Innovation and Technology
B2B Marketing Measurement Isn’t Trusted, And It’s About To Get Worse

B2B Marketing Measurement Isn’t Trusted, And It’s About To Get Worse
Let’s face the hard truth. Trust in marketing measurement is already poor, and if left unchecked, it’s poised to get 20% worse.
The pain that your organization feels surrounding B2B marketing measurement problems is real. Forrester’s Marketing Survey, 2024, revealed that 64% of B2B marketing leaders feel that their organization doesn’t trust measurement for decision-making. This hurts because marketing is a discipline with credibility that depends on data, facts, and insights, yet many marketing leaders don’t have faith in their company’s measurement when it matters the most.
Not having trusted measurement hinders marketing’s ability to get its job done. Optimization of marketing efforts requires data to inform adjustments. That can’t happen when the metrics used to describe performance aren’t trusted. And without measurement to clearly depict marketing’s contribution, securing the budget and resources necessary to drive business impact becomes a losing battle.
Why Is Measurement About To Get Tougher?
We’re predicting that marketing measurement is about to get more difficult because of these compounding market forces:
- Buying complexity obscures so much. B2B sellers tell us that deal cycles have grown longer. Buyers tell us of the large quantities of individuals now involved in purchasing decisions. Persistent time-lag issues in detecting business impact grow more difficult with lengthened selling cycles. More people interacting with sales and marketing more times places more pressure on measurement systems already struggling to capture and make sense of their behaviors.
- Technology sprawl yields fractured data. The volume of technologies that make up the go-to-market technology stack results in disconnected data sources, and in turn, disconnected data is now a leading analytics challenge. Stitching together a cohesive picture of buyer behavior across these technologies is stretching the resources and skills of analytics teams — and this shows little signs of being alleviated.
- AI-inflated hope drives an expectation gap. AI has the potential to power meaningful improvements throughout B2B. This promise carries into widespread expectations that better measurement is possible by using AI to make sense of large volumes of data at speeds that humans will never replicate. But the distance between that vision and the current state of B2B marketing measurement should be counted in years, not months. B2B planning, processes, and data aren’t yet in shape to meet AI’s potential. Stakeholders of all types will struggle for the foreseeable future to make sense of and develop faith in AI-driven views of performance. Expect a prolonged period of experimentation, missteps, and resets before B2B marketing analytics teams come anywhere close to cracking this code.
- Measurement can’t keep up with a renewed emphasis on reputation investment. B2B marketing investments have traditionally skewed toward capturing and advancing demand and so, too, has the focus of marketing measurement. But there’s growing recognition that demand efforts are not enough, and selling organizations must do more to influence buyers before they enter active buying cycles. Reputation spend now represents nearly one-quarter of marketing program investments, but we’re not seeing similar prioritization among what marketing leaders measure. Measurement analytics teams currently fall short in the skills and capabilities to measure this area that they’ve traditionally deprioritized.
What’s To Be Done?
Each of these market forces are larger than measurement, and there’s little that your analytics team can do to hold any of them at bay. What will separate the winning organizations from the rest is how they respond. In the face of these forces, here are a few actions that you can take to enhance your organization’s trust in marketing measurement:
- Tune your processes to buying complexity. Do the work to make it easier to link buyers to opportunity records, and work to capture not only self-guided interactions but personal ones, as well.
- Economize the B2B tech stack. Squeeze out duplicative capabilities found in best-in-breed solutions in favor of the broader solutions of platform providers. A more consolidated set of technologies will carry less overhead when it comes to data preparation and consolidation.
- Set clear reputation objectives. It’ll take time and resources to create comprehensive approaches to measuring reputation. In the meantime, start small by working with stakeholders to be sharp about setting reputation objectives and select a handful of available indicators that can show progress.
- Pair AI efforts with insight activation. Marketers are right to be excited by the potential of AI. At the same time, there’s a clear need to enable them to work more productively with the analytics already available. Marketing analytics teams need to redirect more of their time toward enabling their stakeholders to drive better results using existing resources. Doing so will better prepare them for the potential that AI is bound to unlock.
Conclusion
The future of B2B marketing measurement isn’t looking bright, but it’s not all doom and gloom. By recognizing the challenges ahead and taking proactive steps to address them, you can enhance your organization’s trust in marketing measurement and drive better results.
