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The Life and Lies of Advertising Fraud

Posted on by Pavel Tantsiura
In this issue:

There is always someone who thinks he is smarter than the others who want to extract an extra buck or two without breaking a sweat due to some elaborate sleight of hand shenanigans. What is advertising fraud? Ad Fraud is probably one of the most poignant examples of fraud in any industry.

As such, programmatic advertising scams are one of the most significant problems in an adtech industry, the one that gives it a bad rap. You know how it goes: if there is any form of money and multiple middlemen involved — expect something fishy to turn up. According to AdAge, every $1 out of $3 spent on online advertising is snatched by the fraudsters.  

Every year ad fraud causes damages amassing up to $16,4 billion in 2017 with expectations to rise towards $20 billion in 2018. These are some crazy figures. But why those numbers are growing? Despite all efforts, every time there is a new technological solution to detect it — ad fraud evolves and starts all over again.

But first, let’s sort a few things out.

What is Advertising Fraud?

Programmatic digital advertising fraud is a deliberate, malicious activity that manipulates the delivery of ad content and prevents its serving to the targeted audience. One of its primary weapons is bots. These software programs carry out the dirty work.

AdTech attracts fraudsters with its money figures. Just think about it — the payouts are enormous and risks of penalty are limited. It is not card fraud where you can get a big-time if busted. It is not much you can do with it after you’ve been cheated. It is not like someone stole your money; it was you who spent it the wrong way. Sure, you’ve manipulated into doing so — but the fact remains.

Digital advertising scams operate on multiple levels. It can manipulate traffic, and it can work with more sophisticated things, such as impressions, conversions, and full-on imitation of user activity. For these kinds of scams, stats are the primary field of tricks. The distortions and obfuscations of a real state of things cause the challenges with Ad Fraud. Ad Tech is a performance-oriented thing. Numbers and results are everything. The effectiveness of the campaign is based on what the metrics show — in terms of traffic, bounce rates, impressions, conversions, etc.

However, metrics are fallible; certain manipulations with the information can rig them and this is the flaw exploited by the fraudsters. Sure, there are fail-safe mechanisms that prevent more blatant attempts, but there is always a way to “get on through” and “rig the game.”

What drives Ad Fraud?

To understand how to counter programmatic advertising scams, one needs to understand what drives the fraudsters with their malicious intentions to the Ad Tech industry. And the reason is in its very nature.

There are two major types of programmatic advertising scam operation. In terms of technical solutions — there is not much difference. The difference is in the scope and intentions of operation.

The first type is when a criminal intends to feed off your operation. It’s like a parasite that sucks resources (i.e., money) and is interested in a long-term relationship without making much of a fuss in the process. It is a form of pickpocketing in the realm of ones and zeroes.

Competitors can be the ones who perform the second type of ad fraud, as a means of disrupting the marketing operation and damage overall business proceedings. In this case, it can be very damaging and potentially destructive to the company.

How exactly Scams affect Digital Advertising?

While financial gain is the main reason for scams, the direct result in Ad Tech is not exactly that. It is insufficient information that affects critical decisions regarding the proceedings of the campaign.

In addition to wasting money, distorted stats and warped campaign results take the ground off the marketer’s feet and leave them bumfuzzled.

Even though the chosen strategy might be useful in a normal situation, the presence of malicious sources dilutes its effect.

Common Types of Ad Fraud

Cookie Stuffing

Cookie stuffing is one of the most common types of Ad Fraud. It is primarily used in affiliate marketing schemes. Cookie stuffing misleads and dilutes audience information and subsequently messes up the results of an entire campaign.

Cookie stuffing done right sucks the campaign into a warped wormhole. You get the results, and they often look outstanding. Judging from the performance stats your advertising is working, so you keep doing what you’ve been doing (while you actually lose money in reality.)

How does it work? Cookies are vital elements in tracking the user’s journey from affiliate to the central sites. When a user comes and clicks on an affiliate link — there is a cookie exchange. When a user comes to the source site — the source site pays for it to an affiliate. Cookie stuffing pads out the stats and makes the source site to pay more while gaining less.

Traffic fraud

Traffic generates revenue. However, traffic is a thing that can be easily imitated, and that imitation can trick the analytics into thinking that everything is going better than ever thus increasing spending for theoretical results. It is the easiest to implement as well as detect.

Impression Fraud

Impressions are in the center of CPM-based operation. The goal of impression fraud is to generate hollow fake impressions that will be subsequently traded as real albeit delivering zero benefits. Since these impressions are essentially useless, their uselessness affects overall CTR and thus it damages the position of the website.

Here’s how it works — advertisers buy ads from the publisher, but some part of ads is served to intentionally irrelevant low-profile websites that do not generate anything. However, advertisers do not see that immediately.

According to reports, their ads are served to legit websites relevant to the target audience. This trick is achieved by an elaborate redirect planted into ad calls.

Click Fraud

Cost-per-click is one of the standard models for digital advertising. Clicks are also one of the easiest things to rig.

According to Pixalate, in 2017 one click out of five was fraudulent. And there is a tendency towards two out of five. Why is it so? Click fraud is simple to pull off.

Ad Click fraud inflates the numbers of a click of CPC ad and presents a distorted picture of the ad activity. While the number of clicks is there — the results of the clicks are not. This racks up fraudulent charges and so on. A perfect bleeding scheme for the fast times.

Curiously, it is more often used by competitors than criminals.

However, ad click fraud is the easiest to spot all types of Ad Fraud. You can do it just by checking the reports on the following subjects:

  • IP address
  • click timestamp
  • action timestamp
  • user agent

Action Fraud

Action Fraud is a more sophisticated type of Ad Fraud. While Traffic fraud rigs the numbers and distorts the stats — action rigs the stuff that makes money moving. Action Fraud is designed to imitate meaningful user activity.

As such, Action Fraud is much more dangerous and can potentially completely derail the campaign and affect the position of the website.

Conversion Fraud

Conversions are the spice of Ad Tech. It is the most important thing in business. While merely an action taken by the user — it denotes an intent and this thing costs a lot.

How does it work? There are ad fraud bots involved. With a little help from a couple of scripts, you can train the bot to perform simple actions.

The simplest manipulation includes filling forms with some sort of information. More elaborate bots can also click on the links, imitate user journey,s and even download files. Such things can seriously mess with CRM.

Retargeting Fraud

While considered to be more precise and thus a more effective form of digital advertising, retargeting can be easily muddled by misleading information.

How does Retargeting Fraud work? With a little help of ad fraud bots, fraudsters try to realistically imitate user behavior in a couple of specific scenarios. Because of its behavior, bots usually fly below the radar and are not spotted as bots. As a result, bots perform actions that qualify them as leads.

This trick boosts the prices for their impressions and since there is nothing you can do with them business-wise — it turns into a waste of money and effort.

Affiliate Fraud

The affiliate model is one of the most common in digital marketing. It is a surefire deal. You get a conversion — you get paid. However, it can also be exploited for malice.

Here’s how affiliate fraud works — just like in a regular operation affiliate attract users but worked over in order to rig the stats and bloat the charge.

One of the most effective approaches involves Cookie Stuffing. Instead of a usual cookie exchange, affiliate sites spurts loads of cookies onto user computers that provide false flag signals. After that affiliate claims his cut.

However, this fraud can be disrupted by anomaly-based and credential detection and neutered before wreaking havoc.

Ad Fraud Detection & Prevention Methods

The problem with Ad Fraud, in general, is that you can’t reverse its effects. If the damage is done — you have to admit the failure and move around it. The only effective way of fighting Ad Fraud is by preventing even the slightest possibilities for it to happen.

You can also read our case study for a Custom Ad Fraud Detection System that shows the following methods on practice.

There are four major types of Ad Fraud Prevention:

Signature-based

You know the saying — actions speak volume. And ad fraud bots tend to act unnaturally overzealous regarding ad content.

The signature-based method uses a set of patterns to detect suspicious actions, impressions, click, or traffic. It compares patterns with the monitored activity and determines whether it is suspicious and worthy of further investigation.

As a result, fraudulent activity can be shut off before it settles in and brings some action.

Anomaly-based

If there’s something strange in your neighborhood — that’s an anomaly and that is telling. The anomaly-based method uses statistical analysis and historical data to check ad spaces, websites, or publishers and detect questionable happenings, such as suspiciously spiking traffic, odd ad space placements, and other things of interest.

