Tag Archives: Big Data

Will AI Render Media Agencies Obsolete?

11 Sep

artificial_intelligenceArtificial intelligence (AI) is already reshaping how advertising is developed, planned and placed. The marketing applications being envisioned and adopted by agencies, consultancies, publishers and advertisers are nothing short of remarkable.

From the onset of “Big Data” it stood to reason that the concept of predictive analysis, the act of mining diverse sets of data to generate recommendations wouldn’t be far behind. Layer on natural language processing, which converts text into structured data, and it is clear to see that “deep learning” is on the verge of revolutionizing the ad industry. As it stands, algorithms are currently optimizing bids for media buying, utilizing custom and syndicated data to match audience desires (or at least experiences) with available inventory.

Effective, efficient, automated methodologies for sorting through vast volumes of data to evaluate and establish patterns that reflect customer behavior for use in segmenting audiences and customizing message construction and delivery holds obvious promise.

So, what does this mean for media agencies? Will they be at the forefront of automation technology? Or will they be swept away by the consultancies and ad tech providers that are already investing here?

If media agencies desire to remain in control as the industry evolves, there are real challenges that they will have to address to remain viable:

  • Re-establish role as “trusted advisor” with the advertiser community. Recent concerns over transparency, unsavory revenue generation practices and a failure to pro-actively safeguard advertisers’ media investments from fraud and from running in inappropriate environments have created serious client/ agency relationship concerns.
  • Attract, train and retain top-level talent to re-staff media planning and buying departments. The focus will need to be on bridging the gap between developing, and applying automation technology and providing high-level consulting support focused on brand growth to their clients. Presently, media agencies are not effectively competing for talent, whether in the context of compensation and or personal and career development options being offered by their non-traditional competitors.
  • Provide a framework for addressing the compensation conundrum. Whether this is in the form of cost-based or performance-based fees tied to project outcomes, commissions or hybrid remuneration systems, tomorrow’s successful media agencies will need to establish clear, compelling compensation systems. These systems will need to reflect value propositions that will differentiate them from an expanded base of competitors, while offsetting (to some extent) non-transparent sources of revenue that many media shops have come to rely on in recent years.

This will not be an easy path for media agencies, particularly for those that are hampered by legacy systems, processes and management perspectives that may limit their ability to more broadly envision and ultimately, assist client organizations addressing their needs and expectations.

Either way, the race is on, as management consulting firms are acquiring various marketing and digital media specialist firms and as media agencies raid the consultancies for personnel to build out their strategic consulting capabilities. The key question will likely be, “Which business model holds the greatest promise, in the eyes of the Chief Marketing Officer, for improving brand performance?

 

 

 

Does Anyone Really Want Advertisers to Solve the Attribution Dilemma?

14 Mar

conspiracyIt has been decades since the concept of Marketing Mix Modeling (MMM), the forerunner to Attribution Modeling, was introduced. The concept was relatively straightforward, marketers would apply statistical analysis to sales and marketing data to quantify the impact that each element of the marketing mix had in driving brand sales and profit. Once the causal relationship had been modeled, marketers would then be able to accurately forecast outcomes and inform resource allocation decisions.

While the concept may have been straightforward, the solution, for most marketers, has been elusive. Why? First and foremost, MMM has some inherent challenges, particularly when it comes to quantifying the impact of longer term brand equity development tactics versus those focused on short-term sales. Secondly, these models have not fared well in accurately assessing the impact of various media types on outcomes to assist in refining allocation decisions.

Fast forward to the late ‘90’s when we experienced an explosion in online media, the birth of e-commerce and the introduction of “Big Data.” The emergence of digital media and the attendant level of data that marketers where now able to gather led to the launch of “Attribution Modeling.” The goal, to assess and quantify what marketing and media touchpoints influenced an advertiser’s target audience, and to what extent, across the purchase funnel in an effort to optimize media spending across the ever expanding gamut of media alternatives.

While there are multiple variations of attribution models to consider, most marketers have relied on single-source attribution models, often using a “last click” approach which assigns responsibility for an outcome to one event. While simple, this flawed approach to attribution modeling gives too much credit to digital media, at the expense of traditional media and other marketing touchpoints.

Sadly, for advertisers that are doing both MMM and Attribution Modeling, it is rare that the feedback from these related, but different approaches synch. Further, there remain audience delivery measurement (i.e. cross-channel measurement), multi-touch attribution challenges that introduce a layer of complexity that drives up the cost of attribution modeling.

