Five classic ways to make your B2B content budget go further

It’s no secret that the past couple of years have been tough for enterprise technology companies. Between economic downturn, geopolitical instability, and unpredictable demand, most organisations have had to tighten their purse strings significantly.

This is putting a lot of pressure on B2B technology marketers.

In challenging circumstances like these, organisations look to their marketing function to drive demand and keep their pipeline strong. At the same time, they often pare back marketing teams and budgets, as they look to minimise every minimisable expense. According to Gartner’s 2024 CMO spend survey, average marketing budgets have fallen by 15 per cent this year alone.

We’ve supported the brilliant B2B marketers we call our clients through such moments before, and we surely will again. If you’re being asked to do more with less, and you need a little inspiration, here are five tried-and-tested methods.

#1) Make the most of the content you already have

Repurposing an asset can be much cheaper than creating one from scratch. So, dive into your library of existing content before you commission something utterly new.

Maybe you’ve an evergreen ebook that could be atomised into a fresh set of infographics. Or perhaps you’ve a white paper that previously didn’t perform too well, but suddenly has new relevance for your audience and just needs a new promotional push.

#2) Refresh your highest-performing pieces

Another quick and easy win is to refresh an asset that you’re really proud of. Take a content piece that you know your audience love, and look for opportunities to revitalise it with some up-to-the-minute context.

Think about how your thoughts and insights on the topic have evolved since the piece was originally published. If it makes any predictions about the future, ask yourself whether they’ve materialized – and if not, why not? Sometimes, all a classic content piece needs is some timely scene-setting – perhaps through a new introduction or executive summary – to become almost as powerful as the day it first launched.

#3) Narrow your focus to high-intent prospects

Typically, when economic conditions get tough, organisations are even more keen to see their marketing spend having an immediate impact on their bottom line.

One way to get more bang for your budget – at least in the eyes of your organisation – is therefore to focus on prospects with a very high likelihood of buying in the immediate future. (Though you’ll want to get back to building a diverse pipeline of prospects at a range of intent levels just as soon as you can.)

From a content creation perspective, that means asking some new questions. What problems are you solving for your newest customers? Which sub-personas are buying from you most frequently? What are customers asking you for right now?

By honing in on the needs of those most likely to buy, you’ll make sure the value your content delivers is both more immediate and harder to miss.

#4) Talk to your fellow marketers to avoid duplicating effort

Across very large enterprises, you’ll typically find multiple teams of marketers working on their own content pieces. Working autonomously helps those teams to avoid content creation bottlenecks, but it can also lead to duplicated effort.

When the sun is shining and budgets are ample, this isn’t a huge issue. If you end up with two content pieces that explore a similar topic, that’s probably not the end of the world – they might even be useful assets for different stages of a multi-touch nurture campaign.

But when your budgets are constrained, being on the same page as your colleagues in other parts of the business will help you all to make the most of your resources. Share your content plans early, and minimise the chance that you’ll duplicate each other’s work.

#5) Don’t risk the quality of your content

When you need every pound, dollar, or euro of your spend to deliver measurable returns for your business, cutting corners is extremely risky.

With all eyes on your output, it’s important to get things right first time — or at least, as close to first time as possible. The last thing you want is to have your content go through double-digit rounds of edits, only to end up with a piece that doesn’t land with your audience.

That’s why, when you’ve to spend less on your content, the smart play is usually to sacrifice quantity, not quality.

If you’d like to chat about how you could make your content budget go further, get in touch with us today.

A checklist to help prepare your subject matter expert for interviews and content feedback

It’s hard to overstate the value that subject matter experts (SMEs) can bring to B2B technology content. When a great copywriter talks to a true SME, they’re able to tease out their niche knowledge, thought-leading opinions, and surprising insights and transform them into content that’s original, engaging, and authoritative.

But for many marketers, looping SMEs into the content creation process is far from easy. In the CMI’s Outlook for 2024 research, 39% of marketers said they have difficulty simply accessing SMEs, while 41% reported issues with workflow/content approval.

Often, the challenges marketers face are a result of their organisations’ complex internal structures and dynamics. We can’t make those things vanish – but we can help you work within them. Over the many years we’ve spent supporting B2B technology marketers, we’ve learned a huge amount about preparing SMEs to become engaged, enthusiastic participants in the content creation process.

We’ve distilled all that wisdom into a short checklist. Download it to discover:

  • How to select and onboard a new SME
  • How to prep them for an input call
  • How to keep their feedback flowing (and your project rolling forward)

“SMEs are always bouncing from one thing to the next, so setting expectations and boundaries is essential. They need to clearly understand the purpose and outcome of the piece, what you need them to do before and after the call, and the deadline – these things are often forgotten.”

– Senior marketer for a global B2B technology enterprise

How to commission B2B tech thought leadership – a guide

Life can be tough for a B2B marketer – especially when you get a brief to write a thought leadership article for your CEO about something as vague and ill-defined as “the role of technology in sustainability”.

The first thing you do is probably call your friendly neighbourhood B2B content writer. It’s no secret that thought leadership content is mostly ghostwritten by a copywriter – hopefully, based on an interview with the subject matter expert (SME).

But when you’re provided with a scant brief like this one, how do you set your writer up for success so they can write with authority, deliver real insight, and win you awareness, credibility, and traffic?

Let me help you out.