It is very useful for neutering bot and click-farming facilities.

Credential-based

This method is used to determine the possibilities of fraud activities. In order to do that, it uses reverse crawling and checks the content and its tagging. Then it performs a comparison with requirements for impressions. Also, it compares the value with the trustworthy rankings like Alexa.

If things don’t click — it is implied to be a possible leeway for fraudulent activities.

Honeypot-based

Bluff is the best way of exposing the fraudster. In the realm of ones and zeroes that is even easier than in the real world as bots are script-driven and don’t have second thoughts regarding the heat around the corner.

How does it work? A honeypot is an additional field in the form that is not seen by the users due to a special script. However, bots don’t know that, and they fill that field and bust themselves. This triggers the rejection mechanism that prevents further fraud bot activity.

IP Blocking

After the fraudulent activity was exposed — the next step is to block the source. One of the more effective methods is to block its IP. That will surely limit the fraudster’s reach.

Basically, it is a good idea to maintain a wholesome blacklist and constantly compare it with widely available blacklists. Aside from proven fraud-likely IP’s, there also must be an additional list regarding suspicious IP’s.

However, it should be noted that IP Blocking is not a firewall that will prevent all instances of fraudulent traffic – it can limit and neuter the exposed IP’s but it can’t predict possible fraudulent IP’s. 

We have an entire article dedicated to how ads.txt helps to Fight Ad Fraud.

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AdFraud Problems and Solutions

Problem Who’s affected? Solutions
Spambots inflating impressions, clicks, views, etc., driving down ROI Advertizers Anomaly-based / Signature-based / Honeypot / IP Blocking
Adverts posted on dead space low-traffic sites Advertizers Signature-based
Cookie Stuffing distorts campaign performance results and inflates affiliate conversion charges Advertizers Anomaly-based / Credential-based
Conversions forgery messes with CRM and causes massive time/money waste Advertizers Anomaly-based / Credential-based
Retargeting manipulations cause monetary losses on charges for the hollow actions Advertizers Anomaly-based / Signature-based / Honeypot / IP Blocking

In Conclusion

Ad Fraud is one of the biggest banes of an advertising industry that runs over the thousands of advertising ecosystems. Hopefully, this problem is actively tackled and there are numerous solutions that limit the influence of the fraudsters and prevents them from damaging the publishers and advertisers.

Real-Time Bidding 101: Guide for Advertisers and Publishers

Posted on by Pavel Tantsiura
In this issue:

The modern Ad Tech industry is at the cutting edge of technological progress. It uses the most advanced methods of data analysis and content delivery in order to present an advertising content to the user in the most precise and effective manner.

Ad Tech is fascinating because of all the things it does to present the most accurate content to the user. All the algorithms used to analyze user behavior match it with the present ad inventory and deliver the content — there is a lot of going on behind the scenes of the simple ads delivery operation.

What is Real-Time Bidding?

Real-time bidding approach was developed in the late 2000s out of ad networks dire need to utilize those parts of ad space inventory that were left unused for a variety of reasons, most notably lack of demand from the advertisers.

But instead simple utilization, Real-time bidding became a long-awaited shot in the arm to the ad industry that revitalized it and brought it to another level. Soon enough, it became apparent that the RTB architecture was very effective not only in filling the remnant inventory but in managing the entire inventory without much of a fuss.

At the moment, Real-time bidding is handling around 90% of all programmatic buying in digital advertisements which comprises a third in overall spending on digital ads.

How Real-time Bidding Works

Real-time bidding is one of those things that are best described in practical terms.

Let’s take a standard programmatic advertising situation. You know how it goes — you visit some site, watch some stuff and go on elsewhere but then there are some ads related to the stuff you’ve been watching on that site following you elsewhere presenting something that might be interesting to you. That’s retargeting in action. However, this is only a part of the story.

There is an entire sequence of events triggered by the users to visit the page that occurs in order to present ads to the user.

Here’s what happens. The user visit triggers a request from the publisher to the Supply-Side Platform that analyzes the request and transfers it to the Ad Exchange that connects with Demand-side platforms (AKA DSP) on behalf of the publishers and opens up an ad call bidding request to the available advertisers who enter the bidding process through the Demand-side platforms.

That’s where Real-time bidding occurs.

Real Time Bidding Diagram

The process real-time bidding can be described as a fully-automated sequence of bids that works under a couple of pre-set algorithms with very distinct specifications regarding relevant audience segments, content, price ranges, and other elements.

Basically, Real-time bidding is an auction where advertisers try to outbid one another for the specific ad space. The endgame is usual — those who place the highest bid get the spot. The difference between traditional auction and RTB is that it all happens at lightning-fast speed. We’re talking about thousands of such auctions occurring at the span of milliseconds. Just think about it — a standard transaction in RTB usually takes about 100 milliseconds to happen.

Needless to say, in order to maintain such high proficiency in this process, one needs some serious scaling capacities.

Benefits of Programmatic Real-Time Bidding for Publishers and Advertisers

The introduction of Real-time bidding into digital advertising became a game-changing moment for the industry. It completely transformed the way advertisements are presented to the user and introduced a completely new business model for advertisers and publishers.

Overall, there are four major contributions of RTB protocol to ad tech industry.

Streamlined Process

The biggest innovation of Real-time bidding to ad tech operation is streamlining of the process to its bare essentials. Instead of sweep buying of the bunch of impressions, advertisers can do much more cost-effective per-impression buying process which makes the most out of ad budget due to increased flexibility of the process.

On the other hand, RTB turned the laborious and often tangled process of placing ads on relevant spaces into the more automated realm.

The whole meticulous process of sorting ad spaces and checking its relevance and credibility is relegated to the automated platforms that do all the dirty job within a blink of an eye. Now — all it takes to make an effective ad tech operation is to set the requirements and adjust them according to the incoming results.

Superior Efficiency & Flexibility

Campaign Performance and ability to adjust campaign accordingly is one of the strategic priorities in an ad tech operation. RTB algorithm brings additional flexibility to the mix.

The thing is — Real-Time Bidding allows managing the campaign as if it was a real-time strategy — as it goes. This gives a lot of space to maneuver and analyze the efficiency of ads with certain audience segments and ad spaces. This leads to constant improvement of the strategy to its most effective state. Real-time factor reduces the waste and impact of wrong decisions to a minimum. This also makes whole advertising turnaround much faster.

Price Optimization

Keeping an ad budget under control is one of the biggest challenges of maintaining an ad tech operation. Real-time bidding allows to automate that peculiar aspect and keep the things within reasonable boundaries by setting specific price-requirements.

The other important aspect of budget control is price optimization which can also be automated in correlation with the campaign performance results via real-time analytics. This allows to maximize the revenue and concentrate an effort on the most lucrative audience segments.

Anti-fraud Protection

Ad Fraud is one of the biggest problems in the Advertising industry. Each year it eats up a significant part of ad spending of advertisers. Given the lightning-fast nature of RTB operation — it seems like tailor-made environment for massive fraudulent activity.

However, with the increased automation of the process and constantly adaptable campaigns — the overall influence of ad fraud is minimized. The fact of the matter is — modern fraud detection system cut off the majority of fraudulent sources long before they get into the mix.

In addition to that, campaign analytics can expose any semblance of suspicious activity (for example, anomalous click-through rate) and take them out of charging due to fraudulence.

Challenges of Real-Time Bidding

Efficiency Scaling

Scalability is one of the biggest challenges of ad tech. Since the whole operation needs to maintain high-speed reaction and adjustment to the incoming information — the scaling capacities of a DMP must be nothing less than exquisite, which is a challenge considering how much information goes through and how fast it must be processed.

The solution for the scalability challenges lies in cloud computing. For example, such platforms as Google Cloud, AWS and Azure offer autoscaling features that take a lot of headache out of an equation.

Prediction Mechanism

The prediction mechanism is one of the most important elements of an ad tech operation and as such it must be tailor-made to the requirements of your operation and deliver the results according.

In the center of the prediction mechanism is a combination of supervised machine learning algorithms that includes classification, regression process.

These processes sort out and recognize the incoming data and subsequently calculate possible outcomes and their likeness of accordingly.  These mechanisms allow predicting the possibilities and opportunities for conversions with particular audience segments on specific ad spaces.

In addition to that, there is an additional algorithm involved for the purposes of user modeling and subsequent that adapts to the results of the campaign.

