how to produce an endless number of iterations of your ad. With dynamic creative, you have one ad layout with variable attributes that can be generated in real time. Barnes was able to apply software tools to her designs — swapping out colors and weaves — to create designs that grabbed attention in her target markets. Likewise, being able to grab images from your data assets and update ad components — price and copy, for example — through a data feed makes it easy to change ads without going through the creative process again.
Once you’re able to mass-produce ads, quickly test and optimize creative components to improve campaign performance. Identify the best ads to serve to customers and adjust those ads to improve performance. Use your data to create options and technology to select the best. By using a dynamic creative template, content-feed options, and digital assets, you can create relevant, personalized, and timely ads that are deliverable to large audiences — complete with a 1:1 personalized feel. Dynamic creative allows you to reach granular audiences with flexible ad creative that’s personalized in real time to drive user engagement, conversions, and integrated experiences across devices.
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Read the full blog post at - https://blogs.adobe.com/digitalmarketing/advertising/brilliant-advertising-unlock-power-programmatic...
The Blog Post below is from Pete Kluge, Group Product Marketing Manager at Adobe
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Why Do Audience Match Rates Matter?
Why do match rates matter? Because audiences matter. Whether your business does offline direct marketing or online programmatic advertising, the ability to reach the right audience is fundamental to achieving your marketing goals.
In digital advertising, reaching a higher volume of a high-value audience gives an advertiser more opportunities — through leads, sales, and revenue — to drive performance. Nowadays, many online advertisers use a data-management platform to consolidate audience data — for instance, site visitors, offline customer relationship management (CRM), partners, and third-party demographics — and end up with robust, individual, anonymous user profiles they can use for audience segmentation and targeting across the web.
So, What Exactly Is a Match Rate?
The pursuit of data-targeting at scale has popularized the match-rate concept, which usually refers to the percentage of users that a demand-side platform (DSP) recognizes within a given audience segment. Data naturally leaks throughout the various stages in the activation progression — from data-onboarder to data-management platform (DMP) to demand-side platform (DSP) to inventory. In the activation process, lost profiles directly correlate to decreased match rates, reducing the targeted scale advertisers can achieve.
As the graphic below illustrates, four distinct data matches occur during the media-execution process:
Offline ‣‣ Online Onboarder;
Onboarder ‣‣ DMP;
DMP ‣‣ DSP; and
DSP ‣‣ Ad Exchange/Inventory.
Let’s look at match rates within the context of one of the more popular real-world use cases: retargeting site visitors — users who have demonstrated both high interest in an advertiser’s brand and intent through their actions while on the site (abandoning shopping carts, visiting specific product pages, etc.). Retargeting is an evergreen (or “always-on”) tactic for many advertisers because these audience segments are the low-hanging fruit that consistently drives performance. For most advertisers, these coveted, high-performing audience segments can never be too big or have too many members. Fortunately, advertisers can gain more from this limited group of high-value users by working with integrated data-management and media-buying platforms that deliver greater audience matches.
But, Do Match Rates Really Matter?
To illustrate why match rates matter, let’s look at an example of the impact for display advertising by comparing the reach of different DSPs within one DMP. Using our previous retargeting scenario, we’ll take a more simplified approach, assuming a frequency of one ad view and each DSP’s consistent synchronization of cookies with ad exchanges.
- The advertiser wants to reach their best-performing audience segment — shopping cart abandoners.
- One-million users in the DMP can be targeted.
- Advertiser pushes the retargeting segment to three DSPs, including the Adobe Advertising Cloud DSP.
- Three DSPs have three different audience sizes and match rates with the DMP segment (90 percent, 70 percent, and 60 percent).
- The result is a significant impact on the number of converters and the revenue.
Advertisers often work with many different technology platforms, and a common challenge they face is that sharing data and audiences across the different layers of their technology stack is often difficult — or even impossible. When building a stack, one of the primary considerations for marketers is whether the advertising layer is tightly integrated with the other platforms. Can data and audiences be shared easily across platforms? How high are the audience match rates? These are important questions that should be asked early in the planning phase — not after the ink has dried.
