Programmatic Media Buying 101: Why DSPs & DMPs work better together?

Data-driven advertising has been proven to deliver the most effective way of managing an advertiser’s spend as well as the most efficient way to monetize a seller’s digital assets.
The effectiveness of data-driven decisions –planning, selling, buying– make it necessary for both sellers and buyers to take as much control of their data as possible, and for this reason Data Management Platforms (DMPs) are a key technology for media buyers, publishers and marketers. A good DMP should not only be able to collect data from different sources, but also allow for the creation of audiences/ segmentation, consolidated reporting and campaign optimization – the place where people, platforms, partners and processes are brought together to apply audience data that is actionable. For all those marketers, media buyers and advertisers running programmatic advertising the DMP should be the source of truth for activation and analysis purposes.

What Can A DMP Offer?


Web and mobile experiences, speed of ad delivery, relevant ads and smooth and uncluttered paths to purchase have all contributed to the expectation of today’s consumers.  A good versus bad experience will make or break a retailer. The DMP enables advertisers and brands to craft and deliver personalized communications and offers to existing customers, while simultaneously reaching new customers (identified and informed by existing customer data) through digital advertising making sure the experience is seamless and relevant.

So what do advertisers look for when purchasing a DMP? According to John Lockmer, Director of Programmatic and Ad Operations for DuMont Project there are two main factors he considers when shopping for a DMP:

  1. How the platform will connect to his firm’s ad tech stack?
  2. How much it will cost to use?

With costs ranging from a minimum of $15,000 per month for basic usage to up to $500,000 for a license to manage up to 50 million users, advertisers are looking for alternatives which includes an integrated DSP (Demand Side Platform) and DMP solution.

“It makes it easier for us to work with them, as it does not require a yearly contract and commitment like [standalone] DMPs,” Lockmer said.

 

Tight integrations between a DMP and DSP hold a number of advantages for programmatic media buyers:

  • More efficient media activations – which means you can message your known audiences and address them with the right message
  • Advertising Efficiency – when there are clear signs that a user is no longer interested or have already bought your product, you can stop advertising to them
  • You can diversify your data to include first, second and third party sources for maximum advertising impact
  • Better understanding of the impact of your media buys across all online channels with more accurate and robust analytics
  • NO data leakage
  • If you work with Digilant, there is little or no added cost to activating the DMP

In order to execute a data driven programmatic media buy on a DMP, it’s also important to understand the different types of data available to today’s digital advertisers.

First Party Data

Advertisers have numerous potential first party data assets that they already own: CRM, Point of sale (POs), website, search, digital marketing and offline (point of sale, shopper visits, etc) marketing data. This data is frequently referred to as first party
data. The most important evolution for media buyers in first party data is the ability to activate it for programmatic campaigns, in addition to using the data only for email marketing or direct mail campaigns.  An necessary part of using first party data for programmatic is taking out any Personally Identifiable Information, know as PII, by using on-boarding service providers like LiveRamp – used to translate offline or email data signals to a digital user ID, so that DSPs can now translate different kinds of data for programmatic media campaigns.

Second Party Data

Second party data is acquired through exclusive relationships with data providers who do not sell their data in the open market. A DSP platform can help strike a deal with a data provider to enrich an advertiser’s first party data or directly activate second party data. DSPs are in a unique position to provide data intelligence to help advertisers make that data actionable. The DSP data intelligence comes from developing data science models from previous advertising campaigns that can be applied to enrich advertiser data and their campaigns.

Third Party Data

Data Management Platforms (DMPs), collect audience content consumption anonymously through access to publisher sites and sell the information as 3rd party data to advertisers. For sellers, the data that DMPs help collect is leveraged by sell side platforms (SSPs) to understand the value of their content and properties to increase monetization. For buyers, DMPs provide paid access to audience data from many publishers to which they otherwise not have access. DMP platforms that perform this data collection and distribution (“data exchange”) pay a small fee to sellers to be able to collect data and make it available for media buying platforms.
For example, BlueKai, acquired by Oracle, is one such DMP platform, the idea was to be able to monetize the data collected on both sides (sellers and Buyers), making it necessary for it to be anonymous, impartial and independent. This type of data is frequently termed third party data (3P). All DSPs have access to the same third party data for a price. But, additional layers in the media technology stack have implications. One, there is an additional fee to advertisers; and two, there is data loss as the audience universe do not exactly match between platforms. Since these different types of data are housed in different areas, a gap between first party data and third party data has been created for marketers and media buying platforms. these two data sets live in two different companies, in different technology solutions, and in different formats.

DSPs and DMPs Work Better Together

How can we bridge this gap? Digilant’s solution lies in its integrated DMP and DSP that bridges data management and media activation.  With all the effort, platforms, people and cost involved in executing data driven programmatic advertising, advertisers need to understand that the recipe for success is not pre-packaged, the right combined DMP and DSP will can help them achieve the right ingredients to create the right programmatic buying strategy that leads to campaigns that scale and perform.