Ad Fraud Detection

While overall Real-time Bidding is much more controlled operation than other types of digital advertising, its velocity (i.e. too much too fast) makes it much more ad fraud-prone. In order to shut off any semblance suspicious activity out of the equation and minimize the influence of ad fraud on an ad campaign.

The challenge comes with identifying and preventing ad fraud activity. The thing is — ad fraud is constantly evolving and each day brings new challenges.

However, there are certain patterns that can be easily identified in case of bot activity. With the little help of certain algorithms, bots can be shut off from the system and their activity will do nothing more than shake the air between the ones and zeroes.

Bid Optimization

The process of bidding is a balancing act — you need to know approximate ranges of your spending and plan the whole thing in relatively long terms. The whole bidding process is organized around the campaign goals — how many clicks or conversions are expected and what can be considered as a success.

In addition to that, you need to assess the effectiveness of the spending on a particular type of ads and consider different options for a variety of scenarios.

The key thing for an effective bid optimization is predictive analytics. The stats give you the bigger picture of your campaign in real time and that will help you to adjust bidding algorithms accordingly on the go without experiencing an aftermath of past ineffective decisions.

Budget Control

The other important element of RTB optimization is budget control. The fact of the matter is — there must be boundaries of how much can for certain types of ads and over certain periods of times.

Here’s how works: if an ad of a specific type delivers good results on a specific ad space — there are more of such ads placed and if a specific type of ad fails to deliver in a particular ad space — it ceases and resources are relocated elsewhere.

Conclusion

Real-time bidding is one of those technologies that require a clear understanding of its possibilities and distinct boundaries to work in. We’ve covered the basics of the concept and broke down all the major challenges that come with the implementation of this process – but in the end, it all comes to business analysis during the inception phase to make sure all the RTB algorithms and other technologies involved are chosen wisely. 

What You’re Paying For or How Ads.txt Helps to Fight Adtech Fraud

Posted on by Pavel Tantsiura
In this issue:

Considering the amount of advertising online, we’ve all faced a situation when we were misled by ads. Expectation vs reality is fun when you see collections of other people’s pictures experiencing online shopping troubles, like this:

Expectation vs Reality in Online Shopping

However, when you’re the one who is trying to understand where your money is going, the situation might not seem fun. Especially so, when you are buying ads for your business (and the budgets are not small). How to make sure you’re not a victim of advertising technology fraud? IAB Technology Lab offers a simple enough solution: ads.txt implementation.

The Problem

One of the major problems, when one is dealing with programmatic ads, is being tricked by the scam artists and ending up paying for the ad space that you don’t get.

One of the most common scammer tricks is to buy cheap ad space from sites from the low-end of the spectrum, yet advertise it as premium space and charge a much higher price for it. As a result, you might think you’re buying Bloomberg.com ad placement when in reality it’s some WeirdoVillage.biz with an annual audience of 33 users. Not the result you’re looking for.

How often this happens? Google and IAB run secret tests and discovered thousands of fake ads on major exchanges like AppNexus, PubMatic, and even Google’s own AdEx exchange. Whoops.

The Solutions

IAB’s started an initiative to increase transparency regarding programmatic advertising called ads.txt implementation. Basically, it’s a text file that’s published in the site’s root directory with the information on Authorised Digital Sellers (or ADS, which is where the name comes from).

This file creates a public record of sellers and helps buyers to quickly identify who is allowed to handle the ad inventory for which publishers, making it much harder for scammers to sell fake inventory for profit.

For example, here’s a part of Bloomberg’s ads.txt:

google.com, pub-8615378344367221,  DIRECT
google.com, pub-1979187633561026, DIRECT
indexexchange.com, 184795, DIRECT
Appnexus.com, 8355, DIRECT

As a buyer, you can see which sellers you should contact in order to have your ads run on Bloomberg. Also, the ads.txt provides the IDs of the publishers, so you can compare the data you get in your ad reports to the identification numbers of your publishers.

What’s Next?

As of August 2017, out of the top 500 publishers around 7% had already implemented this solution on their platforms. The early adopters include such media giants as The Washington Post, Forbes, The New York Times, Bloomberg, Gizmodo Media Group, and others.

As of November 2017, you can see the stats of ads.txt adoption, pulled from Alexa’s top 10,000 global domains that sell advertising (except Google, Amazon, and Facebook since they don’t sell their inventory to third-parties.)

The rate of ads.txt adoption among Alexa's top 10K publishers

We mentioned above that there are solutions, not just one. Many publishers are waiting for the blockchain technology to change this area in the industry. Indeed, blockchain can help to streamline the data and weed out the fake ads. However, widespread implementation of this technology is still years away and ads.txt is a much simpler and quicker way to protect authenticity.

Also, if you are a publisher, consider implementing this solution on your platform. It doesn’t cost you much (in either time or money) and, in fact, you might actually profit from it since many ad buyers are switching to publishers with ads.txt implemented.

Read also

Cloud computing security issues

How to make a live streaming website

Types of data breaches

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Digital AdTech: The Complete Guide

Posted on by Pavel Tantsiura
In this issue:

You might’ve heard the term Ad Tech, but wasn’t sure what it meant. How does it all work, considering the vast data transfers and processes? What are the Ad Tech industry challenges? All about ad campaigns, ad networks, media buying, and more in our article.

In this day and age, the Internet is the ultimate field of opportunities. Just think about it – everything is within a click or two (okay, sometimes, three.) You can do practically anything. Naturally, you can make money on the web – in fact, you can make it out of any user’s move (because duh, why not?)

The whole monetizing frenzy is hitting the fever pitch right now and it important to understand how to “make it” “the right way.” The advertising industry might seem like a logical answer.

Since the digital advertising industry is experiencing a period of bloom due to the increasing amount of time spent by consumers on digital media – it is a logical solution for an issue of monetizing traffic and a sound way of improving interaction with the user on the platforms.

digital-advertising-vs.-programmatic-advertising

What is Ad Tech?

Adverting Technology (Ad Tech) is an umbrella term that describes systems of analyzing and managing tools for programmatic advertising campaigns. 

It covers the entirety of the ad delivery process from selecting the subject of an ad and its position to choosing its recipient. Ad Tech solutions allow you to see the bigger picture regarding your campaign and lets you make use of it to maximum effect.

Direct benefits of this tight knot of broad array processes are the higher efficiency of operation which means growing brand recognition which leads to increased profits. That indirectly leads to an expansion of interest.

However, there is a catch. Ad Tech is not something you jump on and ride. Digital Advertising is a costly thing and you need to be sure that every dime is doing tick-tick-tick. The whole thing is extremely demanding from technical and logistical points of view. It involves a staggering amount of data and needs enormous computing capacities. Because of that, you need the services of Ad Tech companies who know it inside out and can turn it upside down to get through. In this sense, AdTech companies are some sort of cavalry.

The primary benefit of its use is that it minimizes budget spending and makes the digital marketing strategy much more cost-effective.

In order to make maximum effect from the Ad Technology adjusted campaign, the company needs a system that is specifically designed for its needs. The mechanisms that process and categorize incoming data need to be specified to a tee. It should fit perfectly in order to make the process of managing, delivering, and targeting the adverts as useful as possible. It helps you to make sense of the collected data and put it to use. It finds the links and connects the dots.

Basics of Ad Tech

Ad Tech’s primary field of operation lies in the analysis, managing, and delivering advertisements according to the requirements of the ad. 

The endgame of every campaign is more or less the same – increased effectiveness and growing activity on the used ad space.

In the center of Ad Tech’s operation is the advertising ecosystem that consists of Advertisers, Demand-side platforms, Ad Exchanges, Supply-side platforms, and Publishers. Together they form a loop of ad supply and demand that generates revenue – this is achieved through collecting and processing information on the user activity on a particular platform.

advertising technology in digital advertising campaigns
The importance of user data

Why is user data important for Ad Tech?

It is important to understand that in Ad Tech value of information depends on the way said information is further collected and used. The main source of information in Ad Tech is the consumer. His contribution is technically very simple – it consists of merely hanging around on a certain site. However, it involves a lot of machinery behind the scenes that gather incoming information in one place.

There are two ways of getting data:

  • Third-party – when you buy it from somebody else;
  • First-party – when you gather it on your own;

The endgame is that it refines ad targeting with some fancy data spice – that results in a substantially more inspiring bottom line. Since we still keep getting “Why? Why? Why?” here’s snappy reasoning: actual data taken from actual people (with values, behaviors, attitudes, and attributes) allows delivering product directed to the target audience accordingly and not approximately.

