How Alphabet’s Layoffs Could Affect Your 2023 Google Ads Strategy

Google came in like a wrecking ball with its January 2023 workforce reduction. Alphabet, Google’s parent company, laid off 12,000 staffers as other Big Tech companies scaled back investments they made when they experienced accelerated growth during the pandemic.

The staff reduction lines up with the direction Google is reportedly headed: Heavier reliance on AI and resellers. Sundar Pichai, CEO of Google and Alphabet, mentioned AI three times in the email he sent to Googlers and posted to the company’s blog, The Keyword.

“I am confident about the huge opportunity in front of us thanks to the strength of our mission, the value of our products and services, and our early investments in AI. To fully capture it, we’ll need to make some tough choices,” he wrote. Using the future tense when mentioning “tough choices” implies more restructuring is on the horizon.

Digital marketers will be consumed by changes at Google in 2023. While they migrate from Google Analytics to GA4, they’ll also need to rethink their Google Ads strategies. For better or worse, Google’s latest announcement will impact you regardless of your monthly spend.

Conversational AI

In recent years, Google Ads has been nudging advertisers toward embracing artificial intelligence. The platform leverages AI extensively to match advertisers’ assets with target prospects. The results can be mind blowing, but the AI also goes down unprofitable rabbit holes. Human intervention is still required.

Alphabet has invested billions in AI. The deafening hype surrounding ChatGPT upped the ante. Now Google is reportedly expediting the rollout of new AI capabilities. You can be sure these features are getting baked into Google’s own support services.

Conversational AI is a Google Cloud service that promises to streamline customer service with its chatbots, voice bots, and telephony helpdesks. A useful Google Ads chatbot would be welcome, but there will still be customers who prefer to talk to a real person. In some years, they’ll get over that.

Your Google Ads Rep

It’s very possible that your Google Ads representative was among those let go.

Over the past few years, Google has been increasingly encouraging advertisers to partner with approved resellers in its network, according to a Digiday report. Google Ads team members were fretting about layoffs as early as November 2022.

Google Ads reps get a bad rap, but I’ve only had positive experiences with them. Advertisers who find them unhelpful tend to have unreasonable expectations.

If your monthly Google Ads budget is minimal, the guidance you’re getting is basic but potentially invaluable. Google Ads reps assigned to the bottom tier lack the bandwidth for in-depth analysis. They still deliver quick wins by helping advertisers set up their conversion tracking and targeting so their campaigns can actually perform.

Google Ads campaigns have become increasingly foolproof in recent years. Working knowledge of Google Tag Manager is no longer necessary to track conversions reliably. Much of the hand holding Google reps do has been made redundant.

Smaller advertisers should consider hiring a freelancer or in-house ads manager to get the most out of Google Ads. The authorized Google resellers are likely out of their price range. Someone who understands how Google uses AI and your product’s audience will yield better results than most agencies.

How to Prepare

No matter the size of your spend, this should be top of mind in 2023. At the minimum, you should:

  • Consider hiring a freelancer, an in-house staffer or an agency to handle your Google Ads management
    • Ads managers with expertise in your niche yield the biggest ROI; agencies are hit or miss
  • Brush up on Google Ads’ AI applications and continue to follow updates
  • Start migrating Google Analytics to GA4 ASAP
  • Learn GA4’s AI capabilities as they’re announced
  • Consider partnering with a Google Ads reseller for enterprise-level requirements

If you need help navigating Google Ads in 2023 and beyond, send me a message below:

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3:33 1964 - Jay Forrester Introduces System Dynamics
In 1964, Jay Forrester introduces System Dynamics, a methodology for modeling and simulating complex systems. 

3:57 1970 - Apollo 13 Lunar Mission
In April 1970, the Apollo 13 mission to the Moon almost ends tragically. 

4:16 1982 - Release of Autodesk's AutoCAD
In the early 1980s, CAD software enters the mainstream. 

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6:40 General Electric's Digital Twin for Industrial Internet
In 2017, General Electric introduces its digital twin technology for industrial applications.

7:02 Microsoft's Azure Digital Twins Platform
The 2018 launch of Microsoft’s Azure Digital Twins platform accelerates adoption with a comprehensive cloud-based service. 

7:25 COVID-19 Pandemic Accelerates Digital Twin Adoption
In 2020, the COVID-19 pandemic accelerates the adoption of advanced manufacturing technologies, including digital twins, as companies seek to mitigate the disruptions in their operations, supply chains, and workforces.

7:37 Siemens Xcelerator Platform
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8:00 NVIDIA Omniverse Platform
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8:35 2030s - Digital Twins Become More Intelligent and Autonomous

9:11 2040s - Synthetic Holos Replace Digital Twins


#digitaltwin #digitaltransformation #industry40 #singularity #artificialintelligence #ai #machinelearning #robotics #humanoid #humanoidrobot #humanoidrobots #digitalthread #plm #digitalengineering #cad #3d #bigdata #blockchain #iiot #4ir #manufacturing #digitaltwins #futuretechnology #futuretech #smartcity #iot #internetofthings #innovation #quantumcomputing #digitalimmortality #transhumanism #simulation

Digital twins are everywhere.