Programmatic Media Buying 101: What is a Data Lake?

A data lake is a centralized place, like a lake, that allows you to hold a lot of raw data in its native format, structured and unstructured, at any scale. You can store your data as-is, without having to first structure the data or define it until its needed.  It can then be used for creating reporting dashboards and visualizations, real-time analytics, and machine learning to guide better programmatic advertising decisions.

As data grows and diversifies, many marketing and especially digital strategy teams are finding that traditional methods of collecting data are becoming outdated and are pushing for something more centralized like a data lake.  According to Aberdeen research done in September 2017, the average company is seeing the volume of their data grow at a rate that exceeds 50% per year. Additionally, these companies are managing an average of 33 unique data sources, according to the research study. With data split into silos by team, like search, social or direct marketing, CMOs are being challenged with how to efficiently manage the analysis for their media campaigns.  If they don’t consolidate their data, they risk targeting the same consumer more than once or even exposing them to the wrong message.

Why Do You Need a Data Lake?

Most data platforms will only store data if it’s been formatted to fit a particular structure, like rows and columns.  So unstructured data like log files, data from click-streams, social media, and internet connected devices typically can’t be uploaded into a data platform until the data has been defined.  A Data Lake allows you to import all marketing data in real-time, from multiple sources and in its original format. It also allows you to scale data of any size.  Then you can figure out how to use it in an automatic yet personalized way to attract and retain customers through digital advertising.  Companies like Digilant can help you set up a Data Lake and use it for media activation.

What is the difference between a data lake and a Demand Management Platform (DMP)?

If you are a digital marketer, a Data Lake allows companies to collect PII data (Personally Identifiable Information), which DMPs do not.  A DMP’s is main function is the collection of cookie data for media audience activation where a Data Lake is often the first step used by data scientists to expand the knowledge of the DMP.  The DMP often connects directly to the media activation tool which for programmatic is most likely a DSP (Demand Side Platform).  A DMP will establish connections between several external data providers, and the data lake then supplements it with new internal data like social media feeds or connected device data.

Four Main Advantages to Having a Data Lake

1. DATA INDEXING
Data Lakes allow you to store relational data (a collection of data items organized as a set of formally-described tables from which data can be accessed or reassembled in many different ways without having to reorganize the database tables.) —operational databases (data collected in real-time), and data from line of business applications, and non-relational data like mobile apps, connected devices, and social media. They also give you the ability to understand what data is in the lake through crawling, cataloging, and indexing of data.

2. ANALYTICS

Data Lakes allow data scientists, data developers, and operations analysts to access data with their choice of analytic tools and frameworks. This also includes open source data frameworks such as Apache Hadoop, Presto, and Apache Spark, and commercial offerings from data warehouse and business intelligence vendors. Data Lakes allow you to run Analytics without the need to move your data from one system to another.
3. MACHINE LEARNING

Data Lakes will allow organizations to generate different types of marketing and operational insights including reporting on historical data, and doing machine learning where financial models are built to forecast likely outcomes, and suggest a range of actions, if taken, have the ability to achieve optimal results.

4. IMPROVED CUSTOMER INTERACTIONS

A Data Lake can combine customer data from a CRM platform with social media data analytics, as well as a marketing platform that includes buying history to empower the business to understand the most profitable audiences, the root of customer churn, and what promotions or rewards could increase loyalty.

In Summary

Marketers and Media Buyers would want to implement a data lake for three main reasons. First, they want to take advantage of more advanced and sophisticated analytical tools and dashboards, using a more complex and diverse foundation of information. Secondly, they also want to make traditional activities — like data access and speed of retrieval — more efficient and easier to accomplish. The third reason is they want to bring all the data from the different parts of the organization into one place creating efficiencies of time as well as cost savings.  While not every company succeeds at achieving all three objectives simultaneously, the most effective ones will able to see positive results on their ability to make better programmatic media buying decisions.

Why Media Buyers Need to Focus on the Consumer Using a Journey Map

By Mike Addonizio, Director, Platform Solutions at Digilant

Stop the Channel Obsession

The complication of today’s digital media landscape has confused advertisers. It seems advertising’s most proven and basic principles, such as communicating the right message to the right person at the right time, are getting lost to an infatuation with channels and irrelevant metrics. It comes at a time when digital advertisers should have an easy time targeting the right audiences and being efficient at managing their ad spend. Instead, as publishers like Facebook and Google build barriers between their ecosystems, brands are mirroring them by organizing their internal agencies and teams in the same way. Social, search, display, and owned channels are siloed instead of synergized and are being evaluated by misguided KPIs, such as clicks or engagements they generate.