Can Adobe Advertising Cloud Help You Increase Audience Match Rates?
Adobe Advertising Cloud is the first independent end-to-end platform that unifies audience data, media execution, and creative personalization to enable full-funnel ad-buying and optimization — from lower-funnel performance tactics (e.g., search, display) to upper-funnel brand tactics (e.g., video, programmatic TV). Our focus is on achieving the highest audience match rates possible. We’ve been able to achieve match rates exceeding 90 percent for first-party audiences ported from Adobe Analytics Cloud into Adobe Advertising Cloud DSP.
And, what about the end viewer? Consumers demand relevant ad experiences. In a recent survey, 78 percent of respondents said they want relevant ad experiences, but only 28 percent feel they are actually receiving them. By reaching more high-value audiences, an advertiser can better personalize experiences across display, video, and other channels.
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Read the original blog post at - https://blogs.adobe.com/digitalmarketing/advertising/audience-match-rates-matter/
The Blog Post below is from Pete Kluge, Product Marketing Manager for Adobe Media Optimizer
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5 Reasons Now Is the Time to Implement Dynamic Creative
Dynamic Creative Optimization (DCO) was introduced to marketers a decade ago, but after the initial excitement, the implementation and delivery of use cases didn’t match the expectations. However, today, DCO is riding a new wave of adoption by advertisers and agencies.
Gartner shows DCO rising on the “Slope of Enlightenment” for its July 2016 Digital Marketing and AdvertisingHype Cycle. According to Gartner, this is the phase where “more instances of how the technology can benefit the enterprise start to crystallize and become more...” We believe several factors contribute to this newfound enthusiasm.
Five Reasons Why DCO Is Back and Stronger than Ever
1. Programmatic Advertising Powers DCO and Retargeting
Before demand-side platforms (DSPs) and real-time bidding (RTB), media for DCO was bought directly from the publisher or an ad network. Getting sufficient scale and unique reach could be a challenge—an advertiser had to buy media on multiple publishers or ad networks. Reaching many small and granular audiences required a manual and cumbersome set-up process. This lacked efficiency and there was no way to de-dupe user targeting among the different inventory partners.
Being able to retarget ads to consumers who show interest in products and services through their online behaviors is an important application of DCO and RTB technologies. Combining DCO with real-time audience-based buying through a DSP addresses key challenges around scale and unique reach. The DSP is integrated with many ad inventory sources for maximum scale and has controls like frequency capping across all the inventory, allowing the advertiser to better manage scale and reach. Advertisers now have access to vast amounts of data and advanced technology platforms to apply that data to display advertising campaigns.
2. DCO Moves Beyond Retargeting
Early on, DCO was used primarily by the retail and travel industries for retargeting high-value consumers with advertising. Given the large number of possible ad permutations for retail and travel (thousands of SKUs or origination/destination combinations), these are the logical verticals to be the first to adopt DCO. But advertisers now grasp how DCO can be used beyond retargeting for campaigns across the marketing funnel and across verticals.
While DCO campaigns at the lower end of the funnel—like retargeting and loyalty programs—have always made sense, DCO is also now being applied to top-of-the-funnel prospecting and awareness campaigns. Even if very little is known about a user (for example, from a geotargeted prospecting campaign), DCO can algorithmically optimize the ad content to drive the best performance for the advertiser. DCO evaluates all possible ad permutations and optimizes creative elements and delivery to the best-performing option for the advertiser’s objectives. Any vertical that has granular audience data can benefit from DCO.
3. It’s All about Experiences
Consumers are engaging with brands across multiple devices and digital channels and they’re expecting a personalized, consistent, and compelling experience whenever and wherever they’re accessing brand content. This is truer today than ever before. The fact that ad blocking is on the rise sends a clear signal that consumers are demanding better ad experiences.