The virtual replicas of physical entities are revolutionizing industries from manufacturing to healthcare to urban planning with their advanced simulation capabilities.

Let's examine how we got here and where we may be heading.

Emerging from the aerospace and automotive industries, digital twin technology is now gaining popularity across sectors. The virtual replicas of real-world entities are used for comprehensive simulations, predictive maintenance, and virtual prototyping.

0:17 Alan Turing's Computing Machinery and Intelligence
Though it’s primarily focused on AI, Turing’s paper provides the theoretical and computational foundations necessary to build smart, data-driven virtual models of physical assets.

1:06 First Commercial Computer (UNIVAC I)
The UNIVAC, the first commercially produced computer in the United States, is released in 1951. First deployed at the US Census Bureau, the UNIVAC I offers a glimpse into the potential of computing to handle vast amounts of data quickly and accurately to solve complex problems.

1:59 Monte Carlo Simulations
Monte Carlo simulations go mainstream around 1952. The experimentation method was initially developed for the Manhattan Project efforts to create an atomic bomb during World War II.

2:10 Development of FORTRAN
In the mid-50s, IBM’s FORTRAN delivers the computational power necessary for early forms of digital modeling and simulations. Its ability to handle large-scale computations and numerical analysis advances technology required for future digital twinning.

2:37 Launch of Sputnik and Advances in Aerospace Simulation
In 1957, the Soviet Union launches Sputnik, touching off the Space Race with the United States that accelerates simulation technology. The pressure pushes scientists to develop superior computer models to predict satellite paths and behavior in space.

3:09 Digital Simulation in Aerospace
In the early 1960s, the aerospace industry begins using digital simulations to design and test aircraft.

3:22 Introduction of CAD (Computer-Aided Design)
Ivan Sutherland develops Sketchpad for computer-aided design. It revolutionizes the way engineers and designers work by enabling precise digital drawings and models.

3:33 1964 - Jay Forrester Introduces System Dynamics
In 1964, Jay Forrester introduces System Dynamics, a methodology for modeling and simulating complex systems.

3:57 1970 - Apollo 13 Lunar Mission
In April 1970, the Apollo 13 mission to the Moon almost ends tragically.

4:16 1982 - Release of Autodesk's AutoCAD
In the early 1980s, CAD software enters the mainstream.

4:45 Advancements in Product Lifecycle Management (PLM) Systems
Throughout the 1990s, PLM platforms integrate various tools and processes, including CAD, to ensure consistency and accuracy of data and enhanced communication across departments.

5:21 Dr. Michael Grieves Coins the Term "Digital Twin"
In 2002, Michael Grieves introduces the concept of the digital twin at a Society of Manufacturing Engineers conference in Michigan.

5:47 NASA's Strategic Roadmap for Digital Twin Technology
In 2010, NASA develops a strategic roadmap for digital twin adoption for future missions.

6:09 Industry 4.0 Concept Introduced
The fourth industrial revolution begins in earnest in 2011 as the Industry 4.0 concept is introduced at Germany’s Hannover Messe.

6:40 General Electric's Digital Twin for Industrial Internet
In 2017, General Electric introduces its digital twin technology for industrial applications.

7:02 Microsoft's Azure Digital Twins Platform
The 2018 launch of Microsoft’s Azure Digital Twins platform accelerates adoption with a comprehensive cloud-based service.

7:25 COVID-19 Pandemic Accelerates Digital Twin Adoption
In 2020, the COVID-19 pandemic accelerates the adoption of advanced manufacturing technologies, including digital twins, as companies seek to mitigate the disruptions in their operations, supply chains, and workforces.

7:37 Siemens Xcelerator Platform
Siemens introduces its Xcelerator platform in 2021.

8:00 NVIDIA Omniverse Platform
NVIDIA’s Omniverse platform, introduced in 2023, integrates AI, simulation, and photorealistic visualization technologies

8:20 Manufacturers Embrace the Industrial Metaverse
Heading into the mid-2020s, manufacturers warm up to the industrial metaverse.

8:35 2030s - Digital Twins Become More Intelligent and Autonomous

9:11 2040s - Synthetic Holos Replace Digital Twins


#digitaltwin #digitaltransformation #industry40 #singularity #artificialintelligence #ai #machinelearning #robotics #humanoid #humanoidrobot #humanoidrobots #digitalthread #plm #digitalengineering #cad #3d #bigdata #blockchain #iiot #4ir #manufacturing #digitaltwins #futuretechnology #futuretech #smartcity #iot #internetofthings #innovation #quantumcomputing #digitalimmortality #transhumanism #simulation

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Digital Twin 100-Year Timeline: From Early Simulation Technology to Synthetic Human Integrations

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