In other words – you don’t snipe with your eyes closed and hands behind your back. But that precious information is not lying around waiting to be picked up. It needs to be collected – and it happens pretty much in the same manner as bees collect nectar.

What kind of user data feeds Ad Tech industry?

What kind of user data feeds the Ad Tech industry?

A thorough study using user tracking (among other things) forms the foundation of an ad campaign. Subsequent reaction of the consumer to the advertising leads to further developments. Not only that but it also helps to calculate the best area for placing ad content.

Among the parameters monitored are:

  • Referring sites – from where the user came from;
  • Overall journey (user experience) on-site – including mouse cursor movement;
  • Events (scrolling, clicks, highlights, media views, other stuff);
  • Search queries;
  • Time of session;
  • Behavior on site:
    • Contextual and thematic preferences to certain topics and pages;
    • Various interactions with the page’s content (downloads, etc);
    • Transitions to another place through links and ads;
  • Demographics (if not blocked or obscured);
  • Consumer’s gear (browser specs, ad-block on or off, etc.);
  • Interaction with ad content;

There can also be direct feedback (comments, etc.), but it is purely optional and usually, it is extremely insufficient.

While gathering these kinds of information can be considered as stretching the limits of user privacy – it also allows to deliver of much more relevant and useful content to the user who makes the case of a more pleasant user experience with a couple of benefits.

Even though that breakdown makes it seem like a relatively little thing – in reality, it is millions upon millions if various events. And that amount of information needs some serious power to be handled properly.

how-to-manage-advertising-campaigns-with-ad-agencies
How does Ad Tech manage user data?

How does Ad Tech manage user data?

One of the primary “weapons” used by Ad Tech is retargeting. It is a way of bringing the users back to the site after they left. This method works with showed intentions of the users that were registered by the system. It shows ads connected to it throughout the user’s subsequent journey through the web.

This information helps to makes ads closely connected to the customer’s interest. Usually, it is one of the two – it is either based on the context of a session and the preferences of the user. As a result of accordingly adapted content the value of the ads to the customer increases and so are the chances of his reaction to it.

However, the collected data on its own is unstructured and needs to be sorted out.

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Collected and unstructured data should be sorted out and for that, it is being transferred from the site to the Data Management Platform (DMP). Its purpose is to go through, analyze and categorize incoming data, which helps to segment the audience and optimize the campaign correctly. DMP also ties activity and incoming results of the campaign together into one relatively easy-to-follow interface where it is.

After data is sorted out – it is sent to Ad Server which operates the ads through the ad spaces and directs specific commercials at specific users. That is where retargeting kicks in. Data on user interaction with ads is also being collected and sent to DMP. That allows adjusting the campaign according to incoming results.

The basic scheme of Ad Tech operation looks like this:

  • User activity and behavior on site is being monitored (find out how to make behavioral targeting GDPR-Friendly);
  • Data from the website is being transferred to the Data Management Platform where it is  being sorted out, categorized, and segmented according to set specifications;
  • After that, the segmented data is sent to Ad Server which delivers appropriate and relevant ad content to the user. It may be:
    • Personalized according to user behavior and traits;
    • Contextual – based upon user activity.
  • User activity on the ads is being monitored;
  • Ad Campaign adapts to incoming information and collects the cream of the crop.

If done right – Ad Tech maximizes the efficiency and profits of the campaign.

media-agencies-create-ad-tech-solution-for-mobile-apps
How does Ad Tech generate revenue?

How does Ad Tech generate revenue?

 Ad Tech ups the stakes considerably by making the process of interacting with ads the part of money-making. It is achieved by the diverse system of monetizing where every player involved gets his cut for his services.

One of the biggest innovations that brought in Ad Tech is a clarification of the balance of responsibilities in the ad campaign. Basically, there are three major players in Ad Tech:

  • Advertisers – the ones with the adverts. DSP is Advertisers middle-man to the Ad Exchange
  • Publishers – the ones with spaces for adverts i.e. ad inventory. SSP is the Publishers middle-man to the Ad Exchange
  • Ad Exchanges – these serve as the mediator between advertisers and publishers. Ad Exchanges operate through DSP and SSP to both sides of the operation. The main purpose is to provide connections, communication to each of them.

Monetization occurs according to the selected business model. Its general operation includes fees divided between involved parties – advertisers, publishers, platforms. In any case – everyone benefits from everyone.

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The most common and effective models are:

  • Cost per impression (CPI) – more often tied with cost per thousand / cost per mile. Preferred by ad publishers more than advertisers. Usually combined with cost per click ratio;
  • Cost per action (CPA) – when the user more directly interacts with ad content i.e. cause conversion. This can be furthered into cost per install which directly deals with consuming the product;
  • Cost per click (CPC) – splits the risk between the publisher and the advertiser. Best used for contextual-based content. CPC later evolved into click-through rate—revenue based on the number of clicks divided by the total number of impressions served throughout the campaign;
  • Cost per lead (CPL) – when ad content brings contacts with consumers.
Advertising Technology Conclusion

Advertising Technology: in conclusion

One of the significant advantages of using Ad Tech is that it allows integrating the whole toolset into a single system. Numerous automated processes and conjunct workflows enable more precise and expedient audience targeting. Because of that, it is possible to collect more diverse data that will result in highly relevant and accurate inciting ads.

There is no magic behind Ad Tech – it all depends on skills and ability to use them correctly. The scope of operations is leaning on tried and tested solutions and reliable platforms to keep the information safe from leaking and to stay away from fraud.

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AdTech, Big Data, AI, and Machine Learning Conferences and Meetups You Shouldn’t Miss in 2018

Posted on by Pavel Tantsiura
In this issue:

Here’s the list of upcoming AdTech / MarTech, Business, AI, and Machine Learning-oriented conferences worth visiting.

It’s time to catch up with the latest news from industry insiders, set up some new connections, and expand your professional network. There is whole lotta interesting stuff going on. It’s better to know what happens when in order to get the latest insights from the folk in the know.

Programmatic I/O

  • San Francisco, CA, USA
  • April 10-11, 2018
  • Topic: AdTech
  • Website

Stay ahead of programmatic trends and connect with peers and industry partners you won’t meet anywhere else. Hear from innovators, industry leaders, researchers, and analysts on both the buy and sell-side of programmatic media and marketing.

d3con

  • Hamburg, Germany
  • April 10-11, 2018
  • Topic: AdTech
  • Website

Since 2011 d3con is the first and biggest German event about the future of digital advertising. More than 1,500 participants from the leading agencies, publishers, and service providers meet once a year in Hamburg to discuss, network, and learn at the top level.

AI Expo Global

  • London, UK
  • April 18, 2018
  • Topic: AI
  • Website

Topics covered include Business Intelligence, Deep Learning, Machine Learning, AI Algorithms, Data & Analytics, Virtual Assistants & Chatbots as well as case study based presentations proving an insight into the deployment of AI across different verticals.

MarTech 2018

  • San Jose, USA
  • April 23-25, 2018
  • Topic: MarTech
  • Website

MarTech® is for senior marketing, IT, and digital executives and experts at the intersection of marketing, technology, and customer experience. What’s working? What’s not working? Dial into the global digital transformation with the marketing technology explosion at The MarTech Conference!

Artificial Intelligence Conference: New York

  • New York, NY, USA
  • April 29, 2018
  • Topic: AI
  • Website

The Artificial Intelligence Conference delivers an unsurpassed depth and breadth of technical content—with a laser-sharp focus on the most important AI developments for business.

COLLISION

  • New Orleans, LA, USA
  • April 30, 2018
  • Topic: Business
  • Website

The Collision is “America’s fastest growing tech conference” created by the team behind Web Summit. In three years, Collision has grown to almost 20,000 attendees from 119 countries. Attendees include CEOs of both the world’s fastest growing startups and the world’s largest companies, alongside leading investors and media.

AdSummit

  • Kyiv, Ukraine
  • May 16-17, 2018
  • Topic: AdTech
  • Website

Ad Summit was designed for digital advertising executives to implement best practices & strategies, expand their markets and generate a new revenue stream.