Here is my guide to commissioning outstanding thought leadership writing that gets read, remembered, and shared. (It doesn’t matter what content type you’re commissioning; from a blog to a white paper, it’s the same approach.)

Step 1: Propose ideas people haven’t thought about yet

“Know your audience” is the golden rule of marketing. Because relevant content gets read. While this is true for most forms of B2B marketing – where you find out what questions your readers are asking and answer them with content that makes their job easier – thought leadership is a bit of an anomaly.

B2B technology thought leadership isn’t usually so closely linked to client questions; it’s more about proposing new ideas people have yet to think about.

That means the challenge when writing B2B thought leadership content is making sure what you say is relevant and interesting to your target reader, and speaks to a need they can see, even if they have yet to think of the question they need to ask.

Step 2: Look around you – the unique angle is probably already there

Nobody likes a copycat. By contrast, original content gets remembered, which is why true thought leadership offers new perspectives for people in your industry.

This may well include a strong opinion that sparks debate. (Thought leaders don’t please everyone.) But not every piece needs to be radical. You can simply present a well-known concept in a different way – just make sure it’s a truly unique take.

And you shouldn’t have to go far to find that fresh angle. It’s likely you’re already sitting on a wealth of knowledge across SMEs in your business. Some of these people might even be ready-made thought leaders. All they need is your help to convey their distinctive viewpoint.

Finding a unique angle will help your piece avoid the fate of so much content that’s wrongly passed off as B2B thought leadership, but makes little impact.

Step 3: Build a detailed brief

Before commissioning a thought leadership piece, you’ll need to ensure your copywriter has a clear view of your sector, brand, and audience. They should be familiar with your target readers’ challenges, clearly explain the unique idea, and understand why it’s important to the people in that industry.

This means you’ll need a watertight brief, an experienced writer in your sector, or – ideally – both.

This will put your writer in the best position to have a valuable conversation with your SME and ask the right questions to clarify their thoughts.

To improve the process further – and depending on how well-developed the angle is – you could ask your writer to sketch out an outline, write some questions, and find some third-party data to support your SME’s brave new vision.

Ask your copywriter to share these with you and your SME ahead of the next stage.

Step 4: Choose a writer that’s experienced in interviewing

Interviewing is the most crucial part of the process as it helps you get the best content. When I worked in B2B journalism, the strongest stories always came from speaking directly to SMEs.

But not all writers have the experience or skills to interview SMEs. At Radix, we’re fortunate to be trained in interviewing experts as a core part of our skillsets. Here are a few of the areas we feel are most important:

  1. If there’s anything you’re not sure of, don’t be afraid to ask as this will help you translate the interviewee’s expertise into compelling content.
  2. Ask for real-world examples to bring the idea to life as this will make it much easier and more pleasant for your audience.
  3. Look for structures and narratives in what the person is telling you to help construct the piece, then summarise at the end of the interview.

One of our favourite things is watching the expert relax after we’ve asked some questions, because this means they were absolutely the right questions, and we know it’s going to be a good thought leadership piece.

Step 5: Double-check the angle (and make use of the tangents)

Asking questions is one thing. Articulating the answers and finding the best angle is another. To do this, your copywriter must be agile when interviewing and ruthless when writing.

This is where you will both be rewarded for creating an outline (in Step 3) as it gives your writer the chance to validate with you where they feel the best points are and which parts of the conversation should go in the main piece.

Of course, things can change during an interview, so your writer should let you know if the idea morphed and if the SME agreed to it. Also, your copywriter might think of ways to turn peripheral ideas that came up into other valuable content pieces.

This is what we do every day at Radix: gather and untangle the often-tangential thoughts of people who are too busy to do so. Then we organise, condense, and structure them into a captivating narrative, suggesting extra content where the opportunities present themselves.

Step 6: Create something outstanding

Thought leadership content can transform industries by challenging accepted beliefs, predicting new trends, or expressing surprising new visions. True thought leaders can provide valuable insights by commenting on industry developments or educating readers about complex topics.

But it will only stand out if the writing is superb.

So, my final piece of advice is to select your writer carefully. Look for an exceptional copywriter who understands B2B technology markets and all the other elements that make a piece of writing outstanding, such as accuracy, clarity, authority, empathy, and wizardry.

Extraordinary writing will make your SME’s piece stand out. (This point is even more important in B2B tech content due to the, sometimes… ahem, dry subjects.)

Putting thoughts into words

If you’re finding it hard to put your client’s thoughts into words and help them lead an industry, here’s some related Radix content on this subject. Or you can talk to our team about it.

Five AI-infused technologies that are transforming healthcare

A few years ago, I had surgery to fix some mobility problems caused by a form of hip dysplasia.

It took a while to figure my issues out; x-rays, CT scans, even an arthrogram-aided MRI couldn’t get a clear enough picture. Eventually, the diagnostics team used my scans to create a 3D model of my pelvis – a “digital twin” of me that showed my consultant exactly where the problems and damage were.

Two surgeries later, I’ve emerged with a sizeable scar and a real appreciation for how complicated the human body is, and how much technology can do to support healthcare professionals.

These days, I do a lot of healthcare-related writing for various clients, with topics ranging from rural care access to the latest advances in diagnostic AI. And that means I get to see a lot of exciting technologies as they emerge.

Here are five technologies that are making a difference in healthcare – and how they work.

