AdTech Today: Evaluating the Human Component versus A.I.

With the rise in computing power and the emergence of automation in industries including healthcare, retail, finance, automotive and advertising there are a constant flow of incremental updates, user improvements and partial solutions to ease workloads, improve efficiency and capture consumer interest. Algorithms and machine learning are making leaps and bounds pushing automation into new territories. But what is happening behind the curtain? Stepping back for one moment to quote Aldous Huxley,

Science and technology would be used as though, like the Sabbath, they had been made for man, not (as at present and still more so in the Brave New World) as though man were to be adapted and enslaved to them.
— Brave New World (First Perennial Library Edition Published 1969)

Is a human beholden to data and automation or does the inverse in fact hold true? The human component should not be underestimated and is essential in not only a philosophical context but also in any strategically implemented and automated marketing campaign.

So where should human oversight occur? After final negotiations have been reached and the marketing plan agreed upon what is left for a human to do? There are intuitive decisions at all stages requiring human intervention based on shifting inputs that even advanced computation cannot (yet) address.

Welcome to campaign optimization.

Optimizing is arguably the most time consuming step in running a successful programmatic advertising campaign if the advertiser, agency and client have undertaken adequate due diligence. During pre-campaign planning there should be effective, well-defined and clearly communicated parameters and goals established between the agency or in-house team and the client that outline and reinforce the overall brand marketing strategy and the specific campaign.

Programmatic Campaign Planning

A typical programmatic campaign is broken down into the following four phases allowing for further examination of human and artificial components at each successive stage.


Programmatic Campaign Outline (Planning Phase) : HUMAN

  • Targeted Site List
  • Ad Context (Ad Types)
  • Audience Data (Contextual Targeting, Keyword Targeting)
  • Safety


Campaign Initiation (Startup Phase) : HUMAN/A.I.

  • Tag Testing
  • Remarketing Pixels
  • Resource Caps and Parameters (Campaign Daily Budget Spend, Flighting, Frequency)


Campaign Strategy (Implementation Phase) : HUMAN/A.I.

  • Execute Media Buy
  • Install Testing Opportunities for Optimization (Granular Targeting Approach)


Optimization (Testing Phase) : HUMAN

  • Analyze Successful Testing Strategies
  • Evaluate Conversion Metrics (eCPM, CTR, Viewability)
  • Identify Aggregate Reporting
  • Assess Granular Performance Data (Site-Specific, Creative and Viewability)


A healthy mix of human driven insight and testing oversight with regard to automated advertising strategies determines campaign success or failure. Combining artificial intelligence tools with human intervention leads to an efficient, performance driven and highly optimized advertising campaign. Automated tools are capable of processing huge volumes of data without a break. A human can ditch the redundancy and inefficiency associated with computation and instead guide the campaign through each phase adjusting for errors, integrating anecdotal knowledge and applying other insights. These small but significant adjustments are integral in ensuring the campaign maintains the correct course.

Agencies already understand and brands are learning that a silver bullet solution in the form of a full-stack, single platform end-to-end system does not yet exist. Stringing together different platforms still remains the only way to synthesize a variety of different tasks including data collection, ad buying, audience identity mapping, targeting, remarketing and ad delivery execution.


Filtering smaller sub-groups from lookalike audience samples allows artificial intelligence platforms such as Adgorithms' Albert to iterate small, relatively cheap campaigns. This process known as micro-segmenting enables these simultaneous mini campaigns to yield data that in turn allows a system like Albert to predict different ad elements in A/B testing scenarios to select the best performing combinations. The most successful end result(s) are deployed at larger scale achieving a dramatic increase in conversion opportunities.

Lookalike audiences are generated from isolated user profiles developed from first-party (CRM) data representing the highest-value sample of past customers. This "high" value should be attributed to customers that exhibit the appropriately defined performance metrics as outlined in the planning stage (e.g. leads, keywords, ROAS, etc.) This process represents another phase requiring human participation and evaluation of collected data samples.