DCO is the solution advertisers need to deliver a better experience for their consumers. Advertisers have access to deeper audience insights than ever before and DCO allows advertisers to deliver relevant and engaging ad experiences, and in turn drive better engagement and performance.
4. Data Feeds Are Everywhere
A key component of DCO is the data feed. This is the content that is used to populate a dynamic ad in real time. In a change from just a few years ago, many advertisers are now using data feeds regularly to power their online advertising.
In addition, DCO technology has become more flexible in ingesting data and it no longer requires a third-party vendor. For example, a Google Merchant Center feed can easily be translated for DCO and an Excel file can be mapped for DCO.
Digital advertisers are generally more comfortable using data feeds and customer files to power their advertising campaigns, and they have a greater awareness of how data feeds support DCO.
5. Creative Flexibility
While early DCO vendors required an advertiser to select from a set of predefined and inflexible templates, today’s DCO solutions offer an agency and advertiser complete control and flexibility over the creative layout design. Dynamic ad templates can be custom built for the advertiser so they have control over how their brand is conveyed and experienced by the consumer. The ad layout can include features like a promotion countdown clock, drop-down box, search form, and product carousel, and can be delivered on mobile and across devices.
What does the future hold for DCO?
As DCO approaches the “Plateau of Productivity” on the Gartner hype cycle, it will attain mainstream adoption. We will continue to see advertisers better understand how DCO works and what it can do for them. Access to data and ad-buying technology combined with DCO enables advertisers to deliver relevant and personalized ads to drive better performance and improved ROI.
Last year, Adobe acquired Tumri from Collective, adding DCO to its advertising technology stack alongside Adobe Media Optimizer, a cross-channel programmatic ad-buying platform, and Adobe Audience Manager, a data management platform (DMP).
This is the first in a series of five blogs on DCO. Stay tuned for blogs on what DCO can do for advertisers.
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Read the original Blog post at - https://blogs.adobe.com/digitalmarketing/advertising/5-reasons-now-time-implement-dynamic-creative/
The Blog Post below is from Manu Malhotra, Consultant for Adobe Media Optimizer at Adobe
Edit: This article has been published as a Knowledge Base article for Adobe Media Optimizer and can be viewed here
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Dealing with Model Inaccuracies
AMO technology predicts performance based on data models it builds over a period of time. However, at times, it is very challenging to get the models accurate. When models go off because of various factors changing in the eco system, it results in uncertain performance. Hence, it is very important to keep a close eye on model accuracy.
What is Model Accuracy?
Model accuracy shows how precise the cost and revenue models are which are being used to optimize bids. In simple terms, model accuracy is a comparison of predicted performance and the actual performance. You can check model accuracy by clicking on Portfolio Cards > View. Day on day break down of accuracies is listed in the table.
The model accuracy reports for multiple portfolios can also be easily accessed in AMO by clicking on Reports > Create Report > Model Accuracy > Forecast Accuracy
Why is it important?
If model accuracy is off, it simply means AMO doesn’t have as much information as is required and hence the bidding on the bid units is not resulting in expected impactful returns.
Why do I have inaccurate cost models and what can I do to correct them?
- Following a large scale account audit, check if you have changed a large number of landing pages / ad copies. In such a case it might result in cost model inaccuracy. It should take some time for quality score to build again.
- Nature of the business – Check if there is a case of seasonality or a big event such as Olympics or change in competition such as a new entrant or aggressive strategy by competition. This can bring in cost model inaccuracy. Though AMO will adjust and adapt to changes but it may take time. In such cases try reducing the cost half-life to make AMO take more consideration of recent change in eco system.
- New Additions – If new campaigns and keywords are getting added, this will impact cost models. In such cases, you might like to add the new campaigns in active state initially in a separate portfolio. Else, wait for some days and AMO cost models will stabilize.