FAQs
- Why is trust in marketing measurement so low?
- According to Forrester’s Marketing Survey, 2024, 64% of B2B marketing leaders feel that their organization doesn’t trust measurement for decision-making.
- What are the causes of the decline in trust?
- The main causes include buying complexity, technology sprawl, AI-inflated hope, and the inability to keep up with a renewed emphasis on reputation investment.
- What can be done to improve trust in marketing measurement?
- Tune your processes to buying complexity, economize the B2B tech stack, set clear reputation objectives, and pair AI efforts with insight activation.
- What is the future of B2B marketing measurement looking like?
- The future of B2B marketing measurement is looking challenging, but by recognizing the challenges ahead and taking proactive steps to address them, you can enhance your organization’s trust in marketing measurement and drive better results.
Innovation and Technology
Instilling Clear-Headed Leadership With AI

Introduction to AI Leadership
Don’t fret, and don’t fight, the artificial intelligence wave. Instead, be an educator. Get out ahead of it and make it work in a positive way for everyone around you. The good news is you don’t have to be a techie to take a leadership role with AI.
The Need for AI Advocates
That’s the word from Ab DeWeese, a venture capitalist and consultant, who explains, in his latest book, Essential AI: Your All-in-One Quickstart to Using AI in Business and the Workplace, that the rise of AI is demanding clear-headed leadership. “Be the change – become an AI advocate," he urges. As AI has massive potential, "the more we each take responsibility for understanding it and sharing our knowledge, the better off we will be,” he says. AI advocates can not only make their jobs more future-ready, but also add value to the worlds around them.
The Role of an AI Advocate
“Whether you’re just AI-curious or you’re an AI enthusiast and early adopter, you have a unique opportunity to act as an educator, champion, and agent of change, helping others see the immense value and potential of AI as you leverage them yourself,” DeWeese observes. The role also provides "a chance to share the vital nature of AI guardrails and how to avoid AI risks.” “In our AI future, power, career success, and compensation is going to concentrate among those with AI skills and knowledge,” he adds. By bringing AI to the workplace in a fair and effective way, one can become an agent of positive change, “the go-to guru showing others how to work less to produce more, freeing up their creativity and productivity.”
Designing an AI Advocacy Role
DeWeese makes several recommendations for designing an AI advocacy role:
- Start with education. “Provide clear, straightforward information about what AI is, how it works, and how it can enhance productivity and efficiency. Use simple language and relatable examples to demystify AI. Get them working with AI yourself and invite them to engage them immediately with your help. Or sit next to them and show them what it looks like and how to get started. As you’ve seen yourself, once you become familiar with it, it becomes easier immediately.”
- Demonstrate the tangible benefits of AI. "Show, don’t just tell. Use real-life examples and case studies to illustrate how AI solves specific problems or simplifies tasks. The more concrete and relevant your examples, the more compelling your case will be."
- Share examples of where AI has been successful. "Stories are powerful—they make the abstract concrete and the unfamiliar familiar. Show co-workers “what a productive, problem-solving AI session looks like. These examples can motivate and reassure those who are hesitant about change.”
- Choose a complex task co-workers may have and help work it with them. For example, a customer service representative may have an idea for a process improvement they’d like to demonstrate to their manager, DeWeese advises. “Show them how they can use AI to articulate a concept they may still be struggling to get clear. This process isn‘t just for people with highly developed skills and jobs. It’s incredibly helpful for people at any level with ideas they want to develop.”
- Help co-workers develop prompt development skills. "Work the task with them by helping craft a prompt for AI that might look like this: ‘I am proposing a new process improvement to my boss. Please help me develop this idea into a clearly articulated, benefit-and result-oriented proposal.’ Work with AI iteratively to develop this idea until it’s in a compelling, coherent form."
- Address concerns head-on. "Don’t shy away from tough conversations. Acknowledge fears about job security and explain how AI can augment, rather than replace, human capabilities. Point out the benefits you’ve seen and learned about, like saving time and producing interesting new results. Explain how a highly developed AI understanding will set them apart in our AI future. Explain how humans are critical, especially those who can manage AI technology."