1. Deep learning models for diagnostics

Radiologists work through hundreds of scans each day, identifying and recording their findings. Pair that with highly complex cases, potential interruptions, and additional responsibilities, and there’s an enormous cognitive load to contend with. Over a long shift, the risk of a radiologist missing something on an image grows, even when they’re highly experienced.

So what can AI do to help? Deep learning – a form of AI where a machine learns to complete multiple layers of processing – can support radiologists by offering additional detail in the reading process. These models can be trained to look for specific clinical findings, such as masses, bleeds, and breaks, and flag them to the radiologist for confirmation.

Let’s take chest x-rays, for example. They’re the most widely used imaging test in the world, but there are several layers of bone and organ to contend with, which means findings can get lost in the density. One recent study paired 20 radiologists with a deep learning model, which was trained using more than 800,000 previous chest x-rays. Of 127 clinical findings, the model led to a statistically significant improvement in accuracy for 102 of them.

There’s a worldwide shortage of radiologists, pathologists, and other diagnostics professionals right now, and demand is growing as our global population gets older and sicker – so the support of a deep learning model could make a major difference.

2. Virtual reality simulations for clinical training

All clinical professionals need to learn in a practical environment, but not every patient wants to be the proverbial guinea pig, especially in emergency, sensitive, or high-stress cases. Wouldn’t it be so much easier if we could train clinicians in any situation on demand, to make sure they get practical experience in a wider range of potential scenarios?

Oxford Medical Simulation provides virtual reality training to help doctors, nurses, mental health professionals, and other clinical trainees test out medical scenarios in a realistic but totally safe environment.

As trainees care for the citizens of Uncanny Valley, AI sits behind both patient behaviour and physiology, adapting in response to their clinical decisions. That means not only are trainees making medical decisions, but they can also practice their bedside manner.

3. Predictive models for understanding patient risk in nursing

A lot of healthcare discussions centre on treating illness and fixing things – the reactive component of care – but let’s talk about prevention for a minute.

Over decades of health research, clinical professionals have developed a pretty good idea of various risk factors and what they cause. Smoking leads to various cancers; high cholesterol can cause heart attacks and strokes; being overweight can put you at risk of diabetes, and so on.

But human bodies are complex, and what puts one person at risk of developing rheumatoid arthritis, for example, may lead to nothing for another. It can be difficult to predict who’s at risk of what without infinite time and budget for research – especially when there are lots of tiny interacting factors involved.

Predictive modelling can do a lot of that work for us. AI can rapidly data-mine millions of historical cases, using both numerical and natural language processing to identify common circumstances, demographics, and characteristics. The model can then be applied to any patient to assess their level of risk.

In nursing, this is already helping clinicians understand things like which factors affect the likelihood of an elderly patient suffering a fall, or what might cause an adverse reaction to medication. It has the potential to become really useful when integrated with electronic patient records, where the system can actively flag risks to a patient’s team to trigger preventative care.

4. Large language models for information sharing

Large language models (LLMs) are really having their moment – in all sorts of industries. Able to process vast amounts of text-based data and use it to inform human-like responses to prompts, LLMs are behind adaptive chatbots, services that can summarise search queries and, yes, those exceptionally famous generative AI tools.

As with all technologies, the standards for healthcare use are significantly higher. But as they mature, LLMs have the potential to extract more value from the billions of medical records, statistics, research findings, textbooks, and journal articles out there.

Applied carefully, LLMs can make it easier for researchers to access and assess existing literature, and work from larger sample sizes. Clinicians can use advanced search tools to find similar cases to help them make diagnoses or treatment decisions. And the general public can use clinically-verified chatbots to find information about their symptoms or diagnosed conditions, to help them manage their health.

5. Artificial intelligence for taking care of your own health

Speaking of managing our own health: I’d wager we’re all guilty of searching our symptoms online and going down a horrible rabbit hole of worst-case scenarios for what’s likely to be a simple headache. (I definitely went looking for images of my upcoming surgery and squeamishly regretted it.)

But there are more sensible ways of checking up on your health. Ada is a healthcare AI, designed by doctors and scientists and delivered in a handy app format, that draws on a vast, clinically-validated information base to offer assessments, triage options, and long-term tracking tools. If you’ve got symptoms that you’re worried about, but you’re not sure if you need to see a clinician, the app guides you through a questionnaire to work out what you’re likely suffering from.

With clinician shortages getting progressively worse, it may become more difficult to access services quickly, especially for minor ailments. We’d all benefit from better ways to understand our own bodies, find accurate information about our health, and decide whether that headache needs an ibuprofen or professional intervention.

Healthcare technologies are all about the people on both sides of the care equation

As B2B technology copywriters, we spend a lot of time highlighting cost savings, productivity boosts, efficiencies; business benefits that can obscure the people the technology serves.

In healthcare, it’s so much easier to draw a clear line between a technology and its value for individual people. (And, we’re all patients at one point or another.) For copywriters and B2B tech marketing audiences alike, this offers an extra connection we might not naturally feel when reading or writing about payroll software.

In healthcare, there’s no true substitute for human expertise and experience. But as AI continues to mature, there are so many clear applications where the technology can augment clinicians’ work with the right ethical and safety guidelines in place. With pervasive burnout affecting medical professionals around the world, anything that can ease their workload and support clinical decision-making is worth exploring.

Leadership agrees: in the UK, the NHS recently announced major investment in AI, with similar work going on across the EU. And the US government is investing heavily in AI for biomedical and behavioural research, with individual health systems working on their own AI deployments.