The true value of applied technology solutions improves efficiency and precision at high volumes (millions per minute) of consumer touchpoints occurring daily through online and offline user activity via messaging, survey outreach, social channel engagement and website browsing. The adjustments that synchronize setup, execution, testing and optimization require human inputs to adequately bridge gaps a computer is unable to sidestep in delivering a successfully run campaign.

Decoding Consumer Micro-Moments

The search for knowledge or information during a consumer's decision buying process mirrors branch and node pathways not dissimilar to those found in decision tree modeling in machine learning and management science.

Google's classification of consumer micro-moments identifies waypoints in the search and product selection process in which individuals seek answers and information to fill otherwise stalled gaps of available time in a daily commute, while being held up in line at a supermarket, or delayed at the car dealership waiting on the final negotiations prior to purchase.

These "I-Want-To-Know", "I-Want-To-Go", "I-Want-To-Do", and "I-Want-To-Buy" moments broadly define opportunities where advertisers can capture and engage prospective and pre-existing customers. Structured around the ubiquity of connected mobile devices in the hands of today's consumers grasping for solutions within arm's reach and a moment's notice yield opportunities for ad delivery optimization and consumer engagement at the most critical junctures.

The proactive advertiser is given the perfect opportunity to serve the most relevant piece of content fulfilling the desired need of their targeted audience one individual at a time. This level of granularity is made possible with the use of programmatic advertising tools including data recording (i.e. pixel tracking, mobile ID tagging or geographic location targeting), artificial intelligence and automated media buying. A consumer's decision buying journey and the complex number of steps taken within this process enable setup of a feedback loop for precision marketing.

A consumer will not necessarily travel in a linear pathway through these identified moments. Broadly defined but subject to variance based on idiosyncratic consumer behavior in product selection, user querying/research patterns or prior consumer action(s) suggests any number of possible transits exist. Users are prone to bouncing around both "forward" and "backward", returning to previous moments already visited and/or skipping specific moments altogether without a uniform point-of-entry. One consumer may proceed directly to purchase while another initiates a new product or brand search after dumping a competing brand's product due to channel or platform inconsistency restarting the process once again.

The important takeaway is not pinpointing the exact consumer journey from start to finish but rather identifying the correct moment (stage) where a targeted user is currently located. At this intersection the advertiser is now capable of serving appropriately relevant and engaging content. The eventual conversion can be traced backward to these data points with little effort once a programmatic platform with the automated components are activated and online.

"I-Want-To-Know" or "What" Moment

During the research phase in which a consumer is looking for initial product information, solutions, knowledge or missing pieces of a larger puzzle there exist a number of opportunities to serve prospective users. With regard to product or service-related searches, consumers may have seen prior television spots leading to further investigation on digital channels for additional product knowledge and literacy.

"I-Want-To-Go" or "Why" Moment

The "Go" moment pertains to a geographical search in which consumers have selected a product, a business, a restaurant or a retail outlet and are pinpointing how to find the best option. Local search becomes extremely relevant with consumer attention transitioning to location details including maps and directions to fulfill these wants.

"I-Want-To-Do" or "How" Moment

Instructions, video tutorials and how-to guides are all relevant for the consumer during these "Do" moments. Prepping to cook at home, determining step-by-step DIY instructions, watching tutorials and finding "how-to" guides via online search and video are all relevant to consumer wants and needs during these moments.

"I-Want-To-Buy" or "Where" Moment

Pertaining to consumer search for product price comparison, confirmation of the best available deal and search for general deals all define a consumer's criteria in the moments just prior to purchase. Consumers may often discover alternative brands or new products during these searches. If there are too many steps separating a consumer from the most direct path to purchase (i.e. if a mobile experience does not match up with the desktop website) the brand may face a high probability of losing that customer in search of a more seamless or consistent experience with a competing brand.

