Category: Content Marketing

Why don’t I want to write this blog right now?

Posted on by Steve George

For as long as most of us can remember, marketers have struggled to get subject matter experts (SMEs) and other stakeholders excited about engaging with content creation. And there are a few very good reasons for that:

  • It’s a one-way value exchange: If people aren’t interested in building their personal brand and getting their name out there, there’s usually little to no value for them in contributing to content.
  • It’s not their circus, and those aren’t their monkeys: Everyone has their own responsibilities to worry about during the work day. Any new expectation that doesn’t fall within their remit tends to really irritate them.
  • People outside of marketing (allegedly) don’t get why it’s important: Historically, we’ve been told that many non-marketing folks simply don’t understand what marketers are trying to achieve, or why they need expert input to do it. I’m not convinced that’s the case for a lot of people, but it certainly can happen.
  • It isn’t easy: Contributing to content and marketing projects puts huge pressure on people to articulate their expertise in a really clear way, which is something most of us don’t have to do very often.

The trouble is, I don’t really want to contribute to Radix’s marketing content right now, and it isn’t for any of those reasons. I know the value marketing delivers. I understand why it’s important. It is a defined responsibility for me. And I even fall into the very small group of people in the world for whom articulating complex concepts comes relatively easy.

So, what is my problem? And is there anything I can glean from it that could help marketers make some real steps forward in how they engage SMEs and other content contributors?

Our first mistake is making sweeping assumptions about human motivations and needs

Around ten years ago, I received an adult diagnosis for obsessive compulsive disorder. Very recently, I’ve also come to understand that I fall somewhere on the autism spectrum. The two are tightly linked, and while they have a minimal impact on my daily life, they do shape a lot of my attitudes and behaviours.

For me, structure is incredibly important. Predictability is king, and the thing I find difficult about contributing to marketing is its ad hoc nature. For those responsible for managing marketing, it’s a continuous strategic task that’s always front of mind. For me, it’s typically appeared as intermittent requests that can come at any time, and must be tessellated around my client projects.

That shouldn’t be an issue, but it is. If these requests catch me at the wrong time, while I’m focused on something else, that completely shapes how I feel about them. A process I understand and want to help with becomes frustrating, without anybody doing anything wrong.

The answer to the titular question, “Why don’t I want to write this blog right now?” is simple. When I logged on to start work today, I didn’t know I would be writing it. Even though the idea was mine, and it’s an idea I believe in, the organic nature of how this blog originated doesn’t align with my own need for structure and predictability.

I’d never really reflected on that until writing this. I have no desire to build a personal brand or become a leading voice in my field. My motivation for engaging with marketing is simply that I recognise its critical role in enabling me to continue to do a job I’m great at, for clients I really like working with, alongside a team of people I love. And what I need to make that happen is for the whole thing to be very structured and predictable.

We’re all individuals with our own passions, neuroses, drivers, frustrations, and preferred ways of working. If marketers want to get people excited about contributing to their projects, the ways they engage with SMEs must be as precisely tailored as their strategies for audience engagement.

If you give people what they want, you tend to get what you want too

I use myself as an example simply because there’s no SME I know better. My proposition isn’t that everyone should adapt how they engage content contributors to align with my needs. The point is that if we want to get the most from every contributor, we need to engage them on their terms, just as we do with customers.

Thinking practically, it isn’t really feasible (or valuable) for marketers to dedicate the same time to mapping out the needs and motivations of SMEs as they with their customers and prospects. But they absolutely can do that for select ‘high-value’ contributors.

It’s important to forge close relationships with great contributors. Learn their motivations, replicate the conditions that enabled them to make a great contribution to your project, and give them more of what they want.

For some (like me), that might mean making the process extremely structured and predictable by securing a recurring slot in their diary for marketing input. For others, it could be the opposite, creating an organic workflow where they can provide ideas and input however and whenever they like.