- Significant changes in settings – Any changes in campaign settings such as geo targeting or match type strategy at search engine level can result in cost model inaccuracies too. You can either wait for next sync cycle for AMO to fetch the changes from search engine or you can make changes directly from AMO so that the technology is very much aware of the changes.
- Significant changes in budget: This is a tricky scenario, try sticking to small and incremental changes in budgets. However, if you do have to make drastic changes because of business requirements, be ready for cost model inaccuracies. To handle it, try reducing the half-life.
- Changes beyond your control: Bing updates its search algorithm, google decides to do away with right side ads, what do you do? Try reducing the half-life and technology should well adapt swiftly to the change.
How to handle Revenue Model inaccuracy?
- Special promotions: The rate of conversions will see a jump and models might take some time to adapt and learn from the changes. It is suggested to reduce the half-life for models to adapt and learn quickly.
- Market competition: In case of competition getting aggressive or new entrants bidding high results may differ from forecasted. In such a case resort to reducing revenue half-life for models to catch up.
- Lag in revenue numbers from feeds: This can happen for operational as well as other business reasons. In such a case try increasing revenue half-life to accommodate the lag in reporting revenue.
Apart from these scenarios, at times there are pixel tracking codes issues where in pixels aren’t firing for some reason on the web properties. It is best recommended to highlight such an issue to AMO and the client team to troubleshoot it.
The Blog Post below is from Nidhi Kapoor, Senior Consultant for Adobe Media Optimizer at Adobe
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Bulk Edit Feature to Support Manual Bidding
‘’Manual Bidding” is the most common and important step seen in case of newly created campaigns. This method let the advertiser set the manual CPC for keywords as per its targets and enhance their exposure.
AMO has its competitive bidding technology with which it takes the control and automate bids on bid units (keyword + match type) using its algorithm such that it maximizes advertiser’s objective.
The process being followed in AMO for newly created campaigns is that when they are new should be kept under ‘Manual Portfolio’ first for few days before getting assigned to the ‘Optimized Portfolio’. This is to ensure that they build good performance data history around them before getting under AMO’s technology. In an Optimized portfolio, bid units are bid automatically by the technology as per its algorithm. The factor history plays an important role in bidding technology of AMO as it helps in generating the models (cost & revenue) and therefore calculating appropriate bidding for bid units.
Usually the common method seen among advertisers for manual bidding regularly for keywords in bulk are through the bulk sheet method. In this, keyword's bids are modified as per their performance, business requirement or some best practices such as for example:
- Keywords with conversion and avg pos worse than position 3 = +20%
- Keywords with conversion and avg pos between 2 and 3 = +10%
- Keywords with no conversion and avg pos worse than 3 = +30%
- Keywords with no conversion and avg pos better than 2 = -10%
These increases or decreases are made as per the bids in ‘current bid column’. This method requires downloading the current status of keywords first in a bulk sheet format and then making changes and posting the modifications later on through AMO on search engine.
There is also another way to execute and expedite the manual bidding is by using AMO’s ‘bulk edit feature’.
To use the ‘bulk edit’ feature, visit the keywords tab, create a filter to select the keywords to perform the bid increase/decrease action. To start with, use the ‘Add Filter’ option, select the date range of the data on which the analysis will be appropriate for keywords and then filter the keywords on the basis of their conversions/avg. position data etc.
Select those filtered keywords > click on the ‘bulk edit’ option on the left > select the ‘available actions’ such as ‘formulaic bid change’ in case of ‘manual bidding’ and then increase or decrease the percentage depending upon the data, best practices, budget targets and requirement of exposure. In case of increase, it’s always good to set the max limit and in case of decrease, the minimum bid limit to avoid the sudden increase or decrease. Click ‘Apply’ then to execute the changes.
Changes made will be available under ‘bulk edit status’ link under the ‘filter’s row. This is one of the quickest method to avail the option of manual bidding in bulk, change the ‘status’ of keywords, ‘create’ and ‘Find & Replace’ in bulk.