- Encourage hands-on experience. "The most effective way to convert skeptics is to let them experience AI firsthand," DeWeese states. "Invite colleagues to collaborate with you and see the benefits for themselves. This practical, hands-on experience can demystify AI and demonstrate its value in a way that words alone cannot."
- Have fun with it. "If you don’t have a specific work task to work on together, use AI to research something fun, like activities you can do together, an upcoming vacation, or writing a song."
Conclusion
Ultimately, humans matter more than machines ever will. The key is to impress this upon co-workers – and be the change.
FAQs
- Q: What is an AI advocate?
A: An AI advocate is someone who educates and champions the use of artificial intelligence in the workplace, helping others to understand its potential and benefits. - Q: Why is it important to become an AI advocate?
A: Becoming an AI advocate can help individuals make their jobs more future-ready, add value to their organization, and become a leader in their field. - Q: What skills do I need to become an AI advocate?
A: You don’t need to be a techie to become an AI advocate, but you do need to be willing to learn and share your knowledge with others. - Q: How can I get started as an AI advocate?
A: Start by educating yourself about AI, then share your knowledge with others, and encourage them to get hands-on experience with AI.
Innovation and Technology
5 Game-Changing Quantum Computing Use Cases

Quantum computing is no longer a futuristic dream; it’s being used right now to optimize finance, discover new drugs, secure networks, and even build better batteries. We’re going to hear a lot about quantum computing in the coming years. Once real-world mainstream use cases start to appear, it will become one of the hottest topics in tech, up there with AI.
The Current State of Quantum Computing
Things are moving steadily towards that point. The investment pouring into quantum service providers and startups shows that industry understands its significance. And a growing number of real-world use cases are emerging to demonstrate its value outside of the laboratory. Quantum computers harness the properties of quantum mechanics to perform some tasks millions of times more quickly than classical computers. This will make them hugely transformative in fields including finance, cybersecurity, medicine and material sciences.
Real-World Applications of Quantum Computing
So, let’s take a look at what quantum computers are actually being used for today to understand how they are already pushing the boundaries of what’s possible.
Optimizing Transactions In Financial Services
A collaboration between IBM, Quantinuum, Banca D’Italia and several universities has produced a quantum computer system capable of tackling highly complex optimization tasks. It’s thought that this technology could save financial institutions millions of dollars by reducing delays in settling payments on the TARGET2-Securities platform used to manage stock trades. Quantum computers are great for solving these kinds of mathematical problems, involving finding the best combinations of numerous complex variables. In this case, the optimization involves finding the most efficient methods of processing transactions as quickly as possible. The World Economic Forum believes that applying quantum computer technology to financial services optimization problems in this way will unlock $2 trillion in economic value by 2035.
Drug Discovery
Quantum computers are especially good at simulating the real world because the real world follows the rules of quantum physics — something traditional computers, which rely on simple binary logic, struggle to replicate accurately. In fact, Nobel Prize-winning physicist Richard Feynman once said, “Nature isn’t classical, dammit! And if you want to make a simulation of nature, you’d better make it quantum mechanical.” Quantum computing pioneers Qubit Pharmaceuticals leverage this ability of quantum computing to more accurately model and predict the interactions between medicinal particles and disease targets in the human body. According to their founder, 70% of these interactions are too complex to model on classical computers. This means that quantum computers are far more likely to identify potential candidates for new drugs and treatments. Google and IBM are also building quantum computing technology optimized for this task.
Quantum-Secured Networks
Network security protocols developed using quantum techniques have been rolled out in high-stakes environments, including telecommunications and government communications infrastructure. Samsung has built quantum key distribution (QKD) into its Galaxy Quantum range of smartphones, and the technology has been used by Hyundai and Toshiba to create quantum-secured networks. China Telecom is planning to launch the first quantum-secured global telecommunications network by 2027. QKD works because of the quirky quantum principle that observing a particle changes its state, meaning any attempt at snooping can instantly be detected and shut down.
Better Batteries
Batteries are usually the most expensive component of electric vehicles. The need to generate a large amount of energy from a device of the minimum size, weight and manufacturing cost creates a tough engineering challenge. A partnership between Hyundai and IonQ, however, has resulted in technology that can better model the properties of lithium compounds used in battery cathodes. This enables researchers to quickly test candidate materials via simulation and vastly speed up the discovery process. The result is batteries that hold power for longer, charge quicker and can be made from a wider range of materials.