The problem is obvious. Pitting channels and vendors against each other and measuring only channel specific metrics, will ultimately lead to wasted dollars. It prevents team collaboration and undermines customer-centric strategies. It results in brands arbitrarily devoting portions of spend to “high-performing” channels with short-term campaign goals in mind. Teams are likely double-counting revenue dollars due to the lack luster attribution models, and certain channels are receiving more (or less) credit than they actually deserve. Somewhere in this narrative of media buying execution, marketers are forgetting that the only common fabric between these channels is the consumer. When they return to thinking about the customer first, advertising becomes less complicated.

It’s All About the Journey Map

As publishers build walled gardens for their user bases, advertisers must render the obstructions useless while maintaining cross-channel identity and journey context. When we factor in mobile phones as a primary means of receiving and sending communication, this complexity only becomes more aggravated and will continue as new devices appear in the future. The solution is a synergy between technologies that focuses on the consumer.
From a tech standpoint, there needs to be a convergence of DMPs (Data Management Platforms) and CRM (Customer Relationship Management) systems. One solution looks like the image bellow.

Winning with A Customer-First Ad-Tech Solution

  1. Successful media buyers will use CRM systems to inform their DMP of the current customers that should be suppressed, receive different messaging, or pass high-value customers lists for optimized lookalike modeling.
  2. A good data strategy should include using a DMP to inform a CRM of the user journey prior to acquisition as well as other relevant attributes about the context of current customers.
  3. Segmentation must occur across the two platforms, and audiences must exist in a delivery environment that is channel agnostic.

This combination of technology, consumer focus, and working with the right media partner like Digilant has proved to be a winning recipe for digital marketers.

Programmatic Media Buying 101: Digital Marketing Data Sources, How to Apply Them?

The rise of digital advertising has given marketers fuel to reach their ultimate marketing goal: connect the actions of users into a meaningful whole. When marketers know a lot about their consumers, advertising is personally relevant and more effective. Personalization of brand experiences is a powerful way to drive conversion – and in digital advertising, personalization is driven by data.

Pre-digital direct marketers relied on research of public records of births, marriages, and property deeds. They bought mailing lists from catalog companies to reach out to potential customers. Audience segmentation and tracking purchase intent are not new strategies, but digital data collection has significantly increased their impact. And online consumers leave a digital data trail behind wherever they go.

The Digital Data Trail

Now that there is much more data available for marketers to use, behavioral targeting has become a much more popular tactic for media buying. Most digital advertising still relies on at least some information about individual attributes — like gender, geo-location, and age. But programmatic buyers and also have the ability to collect data related to online behaviors.

While a lot of privacy-conscious consumers delete cookies or use the “limit ad tracking” features on mobile devices, advertisers aren’t interested in personally sensitive information – like cheating on taxes or a romantic partner. They are more interested in behavioral data signals that indicates whether consumers are in the market for a car, house, or coffee maker.
Social media sites or other login-based services have access to personal identifiable information (PII), but tying it to other data points would drive away customers. The ongoing stream of “shares”, “tweets”, “likes” — or other “reactions” — is revealing enough info to be worth a lot to advertisers – even without names and emails addresses.

Online activity allows data providers to identify specific audience segments, These segments can be defined by variables like (1) geolocation, (2) device type, (3) marital status, (4) income level, (5) profession, (6) shopping habits, (7) travel plans and a variety of other factors. These valuable segments can be sold to the highest bidder wanting to reach segments as specific as men in trouble or burdened by debt: small-town singles.

There are many players in the data game – and some play multiple roles. 

  • Brands collect information about their customers, such as email addresses and purchase history, which is helpful when tailoring their experience through product recommendations or incentive offers. 
  • Publishers sell data about readers who visit their site, which is valuable to advertisers purchasing ad space on their site – but can also be used to track their site visitors in other places online.
  • Other data collectors who may sell data may not be thought of as “ad industry” types at all, such as:

1. Political campaign groups often rent out their lists to firms as a fundraising strategy

2. Credit-card companies issued directly or through banks sell anonymized data to advertising companies – in cases where cards are issued directly, customers can be cookie’d whenever they login then go elsewhere online.

3. Online auctions offer a huge amount of user info, again anonymized, but revealing.

4. Any company, site or service that requires a login can collect data. For example, social media sites garner huge amounts of data as users “like” “tweet” and “share” about their interests.

How Companies Collect & Use Data?

The data game players are defined by how they collect and use data – either as first-party or third-party.
First-party data is any information that’s collected by a company that has a direct relationship with the consumer. First party data tends to be considered as more valuable because it usually is more accurate and is free for the advertiser.

  • If we take the fictional example of Heart and Sole shoes, they would like collect data about customers’ style preferences and shoe size through the user’s’ purchase history.
  • If we look at a fictional online publisher, say Knitting News Weekly, they may associate an ID to anonymously track the articles that their visitors read and share
  • Another fictional example, like Gloria’s Games App might use an API to gather data themselves, for example, the most common geographic locations where the mobile app is used.

