The future for traditional agencies is one where artificial intelligence (AI), machine to machine learning, deep data, plus human and computer teamwork, all have a prominent place.
In fact, this future is already happening for some agencies. This change, as well as the driving force behind it, is the focus of this post.
Today’s Advertising Agency
In most traditional agencies you tend to have two distinct approaches to delivery; those that provide specific services like SEO, PPC, content, PR, etc. and those that provide software as a service (SaaS).
The service provider typically uses technology in order to help them to deliver a service, but the benefits to the customer are, in most cases, derived passively through the service end results as an indirect benefit.
Agencies delivering software as a service have primary goals of supporting that software and empowering people to use it as effectively as possible for achieving their unique objectives through software use.
You can see how this traditional agency model looks below with the agency at either end of the spectrum:
Tomorrow’s Advertising Agency
The ‘new agency’ successfully combines service and software; giving customers the advantages of direct access to all of the data that specialists use to make informed decisions as well as direct access to the experts delivering the service.
The goal of this combination of expertise and technology is a greater level of service delivery, and objective completion fueled by human/computer/data collaboration.
This changes the agency model to something more like the example below (in this case, the agency example placed in the center of this model is the agency that I work for, Vertical Leap):
Agencies: AI and Machine Learning
Artificial intelligence is already here.
Google has self-driving cars and computers have been machine learning and taking over the jobs of humans for some time.
In fact, it is widely predicted that almost half of all human jobs will be completed by machines in the next ten years, and we can already see this in some forward-looking agencies.
Anything that has a clear, defined process can be, and in most cases should be, completed by a machine rather than a human.
Because the machine will complete the process exactly the same every time.
The machine will never get bored, make errors or derive a negative sentiment from completing the same task hundreds (or even billions) of times.
An example of machine learning for a traditional digital agency is completing keyword research.
Experts have a clear process that they follow identically each time they complete the task. Although this may get added to and refined over time, the process and decision tree remain the same (or can be easily added to as part of a machine process).
This includes specific tools used, the type of data collected and data integrity work completed for aggregating segmented data sets.
The desired end result is the same each time and, therefore, can be directly compared for accuracy, efficiency and effectiveness of outcome.
Human and Computer Collaboration
Collaborative working between humans and computers/machines is the biggest change and challenge for agencies of the future (or more realistically agencies ‘of the now’).
There are some great examples of this working in many areas, and one of my favorite examples is chess.
The reason why I like chess to demonstrate this is because lots of agencies are going through the same process (often at steps one to two) and need to get to step three.
Man (Grand-Master) beats machine (Supercomputer).
In 1996, the computer challenge came from the IBM chess supercomputer Deep Blue against the industry leading chess grand-master. The result: man won and the wider chess community was pleased that man is still seen as superior to machines in this extremely expert field.
Machine (Supercomputer) beats man (Grand-Master).
After further computer refinements, Deep Blue made a return in 1997 leading to a historic chess victory.
The win shook the chess world and led to initial fears of the end of human-led chess expertise and tournament winners – in fact, the opposite proved true.
Men (amateur men) and machine (average computers) beat grand-masters and supercomputers.
Through effectively working together, amateur chess players combined with fairly standard chess computer software were able to beat the very best components in the human and supercomputer chess field.
Through identifying what roles added the most value and with man/machine working together, the cumulative end result was greater than the individual performances.
Getting to step three is the real goal for future-thinking advertising agencies.
In the next 12 months, I’m confident the following will be much more prolific within traditional advertising agencies. These are just my initial thoughts, and I would love to hear what you would add below and whether you agree with me or not.
Expertise will remain very distinct however, experts will communicate more frequently and more effectively for cumulative gains.
Whether this is cross-company communication or collaborative cross teamwork, agencies working with isolated specialists will decline.
Regardless of specialism (SEO, PPC, content marketing, etc.), multi-channel working will be required for maximum potential gains. You can see an example of this below, in this case showing an integrated marketing strategy.
One of the largest driving forces for more companies outsourcing advertising requirements over the months to come will be because of the need for depth of data.
Gut feel will rightfully become a thing of the past and data will be the centerpiece for most, if not all, advertising agency decisions.
Deep data platforms will provide the knowledge base for actionable insights and manual agency tasks will become automated so that expert time is spent only on expert tasks.
The data-driven model will look something like the following (with specialisms being added as applicable):
A lot of time gets spent talking about elements of a bigger picture that can be summed up as ‘customer or consumer value’.
I genuinely believe that value will become a more tangible requirement and a measurable metric for agencies to deliver upon.
There will be many manifestations of this and the growth of roles like Customer Experience within agencies will be one telltale sign that this movement is happening more frequently.
Agency consumers have greater historical outsourcing expertise than ever before, have clear expectations and often very distinct objectives on which to objectively measure success.
The next phase of this agency measurement becomes less about the services sourced and more about the wider value derived.
I hope this post has provided food for thought and prompts conversation and perhaps a debate on what is to come for traditional agencies.
I really want to hear what you think about this, and hope you comment below and engage with me and this topic socially.