And all that means good news for me, with plenty of new technologies to learn and write about. So if you have a healthcare topic that you need to dig into, you know who to ask for.

Why it’s time for B2B marketers to enter the data mesh

B2B marketers love data. Marketing was one of the first business functions to put big bets on analytics and automation, and today, the best B2B marketing campaigns are driven by data. It might not always be complete or accurate, but data helps talented marketers set the general direction of their campaigns and pin their instincts on something tangible.

But what if marketers could easily access trusted data (and lots of it) and use that data to deliver better results?

What if they could uncover new insights hidden in data throughout the business – and use them to create hyper-personalised content and more effective campaigns?

What if they could imagine possible futures for their campaigns and quickly test their hypotheses to see what works?

Well, in a data mesh, they can.

What’s a data mesh? And why should marketers care?

In large, complex organisations with monolithic data architectures, accessing timely, relevant insights can be a laborious process. It relies on specialist data teams to drag insights kicking and screaming out of a central data lake.

The data mesh approach helps overcome these difficulties by decentralising the data architecture and making each domain (marketing, sales, product, etc.) the owner of the data it produces. It’s an approach that’s been growing in popularity over the last few years (which explains why tech consultancies often ask us to write about it) as large enterprises look for ways to reduce organisational and operational complexity.

In a data mesh, the people closest to the data are responsible for managing it and using it to create “data products” that solve their most pressing issues or open up new opportunities.

Federated data ownership removes the operational bottlenecks of centralised structures, so marketers can access and use data how they need to, when they need to. And with data products visible and accessible on a self-service platform, everyone can access products built by other domains and combine them in useful new ways.

New marketing opportunities – and responsibilities – in the data mesh

The data mesh approach empowers marketers to cut out the middleman and start experimenting with their data to find ways to improve content and campaign results. When data users become data owners, the possibilities are limitless.

Marketers who build and own data products can understand their customers and prospects better than ever. They can optimise their campaigns on the fly and conduct low-risk, high-reward experiments with different approaches. They can even begin to create the kind of hyper-personalised content and communications that most marketers can only dream of.

More than most business functions, marketing thrives on data from across the organisation. Insights from sales, service, product, R&D, manufacturing, supply chain, and more can all add valuable context to marketers existing knowledge about their customers.

With a data mesh approach, marketers can easily access data products from other business functions to quickly create new capabilities. For example, combining product and sales data products with a customer-intent data product might help marketers target specific prospects with campaigns that are more likely to land.

But before we get too carried away, it’s important to remember that federated ownership also means federated responsibility. In a data mesh, every domain is a data custodian, so marketing becomes responsible for the governance, compliance, and quality of its data.

Meaningful change takes time

Adopting a data mesh approach requires a fundamental cultural shift; it’s a completely different way of thinking about data and how it’s managed, governed, and used.

This shift in mindset includes a switch to what technologists call “product thinking”, where success is defined by the outcomes products deliver, rather than the outputs of projects. It might also require changes in how teams are structured and how they operate. And it will certainly involve fostering a new culture of cross-functional collaboration, as different business units contribute to combined data products.

It’s not something that happens overnight, and it can take years for large organisations to successfully embed the data mesh approach. But if you’re looking for a long-term, strategic approach to getting more bang for your marketing buck, data mesh could be a conversation worth having with your colleagues in IT and elsewhere in the business.

Stay up to date with what’s next in tech 

If you’d like to keep up with how emerging tech trends can have a big impact on B2B marketing – and get practical advice on other ways to maximise the value of your content – sign up for our newsletter.

Star power: Can nuclear fusion fuel the earth?

We spend a lot of time writing about the impact of global warming, from mitigating the risks of climate change to accelerating decarbonisation and renewable energy adoption. And if I’ve learnt one thing, it’s that if the world doesn’t speed up its decarbonisation efforts, humanity could be facing a desolate future.

Solar and wind power are both brilliant steps in the right direction, but when there’s no wind and the sun isn’t shining, we can’t use them to produce electricity. So, what are the alternatives?

Imagine if there was a way to power the world that was clean, carbon free, and possible whatever the weather.

The answer could be written in the stars.

These giant balls of plasma generate an abundance of energy through a process known as nuclear fusion. But is it a process we could ever recreate on earth?

We already have nuclear energy. So what is fusion?

Today, nuclear power plants use a process called nuclear fission to produce energy.

Nuclear fission uses unstable atomic isotopes (like uranium 235) and harnesses the energy they create as they decay. It’s highly efficient and doesn’t generate carbon dioxide. However, fission does create some pretty nasty waste products that can stay radioactive for millions of years.

Typically, power plants use geological disposal to handle this waste – burying radioactive material deep underground so thick layers of rock can stop radiation reaching the earth’s surface.

But if that doesn’t happen because of disaster or meltdown, it can be utterly devastating.

Instead of using elemental decay, nuclear fusion combines two isotopes of hydrogen: deuterium and tritium (which are abundant in water and lithium). This creates an atom of helium, a lone neutron, and a lot of energy.

In fact, fusion can generate nearly 4 million times more energy per kilogram of fuel than oil or coal, with no carbon emissions at all. There’s also no long-term radioactivity; only the beta-emitting ingredient tritium, which has a short half-life of just over 12 years. And there’s no risk of meltdowns, as fusion reactions can’t sustain themselves outside of a reactor.

It’s a lot safer than fission. But it’s also far more difficult to achieve.