Big Data: Toronto 2018

  • Toronto, Canada
  • June 12, 2018
  • Topic: Big data
  • Website

The conference will focus on technical and practical verticals including use cases around predictive analytics, advanced machine learning, data governance, privacy, cybersecurity, Smart Home & IoT, digital transformation, Hadoop, cloud analytics, and cloud computing.

Deep Learning for Robotics Summit

  • Amsterdam, the Netherlands
  • June 28, 2018
  • Topic: AI / Machine Learning
  • Website

Where AI meets the real world. Improving robotics via deep learning & creating the next generation of smart robots

Artificial Intelligence Conference: San Francisco

  • San Francisco, USA
  • September 5, 2018
  • Topic: AI / Machine Learning
  • Website

The Artificial Intelligence Conference brings the growing AI community together to explore the essential issues and intriguing innovations in applied AI. We’ll delve into practical business applications, compelling use cases, rock-solid technical skills, dissections of failures, and tear-downs of successful AI projects.

Future Port Prague

  • Prague, Czechia
  • September 6-7, 2018
  • Topic: AI / VR / Healthcare
  • Website

By creating Future Port Prague together with our visionary partners, we want to help people and businesses in our region better understand the phenomenon of exponential progression; not just the technology, but the deeper societal changes that will require a rethinking and rewiring of our business models and environments, our education systems, and most importantly our own mindsets.

Ad: Tech

  • London, UK
  • September 26-27, 2018
  • Topic: AdTech
  • Website

As we arrive in a post-GDPR world, what will advertisers and marketers have to consider in order to develop innovative, yet compliant channels of engagement? Now co-located alongside stellar industry events Technology for Marketing and eCommerce Expo, ad: tech London is here to help savvy practitioners unlock the power of the latest emerging tech, spur opportunities for experimentation, and open minds to the future.

Artificial Intelligence Conference: London

  • London, UK
  • October 9, 2018
  • Topic: AI / Machine Learning
  • Website

Organizations that successfully apply AI innovate and compete more effectively. Those who fail to implement AI successfully will fall behind. The AI Conference in New York will give you a solid understanding of the latest breakthroughs and best practices in AI for business.

World Summit AI

  • Amsterdam, the Netherlands
  • October 10, 2018
  • Topic: AI / Machine Learning
  • Website

From applied solutions for corporates and enterprises to the implications of AI on society, including ethics and AI4good, World Summit AI will tackle head-on the most burning AI issues for 2018 and beyond.

Web Summit

  • Lisbon, Portugal
  • November 5-8, 2018
  • Topic: Business
  • Website

We live in uncertain times for business. At Web Summit we welcome the people who shape the world around us. Our attendees hear from C-level executives driving change at the world’s most influential companies, participate in workshops, roundtables, and more.

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The Essentials of Retargeting Ads in Advertising

Posted on by Pavel Tantsiura
In this issue:

The world of digital advertisement is strange and confusing. All those buzzwords: ad remarketing vs. retargeting, data management platform, ad fraud detection, data segmentation, and so on. Sometimes it seems like the Internet was made specifically for it.

On the one hand, ads are simply a means of promoting certain kinds of products and services — a reasonable solution for exposure. But on the other hand, if you think about the mechanics behind delivering this or that ad to the customer — it gets really-really complicated.

In a way, it is fair to say that over the years digital advertisements had evolved into a legitimate kind of fabric of The Internet. You can’t imagine a web page without obligatory ad spaces.

The rise of Facebook, Twitter, Tik Tok, and Instagram started an ad gold rush of sorts — every advertiser wanted a piece of the cake. This caused the ad tech arms race which contributed to the rapid evolution of the ad tech industry.

Over the years certain advertising techniques had been developed. Some of them came and went, but some had proved to be a real deal. The thing is — advertisers go to incredible lengths to make the process of delivering ads as smooth and effective as possible.

That’s where one particular buzzword starts appearing frequently — ad retargeting. It is one of the most effective methods of delivering advertisements on the Internet.

Why is ad retargeting so awesome? Because it offers a completely different approach.

Why? The trick is simple — it offers a completely different approach. Instead, trying to shove certain products down the users’ throats by strategically littering various ads all over the place, retargeting applies contextual tracking methods and shows users something they are interested in and keen to purchase.

What is retargeting of ads?

Ad Retargeting (AKA Remarketing) is a method of delivering relevant advertising content to the users based on a digital footprint and collected user data such as preferences and on-site behavior.

Why is it important? It might sound a little bit clumsy, but here is an explanation for ending all comments on the matter — actual data taken from real people (with values, behaviors, attitudes, and attributes) allows product delivery directed to target audience accordingly and not approximately. It is a long way of saying “giving people what they want.”

The biggest advantage of applying ad retargeting is a drastic increase in the efficiency of delivering ad content. Here’s how:

  • Keeps the campaign costs streamlined and within reasonable scope;
  • Cuts the dead weight of disinterested users and leaves only those who have expressed (clicked, if being exact) some interest on your website (whether it is product or service or something else.)

Retargeted ad content is based on the actual interests of the users calculated out of their behavior on the source site. This makes ad content significantly more relevant to the users. That peculiar detail ups the chances of getting those sweet conversions, i.e., purchases or downloads.

That’s a big deal. Just think about it — according to recent studies around 98% of users leave the website before converting. 98%, Karl! Retargeting done right can significantly down that number.

Overall, the purpose of Ad Retargeting can be summarized by the following so-called “prime directives”:

  • Increase brand awareness through the multi-channel presence and personalized ad content;
  • Convert awareness into an interest that will result in sales/downloads and subsequent revenue;
  • Expand the market turnaround through a combination of awareness and sales conversion results (thus more marketing opportunities).

Every Ad Retargeting strategy revolves around these three directives in one or another.

Why does ad retargeting matter?

Conceptually ad retargeting is based on one simple thing — users are not focused on only the product; their attention span is limited and disjointed. In fact, they are in a constant process of journeying. Because of that, they need to be reminded of something in order to persuade them to proceed. Think about retargeted ads as subtle and reasonable nudges.

Based on the incoming information, ad retargeting performs a following of the user with the content relevant to him. This ad content follows a user on every site he visits and constantly reminds him of either “you might also like” kinds of content or some sort of “unfinished business” in case of some unfinalized actions such as purchases or registrations or anything else. Ultimately, the user can be convinced to perform certain actions (however, it depends on the message itself more than the technology).

For example, users don’t always purchase some product right away — they can be distracted or lose interest for some reason. That’s where retargeting flies in and makes the save.

Or here’s another example — the user downloads a certain application. In this case, retargeted ads can suggest some apps similar to that he already uses.

On a more basic level, ad retargeting can be applied internally on-site as a means of customizing content according to the user’s on-site behavior. For example, if he’s reading about Conan the Barbarian, he might be interested in checking out Ator The Iron Warrior.

But you might ask “But what about banner blindness?” Here is how ad retargeting counters banner blindness — the trick is in playing on the existing engagement of the user to certain kinds of content (product, service, texts, etc). Because of that added relevancy, users tend to notice otherwise ignored ads.

The current state of the ad retargeting/remarketing industry

At the moment, Ad Retargeting is one of the premier methods of delivering relevant advertisements to the users. It is easy to see why — unlike straightforward ads that simply hang on the ad space and are promptly ignored retargeting provides relevant ad content that has more chances to click with an audience and generate conversion.

Aside from advertising itself, retargeting is closely associated with eCommerce. Just think about how many times you visited some online store and then had saw loads of related ads with some suggestions following you on every site — that’s remarketing in action.

Another significant industry where Retargeting is widely used is the news media. But instead of purely pragmatic intentions of selling something, retargeting is used for means of content customization based on the topics and user preferences.

Retargeting stats 2018

Here are a few stats for you in terms of retargeted advertising:

 

How does retargeting work?

Ad Retargeting operation revolves around information. Just like The Prisoner’s Number Two — Ad Retargeting needs certain information in order to successfully proceed with its operation.

The main source of information for Ad Retargeting is the user himself. His contribution is technically very simple — it consists of merely hanging around on the website and leaving a digital footprint. This digital footprint feeds ad targeting mechanisms with some sweet data spice they construct user profiles and calculate which kind of content might be relevant to him. That results in increased efficiency of delivered ad content.