Some apps also use external SDKs — or a software development kits — from a technology provider that will track user data. In this scenario, the technology provider is a 3rd party data collector. And third party data is any data collected by platforms or services that do not have a direct relationship with the consumer. These service providers obtain data in many different ways, such as:

  • Paying a publisher to collect data about their visitors.
  • Or piecing together behavioral or interest profiles and audience segments to be sold to advertisers.

Let’s not forget the new comer to the data party – 2nd party data, which is essentially first-party data that you are getting directly from the source. Buyers and sellers can arrange a deal in which the first-source party offers specific data points, audiences, or hierarchies to the buyer. The sharing of high-quality, first-party data gives marketers access to many hard-to-find audiences they may not have been able to reach.
Whether first-party or third-party, data is often housed and managed for programmatic buyers by a Data Management Platform – or DMP. DMP’s give marketers — and sellers of data — a centralized way to:

  • Create target audiences, based on a combination of in-depth first-party and third-party audience data;
  • Accurately target these audiences across third-party ad networks and exchanges,
  • And measure performance with accuracy.

Summary

  • Marketing based on consumer data has always been around; digital has just made it more powerful.
  • Personally Identifiable data isn’t critical; marketers can get a lot of value from behavioral and interest-based data.
  • First party data is often considered most accurate and more valuable.
  • DMPs help marketers collect and manage and organize consumer data so that they can use the insights to activate a marketing or a programmatic media buying strategy.

How to Become a Better Programmatic Marketer?


Programmatic ad buying has gone from being an advertising technology used only by the largest of businesses, to a key marketing tactic for any brand that wants to be seen and heard in today’s constantly expanding digital ecosystem. Despite its widespread prevalence, programmatic ad buying is an advertising practice that requires sophisticated training and knowledge to properly implement and get the most out of your ad dollars. If you want to plan and execute a programmatic ad campaign like a pro, you need to know what strategies to adopt, what trends and data to pay attention to and which metrics to follow to monitor performance?

Although programmatic ad buying campaigns can vary greatly in their tactics, with some aiming to amplify brand awareness, and others more focused on generating leads, a marketer that can develop a programmatic ad buying strategy that effectively reaches desired ROI while maintaining transparency is considered successful. Transparency refers to providing buyers with a clear view of the price of inventory purchased, the data leveraged to place their ads, and the environments in which those ads will ultimately end up, and being able to identify attribution.

How does programmatic advertising fit into an overall digital marketing strategy?

Whether you’re using digital media for direct acquisition or for brand awareness, if you’re still buying it traditionally, you’re letting go of opportunities to optimize your ad spend and maximize your total addressable market. In order to compete in today’s digital marketplace, integrating programmatic ad buying into your digital marketing strategy is a must.

In the broadest sense, programmatic is the automation of marketing activities, from the smallest programming of a post to implementing a highly layered real time omnichannel campaign. If you haven’t already dove into programmatic ad buying and are debating whether or not to get your toes wet, considering the following:

  • Would programmatic buying more efficient than how my brand is currently buying media?
  • Would programmatic buying be more transparent?
  • Would programmatic buying be more profitable?

How does the process of programmatic ad buying work?


The development of algorithms using data science driven technology that analyze the behavior of an individual user, is the driving force of programmatic ad buying, optimizing bidding in real time and reaching audiences composed of the users that are most likely to convert.

Businesses that bid for inventory through programmatic ad buying can compile an enormous amount of data that can become audience segments. The sooner you launch a campaign and the more time it has to gather this data, the sooner your programmatic ad buying platform’s data intelligence can strengthen your overall digital marketing strategy through more efficient targeting.

Learning about how programmatic ad buying can drive your digital marketing campaign is great, but it’s equally as important to know what’s underneath the hood. Purchasing programmatic ads involves the following systems:

1.) DSPs (Demand Side Platforms) facilitate the purchase of ad inventory and allow marketers to reach their target audience when integrated with a data management platform. In Today’s marketplace there’s a wide variety of DSPs available to brands looking to buy ads programmatically, and programmatic agencies such as Digilant who can manage your campaigns.
2.) DMPs (Data Management Platforms) compile and analyze massive quantities of cookie and mobile data that provide insights that help advertisers make better and more informed decisions. Generally the data sets with which DMPs work with are:

  • 1st party data: Data compiled directly from the advertiser; their website, social media platforms, email marketing and display campaigns, or their own CRM.
  • 3rd party data: Data compiled from external sources. The user data points generally consist of age, gender, social and professional interests, geographic location, and other interests or needs of the user inferred from their online behavior.