That said, since the onset of these two modeling tools being introduced, the industry has dramatically evolved its data gathering capabilities, enhanced CRM and DMP capabilities, conceived of and launched programmatic media buying, where algorithms have replaced media buyers and now we’re seeing the use of artificial intelligence bots, such as Adgorithms’ “Albert” that can plan and place media and create content. Heady stuff to be sure.

This got the cynic in me thinking; “Well if we can master all of this from a technology perspective, surely we should be able to cost efficiently and effectively master attribution modeling.” That led to idle speculation about whether or not the ad industry really wants advertisers to solve the attribution modeling dilemma?

After all, what if John Wanamaker was wrong? What if more than half of his ad spend was wasted? Remember, the marketing and media choices available to him in the 19th century were considerably more limited than those available to advertisers today. Would accurate attribution models eliminate some of the following marketing and media options from consideration?

  • Television
  • Radio
  • Magazine
  • Newspaper
  • OOH
  • Cinema advertising
  • Product placement
  • Direct mail
  • Email
  • Sponsorships
  • Online display
  • Online video
  • Podcasts
  • Paid search
  • Organic search
  • Mobile
  • Social media
  • Native advertising
  • In-store advertising
  • In-store displays
  • On-package advertising
  • Trade promotions
  • Price promotions
  • Couponing
  • Affinity marketing
  • Affiliate marketing
  • Applications
  • Earned media

Crazy. Right? Reminds me of a quote by the American journalist, Gary Weiss:

“One problem with the focus on speculation is that it tends to promote the growth of the great intellectual cancer of our times: conspiracy theories.”

What do you think…

 

Big Data. Big Deal. You Bet.

5 Dec

digital trading deskThe evolution of media channels, ad targeting and the role of ad tech have significantly reshaped the media marketplace, allowing advertisers to select inventory and direct their messaging with an incredible level of precision. These developments have long been hoped for and yet, now that they are here, there is much that advertisers don’t understand about one important bi-product of the ad tech revolution… the disposition of the data gleaned from their investment at all levels of the media investment cycle.

In our contract compliance auditing practice, it is not uncommon that we find contract language gaps relating to issues such as:

  • Who owns the data?
  • Where is the data stored?
  • For how long?
  • How secure is the data?
  • Is the data kept separate from that of other advertisers?
  • Is your data being used to aid other advertisers?

These are important questions that heretofore have yet to be addressed by many advertisers within their agency agreements. “Big data” represents a potential treasure trove of information that can drive marketing strategy for advertisers by leveraging the insights gleaned from media transactional and customer behavioral data. That is, if and only if they are in receipt of the layers of data available to them and that they have the rights to use the data.

Rights to use their data? As odd as that may seem, data ownership is not automatically ceded to an advertiser. In spite of the fact that without an advertiser’s investment there would be no media buy and no corresponding data stream. Yet, many within the media chain have taken aggressive actions to claim that data as their own. Ad agencies, trading desks, publishers, demand side platforms (DSPs) and third party ad servers to name some of the entities that desire to own, or at a minimum, have unrestricted access to that data.

This jockeying for data ownership and access carries additional risks for advertisers in and around the topic of data privacy and security. Particularly as it relates to first-party data that may be utilized in the planning and placement of programmatic digital and addressable TV buys. Why? Because the unregulated, unsupervised use of an advertiser’s first-party data could be in violation of their users’ privacy rights.

Ownership and access rights to third-party data, which is often accessed on the advertiser’s behalf by its agency and or ad tech providers such as data management platform (DMP) and ad platform providers are generally clear and typically spelled out in licensing agreements between the various stakeholders. Then there is second-party data, which can best be described as information that users didn’t give you directly but was acquired through an advertiser’s relationship with another entity, such as an SEO platform or that was acquired via feedback from a behaviorally targeted digital display ad campaign. Advertisers must ensure that the use of and or sharing of second-party data is done in a privacy compliant manner to safeguard the interests of the user.

Complicated. Yes, and often little understood by those crafting client/agency agreements. It would certainly be appropriate for advertisers to revisit their agency agreements, with the goal of ensuring that their data ownership rights, privacy considerations and third-party access rights are clear and consistent in this emerging area. It is important to note that industry best practice templated language is still evolving and should not be relied on as an advertiser’s sole source for securing ownership/access rights and protections for agency agreements.

When it comes to advertiser data ownership, we share the beliefs of American businessman and politician Jim Oberweis, who stated:

“I am a strong believer that intellectual property rights need to be protected.”

Want to learn more about evolving your organization’s agency contract language? Contact Cliff Campeau, Principal at AARM | Advertising Audit & Risk Management at ccampeau@aarmusa.com.

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