Major developments are paving the way for fusion on earth

To make fusion reactions happen, scientists need to overcome deuterium and tritium’s natural electromagnetic repulsion. For that, they need to create a huge amount of heat and pressure.

Currently scientists are looking at two key methods to achieve this: magnets and lasers. And recently there have been major breakthroughs in both.

South Korea’s electromagnetic tokamak

South Korea’s “Artificial Sun” is a type of fusion reactor called a tokamak. It’s a donut shaped device that uses magnetic coils to create the intense conditions needed for nuclear fusion. These magnets produce a twisted magnetic field, causing deuterium and tritium atoms to collide and creating energy that heats the walls of the reactor. This heat can then convert water to steam which powers turbines and generates usable electricity.

In 2022, the Artificial Sun sustained a temperature of 100 million degrees Celsius for 30 seconds, and the team are aiming for 5 minutes by the end of 2026. It’s an unimaginable temperature. To put it into context, the centre of the Sun is only a puny 15 million degrees Celsius.

The lasers of America’s National Ignition Facility

In the US, the Lawrence Livermore National Laboratory has used lasers to achieve the first ever net energy gain from nuclear fusion. Physicists fired 192 lasers at a target chamber containing deuterium and tritium, causing a huge implosion of energy that forced the atoms to fuse and release energy.

To be useful to humanity, the energy produced needs to be greater than the energy put in. And the US team has now achieved this not just once, but four times.

Nuclear fusion could be the future of clean energy

Nuclear energy is gaining traction worldwide. It was formally specified as one of the solutions to climate change in the COP28 agreement, and many governments are now pledging more funding for nuclear research.

Current fusion science is a far cry from the cold fusion controversies of the 20th century, and every new development gets us closer to achieving a clean, carbon-free, and near-infinite energy source.

I’m fortunate enough to get to write about electrification and renewable energy in my work at Radix, and it’s so exciting to think that one day – albeit in a few decades – I might be writing about fusion energy in the same way.

If you’re a bit of a physics geek like me, and curious to learn more about nuclear fusion, the International Atomic Energy Agency is a great place to start.

What is synthetic data? And why should B2B marketers care?

Like so many next-big-things, the generative AI wave is towing a host of cottage industries in its wake. One of the most fascinating is the synthetic data industry.

I think it’s worth the attention of any B2B tech marketer because it reveals the complex challenges, opportunities, and risks of generative AI in microcosm – and because the best content about AI acknowledges and navigates that complexity.

Synthetic data: a solution to AI’s biggest obstacles

All AI models must be trained on extensive data. And the more general the task, the greater the variety and volume of data the model needs before it can respond with accuracy and confidence.

But collecting data volumes from the real world poses several issues:

  • Sourcing huge amounts of data is time-consuming and really expensive.
  • It can be hard to find data on uncommon or edge-case scenarios (think MRI scans of rare medical conditions or images of a machine experiencing a one-in-a-million fault).
  • There are privacy and copyright issues with using certain online datasets (such as data gleaned from social media platforms).
  • Data produced by humans can carry human biases.

Synthetic data promises a solution to many of these problems. Unlike conventional data used to train AI models, synthetic data is artificially generated, so it isn’t bound by the confines of reality.

For example, if you were training an AI to assess fuel efficiency across different commercial aircraft, you could use synthetic data generated by flight simulators instead of collecting real-world aircraft telemetry data from hundreds of flights.

By creating artificial data at scale, you can get more data at a lower cost without the copyright complications or biases of human-generated data. And you can also design datasets covering phenomena seldom seen in real life.

Synthetic data’s ability to remove all these roadblocks is so great that last summer, Gartner predicted 60% of data for AI will be synthetic by 2024.

The use cases unlocked by synthetic data

Computer vision models, which need training on large volumes of high-quality images, have been one of the first forms of AI to benefit from synthetic data. But there are many other use cases for synthetic data in its many forms, including:

  • Genomic data to train AI healthcare solutions on rare diseases – without breaching patient confidentiality.
  • Images of different (and potentially unreleased) products to train automatic defect recognition on manufacturing lines.
  • Financial records to develop fraud detection systems without using personal financial information.

Whatever task you want to train an AI model for, it’s likely that synthetic data can help make that process faster, more consistent, and cheaper.

The risk of AI eating itself

With so many use cases for synthetic data, there’s naturally a lot of demand. And one way to meet that demand is… with the help of generative AI. We’re already seeing some vendors working to build a closed loop for AI – where generative AI creates synthetic data that’s then fed into other AI models.

But this Ouroboros model of AI has its critics. When researcher Jathan Sadowski looked into the phenomenon, he found models that were “so heavily trained on the outputs of other generative AIs that [they] become an inbred mutant”.

A consumer-facing model spouting nonsense might, at worst, damage a brand’s reputation. But such degradation in a model designed to detect security risks for IT systems or cancerous cells in medical imaging could have catastrophic effects.

The implications for B2B tech companies and marketers

We’re still in the early days of this new generation of AI and the synthetic data that will support it. And with the major NASDAQ staples investing heavily in the space, any problems will have serious resources and talent thrown at them until they’re resolved.

So perhaps in the future, we will have something approaching a synthetic data utopia that leads to unfathomably powerful AI. But for now, we have a fork in the road that everyone in the B2B technology sector must navigate carefully.