3.) For content publishers, SSPs (Sell Side Platforms) are essential in providing a source of revenue. This platform is where various types of online media manage their unsold ad inventory. Bidders using DSPs are provided with information on the value of the available inventory from the SSP with data on page visits, visitor demographics, number of pages viewed, and length of site visit.

Step by Step Process

It’s essential to know how to work with the data insights that you acquire through your DSP. Once you feel that you have a strong handle on the aforementioned elements involved in the programmatic ad buying process, you’ll want to launch your campaign on a programmatic buying platform.

Whether your campaign is managed or you opt for a platform with self-service, it’s crucial that you partner with a provider that has a great support team to help you through any challenges that you come across throughout your campaign’s operation.

As seen in the above infographic, the programmatic ad buying process can be divided into 5 steps:

  1. Picking: The starting point of any programmatic ad buying process, picking refers to the period during which brands define the inventory criteria that they’d like to set before moving forward with bidding. Regardless of the DSP that you opt to use, you’ll be asked for information surrounding your budget, target audience, and the KPIs you want to achieve.
  2. Matching: Now that the DSP system knows what type of inventory you’re looking for, it will search ad networks and buy audience data from various digital environments and match your ads with the sites and platforms that will best align with your KPIs.
  3. Triggering: Once a match is found, the ad is placed and waits for a trigger. There are various types of triggers, but all refer to an interaction with the ad creative,  whether it’s a click, a mouse-over, or simply a page view.
  4. Tracking: With the ad now visible and receiving engagement from users, data surrounding this engagement will be collected to provide advertisers with insights about how effectively the campaign is operating.
  5. Repeat: Programmatic ad buying is a cyclical process that repeats itself. Once you’ve launched your campaign and have had ample time to analyze its performance, the human aspect of programmatic must come into place. you will have to return to the starting point steadily. Being an automated process, the repetition becomes one more step, which the user assumes as natural and proper to the operation of this system of purchase.

Common Concerns of Marketers New to Programmatic Ad Buying

Programmatic ad buying was specifically designed to help marketers execute more scalable, efficient and precise digital campaigns, so why are some marketers hesitant to give it a shot?

There are several reasons why some brands don’t feel completely secure with implementing programmatic ad campaigns.

1.) Ad Fraud

In today’s digital ecosystem, ad fraud is a huge concern for programmatic marketers. According to a Wall Street Journal report, it’s estimated that more than a third of online ad traffic is fraudulent, meaning a third of ads won’t be viewed by an actual user.

However, with advances in programmatic technology fraudulent traffic can now be detected by analyzing user behavior. The most common forms of fraud come from bots that generate irrelevant clicks and falsifying user characteristics, and ad fraud comes in many forms, including:

  • Selling of inventory automatically generated by bots or background mobile-app services
  • Serving ads on a site other than the one provided in a Real Time Bid – or RTB request
  • Delivering pre-roll video placements in display banner slots
  • Falsifying user characteristics like location and browser type
  • Hiding ads behind or inside other page elements so that they can’t be viewed hindering a user’s opportunity to engage by frequently refreshing the ad unit or page

Fortunately, technology exists that combats ad fraud, tracking suspicious traffic and retargeting ads to user traffic with real potential customers that are most prone to convert.

2.) Viewability

As previously mentioned, a fraudulent ad will never be viewed by a real user, but beyond being seen by a human, what constitutes a viewable ad? The Media Rating Council deems a programmatic display ad viewable if at least 50% of the creative is visible to the user for at least one continuous second. This may sound like a non-issue, but viewability is crucial metric for any programmatic marketer. A study conducted last March found that 57% of ads served are not considered visible and that leads to wasted ad spend and diminishing ROI.

3.) Brand Safety

Companies like Integral Ad Science, that specialize in guaranteeing brand safety, have evolved to fully integrate their services to protect programmatic advertisers’ campaigns from operating in ways that can damage brand reputation. The main responsibility of these companies is to assure that ads across the digital ecosystem don’t appear in environments that could be compromising to a brand’s identity or mission.

It’s ultimately not worth the risk to invest in a programmatic ad buying platform if you aren’t able to guarantee that your ads will be displayed on secure media platforms, and more importantly, alongside relevant content with values congruent to those of your brand. Let this past March’s Google Ad Crisis be a reminder for all advertisers to prioritize brand safety.

Major Brands Relying 0n Programmatic Ad Buying for Results

Many brands today are decreasing their traditional ad spend or cutting it all together. In an interview with CNBC, Adidas’ CEO, Kasper Rorsted, stated, “All of our engagement with the consumer is through digital media and we believe in the next three years we can take our online business from approximately 1 billion euros to 4 billion euros and create a much more direct engagement with consumers.”

This decision marks an important paradigm shift for digital marketers. With the sheer quantity of online user behavior data available and a plethora of digital media channels on which to reach these users, today’s advertisers are positioned to create digital marketing campaigns with incredible scale. When combined with programmatic ad buying, this scale is effectively leveraged to target and uncover the most valuable users in real time.

