- The proliferation of technology gives rise to another trend that marketers must account for—rising consumer expectations. This is true in both the B2C and B2B spaces.
- QuanticMind emphasizes the need to bring in people who understand the complicated marketing ecosystem such as data scientists who can help make data-driven decisions.
- While self-service platforms have campaign optimization tools baked into their functionality, they also pose an inherent conflict of interest to advertisers.
- The complexity of digital marketing has made it possible for lower-level planners to optimize media effectively.
- Agencies must become highly-trained consultants that can help companies navigate the complex martech ecosystem. They must harness machine learning to deliver business solutions that grow and protect a company’s brand.
QuanticMind is a predictive advertising management platform used by top brands including HomeAdvisor, Hot Topic, Windstar Cruises, and Rosetta Stone.
Their technology is focused on optimizing search campaigns through automated bid management, publisher management, data unification and machine learning.
The platform also enables feed optimization and intelligent shopping management for retailers.
QuanticMind recently published a new report, “How to Evaluate Machine Learning Powered Performance Marketing Agencies” which addresses the rise of machine learning-powered agencies and how they are transforming the performance marketing industry.
This 18-page booklet includes industry statistics, data-supported trends, and a blueprint for how marketers can evaluate the new machine learning-powered agency.
Content produced in collaboration with QuanticMind.
State of the performance marketing industry
Digital ad investments continue to grow, with the IAB reporting that digital marketing investments doubled over four years from $13.2 billion in Q1 2015 to $28.4 billion in Q1 2019.
CMO budgets are divided among a variety of different marketing channels, with the largest percentage going to digital commerce, digital advertising, marketing/customer analytics and website infrastructure.
The QuanticMind report leverages data from a 2018 Gartner survey to illustrate the CMO budget allocation as follows:
QuanticMind writes: “We can see that in 2018 there were a lot of different places where investment was taking place, but increasingly, budgets were being assigned to tools and technology that harness the power of the insights and customer analytics that digital provides.”
There are over 7,000 marketing technology providers in operation in 2019, versus 150 in 2011. This increasingly crowded marketplace makes it difficult, if not impossible, to evaluate every single tool.
The proliferation of technology gives rise to another trend that marketers must account for—rising consumer expectations.
Thanks to Amazon, consumers expect their brand interactions to be quick, seamless, and as easy as possible. This is true in both the B2C and B2B spaces.
A Salesforce survey of business buyer expectations revealed that over 70% of buyers expect personalized engagement from vendors and 69% expect Amazon-like buying experiences.
QuanticMind writes, “These B2B companies are starting to expect ‘Amazon-like buying experiences’ from their vendors and a massive 67% of people have switched vendors for a more ‘consumer-like experience.’”
How marketers can navigate the changing landscape
QuanticMind outlines three approaches that marketers can take to navigate the rapidly evolving landscape in the digital marketing industry.
- Build an in-house team—Many CMOs are already doing this, as research from Gartner’s CMO spend survey shows. The budget allocation for agencies dropped from 25% to 22% from 2017 to 2019, a sign that CMOs are looking to bring teams in-house. QuanticMind emphasizes the need to bring in people who understand the complicated marketing ecosystem such as data scientists who can help make data-driven decisions. Even so, without the appropriate technological expertise, data scientists can get bogged down with the management, integration, and formatting of data.
“We have personally witnessed a number of experiences where basic data integration that should have taken 30 days at most ended up taking a whole year because companies just didn’t have the right people with the right experience,” writes QuanticMind.
- Capitalize on free options—Many businesses manage their media using free options which include auction-based models on top platforms such as Google, Facebook, Bing and Amazon. While these self-service platforms have campaign optimization tools baked into their functionality, they also pose an inherent conflict of interest to advertisers.
Per QuanticMind, “In an auction dynamic, allowing the ad platform to make the bidding decisions will create some long-term pains that could end up inflating costs.” Another risk with relying solely on automated platforms to manage your marketing is that you don’t have full control over your data.
- Hire an agency—The Gartner CMO survey revealed that about 22% of CMO budgets are allocated to agencies. The agency model is typically a top-down model with the leadership and expertise focused at the top of the pyramid and lower level planners and strategists with less than three years of experience at the bottom. This bottom-level tier typically comprises 60 to 70% of the headcount that marketers pay for when investing in an agency. The complexity of digital marketing has made it possible for those lower-level planners to optimize media effectively.
QuanticMind uses paid search as an example: “To offer some perspective in the context of paid search: if you want to optimize every keyword that you have in your program, across each of the 210 DMAs, 24 hours a day, seven days a week, across three devices — that alone is 105,000 variations for every keyword, every opportunity where you could change your bid, change your messaging, etc.”
The only way to effectively manage a portfolio of 100,000 keywords or more is via machine learning and automation.
Writes QuanticMind, “It means that the horsepower of the core team of a traditional agency is no longer as valuable as the expertise of individuals who know how to manage and navigate AI-powered platforms.”
The new performance marketing agency model
QuanticMind’s perspective on the agency model is focused on the paradigm shift in digital marketing as a whole.
Agencies must become highly-trained consultants that can help companies navigate the complex martech ecosystem.
They must harness machine learning to deliver business solutions that grow and protect a company’s brand.
QuanticMind advises marketers to demand more from their agencies, hire consultants to help accelerate growth and navigate the complex martech ecosystem, and use machine learning to automate as much as possible.
“Ultimately, the paradigm shift takes us to a hybrid world — one where the right people with the right technology are essential to get superior results,” writes QuanticMind.
For more insights, check out the full white paper, “How to Evaluate Machine Learning Powered Performance Marketing Agencies.”