Truly Random Numbers
Banking giant JPMorgan Chase has been a leading investor in quantum computing research for some time, and it could now be starting to pay off. The bank’s research division, working alongside academics from the University of Texas and other leading institutions, has developed methods of generating truly unpredictable numbers. Classical computers, by comparison, use deterministic methods of generating “random” numbers, so they aren’t truly random and, in theory, can always be cracked or traced back to a seed by sufficiently powerful computers. It’s believed that random numbers generated in this way will form the basis of the more secure cryptography techniques of the future.
Towards Commercial Quantum Computing
Everything covered here is happening in the real world now, even if it is all being built on bespoke architecture by companies with very deep pockets. However, Google’s head of Quantum, Hartmut Neven, believes it will be as little as five years before commercial off-the-shelf quantum applications are available. This will be the real game-changer as the power of quantum becomes accessible to a far wider range of businesses and organizational users, further accelerating innovation. While quantum computers won’t replace classical computers for every task, the tasks they do excel at are high-value and often business-critical. Everyone involved in fields that will be directly impacted should prepare immediately for dramatic transformations that will occur when this technological revolution fully begins.
Conclusion
Quantum computing is no longer a futuristic dream, but a reality that is being used to optimize finance, discover new drugs, secure networks, and build better batteries. With its ability to perform tasks millions of times more quickly than classical computers, quantum computing will have a significant impact on various industries. As commercial off-the-shelf quantum applications become available, the power of quantum will become accessible to a wider range of businesses and organizational users, leading to further innovation and transformation.
FAQs
- What is quantum computing?
Quantum computing is a type of computing that uses the principles of quantum mechanics to perform tasks that are beyond the capabilities of classical computers. - What are the current applications of quantum computing?
Quantum computing is currently being used in finance, drug discovery, network security, and battery development, among other fields. - What is the potential impact of quantum computing on various industries?
Quantum computing has the potential to unlock $2 trillion in economic value by 2035, and will have a significant impact on various industries, including finance, healthcare, and technology. - When will commercial off-the-shelf quantum applications be available?
Google’s head of Quantum, Hartmut Neven, believes that commercial off-the-shelf quantum applications will be available in as little as five years. - How will quantum computing change the way we work?
Quantum computing will enable businesses and organizations to perform tasks that are currently impossible or impractical with classical computers, leading to increased efficiency, innovation, and transformation.
Innovation and Technology
Solving the Climate Crisis: The Role of Technology in Achieving Net-Zero

Technology for social change is revolutionizing the way we approach the climate crisis, and it’s time to harness its power to achieve a net-zero future. The climate crisis is one of the most pressing issues of our time, with rising temperatures, melting ice caps, and extreme weather events becoming the new norm. To mitigate its effects, we need to reduce our carbon footprint and transition to a more sustainable and renewable energy-based economy.
Understanding the Climate Crisis
The climate crisis is a complex issue, and understanding its causes and effects is crucial to developing effective solutions. Human activities such as burning fossil fuels, deforestation, and land-use changes are releasing large amounts of greenhouse gases, including carbon dioxide and methane, into the atmosphere, leading to global warming. The consequences of inaction will be catastrophic, with rising sea levels, more frequent natural disasters, and devastating impacts on ecosystems and human societies.
The Science Behind Climate Change
The science behind climate change is clear: human activities are releasing large amounts of greenhouse gases, leading to a global average temperature increase of over 1°C since the late 19th century. The Intergovernmental Panel on Climate Change (IPCC) warns that we have just over a decade to take drastic action to limit global warming to 1.5°C above pre-industrial levels and avoid the most catastrophic consequences of climate change.
The Role of Technology in Achieving Net-Zero
Technology has a crucial role to play in achieving a net-zero future, from renewable energy and energy efficiency to carbon capture and storage. Solar and wind power, for example, are becoming increasingly cost-competitive with fossil fuels, while energy-efficient technologies like LED lighting and smart grids can significantly reduce energy consumption. Additionally, technologies like carbon capture and storage can reduce emissions from industrial sources, while electric vehicles can decarbonize transportation.