Channel Optimization and the Seamless Experience

Standardizing the user experience across all channels remains paramount for ensuring continued brand health and long term success. Advertisers must adopt a proactive stance in serving and anticipating customer wants and needs with uniform and consistent UX/UI on all brand platforms. Those brands that choose not to adhere to these rules or commit the error by omission stand to lose significant ground in a highly competitive and visible playing field. Today's consumers have far too many options and knowledge to think twice before moving on to more relevant, consistent and efficient alternatives.


Reaching an individual consumer and delivering relevant, high quality creative content tailored from huge swaths of data requires synchronizing the deployment, timing and medium (device) choice for effective engagement with the user.

Tracking and identifying a customer's omnichannel journey is now part and parcel of programmatic advertising technology from which a holistic user profile is generated and stored. Capturing behavioral attributes across social channel and digital platform use, web browsing activity and offline tracking (physical store visits, smartphone geolocation) provides insight to the most effective ad serving strategy during consumer micro-moments.

Traditionally, digital advertising tools such as Google AdWords measured and compiled engagement and conversion data based on a cloaked or invisible user identity generating analytics across display and search campaigns. Large volumes of personal user data now amplify these traditional metrics of click-through rate (CTR), cost per thousand impressions (CPM) and cost-per-acquisition (CPA).  Application of A/B testing and automated functionality in a retargeting campaign empowers the advertiser to further narrow selected samples and hone in precisely on a single target user. Scaling this approach empowers advertisers with delivery of high quality ad content at precisely coordinated times to maximize both conversions and leads.

This highly granular level of detail can still be considered the relative beginning of advanced programmatic advertising strategy.

Collecting data from an individual's transit across mobile, display, video and extending offline yields insights including brand affinity, product interest, shopping style, device usage tendencies and timing to name a few. The power of these actionable, performance-driven insights collected on a user-by-user basis is amplified with cross-device tracking. Consumers that originate product or service related searches on mobile will purchase at a later time and on a different device (usually desktop) if not on an altogether different day.

On the media ad inventory front, automated ad bidding and ad inventory placement using predictive analytics and modeling enhances campaign execution with trading tools such as a newly created trading platform exchange engineered from NASDAQ technology allowing publisher and advertiser capabilities in transacting guaranteed contracts of premium advertising inventory. Automated media buying and bidding optimization is further amplified through a personalization and user attribution criteria standpoint in selecting the most valuable inventory. A staggering thought to consider is the significantly higher volume of media exchange transactions versus financial securities trades occurring in a given day.

Targeting a single consumer based on identifying and acting on micro-moment insights is possible from an exact-timing, content-tailored and channel-specific ad serving perspective. Campaign optimization based on retargeting already identified users on the verge of conversion coupled with the personalized insights gleaned from data enables marketers to concentrate on identifying and reaching consumers with ad inventory while the consumer is still in the purchase funnel just prior to conversion.

Timing is everything.

Using already owned data i.e. from a CRM (Customer Relationship Management) database and connecting the data to an agency's media buy is an obvious choice. Data tracking extends far beyond owned platforms to pixel tracking enabling an advertiser to track a consumer's online journey incorporating a data management platform (DMP) where data generated from offline activity including physical store visits, credit and debit card transactions and geographical coordinates all amplify the selection and execution of media buys. Mobile device ID tagging provides the link connecting online activity with offline tracking.

After data is collected from user behavior and activity, ad placement now incorporates verification techniques confirming the actual targeted user's identity with cookie syncing just prior to the ad transaction occurring via a media inventory exchange and resulting in ad serving on the appropriate channel at the appropriate time to reach the targeted and identified individual.

The flow of data around consumer product interest and search for X (product, knowledge or service) is evaluated in the context of what user action will be taken to obtain X to intersect with that user on the correct device and at the appropriate time to ensure that eventual conversion is captured. These journeys that involve intent and future action are all understood in the context of highly personalized user habits and behaviors.

Identifying future consumer intent through micro-moment driven insights is possible with a large volume of emerging artificial intelligence driven platforms reimagining a multidimensional marketing playing field.