User data used in ad retargeting can be broken down to these elements:

  • Referring sites — from where the user came from;
  • Overall journey (user experience) on-site;
  • Events (scrolling, clicks, highlights, media views, other stuff);
  • Search queries;
  • Time of session;
  • Behavior on site:
    • Contextual and thematic preferences to certain topics and pages;
    • Various interactions with the page’s content (downloads, etc);
    • Transitions to another place through links and ads;
  • Demographics (if not blocked or obscured);
  • Consumer’s gear (browser, language, location, use of AdBlock, etc.);
  • Interaction with ad content;

Basic ad retargeting operation can be described like this:

You visit a site, look at some product. In the meantime — specialized cookie makes the cut. Then you go to another site, cookie connects the dots and because of that, you can see a reminder or suggestion connected to your previous stop in the ad spaces.

The trick is in connecting the link between the source site and subsequent sites. In order to increase the effectiveness and efficiency of delivered ad content, the technology of cookie syncing is applied.

What is it? It is a method of identifying users over the initial point of entry and subsequent visits on the other websites. How does it work? There is a cookie assigned to a certain user. It is stored on a retargeting service domain. When a user visits another site, the ad request is made with the assigned cookie included. That is how the same user is identified and relevant ads are delivered.

Challenges of retargeting

However, no matter how good ad retargeting might be in theory, there is more than one bump on the way to effective use of the technology for the benefit of your company.

The thing is — ad retargeting is not as much dependent on the technology itself as on how it is used. Marketing strategy takes front and center when it comes to making the process of retargeting effective. Without it in place — there is no point in the whole affair. You might as well go and crash into a burning table while covered in gasoline.

Here are some major challenges that often occur with ad retargeting.

Improper ad frequency

One of the reasons why regular users have such disdain towards ads is their overbearing nature. Ads stick out like a sore thumb, annoy, distract, and irritate. And when users see an ad for some product or service over and over and over again his associations with it are increasingly negative, which is the opposite of what an ad is trying to do.

Because of that, it is reasonable to keep ad frequency limited to somewhere around “once in a while but not too much”, i.e. it must be definitely visible, but not everpresent.

Lacking variety of ad content

Another big problem that often happens with retargeting is the lack of variety in the ad content. The thing — even if you have the most beautiful, tailor-made ad in the world, the user will get weary of it after a while. And you just can’t allow that to happen. If an ad is rolling over and over again — it starts being annoying to the user. And that means it will be ignored.

How to avoid that? In order to retain user attention, you need to develop an ad content pool for the campaign. Every piece of the content must have some variation or progression of the message.

For example, you can’t send the same ads for users who just viewed some products and users who are half-way through the purchase. The same goes for users who are looking for something in a specific category and users who just stumbled upon a link. In every case, you need a different message in order to hook the user and get him back on site.

The variety will keep the user’s interest throbbing and hopefully at some point will perform a conversion.

Vague data segmentation

Here’s an obvious thing to boot: in order to be precise in ad retargeting operation you need to know who are you targeting at. Right? Otherwise, ads will miss the point and all your efforts will go for a long walk over the Cursed Earth.

The reason why that might happen is in the way the target audience is defined. User data segmentation needs clearly defined parameters in order to set the ground for ad retargeting. The information itself comes from the tracking tools but it is how it is processed that is critical. And there might be some problems.

One of the most common mistakes is assuming that every user is alike. No, it is not. You need to take into consideration a variety of factors that differentiate the users in order to make ad relevant to them. On-site behavior is the key element. It gives you the direction.

For example, if it is an online store and you have users who viewed the products of the different types — you can send an ad with a showcase of recent products of relevant types. Or if the user just stumbled upon a site you can send an ad with a call to action and convincing argument — some discount or else.

Multi-faceted segmentation of an audience is the key to precise and effective ad retargeting.

The trouble with cookies (can retargeting pixel help?)

Cookies are one of the primary weapons of retargeting. But here’s the thing — sometimes you just can’t use them. For example, if the session is happening from a browser in anonymous mode, cookies will be deleted by the end of the session. This is unfortunate since you will be unable to retarget that particular user.

Also, third-party cookies can be easily blocked in browser settings. Sadly, that is almost always the case. What does it mean? Lack of third-party cookies disables an option of gathering personalized user information. Which is a catastrophe if you are going for relevant ad content.

That means you need to have another option up the sleeve. The tracking pixels can solve the problem. It is possible to construct profiles for retargeting with its help.

Pixel (definition): A pixel is the smallest digital image or graphics unit, which can be shown on a digital display. Basically, a tiny dot on your screen. (That’s what screen resolution is measured in, for example, 1920 by 1080). But, in the industry of retargeting ads, a pixel can help identify if there was an action performed. For example, you might’ve heard of the Facebook retargeting pixel that helps the Facebook retargeting ads work.

Conclusion

At the current moment, Ad Retargeting is the most potent form of online marketing. It is the most balanced and flexible method of delivering ad content available out there.

Its primary advantage over the other methods is in avoiding the biggest user concerns about ads – privacy and inappropriateness.

On one hand, Ad Retargeting is capable of operating without harnessing too much personal data thus it keeps intact the ethical side of things (think of GDPR). On the other hand, Ad Retargeting is able to deliver users what they are actually interested instead of shoving product of choice down their throats by overbearing ads. Win-win!

All this makes Ad Retargeting – whether you go for email retargeting, Facebook retargeting, or Google retargeting – a perfect solution for building an effective Marketing Strategy.

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What is Data Management Platform (DMP) and How Does It Work

Posted on by Pavel Tantsiura
In this issue:

In this day and age, information is, probably, one of the most valuable things in the world. No wonder — it is the stuff dreams are made of, something of a new universal currency. However, one should know how to use it in order to make it work for his own benefit. 

There is no industry where this is more apparent than in the advertising industry and AdTech in particular, where competition is so tough one false move can derail everything. This is where Data Management Platforms (DMP) come in and work some sweet AdTech Magic.

The thing is – modern advertising is extremely complex and multi-faceted operation. Another important thing to note is that the ad industry is massive. Not just very big, but Godzilla-like imposing and intimidating massive. Every little thing counts and makes difference. There are many moving parts involved and all of them are equally important.

Modern DMP’s are required to process millions upon millions of events in a short time span. Just think about that number — it is ridiculous. And it takes a significant computational capacity and very flexible scalability to make it all click.

But first, let’s sort things out.

What is a Data Management Platform (DMP)?

Data Management Platform (DMP for short) is a type of centralized tech platform that gathers data from a set of sources, segments it to predetermined categories, and further transfers in order to attain certain goals of a marketing campaign.

To put it simply, the Data Management Platform is one of the foundations of Ad Tech operation. It is one big dashboard of tools that gives you the big picture of what is going on with your efforts and provides instruments to turn the tide to your benefit.

DMP control panel is basically a war room where you can check the status of the situation and plan your next moves.

DMP and AdTech: How do they work together?

The primary purpose of DMP in Ad Tech operation is to keep a firm grasp on the proceedings of the campaign. The use of information gathered by the Data Management Platform provides additional agility to the Ad Tech operation — it improves the definition of the target audience and subsequent ad distribution.

That gives marketers agility in adjusting the campaign as it goes on according to the target audience’s reactions.

The end result of its DMP process is more efficient and precise targeting to the target audience that generates conversions that in turn enhance ROI from ad spending. This is a very important thing because gestation and hesitation are rather destructive approaches in marketing.

Here’s what Data Management Platform can handle:

  • Manage and adjust ad campaigns;
  • Provide with stats that can help to increase conversion rates, improve user experience, and establish the brand;
  • Make effective use of ad budget with a higher probability of return on investment;
  • Personalize content shown to the users in order to increase the probability of conversion and establish the brand;
  • Study the behavior and preference of the target audience in order to create a credible user profile for more efficient targeting.

What types of data does DMP collect?

Data Management Platform is capable of collecting data from the selected source. All you need to do is to define what kind of information you are interested in.

Basically, a Data Management Platform is attached to the source of information (for example, a website) and gathers information regarding certain user activity.

This information is subsequently merged together into one big picture that can help marketers to understand how to build the campaign and what kinds of approaches will be the most effective with the selected target audience.

All data is divided into first-, second-, third-party. Let’s break it down:

First-party data includes:

  • Web / App data
  • Data coming from the analytics tools (such as Google Analytics)
  • CRM
  • Transaction systems
  • Subscriptions
  • Audience information

Second-party data is exactly the same as first-party except it is given to another company involved in the operation.

Third-party data is collected and segmented independently of the company and later sold to it.