Renewable Energy Technologies
Renewable energy technologies, including solar, wind, hydro, and geothermal power, are becoming increasingly important in the transition to a low-carbon economy. These technologies can provide clean and reliable energy, reduce greenhouse gas emissions, and create jobs and stimulate local economies. Governments and companies are investing heavily in renewable energy, with solar and wind power becoming increasingly cost-competitive with fossil fuels.
Energy Efficiency Technologies
Energy efficiency technologies, including smart grids, energy-efficient appliances, and building insulation, can significantly reduce energy consumption and greenhouse gas emissions. These technologies can be applied in various sectors, including residential, commercial, and industrial, and can help reduce energy waste and improve energy productivity. Additionally, energy-efficient technologies can create jobs and stimulate local economies, while reducing energy costs for consumers.
Carbon Capture and Storage
Carbon capture and storage (CCS) is a technology that can reduce emissions from industrial sources, including power plants and cement factories. CCS involves capturing carbon dioxide emissions from these sources and storing them underground, preventing them from entering the atmosphere. While CCS is still a developing technology, it has the potential to play a crucial role in reducing emissions from hard-to-decarbonize sectors.
Carbon Capture Technologies
Carbon capture technologies, including post-combustion capture, pre-combustion capture, and oxyfuel combustion, can reduce emissions from industrial sources. These technologies can be applied to various sectors, including power generation, cement production, and steel manufacturing. However, CCS is still a developing technology, and significant investment and research are needed to reduce costs and improve efficiency.
Electric Vehicles and Transportation
Electric vehicles (EVs) are becoming increasingly popular, with many countries investing heavily in EV infrastructure and incentives. EVs can decarbonize transportation, reducing greenhouse gas emissions and air pollution in urban areas. Additionally, EVs can improve energy efficiency, reduce operating costs, and enhance the overall driving experience.
Charging Infrastructure
Charging infrastructure is critical to the widespread adoption of EVs, with governments and companies investing heavily in charging stations and networks. Fast-charging technologies, including DC fast charging and high-power charging, can charge EVs quickly and efficiently, reducing range anxiety and improving the overall driving experience.
Conclusion
In conclusion, technology has a crucial role to play in achieving a net-zero future, from renewable energy and energy efficiency to carbon capture and storage. By harnessing the power of technology, we can reduce greenhouse gas emissions, transition to a low-carbon economy, and mitigate the effects of climate change. Governments, companies, and individuals must work together to invest in and develop these technologies, to ensure a sustainable and prosperous future for all.
Frequently Asked Questions (FAQs)
What is the climate crisis, and why is it important?
The climate crisis refers to the current and projected state of the climate system, characterized by rising temperatures, melting ice caps, and extreme weather events. It’s essential to address the climate crisis to prevent catastrophic consequences, including sea-level rise, more frequent natural disasters, and devastating impacts on ecosystems and human societies.
What is net-zero, and how can we achieve it?
Net-zero refers to a state where human activities result in no net emissions of greenhouse gases, achieved by reducing emissions and offsetting any remaining emissions through carbon capture and storage or other technologies. We can achieve net-zero by transitioning to renewable energy, improving energy efficiency, and developing and deploying carbon capture and storage technologies.
What role can individuals play in addressing the climate crisis?
Individuals can play a crucial role in addressing the climate crisis by making conscious choices, including reducing energy consumption, using public transport or electric vehicles, and investing in renewable energy. Additionally, individuals can support climate policies, participate in climate activism, and educate others about the importance of addressing the climate crisis.
What are the benefits of transitioning to a low-carbon economy?
The benefits of transitioning to a low-carbon economy include reducing greenhouse gas emissions, creating jobs and stimulating local economies, and improving air quality and public health. Additionally, a low-carbon economy can reduce energy costs, improve energy security, and enhance the overall quality of life.
How can governments and companies support the development and deployment of climate technologies?
Governments and companies can support the development and deployment of climate technologies by investing in research and development, providing incentives and subsidies, and implementing policies and regulations that support the adoption of low-carbon technologies. Additionally, governments and companies can collaborate with each other, with civil society, and with individuals to raise awareness and build support for climate action.
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