Interested in unlocking data and uncovering your brand’s potential through programmatic ad buying? Learn more about Digilant’s solutions here.

10 Tips For Digital Advertising Best Practices

Keeping up-to-date on digital ad buying best practices is essential for any marketer to successfully navigate today’s digital ecosystem. Given the sustained high-level growth of programmatic media buying in recent years, the way in which we leverage new technologies to bring together the main players of digital ad buying and selling is constantly evolving.
buenas prácticas para la compra digital de publicidad
To understand this evolution, you have to familiarize yourself with the foundations of programmatic buying, an impressions-based buying system that relies on algorithms generated from DSPs (Demand Side Platforms).

What for? It’s simple. DSPs need to access global ad inventory with millions of advertising impressions  in real time, with the ability to adjust to what every advertiser wants or needs.

The main draw of programmatic buying lies in its ability to automate the ad buying process in Ad Exchanges and on websites from a unified dashboard.

Differentiating between Programmatic and Direct Ad Buying

 Before reviewing best practices for digital ad buying, it’s important to understand the difference between programmatic and direct ad buying.

  • Direct buying occurs when a marketer buys impressions in bulk, normally in a specific context on specified sites and from a specific publisher. This involves hours of researching which publishers’ impressions will be best to optimize campaign performance and then negotiating the purchase before launching the impressions.
  • Programmatic buying occurs when a DSP automatically and instantaneously places ads on publishers’ sites after evaluating the quality of individual impressions from the best bidder.

Both buying methods have pros and cons and undergo different processes with online publishers. For example, though real-time buying allows an advertiser to reach wider audiences, it doesn’t offer a guarantee on return.

Best Practices for Digital Ad Buying

Real Time Bidding (RTB) marketing alludes to a type of digital advertising in which a variety of ad spaces are auctioned off in real time. The system identifies the visitor’s user information and then each is shown ads that correlate to their tastes and interests determined by data tracked from their online behaviors.
For this process to work correctly, it’s vital to make use of technology and big data. RTB wouldn’t be possible without generating and evaluating millions of data points. This data contributes intelligence to the entire programmatic buying process.

Additionally, advertisers can attract users more effectively thanks to being able to use data for the personalization of ad delivery. This is very evident if one’s to compare the effectiveness of traditional display campaigns.

Today, the majority of marketing departments are employing real-time programmatic buying for retargeting purposes, for example. However, programmatic ad buying allows marketers to also fulfill many other different strategies, analyze the relationships between all media channels, both online and offline, and consider segmentation possibilities.

10 Digital Ad Buying Tips

1.) Start with a general focus

Programmatic technology uses audience data to target specific consumers across vast amounts of ad inventory by using audience data to target individuals dynamically, on a one-on-one basis — in real-time. It’s particularly useful for advertisers who are seeking the reach of a large bulk buy without sacrificing the accuracy of targeting users.

Rather than pay for large inventory, advertisers hoping to reach consumers’ interest can bid for the right audience and the right time. Programmatic not only makes ads more relevant to consumers it also helps publishers to sell inventory in a more valuable way for advertisers.

Additionally, Demand Side Platforms, or DSPs are able to buy ad inventory across all sources with the use of computer programs called algorithms. An algorithm is a computer application that performs sophisticated calculations based on specific rules. For DSPs, these algorithms determine which impressions a specific customer should buy.

2.) Identify your target

As with any advertising strategy, digital or otherwise, marketers need to establish clear objectives and a well-defined target audience.

If you have a specific product or service to promote, or if you’re simply trying to amplify brand awareness on social media, you need to make sure that you’re reaching the audiences that are most apt to listen to your message. Otherwise, you’re wasting your time.

Start by determining demographic data, such as the gender, age, and location of your audience. After gathering that information, you can begin planning how and where to allocate your ad spend.

3.) Prioritize transparency

 According to Smart AdServer, a third of digital media buyers don’t bid on blind inventories. For that reason, it’s important to segment your audience and provide buyers with as much data as possible.

4.) Think Mobile

 The behavioral capabilities of programmatic buying technologies are strongly linked to cookies. Which is a problem when it comes to mobile, since there are no cookies on mobile devices.

In the past, mobile marketing was used to view products before completing a purchase in a physical store or from your desktop. However, according to eMarketer, 75.7% of U.S. buyers are willing to make purchases directly from their phones and over the coming years that figure is expected to grow significantly.

Additionally, 9 out of 10 smartphone users have used their phone at some point in the buying process, according to the IAB. This is why it’s important to adapt all creatives to mobile devices before starting your next digital ad campaign.

5.) Monitor minimum bids and block lists

Another digital media buying best practice  is the consistent monitoring of your minimum bids. If you’re aware of where your ads will get the most value for their traffic and track minimum bids once or twice a week, you can multiply your return in the short term.