Depending upon the number of keywords to be manual bid, filter requirement and the frequency of changes to be made, a choice can be made between the options of bulk sheet or bulk edit to be used.
The Blog Post below is from Pete Kluge, Group Product Marketing Manager for Adobe Media Optimizer
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Creating Relevant Ad Experiences Without Thousands of Ad Units
Consumers are frustrated with the number of irrelevant advertisements they have to deal with daily:
- According to Infolinks, only 2.8 percent of study participants thought ads on websites were relevant.
- Adobe and PageFair found that in the United States, there were 45 million monthly active users (MAUs) of ad blockers during Q2 2015—equal to about 20 percent of Internet users, according to Strategy Analytics.
- According to PageFair, 33 percent of Internet users find display ads completely intolerable because they are not pertinent or interesting.
To rebuild consumers’ trust and drive better engagement, businesses today need to build more personalized ads.
Many advertisers still use static ads for their display advertising. This means that the actual content within the ad doesn’t change and therefore a different ad must be created for each audience segment. For any brand that is interested in delivering personalized ads to highly segmented audiences, the number of static ads necessary becomes a nightmare for the creative and traffic teams. The result? Impersonal ads that don’t engage the customer.
On the other hand, dynamic ads use a single ad layout (or dynamic template) that can be populated on-the-fly with predetermined personalized content.
Introducing Dynamic Creative Optimization
Dynamic creative optimization (DCO) allows advertisers to drive better engagement and performance from their ads by delivering the most relevant experience to the user in real time. DCO uses an ad layout with several dynamic elements that change depending on who the user is or which audience is actually seeing it. The content changes can include things like the product description, image, price, and call-to-action (CTA). Promotional copy can also be switched dynamically.
Retargeting campaigns is currently the most common use for DCO. It requires an advertiser to maintain a data feed with the dynamic outputs used to populate the ad at the time of the ad call. The ad is assembled in real time to deliver the most relevant content for any user. But DCO is not only for retargeting. It enables advertisers from a variety of verticals to deliver personalized experiences for consumers across the marketing funnel.
Elements of a DCO System
DCO works by combining several elements to output a real-time and relevant ad. Here’s a primer on some terms and definitions related to dynamic creative:
Dynamic Triggers: Pixels on a brand website capture retargeting values (i.e., product SKU) and are used to trigger outputs from the content source—such as data feed or API—to populate a dynamic ad. Other elements that can trigger dynamic ad content include geolocation and audience segment data.
Content: In the case of DCO, content refers to the advertiser feed, API, XML, business rules, offer grid, or product catalog that the dynamic trigger references for outputs to populate fields in the ad template. Content is provided by the advertiser, ingested by the DCO system, and output in the dynamic ad.
Dynamic Outputs: These outputs are ad elements that can be referenced by a dynamic trigger in the content source. Examples include images, URLs, and copy that are referenced in a data feed.
Variable Attribute: Variable attributes are dynamic elements within ads that are not referenced from the content source by a dynamic trigger. Delivery of the ad element is based on business rules (like A/B testing) and is not feed based. Examples include CTA, background color, and offer. Some items, such as copy or CTA, can be either a dynamic output or variable attribute, depending on setup.
Ad Layout or Dynamic Template: In DCO, these elements are the shell design that houses the dynamic content.
Experience: An experience is created by the combination of one ad layout and one or more content sources.
(No Cookie) Default Ad: The default state of a dynamic ad occurs when cookie targeting is missing or does not match the content source. Advertisers predefine defaults for each dynamic output. For example, if the DSP makes an ad call and there is no matching DCO cookie or if the dynamic trigger does not match the content source, the default experience will be generated.
DCO Delivers
Delivering highly personalized ads improves your campaign effectiveness. DCO can help manage the expense of ad creation and production by using an ad template and data feed to create infinite ad combinations without infinite time and money.
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Read the original blog post at - https://blogs.adobe.com/digitalmarketing/advertising/creating-relevant-ad-experiences-without-thousa...
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