Retargeting, Pixels and Cookie Syncing

Re-targeting is a major cornerstone of programmatic strategy. Although re-targeting is nothing new and has existed as a 1.0 version of programmatic, recombining this tool with new programmatic advancements is worth its weight in data. 

Developing an inventory of initial site visitors allows for an effective re-engagement with those consumers that have already interacted with a brand. In analyzing the purchase funnel, a retargeting campaign exists at the very end with limited reach but suitable cost-per-action measurement.


In the burgeoning landscape of data profiling, re-targeting fits into the larger picture utilizing pixel placement (an invisible-to-the-eye image file with a script (code) that places a cookie onto the user's browser) linking that user's web browser with their website visit. A pixel is the script or code and the cookie is the placement of that code downloaded (stored) onto a user's browser. Referred to as a tracking pixel (there are also conversion pixels), a consumer encounters an ad generated from a previously visited website in their future web browsing activity.

In today's 3.0 programmatic world where targeting consumers at all points along the entirety of the purchase funnel is made possible with the applied use of holistic user profiles. Programmatic version 2.0 (associated with advancements in audience buying but more on that later) did not have the the now available automated application of massive amounts of data collection necessary for segmentation of website visitors for selection of sophisticated media buying. Such a selective media buying strategy can yield higher ad inventory quality (brand safety), effective assessment of publisher platform selection and better-negotiated pricing of ad placement in real time (through auction bidding increasingly performed through private marketplace deals).

So returning to traditional digital advertising in which tracking pixels allow advertisers to measure website visitor traffic and digital ad viewing, let's turn to the application of pixels in programmatic advertising campaigns.

Historically speaking, the difference between number of site visitors versus conversion rate (purchase action) was satisfactory in fulfilling KPI requirements for brands, companies and marketers searching for performance metrics. Presently speaking, the demand for granularity is where things become interesting.

Whereas the old model depended on targeting a singular platform, today the capabilities available in reaching hyper specific targets (a single individual) are now possible with data management platforms (DMPs) aggregating user data with omnichannel (multi-device and platform) measurement. Simply stated, the data points collected in real time from mobile devices, the offline data brought online via a partner and a DMP coupled with optimization tools including geo-fencing, precise demographic profiling and analyzing consumer relevance for specified products contribute to deeper insight and greater efficiency in executing media buying. The intersection of data collection and pervasiveness of today's mobile technology allows for the aggregation of this granular assessment of the consumer at an individual level.


Mutual Interest from Demand and Supply Sides

Piggybacking scripts (pixels) are the nuts and bolts that integrate Data Management Platforms (DMPs) with Demand Side Platforms (DSPs) and Supply Side Platforms (SSPs). Furthermore, syncing cookies provides a mutual benefit between the DSP and SSP. Current web browsing technology only allows for identifying a cookie from the domain from which the cookie was set. Without cookie syncing, each side of the demand and supply platforms could only evaluate a cookie set by their respective sides, but not to determine if the other side (counter party) has a cookie on that given user. In order to assess each user as a genuine user, the demand side is interested in verifying (matching) user sets to identify that correct (competitive) bids are executing. In other words, the demand side is willing to place higher bids on users for which they already have cookies on a given user. The demand side will then place the bid ideally capturing the piece of ad inventory that will then instantaneously display for that given user. BAM! Ad served and campaign optimizing continues.

Programmatic Explained

Technology within digital advertising and marketing is currently undergoing a broad and significant disruption thanks to a data-driven automated technology called programmatic advertising.

The arrival and convergence of advancements in data aggregation, artificial intelligence and automation are already impacting many, if not all technology verticals presently (fintech, edtech, autonomous vehicle development, retail etc.)

Any industry capable of benefiting from the aggregation and mining of massive amounts of data in real-time are realizing operational efficiency improvements, campaign optimization and real-time decision making advancements. The same technologies supporting the backbone of programmatic technology are prime tools for a near limitless application across all enterprise level operations.