Any story about synthetic data must be embraced with positivity and the hope that it will crack the code of training society-enhancing AI models. But we must also be ready to ask the most pressing questions about how synthetic data production can scale. And the level of scrutiny must be dialled up as generative AI and synthetic data training increasingly come into contact with critical, high-risk sectors like healthcare, education, and government.

More importantly, B2B tech marketers must be ready to openly discuss these challenges in any content that speaks about synthetic data and generative AI. Our audience is clever, connected, and very comfortable managing risk. They won’t be put off by an acknowledgment of the potential pitfalls and challenges in the field. In fact, they may find the honesty refreshing and ultimately trust the message and the brand behind it all the more.

Recommended further reading

If you want to learn more about synthetic data and AI, there are plenty of articles exploring this fast-growing field.

While it was written just before the recent AI renaissance, Forbes ran an article covering some of the major use cases for synthetic data and the earliest players in the industry. It’s a great place to start if you want a broad overview of the topic.

And for a clearer look at the potential risks associated with synthetic data, this interview with machine learning researchers Sina Alemohammad and Josue Casco-Rodriguez offers an expert outlook on what happens when AI consumes data created by other AI models.

Nature-based solutions: Technology that thinks outside the casing

As a technology copywriter, I get to see how cutting-edge innovations transform and improve the world. But some of the most exciting solutions I come across don’t rely on breakthroughs in smart fabrics or generative AI. Instead they rely on materials and processes that have been around for millennia.

Nature-based solutions use natural mechanisms to solve human challenges – in a way that reduces our destructive impact on the planet.

Here are just a few of my favourite use cases.

#1 Data centre cooling

As humanity generates, stores and analyses more and more data, we need more capable data centres. And keeping those data centres switched on, and cooled down, takes a huge amount of energy. In fact, data centres account for 1–1.5% of global electricity use.

The battle to stop our servers over-heating has sparked some especially neat technological innovations, most notably, liquid cooling. Running liquid past your circuit boards, and then letting it cool off at a safe distance uses less energy than air conditioning, reducing a data centre’s operational costs and emissions. But the technology still lacks standardisation, and requires large initial investment to implement.

So, what solution does nature offer?

About as far away from high-tech as you can get, free cooling solutions simply use the external atmosphere to keep servers at an acceptable temperature. They deliver far lower cooling costs and energy usage than any other option, but are only possible in the right environments.

One place that could be perfect for free cooling a data centre: under the sea.

Using the sea to cool data centres even provides an opportunity to power the servers with offshore wind and solar energy. And, much like wrecks, such data centres could provide valuable habitats for marine life – boosting biodiversity in the surrounding area.

Offshore, underwater data centres do, however, have drawbacks. In some cases, solar and wind energy may be the only viable source of power, as connecting to the onshore grid is very difficult. And a completely weather-dependent data centre isn’t ideal. And then there’s the challenge of performing maintenance…

#2 Urban pollution reduction

The global population is expected to pass nine billion by 2037. As populations increase, so does pollution – especially in urban areas.

One way to protect the health and wellbeing of city-dwellers is to stop pollution at its source (for example, through the transition from petrol and diesel to electric vehicles). Another is to actively remove pollutants from the atmosphere.

Electrostatic precipitators use static electricity to pull pollution particles from the air – and advances in nanotechnology are making the process more efficient. Electrochemical conversion, meanwhile, can pull CO2 out of the atmosphere, allowing the carbon to be repurposed as materials and fuels.

But nature has its own, tried-and-tested solution for capturing and converting CO2. And as well as processing carbon dioxide through photosynthesis, some plants even consume other urban pollutants.

Moss is a great example. Certain varieties naturally feed on common pollutants, removing them from the surrounding atmosphere – and providing a handy way to monitor pollution levels. Combining this natural process with choice technologies can yield even better results. Driving more air through the moss, for example, can increase the quantity of air purified, while solar-powered, IoT-connected irrigation systems can help to keep the moss healthy.

#3 Protecting coastal communities from climate change

The global average sea level is rising, and at the same time, climate hazards – like large storm surges – are becoming more frequent. This combination poses a huge threat to coastal communities. What’s more, creating appropriate hard structures to provide long-term protection is a complicated task because the rate of change is as unpredictable as it is unprecedented.

Again, nature offers some adaptable, sustainable answers. One that’s currently gaining popularity is planting mangroves.

Mangroves have a naturally tight root system that provides protection from large waves during storms while protecting the land from coastal erosion. They need enough space to grow, and the right environment to thrive, but where they’re a viable solution, mangroves also create a valuable new habitat for wildlife. This habitat can increase biodiversity, and even provide sustainable fishing opportunities for local communities.

Humans and nature are better together

As astonishing as humanity’s recent technological advances are, sometimes it can be incredibly beneficial to look away from our screens and machines, and out the window.

Nature may not have all the answers, but the ones it does offer have been stress-tested over timescales even the best-funded R&D team can only dream about. Combining natural mechanisms with our most exciting innovations could yet be the secret to shaping a sustainable future for us and our planet.

 

 

Reviewing B2B copywriting? Steal our 16-point quality checklist

In any industry where quality matters, there are a series of objective tests that a product has to pass before it’s released. But somehow, assessing B2B marketing content still seems to be a highly subjective process.

Maybe there’s a belief that creative work is exempt from objective judgement, or a fear of provoking arguments and resentment among writers and stakeholders. Still, nobody reviewing B2B writing seems to have a clear idea of what good looks like.