6.) Identify what ad formats are growing

Consider the following data from ComScore: After viewing an online video ad, 64% of users are more predisposed to the purchasing a product online. According to Unruly, online video ads increase purchase intent by 97% and brand recognition by 139%. Still wondering what format to use?

Video generates double the engagement that traditional banner ads generate. Even interstitial ads (advertisements that temporarily take up an entire device’s screen) have average bidding prices that are 60% higher than those of banner ads.

In addition to their creative capabilities, new and more captivating ad formats like dynamic creatives, can be programmatically delivered to the user in real time.

7.) Find Similar Users – Lookalike Modeling

Leveraging the data collected from your cookies, DSPs can find new and undiscovered users that look like your customers to whom you can target your ads and optimize conversion rates as your campaigns progress. Lookalike modeling involves defining the attributes and behaviors of your most valuable customers and then using these profiles to target matching prospects. Since these new audience segments are similar to your current customers, you’ll enjoy a higher likelihood of conversions.

8.) Implement Dynamic Creative Optimization

If you combine the power of a DSP with the audience management from a Data Management Platform (DMP), your campaign’s performance will improve significantly.

This lift is attributed to the sorting and classifying of customers based on diverse criteria makes it easier to deliver more personalized ads in which creatives are launched based on where in the sales funnel a user is located.

9.) Brands go for in-house management 

With the emergence of new programmatic software platforms, companies are increasingly willing to control the advertising spend by keeping programmatic buying internal, facilitated by brand marketers. This is the area of programmatic spending that has grown most in recent years.

CMOs that directly manage their digital ad buying build internal competencies in the execution, measurement and optimization of programmatic campaigns.
 

10.) Use attribution models to properly measure campaign performance

The efficiency of programmatic campaigns is calculated by tracking post view and post click conversions. Therefore, client acquisition strategies should be data oriented, steadily measuring and predicting the media channels that willyield optimal results based on the brand’s campaign goals.

Finally, the ultimate best practice for programmatic ad buying is to constantly improve upon the above practices and strategies. At Digilant, we don’t simply follow best practices for programmatic ad buying, we create them as the needs of our buyers and the technology to serve them evolve. Programmatic ad buying doesn’t just help reach new clients; it uncovers new and more valuable audiences.

Interested in unlocking data and uncovering your brand’s full potential? Learn more about Digilant’s solutions here.

How Independent Digital Agency Cramer-Krasselt Built Its Trading Desk

For independent shops like Cramer-Krasselt, the shift to programmatic presents challenges. They don’t have the resources to pour into proprietary tech like the big holding companies. For Cramer-Krasselt, that has meant stitching together ad-tech partners to form its own trading desk — and educating all of its employees on the ins and outs of programmatic.

“For a long time, media-holding companies maintained the agency trading desks as a centralized profit center, and the next trend is midsized independent shops started getting into programmatic by working with companies like Digilant and Choozle,” said Eric Bader, managing director and co-founder for digital consultancy Volando.

The system (named “DesCK”) was moved out of beta last year, and now, the agency has an ad-tech team of 10 to run programmatic campaigns for clients including Edward Jones Investments, Cedar Fair Entertainment and blender brand Vitamix. The agency uses the technology infrastructure developed by its data management and five demand-side platform partners including The Trade Desk, and then adds its own data and budget-control system on top of that.

“We would be locked in if we build our own tech from scratch because there’s a cost, and once you want to change things, you cannot adjust quickly,” said Chris Wexler, the agency’s director of media and consumer engagement. “By leveraging others’ tech infrastructure, we can be very nimble in terms of what we want to buy, how we want to buy and how to measure it.”

One big differentiator in Cramer-Krasselt’s trading desk is that the agency has built it as a multi-DSP tech stack, with one single DMP that is governed by a proprietary analytical, fraud and budget management system that “significantly” enhances the agency’s DSP and exchange partners, added Wexler.

“If we had built DesCK with just The Trade Desk, while the tech is good, we would be missing out on the best results for our clients,” he said.

Cramer-Krasselt built its DMP based on Salesforce-owned Krux and then uses that DMP as “the core source of truth” to get the cleanest view of data possible. This is because if a marketer buys programmatic inventory from a publisher, for instance, the publisher’s own analytics may show it has 100,000 impressions per month, while comScore may say that the impressions are 90,000. Then, Google shows that the actual number should be 80,000 monthly impressions, while Cramer-Krasselt’s own ad server reveals that it is 70,000 monthly impressions.

“The numbers are moving around, so we need our own DMP to assess those data discrepancies and evaluate one DSP over another,” said Wexler.

