Tag Archives: AI

Be Big Somewhere… 3 Keys to Media Planning Success

20 Feb

apertureIn the past, there were two overarching concepts that helped to form the basis of an advertiser’s successful media planning efforts.

Be Big Somewhere – Simply stated, this approach held that in order to break through the clutter and gain the attention of an advertiser’s target audience one had to focus their media in places and at times where they could achieve a significant share of voice vis-à-vis the competition.

Aperture – Core to this concept was the belief that each consumer had an ideal time and place when they could be reached by an advertiser’s message. Simultaneously, there were times when the consumer was either prepared to buy or was gathering information regarding a potential future purchase. The intersection of these two points was the “aperture” and was considered to be the ideal point to expose consumers to an advertiser’s message.

Simple proven concepts that had withstood the test of time… up to a point.

At a time marked by the hyper-fragmentation and proliferation of media where consumers have access to a plethora of choices for accessing information and entertainment, it is questionable whether or not these concepts still hold true.

While the dynamic of a rapidly evolving media marketplace creates exciting content access options for consumers, it poses challenges for advertisers and their agency partners. For example, while the average amount of time consumers spend with media is significant, averaging 721 minutes per day (Source: Statista, 2019) determining the right time and place for targeting an advertiser’s message is difficult at best:

Avg. Time Spent with Media by Consumers in Minutes per Day (2017)

  • TV                                            238
  • Mobile (non-voice)               197
  • Online (laptop, desktop)     123
  • Radio                                         86
  • Other Connected Devices      33
  • Print                                          24
  • Other                                         21

         Total Minutes Per Day         721

Further, over the course of a typical day, studies have shown that consumers are exposed to somewhere between 4,000 and 10,000 ad messages. This exposure leads to increased levels of consumer apathy and message burnout. Thus, achieving a meaningful share-of-voice to break through the clutter, and then to effectively reach the target audience and finding the right aperture in this environment, is certainly more complex.

Compounding these environmental factors, at least for advertisers working with multiple media agencies, is the added challenge related to the development of an integrated, holistic planning process to help optimize media allocation decisions across agencies, platforms, publishers, networks, etc.

Moving forward there are three evolving, but yet to be perfected, media planning tools whose furtherance would greatly aid advertisers and their media partners:

  1. Cross-channel, multi-touch attribution models – In order for advertisers to truly optimize their media investments, it is imperative that they be able to assess the role that each consumer touchpoint plays in achieving their goals.
  2. Cross-platform media measurement tools – Simply put, planners need tools (e.g. common metrics) that will allow them to better understand campaign reach by platform and overall, while being able to calibrate total content ratings, regardless of where consumers view the message.
  3. Artificial intelligence platforms – AI has the potential to greatly assist media planners (and buyers) in analyzing multiple data sets to aid in everything from audience segmentation to creating and comparing alternative strategies and leveraging data on a real-time basis to optimize buys while a campaign is underway.

As the industry continues to perfect these tools and agencies master their application, the ability to plan media seamlessly across platforms will be greatly enhanced. In the words of NHL Hall of Famer, Wayne Gretzky:

A good hockey player plays where the puck is. A great hockey player plays where the puck is going to be.”

 

 

Can AI Bots Solve the Agency Remuneration Issue?

21 Mar

Commodorergb1-243x300It was a simpler time in 1864, or so it seems, when the “Commodore,” James Walter Thompson, founded his namesake agency.

As the ad industry grew over the next several decades, a commission based compensation system was the predominant means of remuneration. Simply put, full-service agencies kept 15% of the gross media rate charged by media owners from whom agencies purchased advertising for their clients. At some point in the 1960’s commission based remuneration began to give way to labor-based fees that were predicated on an agency’s direct labor and overhead costs and a reasonable level of profit.

It wasn’t long afterward that the agency “holding company” was born and full-service agencies gave way to agencies that specialized in a particular area such as creative development, media planning and placement and sales promotion. Both of these trends directly impacted “how” and “what” agencies charged clients for their services. As importantly, advertisers became more acutely interested in understanding more finitely the details behind the composition of their agency partners’ fees. This in turn created anxiety and concerns on the part of ad agencies and clients alike. Advertisers sought to reduce the level of fees that they were paying and the agency community sought to protect their profit margins and maintain some level of privacy surrounding their financial operations.

Fast forward to 2017 and the topic of “non-transparent” agency revenue sources such as rebates, kick-backs, float income and media arbitrage has been at the forefront of contract and compensation discussions since the Association of National Advertisers (ANA) completed their landmark “Media Transparency” study in 2016. Rightly or wrongly, many in the industry feel that client procurement tactics, focused on squeezing agency compensation led to the rise in non-transparent revenue. Agencies for their part, feel as though they are overworked and underpaid, while clients continue to sense that they are paying too much for the resources being proffered by their agency partners.

Challenging times to be sure. Add in the shift from traditional media to digital, the attendant impact on workflow and resources, the rise of new competitors to ad agencies that include consultancies, publishers and ad tech providers and the rapidly increasing impact of technology on operational efficiencies and the topic of agency compensation becomes even more vexing.

And while agencies wrestle with their organizational, talent and cultural issues, the industry is poised for a giant leap forward in operational efficiency. Algorithms that can place media and inform resource allocation planning and artificial intelligence bots that can actually create advertiser content and oversee the production of creative materials have the potential to displace agency personnel across multiple functions. The question is: “What is the impact of these technology trends on agency remuneration systems?”

For an industry that has relied on labor-based fees linked to marking-up employee salaries and selling their time to advertisers, the notion of automation and doing more with less can certainly be daunting. As IBM Watson Chief, David Kenny, once said:

“If you are using people to do the work of machines, you are already irrelevant.”

Thus it is time for the ad agency community to rethink both how they organize themselves to deliver client services and how to evolve from labor-based compensation models to outcome based remuneration systems.

Wonder if there is an AI bot that can assist with this transition?

If you’re an advertiser and interested in learning more about how to compensate your ad agency. Contact Cliff Campeau, Principal, AARM | Advertising Audit & Risk Management at ccampeau@aarmusa.com for a complimentary consultation on this important topic.

 

 

 

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