Self-Hosted or Third-Party?

The difference between custom and third-party data management platform is rather peculiar. It all depends on the need of your business operation.

In the case of the third-party solution — you get a full package with a bob and bunny. It is ready-to-use and guaranteed to operate adequately. But there is one very important thing to note. When you implement the third-party solution — you pay for lots of features that might not need at all. That is not exactly cost-effective. In fact, it can actively bleed your marketing budget if the turnaround will be big enough.

A custom solution is a more complicated but more reasonable approach. Sure, you need to do the heavy lifting of developing the foundation. But you develop the platform exactly fitting to the needs of your AdTech operation. Which makes it far more effective and capable of generating rapid ROI. However, in the case of self-hosted DMP you need to find providers of third-party data on your own.

Ways to use DMP for AdTech

Retargeting

Retargeting is a method of delivering relevant advertising content to the users based on a digital footprint and collected user data such as preferences and on-site behavior.

Retargeted ad content is based on the actual interests of the users calculated out of their behavior on the source site. This makes ad content significantly more relevant to the users. That peculiar detail ups the chances of getting those sweet conversions i.e. purchases or downloads.

You can read about it in detail here.

Data Analytics

You can’t build an ad campaign without having a clue of how your target audience perceives your brand, behaves on your websites, and consumes your ad content. That is what Data Analysis is for.

DMP is useful for Data Analytics because of its scope. You get the big picture and thus you can act accordingly. With a steady stream of data going through DMP you can easily spot every little change in behavior, all while discovering trends and preferences, points of drop-offs, and so on.

That gives you a critical advantage as you can adjust on the fly without bouncing off.

Audience Research

Audience Research is such a significant element of Data Analytics that it deserves a separate spot.

The thing is — targeting requires very clearly defines customer identity in order to click. Since users are not bound to use the only type of devices — they are often visiting one place over multiple devices. All those visits can be processed as a separate ones which is not very helpful.

However, with a little help of DMP, you can construct a unified cross-device user profile (AKA single customer view) and target a particular or all platforms he is using. How? DMP matches cookies coming from the user and assigns them to a single profile.

SEO Optimization

Another huge area where the Data Management Platform is extremely useful is SEO optimization. How? The whole audience research thing can be used not only for more efficient delivery of ad content for your internal needs too.

Basically, DMP helps on three SEO fronts:

  1. Content — a better understanding of what your target audience is interested in;
  2. Keyword Research — profiles can help to find more fitting keywords for content;
  3. Link Building — profiles can help to find better spots for guest posts;

Data Monetization

There is also another method of effective use of DMP. You can just gather information and sell it to other companies — i.e. you can be a third-party data provider.

In that case, you don’t need to worry about anything and just maintain a steady flow of data.

How does DMP work?

Data Collection

The initial stage of DMP operation is to collect data from the selected sources (i.e. first-party) and implement data from second and third-parties.

In the case of first-party data, the operation is performed in a variety of methods. Let’s count them down:

  • Tags — with a little help of Tag Manager (Google’s is a fine one) you can insert snippets of code into a website’s pages that will be tracked according to determined function;
  • Cookies via Cookie Syncing — mapping and unifying user’s ID over the multiple platforms
  • Pixel Tracking
  • Integration with second-, third-party data suppliers;

Data segmentation

The next Stage of DMP Operation is Data Segmentation. Once information is gathered — DMP organizes it according to the present taxonomy. It includes a variety of parameters. Some of them involve the user’s personal data, others include data regarding their interaction with monitored entities.

Segmentation taxonomy is wholly dependent on the selected marketing model and includes only those elements that are vital to efficient targeting.

Data Analysis

Once data is segmented, it is processed to construct a clearly defined customer profile for targeting.

Usually, this operation involves an analysis of users’ past activity on-site, their events and impressions (clicks, etc), preferences, and response to ads.

Data transfer

Once information is gathered, segmented, and analyzed — it can be transferred to ad exchanges, Supply-Side Platform (SSP), and Demand-Side Platform (DSP) which in turn will deliver the goods to the advertisers.

This information will help to perform more accurate ad buys during real-time bidding (RTB) operations.

Possible Challenges with DMP

Integration

Before the whole data management starts — you need to set up the connection between sources. Your ultimate goal is to maintain a steady transmission of data from multiple sources without missing a beat and stumbling into a mess.

In order to make that happen — you need to be sure that all the sources meet system requirements and are compatible with others.

Dealing with Scalability

DMP is as good as its scaling capacity. That is one element essential to its successful operation. The thing is — standard Ad Tech operations consist of millions upon millions of various events happening on sites. And every single bit of this information must be collected.

And if the system can’t handle such a workload — troubles ensue.

One of the most effective solutions for DMP scalability is to use a cloud platform. The majority of services provide automatic scaling features that will seriously ease up the challenge.

Data Storage

Managing data is one thing. But you also need to store it somewhere and that is a challenge. You have an infinite stream of incoming information. It is constantly collected, processed, segmented, and transferred. You have data in active use and data that was already used. All these things have to be stored safely.

One solution is by having your own server network. It is not exactly cost-effective but it can be.

The much more feasible solution is by maintaining the data in cloud storage. Since you have to pay only for used space — it is more or less cost-effective. It also covers the necessity of maintaining backup storage as the cloud is basically an ultimate backup.

In order to make sense of storage spending, you need to apply a multi-faceted approach. In essence, it is further segmenting of the data according to its current value and relevance. In that case, that challenge lies in a correct definition of time windows for data transfer.

Refining Automation

DMP deals with large quantities of data coming from various sources — that creates a necessity of creating a set of automated scenarios that will handle the operation with its own settings. We’re talking about millions of events per second — there is no chance a human being will be able to deal with it manually.

On the other hand, automation is far more reliable in comparison with the error-prone manual approach.

The challenge comes in determining where automation is necessary and where it might be abundant or ineffective.

Woes of Data Analysis

The thing with Data Analysis is that you have to know what are studying data for in the first place in order to make use of it. If you don’t really know what kind of data you need — you will end shooting in the dark which is not exactly the most effective use of time and money.

In order to understand the most effective and feasible approach to analyzing incoming data, you need to understand the nature of the sources of the data and its credibility. Next, go to audience research which gives you an understanding of target audience attitude, and then comes specification of data segmenting according to audience research.

Each step of the way must be thorough and through and through. The price of insufficient or downright faux data can be utterly devastating to the company.

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Personal Data, Privacy & GDPR

The full adoption of GDPR is a game-changing moment for the Ad-Tech industry.

On one hand, GDPR’s expansion of the definition of the user’s personal data is forcing drastic changes of approaches to deliver ad content. On the other, it is a chance to bring transparency and trust to a rather murky realm of Ad Tech.

In the long run, GDPR will turn Ad Tech’s use of DMP on its head. The thing is — GDPR compliance is not a joke.

Technically, that means you need to ask yourself the following questions:

  1. What kind of data are you going to collect and from what sources?
  2. Where is collected data going to be stored? How long is it going to be stored?
  3. Who will have access to it?
  4. Are third-parties involved in the operation privacy-compliant?

Another important thing is to have a system that will store information about the use of information. That is a critical factor in building a fully transparent and trustworthy operation.

Conclusion

At the moment, Data Management Platforms are one of the most effective ways of delivering quality advertising content to the target audience.

However, DMP is an entity that requires to be handled with care.

If done right, DMP is smooth and precise and greatly helps in keeping the pulse on the proceedings of the marketing campaigns.

We hope this article explained what’s, how’s, and why’s regarding this technology.

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How Does Blockchain Amplify AdTech Industry

Posted on by Pavel Tantsiura
In this issue:

Using blockchain, the advertising industry can potentially become more sophisticated. What can we expect from the “ad chain” idea?

Ad Tech is one of those industries that is always in an active search for the next big technological breakthrough. The reasoning behind that is simple: new technologies open up newer and better opportunities for doing more sufficient advertising business.

Considering how problematic are issues of privacy and transparency in advertising, blockchain seems to be a reasonable technological solution with the most potential to make a positive impact.

You know an old saying “When the future comes – embrace it!”

At the moment, there is no technology more enigmatic and perspective than blockchain. Everyone has their own opinion on it and its business prospects. There are numerous predictions, an innumerable number of various pitches, and a mind-boggling level of enthusiasm surrounding this technology.

What’s the deal?