5 Programmatic Advertising Tips to Boost Performance

By Wesley Farris Director of Partnerships at Digilant

Programmatic has evolved considerably. What was once an experimental technology, has now morphed into a cross-channel, data-driven ecosystem with unlimited opportunity and strategic value. In fact, U.S. programmatic spending continues to rise – it is expected to surpass over $27 billion by the end 2017, according to e-marketer. Today, the question is no longer “Will we use Programmatic?” but rather, “How will we use Programmatic?”

Despite programmatic’s growth and widespread adoption, many marketers still struggle with how to best leverage it to maximize ROI. That’s not surprising considering its vast menu of options — programmatic can leave many marketers wondering where to begin. But it doesn’t have to be that way. Below are five tips to help you navigate your programmatic options today:

1.Identify A Goal

goal1Before diving into programmatic, it’s important to first understand and acknowledge the objective of your effort. Is the goal of this campaign direct response or branding? Are you trying to drive people to a physical location or convert online? Are you trying to better understand your audience or learn when and where they are converting?

Identifying the goal of the campaign will enable the selection of the best programmatic tactics. For example, if your campaign goal is direct response, your programmatic efforts should include retargeting. If your goal is branding, focusing on domains with high impact ad units and domains with historical high viewability scores are good starting points. For instance, you might work with a partner who can measure viewability and Limit Fraud to ensure ads are highly visible. Overall, aligning your goal with your programmatic tactics will deliver better performance and improved ROI.

2.Identify The Right Marketing Channels

channel2There are many ways to reach an audience programmatically: desktop, mobile, mobile apps, video, native, audio, and TV, just to name a few. But how do you choose the right channels?Each channel has its pros and cons, and you should carefully weigh them when deciding where to spend your budget. For instance, desktop display tends to be affordable and flexible, but won’t drive as many clicks. Conversely, video and audio can drive high viewability, have better ad recall and are strong branding performers, but they come with higher CPMs.
So, if the goal is a low cost per action or return on ad spend, you are better off spending your budget on desktop and mobile display. If you are looking for better brand recall, video and audio might justify the higher CPM. Cross device targeting is essential if you are trying to drive conversions/sales in order to reach the target audience during all phases of the purchase cycle. In general, if you want to get more value from your programmatic media buys, don’t underestimate the importance of carefully selecting the channels you’ll use for your campaign.

3.Identify Data Layers

With the growth of programmatic, we’ve also seen the proliferation of audience segmentation and big data, both of which can be used to enhance and optimize campaigns.  A great way to visualize the data selection process is to think of audience segmentation as various layers of data. With each data layer, the goal is to filter and remove users that don’t fit the target you are trying to reach. For example, let’s say you want to target women who will be in market to
purchase maternity clothes.

  • Data ProgrammaticFirst data layer might try to segment the entire user population to identify pregnant women. This could be accomplished by looking at a combination of demographic data and apps on the user’s device.
  • Second data layer might look to identify pregnant women who have shown an interest in maternity clothes, or behavior to purchase them. A marketer could target them on search history, contextual content, and their physical location history. These two data layers will help you establish a baseline for pregnant women who have shown an interest in purchasing maternity clothes.
  • Third data layer could be the audience of users who have viewed specific products on a maternity clothes brand’s website and are retargeted.

Overall, a layered data strategy enables you to filter out non-applicable users, and focus on your ideal target audience. Doing so will boost the ROI of your programmatic effort.

4.Attribute Performance

programmatic attributionIt’s important to know what is performing in a campaign and why? Programmatic media allows marketers to understand performance at a level that is unmatched when compared to other traditional media such as print or TV.  Today, there are no longer limitations to properly attribute a programmatic media campaign, and marketers don’t have to rely on CTR or first/last click attribution. Instead, attribution allows marketers to truly understand — on a 1-to-1 level — how their media affected their bottom line. For instance, tying media to physical in-store traffic is a great way to take an abstract media metric and apply it to real world performance, and is readily available in the marketplace. Media can be tied to loyalty data or credit card transactions as well, so marketers no longer need to guess if a campaign made an impact on the bottom line. And from a branding stand point, marketers can just as easily tie a media campaign to the impact on their brand and how consumers perceive it.

5.Optimize

Attribution ProgrammaticFortunately, programmatic media provides more metrics, insights, and hard data than any other form of media.  Tapping into this data can greatly help you uncover insights that aren’t always intuitive, and improve the performance of your next initiative.
For example, if you are a retail marketer focused on sports apparel, you might assume that your audience might skew male. However, a programmatic campaign might reveal that your top performing audience is actually females 25-34.  Be sure to examine your programmatic campaign insights for learnings that will help you fine-tune future efforts. Doing so will ensure increase your ROI and bottom line performances.

There will always be ways to improve a media buy, and programmatic’s flexible capabilities allows for that continual optimization. Pre-flight, mid-flight, and post-flight analysis and strategy can ensure campaign performances continues to improve. When mapping out programmatic efforts, be sure to take the time to apply the the above 5 tips to boost success.

 

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