And that’s ironic. Because in most other contexts, a simple checklist of definable yes/no tests – making quality a little less subjective – is precisely the thing that prevents disagreement.

At Radix, we challenged the idea that evaluating writing is only ever subjective. So, we created a clear, 16-point QA checklist that’s inspired by the process we follow for all our internal reviews – the ones our content leads do before the client sees the work.

Our QA process helps to safeguard quality, but it also improves consistency across our writing team by highlighting areas for development in both writers’ work and client briefs.

And it works so well that we want to share it with you.

B2B Content Marketers checklist for assessing quality technology copywriting

A 16-point quality check for your B2B content

The questions you can use to guide your reviews are grouped into five tests, reflecting the five key B2B copywriting competencies: accuracy, clarity, authority, empathy, and wizardry.

Test A: Accuracy

Q1: Is the copy free from factual errors?

Readers won’t take your content seriously if it’s littered with factual inaccuracies or (worse) straight-up lies. This is basic integrity.

Q2: Have you screened for typos, grammatical errors, and spelling mistakes?

Writers and marketers are only human, and typing is hard. But your reader may not be forgiving, so take the time to proof thoroughly.

Note: If you’re using the QA checklist to identify issues for development, you’ll need a scoring threshold that separates consistent errors from occasional slips. If you’re interested, our wording is: “Are there two typos or fewer per 500 words AND is the copy free from grammatical and spelling errors (that aren’t obvious typos)?”

Q3: Does the piece meet the technical requirements (word and character count limits, templates, style guide, SEO)?

This might seem niche, but it’ll save a lot of headaches when you come to upload documents into your CMS or pass your copy on to designers. The point to take away is that the copy needs to meet the technical requirements of the format.

Plus, adhering to file-naming conventions makes managing content easier for everyone.

(So far, so good. The first three questions should ensure your copy is error-free. But we’re just getting started…)

Test B: Clarity

Q4: Does the copy have a logical structure that presents a compelling argument?

Usually, a B2B decision-maker isn’t interested in reading meandering walls of copy or navigating subversive storytelling approaches. Your content can be long, but you must take your reader with you. That means you need a strong structure that always makes sense.

Q5: Is the point of the piece obvious – from the start and throughout the narrative?

If you’ve got to the end of the introduction and aren’t sure why you should continue reading, or if the piece completely tails off towards its conclusion, the result is the same: you’ve lost your reader. (And your mark for this question.)

Q6: Is every sentence easy to read?

If you find yourself rereading sentences, tripping over grammar, or referring to Google to understand the language, the piece won’t work. If your reader is a senior decision-maker, time-poor, or reading on a mobile device, that only adds to the pressure to ease the cognitive load.

The “every sentence” part of the question sets an incredibly high bar – B2B tech can be complex – but this is important, so we make no apologies for that.

Test C: Authority

Q7: Is there appropriate use of technical or industry terms that are relevant for the intended audience?

There’s no point claiming expertise if you don’t speak your reader’s language. If the content is for a specialist B2B audience, the writer will likely need to use relevant technical jargon where appropriate. And they’ll need to handle it correctly – too much B2B content sprays industry terms around to mask a lack of confidence, and it always shows.

Q8: Are the claims supported by evidence and specific details?

Talk is cheap, so ensure every claim is specific and appropriately sourced. Don’t just say it’s fast; say how fast. Don’t say a viewpoint is widely acknowledged; link to an example. If there are references to studies or ongoing news stories, ensure the sources cited are the most recent available.

Q9: Is the copy free from waffle, hyperbole, clichés, and overly formal language?

Hyperbole fails when it promises the impossible (inflated language makes you less believable). If the writer seems too in love with their thesaurus, they might be making up for lack of relevant knowledge.

“If you care about being thought credible and intelligent, do not use complex language where simpler language will do.” Daniel Kahneman, Thinking, Fast and Slow

Test D: Empathy

Q10: Is there evidence that the writer understands the target audience?

This is fundamental to effective B2B marketing content. If the brief failed to define the audience, the writer should’ve pushed back before they even got close to writing.

Q11: Does the piece avoid making assumptions about the audience?

This is a tricky one. When you’ve done your audience research, it’s easy to go too far and lapse into telling the reader what they must think. Some writers will do this without realising, but making ill-advised assumptions only alienates the audience or dilutes the piece’s credibility.

Q12: Are the content and tone appropriate to the audience’s interests, priorities, and knowledge level?

How many B2B content pieces aimed at a particular sector start by defining the market or saying why it’s important? Newsflash: if you work there, you already know.

You need to understand your audience’s knowledge and awareness level. This is partly about the language, of course. But it’s also about being excited by the right things and going beyond features and benefits to understand the real difference a product, service, or idea will make to someone’s working life.

Test E: Wizardry

Q13: Does the piece offer original insight and value to the reader?

Not every piece needs to reinvent the wheel, but it does need to offer tangible value to the reader – and more content pieces fail on this count than any other. It might be new primary research, an original point of view, or a handy 16-point checklist (ahem), but the reader needs to gain something in return for their time.

Q14: Is it written in the right voice?

This is a little easier if you only write for one brand, but still, the piece needs to sound right. If you cover up the branding, is it still clear who’s speaking? Whether you’re writing on behalf of a brand or by-lining to an individual, reading should feel like the client is sitting in your head, dictating it to you.

Q15: Is it engaging and enjoyable to read? And is it likely to incite readers to action?