Some will be highly motivated to become thought leaders in your market. Others will be much more comfortable providing content ideas without having their name attached to them. Discuss your SMEs’ goals and motivations to uncover how contributing to marketing could help. See how, where, and when they like to work. And use everything you learn to personalize the experience of contributing to your marketing projects.

Closer collaboration builds understanding on both sides

By thinking about contributors in the same way you think about customers, you can discover what each person needs to deliver the most valuable input. And in doing so, you just might change a few attitudes towards marketing.

Practically, all that has to involve is:

  • Frank and friendly conversations between marketers and SMEs where the marketer can really get a feel for how the SME works and what makes them tick. These are the kind of chats that used to happen naturally in our physical office world, but if you’re part of a more dispersed team, you’ll need to make a conscious effort to book these catch-ups in.
  • Being mindful of exactly where, when and how you request SME input, and put yourself in the SME’s shoes to maximize your chances of getting them on side and making them excited about getting involved with your plans. What’s going on in their diary at that moment? Do they have a major client or project delivery deadline looming soon? It’s in your interest to catch them at their stress-free best if possible.
  • Going to them with an offer rather than a request in the first instance. People often don’t really know what marketing could help them achieve personally, so reach out to let them know, and give them a chance to provide input on their terms. If they end the conversation feeling like engaging with marketing and providing input was their idea, brilliant.

Radix’s marketing processes have gone through something of a transformation in recent months. And I’m happy to say, it’s all been framed around how we can get the most from our team. Our expertise is our greatest asset, so we’ve started to approach marketing in ways that make it easy for our people to share their insights and explore topics they truly feel are worth exploring.

I shan’t embarrass the person responsible for delivering our marketing by naming them. But I hope as they review this, they know how much I appreciate their efforts. Meeting me on my terms takes so much more work than simply presenting me with a content concept and making me write it. That effort means a lot to me and builds my desire to help them in any way I can.

Doing all of this doesn’t make the marketer’s life easier – quite the opposite. But it does significantly improve the quality of the content they publish.

While my own neuroses mean that, yes, I didn’t start out wanting to write this blog, I’m more invested in Radix’s marketing than I’ve ever been before. I feel understood, and as a result, I really do want to help.

That feels like a pretty big win for me, and our marketing.

Reviewing B2B copywriting? Steal our 16-point quality checklist

Posted on by The Radix Team

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.

Three ways AI is helping improve animal welfare

Posted on by The Radix Team

As a longtime fan of dystopian science fiction like The Matrix and Metal Gear Solid, I’ve always found AI to be a compelling, if somewhat unsettling, concept. That’s why, despite those cautionary tales, AI is consistently surprising me as a force for good.

Whether it’s generative AI being used to enhance medical research or computer vision helping athletes track and analyse their performance, I currently spend a lot of time writing about how AI can help people work smarter, and more safely and efficiently.

While it’s all fascinating to learn about, for me, here’s one application that resonates much more than the others. It may not seem like the most obvious use case, but AI is already playing a key role in humanity’s efforts to improve animal welfare – and the more I learn, the more it makes sense.

In this blog, I’ll look at three ways AI is helping make life a little better, if not more dignified, for wildlife and livestock. But before we dive in…

A quick guide to the tech

Were you confidently nodding along when I mentioned generative AI and computer vision? If those terms make sense to you, feel free skip to this section. If not, then read on.

Generative AI refers to models that can learn from existing content – like the collected works of William Gibson, or the films of Ridley Scott – to create new text, images, video, and synthetic data.

Computer vision (CV) is a field of AI in which algorithms are continuously trained using visual data to recognise objects and people. This helps it spot and respond to pre-defined patterns and behaviours.

Eager to learn more about AI? Be sure to read my colleague George’s blog about synthetic data, and Katy’s deep dive into AI’s applications in healthcare.

Use case #1: Protecting British wildlife on Network Rail

Network Rail (NR) and the Zoological Society of London (ZSL) – a science-driven conservation charity – are working with Google Cloud to identify, monitor, and learn more about wildlife living in and around the 52,000 hectares of land owned by NR.