According to the hype, blockchain is nothing short of being the lord and savior of every industry imaginable (and a couple of theoretical too). If you go through the think-pieces and overviews, blockchain can seemingly be applied to everything. And yet there is nothing specific about it. More on the reasons why later.  

Sure, blockchain reimagines the way banking is performed over the Internet via cryptocurrencies. It also reshapes the entire medical and insurance management and decreases the influence of the third parties in the majority of operations. But it is too soon to say anything definite about its long-term prospects.

For now, blockchain is in the fad stage, and only after it will pass we will see the real worth of blockchain as a technological solution. Before that will happen, understanding blockchain is what we need, along with the knowledge of what it can bring to the table.

Let’s sort things out.

Blockchain as a buzzword for the Internet

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What is blockchain technology?

The blockchain is a network of distributed data blocks linked and secured with a little help of the fine art of cryptography. It was introduced in 2008 by none other than Satoshi Nakamoto (aka nondescript bitcoin dude). Originally designed as a cryptocurrency transaction framework, it slowly moved beyond to the other areas and is now used in such fields as medical care and insurance systems.

In a way, a blockchain is a new form of a database. Just like a regular database, blockchain allows storing, validate, authorize, and transmit data over the internet.

The difference from a regular database is that it is not situated on a server located somewhere – blockchain is a distributed network of data without a centralized authority. It is installed on specific computers by involved parties in order to enact operation. There is no “ground control” per se, it is all Side A and Side B, and so on.

Once implemented, blockchain is set in stone and can’t be modified in any way. In such networks, block transactions contain data on all prior blocks i.e. blockchain. Blocks cannot be deleted just added and every change is easy to spot in the records. Since you are aware of all involved parties and every action is recorded – it is easy to see who does what, when, and how.

This creates an incredible level of transparency of the operation that raises the trustworthiness of the operation on a new dimension. And that is what blockchain very attractive to the AdTech Industry.

How blockchain is changing advertising

Ad Tech is a kind of industry that embraces many nascent technologies and makes them work for its benefit thus evolving them and the business to new heights. Sure, this attitude is spurned out of necessity, but it does not negate the fact that the ad industry is rather open-minded in terms of adopting and developing new technologies. The blockchain is no different in that regard.

In order to understand how blockchain can be applied to the AdTech industry, we need to understand the problems the industry is facing at the moment.

Basically, there are two of them and both can be greatly eased by the implementation of the blockchain. One is transparency, the other is privacy. There are other issues but these are the two biggest.

Blockchain advertising’s supreme transparency and relative security of privacy is something of a glimmer of hope for an Ad Industry battered by Ad Blocking and compromised by Privacy issues (among other challenges).

What blockchain brings to the AdTech’s table

Brings transparency

As you know – lack of transparency equals lack of trust. The fact of the matter is – there are a lot of things happening in the dark during ad tech operations.

With help of blockchain – a certain level of clarity can be achieved. The thing is – every involved party works with the same information. That and the fact that every action is visible creates a precocious constraint.

In addition, none of the blocks can be modified – the only thing one can do inside a blockchain is to add new blocks. Everyone sees everything. This makes any activity relatively easy to track and analyze.

Even more-so – every change must be verified by all involved which drastically limits the chances of getting away with malicious intent

Promotes supreme accountability

Trust issues are running rampant in the ad tech industry. The fact that one basically needs to rely on the kindness of strangers is not particularly reasonable but it is the reality of the business. And as such, it needs to be resolved.

Hopefully, the transparency of blockchain can seriously increase the trustworthiness of operations between all involved parties. That is especially important in dealing with third parties, such as DMP, SSP, and Ad Exchanges.

What is the problem with third-party providers? Publishers and advertisers can’t see the specifics of how their money is used. This issue is complicated by often sketchy legal contracts and the general unwillingness of third-party companies to disclose their fees in full scope.

But what implementation of blockchain to financial transactions can give is clarity. Everyone involved will see exactly what goes where and why and in which quantity. And that is a huge step forward in terms of building trustworthy relationships.  

Helps to foolproof operations via smart contracts

The concept of smart contracts is brilliant. Plain and simple – it is a foolproof mechanism. If something is not right – it will not proceed.

In essence, the smart contract is a piece of blockchain code stored within a system that defines agreed conditions of operations. The smart contract contains a certain pattern of actions that can be executed if all conditions are met. Any changes should be verified by all involved. Otherwise, nothing will happen.

This thing helps in multiple directions. First of all, it seriously limits the capabilities of ad fraud to get into your system. On the other hand, the smart contract can give users a say in the targeting operation.

Limits ad fraud activities

One of the biggest virtues of Blockchain is that everything is visible and thus you have an idea of what others do inside the system. This alone can seriously limit numerous fraudulent activities, such as bot traffic, domain spoof, and pixel stuffing.

All you need to do is to check the numbers of impressions, assess their nature, and verify their validity. Basically, blockchain is able to provide an additional checkpoint before the financial transaction that will partially limit ad fraud losses.

But it is important to understand that blockchain on its own can’t save you from ad fraud. It can help but you also need other tools.

Enhances privacy

Privacy is probably the biggest issue in the industry right now. While industry players pretended that it is not an issue for quite a while – now privacy concerns and direct actions to protect it actively choke the industry via Ad Block and other tools.

While Blockchain is an open protocol by default, it can be used for the benefit of user privacy. There are two ways it can pull it off.

The first is due to transparency and we already covered this earlier. The second way is a little bit more sophisticated.

Here’s how it works. Instead of gathering data to one store – it is possible via blockchain to store data on user devices. Then, when it comes to targeting, verification mechanisms kick in and either confirm or deny further proceedings. It can be overbearing for the user, but it will surely give him more control over his personal data.

What issues are there with blockchain and AdTech?

Insufficient Scalability

The biggest challenge that holds back any significant development of blockchain technology is lacking scalability. The fact of the matter is – at this point blockchain is simply unable to handle such an amount of operations. It is too slow. For example, Bitcoin is currently capable of processing around 2-3 transactions per second. In the case of ad tech real-time bidding operation, you need to process 2-3 million events and more. That’s a bit of an operational gap, right?

Here’s why – blockchain is decentralized. It is stored directly on the devices of involved parties. Another important thing is that it is constantly growing. For example, once upon a time, the bitcoin blockchain was sized 25 MB. Now it is 160 GB. That’s a lot. And that what slows things down over time.

However, this slowness is justified. The thing is – you need to verify every operation. And that keeps in line every single action inside the system.

One of the possible solutions to the problem is through the diverse use of smart contracts. This will allow to automate operations to a certain extent and make things faster.

Standards are in development

Another big challenge for full-scale adoption of blockchain in ad tech is the lack of standardization. Why it matters? One word – compatibility. Standards are like a universal language. Their existence guarantees compatibility and rapid development of the technology. Standards enable the combination of various solutions into one superior.

At the moment, IAB is actively working on the guidelines, but it is a long way to go. Sure, there are custom solutions here and there, but lack of standardization means none of them are compatible with each other. This also means that a joint effort in evolving the technology and exploring its further possibilities of use is virtually impossible.

Sure, there are custom protocols, cases when the inventory doesn’t meet the specifications, as well as companies still working on OpenRTB 2.3 – released in 2014. This might become a severe issue with the blockchain, as its ecosystem relies heavily on the standardization rules and agreements.

Lack of expertise

While blockchain is certainly a trendy buzzword, it doesn’t mean that there are many experts active in the fields. There are people who can write about blockchain concepts, possibilities, and opportunities. But talk is cheap (unless it is a Keith Richards album), it is the action that matters.

And the reality is – there are not many of those who can do a thing or two with blockchain and not break into tears. In fact, demand vastly exceeds supply. And those who actually have expertise on the subject are most likely already employed.

This is a natural problem for any nascent technology. Basically, blockchain is still in the stage of early adoption when the industries are yet to be convinced in embracing the technologies and their possibilities.

Conclusion

At the moment, blockchain is still an emerging technology with nothing particularly definite in its fold. While it is surely established itself as a viable technology that is able to solve certain biting problems here and there, there are still not many practically feasible and economically justified solutions for full implementation. However, that is more of a question of time than an actual problem.

In the context of the Ad Tech industry – blockchain is something of a dream in the process of a very slow realization. It will take a lot of time before it takes off. The concepts are there but the solutions are not there yet. Because of that, the only thing we can all do is wait for more things to come.

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