Place yourself in the reader’s shoes. Does the end arrive quicker than you thought, or does it seem like hard work? Do you naturally want to take the next step, whatever that may be?

What interests this audience may bore you to tears, but if a piece is well written, you should be able to get to the end and say, “Yes, that would work for me if I was a slurry engineer.” If that’s the case, then hey, good stuff.

Q16: And most importantly… Does the piece meet the brief and reflect the right messaging?

After meeting all the points above, it’s important to consider whether the piece reflects the initial brief. If your answer is no, you must take a few steps back and identify where you went wrong.

Even if you’ve produced the most well-written blog post of the year, it won’t be useful to your client – or your campaign – if it doesn’t reflect what you set out to achieve.

If your content scores 16/16, it’s ready to go…

Having reviewed thousands of pieces of content to date (from individual emails to messaging frameworks and entire websites), we find that this checklist works pretty well as a scoring tool.

Your needs might differ; some questions could be more relevant than others. You may also have technical requirements that require greater nuance.

If that’s the case, feel free to download our B2B content scoresheet and make your own version. Maybe you’ll want to change the questions or weight the scoring somehow. Get creative.

But the point is this: asking clear, objective questions makes it much easier to tell whether your content works and reduces the number of arguments you’ll have about preferences. It can help you spot issues and change how you brief, write, and review. And ultimately, it’ll stop you from rushing out weak content.

If it helps to improve the quality of B2B tech content overall, then by all means, steal away. We’ll be delighted.

Keep it Real: Why B2B marketers should start small with VR

I waited a long time to try Virtual Reality. Up until a few days ago, I remained sceptical about the whole concept. To me, it all just seemed a bit too novel, retro-futuristic and prohibitively expensive to catch on.

Now, I stand before you as a changed man. After being able to give the technology a go for myself using our shiny new office Samsung Galaxy VR, I am a complete believer – but not necessarily for the same reasons as most.

Less V, more R

To get a rounded experience of what the tech can do, I tried as many different apps as possible. I was surprised to see such a wide range of apps available for the smartphone-powered headset, and the quality of experience they delivered was far above what I would have expected from a device at its modest price point.

What surprised me the most was how quickly I felt immersed in the individual apps. I’d imagined that it would take me some time to really “sink into” each environment and scene, but it happened almost instantly in most cases.

I sat through interactive videos, played games and even walked around a museum before diving into what I thought would be the definitive VR experience – a virtual rollercoaster (a decision I would deeply regret moments later).

With the rollercoaster, things were different. The completely digital environment felt alien, and as soon as my carriage started moving, I started to feel extremely unsettled.

As I took off the headset and attempted to supress the urge to vomit, something became very clear. The VR experiences I enjoyed the most and found the most immersive were the ones grounded in reality.

While it’s fun to shoot zombies, hide from killer clowns and ride in a runaway minecart, it was far more fulfilling and entertaining to come face-to-face with elephants or look at the earth from space. That could of course just be a matter of personal preference, but I think there is something important to take from it.

If we look at VR as a way of enabling people to see and connect with real things that they’re otherwise physically detached from instead of a vehicle for delivering novel virtual experiences, it’s much easier to find compelling applications for the technology in B2B.

Show, don’t tell

VR is a great way of showing your customers something amazing instead of just telling them about it. Whatever it is you’re selling, enabling someone to engage with it in a virtual environment or virtually see it in action is going to leave a lasting impression on them.

Companies like Marriott Hotels are already using VR to do just that. Their virtual travel teleporter campaign gave people the chance to explore hotels thousands of miles away, and get a feel for the kinds of experience they offer.

It’s like a product demo, only it’s not just for the techies. A well-crafted VR experience can give any stakeholder involved in the purchasing decision a clear view of what your product is going to do for them. And, enabling them to virtually engage with it brings them closer to the product itself than almost any other type of marketing content.

Don’t ditch your team (especially not your copywriters)

While some may dream of fully-rendered virtual environments that customers can explore and interact with freely, that’s often not going to be what they end up with.

For most, the VR experiences they create will be “on-rails” (that is to say, they will be completely guided). They’re going to feel like highly immersive videos – a content type that copywriters play a critical role in.

Those “on-rails” experiences will likely be guided by voiceovers, so from a production point of view, the process really isn’t going to differ that much from the way marketers create video content now.

Agencies aren’t going to need to hire a whole squad of 3D modellers and dedicated designers with experience building virtual environments to provide their clients with great VR content. With 360-degree video (filmed using increasingly affordable 360-degree cameras) you can create amazing B2B VR experiences using the skills and people you already have.

Don’t think too big

In entertainment media like live sports broadcasting and video games, VR really could change everything. But, if we want VR to become a staple in B2B marketing, I think it would be wise to set our expectations a little lower.

If marketers can set realistic expectations of what we want to do with VR, it could become a very strong part of our content arsenal. By using it to deliver memorable and engaging video experiences that are grounded in reality, it could have applications for a huge number of businesses and campaign types.

So, if you’re thinking about taking your first steps towards creating B2B VR content and experiences, I’ll leave you with these three quick tips to help you keep things simple:

  1. Think of VR primarily as a way of enabling customers and prospects to physically engage with something they’re otherwise detached from.
  2. See it as a way of showing what your product or service can do instead of telling someone. Think of the benefits it delivers that you struggle to put into words.
  3. And most importantly, treat the format the same way you would a video, instead of trying to completely break the mould.

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