So, what is programmatic exactly?

According to Birger Bardowicks and Oliver Busch, programmatic advertising describes the automated serving of digital ads in real time based on individual ad impression opportunities.

This means serving ads (imagine any content type on nearly any medium) and reaching a targeted end user or audience is possible through aggregating the most specific i.e. granular data. 

Purchasing ad inventory to reach the right customer at the right time with the right message is now possible in an automated fashion transacting in a magnitude of milliseconds. The need to select any given ad impression is no longer contingent on analyzing low price data based on the value assessment of potential ad inventory in targeting a singular end user or audience. Instead, advertisers are able to pinpoint in the most direct (efficient) route possible at the exact right (appropriate) moment to achieve successful outcomes reaching their intended audience given a narrow attention span and the dynamic nature of following the consumer journey (online or offline).

To recap, advertisers are only just recently able to tap into programmatic based on the convergence of several significant advancements in technology:

  • Extreme computing power
  • Cheap data storage
  • Advancements in algorithmic development (automation)
  • Stock exchange, auction-like structure
  • Improvements in global advertising infrastructures
  • Personalization associated with an end user's 'real identity' (granularity)

Imagine a hub and spoke design where the spokes reinforce the central hub as well as all of the nodes of the entire wheel structure. This is the design of a programmatic platform.

Below is the real-time illustrated cycle of an ad impression bid, at auction, in real-time (200 milliseconds).

 Source: Mediacrossing

Source: Mediacrossing


Programmatic is built on a digital platform or exchange where automated buying and selling of ad inventories across mobile, desktop, search, display and video allow the demand side (advertisers) and supply side (publishers) to transact in real-time. Public as well as private ad trading platforms referred to as DSPs (Demand Side Platforms) and SSPs (Supply Side Platforms) are available for institutional-like advertisers and smaller independent customers to access ad inventory and auctions directly from the platform or alternatively from an ad trading agency on behalf of creative and media agencies or other customers. Much like buying or selling a stock with stock brokers and traders, programmatic advertising utilizes ad trading desks and specialized ad traders fluent in automated systems responsible for automating a stream of transactions each of which is occurring in milliseconds.

The technological advancements in data and artificial intelligence allowing advertisers to automate serving the right target audiences with the right messages at the right time and track not only online but offline data produced by these users. This data tracking allows unprecedented campaign optimization, retargeting using pixels or cookie-like tracking codes set within a user's IP that are fed back nearly instantaneously to pinpoint the exact behavior, intent and location of a targeted audience in the most efficient timeframe, ever.

Recent advancements in Google's new adtech offering coined Attribution enable consumer credit and debit transaction data tracking with additional offline activity obtained from smartphone location and timeframe data of a consumer's visit to a physical store. Combining this offline data with online activity across mobile, desktop, search, video and/or display yields further consumer insights as to purchase intent, influence (CTAs), and finally action (conversion). This synthesis of data points is programmatic strategy.

Programmatic is the new digital form of globalization.  The borders, walls and obstacles once capable of preventing holistic customer tracking online and offline are now forever demolished.

The personalization associated with tracking and actualizing a campaign based on the real identity of a targeted user across multiple devices and channels (search, display, video and mobile) both online and offline is already evolving to include television viewership metrics (linear (traditional) and non-linear (Over-The-Top i.e. Netflix), radio and outdoor advertising for inclusion into data-driven marketing initiatives.

The availability of programmatic technology is now capable of satisfying the demand for value-added initiatives in business development. In other words, efficiency gains are the new currency. Given the time constraint of a user's attention span reaching a user at the moment(s) that most influence their buying decisions is best enabled in delivering the most relevant offer to that consumer. This is where programmatic trumps once sought after performance-based campaign metrics and traditional campaign tracking metrics based on CTR or CPM. Those old technologies are already dead on arrival.

Programmatic welcomes you to the fold.