Together, ZSL’s Machine Learning (ML) image processing systems and Google Cloud’s advanced data analytics enable NR’s ecologists to rapidly survey wildlife, map their behavioural trends and take protective action at scale.

Connected sensors capture huge amounts of audio and visual information in key wildlife areas. AI tools are then used to analyse the data and inform decisions regarding how to best protect different species.

So far, the initiative has helped track and protect endangered hazel dormice living along the edge of railways in the south of England, and many bat and bird species in and around London – including the rather lovely Eurasian blackcap. It’s also helped NR identify the best places to create “hedgehog highways” on its lines, helping the spiky lads cross over safely.

As climate change drives many species to find new habitats, ZSL and NR plan to use AI to monitor and safeguard their migration without disrupting railway operations. The project’s conservationists also expect AI will soon help them better manage vegetation alongside railways and on road verges to encourage biodiversity.

It’s nice to see organisations working together to protect these creatures, and it’s sure to help boost NR’s reputation with some passengers and investors. You can learn more about the initiative here.

Use Case #2: Observing livestock welfare for healthy herds

The National Farmers’ Union says animal welfare is a high priority for all British farmers, and while there are many RSPCA-assured farms, less than 3% of UK farms are inspected by official Government bodies each year.

There are also more than 1,000 “US-style mega-farms” in the UK, and they can become extremely crowded. These are the most likely candidates for animal mistreatment, given the aggressive turnaround on production and limited space.

It’s often difficult for vets, cattle consultants, and farm advisors to tell what’s happening behind closed doors. Plus, even with the best intentions, farmers may struggle to keep manual track of every animal’s wellbeing.

This is where computer vision and AI-powered analytics can help. Automatic image detection and analysis solutions can provide remote, AI-enhanced livestock surveillance 24/7 – to everyone who needs it.

Non-intrusive cameras are installed in strategic farming areas, providing a live video feed  augmented with on-screen visuals that indicate each animal’s current status, behaviour, and risk level.

Machine learning algorithms continually monitor and analyse the footage, including user responses, to more accurately identify when an animal is at risk or action must be taken to optimise their environment. To achieve this, the AI is taught to recognise and assess the environment’s brightness and humidity, and even animals’ faces and vocalisations.

Users can pre-define scenarios that they want the AI to alert them to, such as abnormal animal activity, whether cows are lying down enough, if their stalls are comfortable, and when food or water is running low.

AI-powered monitoring solutions can also help farmers and vets identify sick animals, predict emerging health issues, and analyse behavioural patterns that are indicative of an animal’s wellbeing. This information can improve farming productivity too, ensuring animals are kept in conditions conducive to safe and efficient pasture and growth.

Use case #3: Reducing avoidable animal suffering in slaughterhouses

Animal welfare organisations The Dutch Society for the Protection of Animals and Eyes on Animals, meat producer Vion, and professional services giant Deloitte have teamed up to develop AI4Animals – an intelligent animal surveillance system.

Their mission is to “significantly reduce avoidable and unnecessary animal suffering through innovative technology”. The solution uses AI to continuously monitor how animals are being handled in slaughterhouses, and alert those in charge of animal welfare to any signs of mistreatment or deviation from regulated protocol.

AI4Animals says many major slaughterhouses lack the time and resources to assess footage captured by traditional camera monitoring solutions. With AI, every frame is analysed in real-time using a rules-based criteria to detect handling issues, such as:

  • People causing stress by walking directly against the direction of the pigs
  • Animals remaining idle due to possible exhaustion or injury
  • Inappropriate use of mobile stunners as defined by regulatory protocol

There are other issues it can detect, but they turn my stomach – so I’ll leave those out for both of our sakes. Should the AI detect an issue, users can manually review any flagged footage to confirm mistreatment or a false positive. The AI will also compile regular reports to help outline deviations in behaviour over time, and inform decisions at a more strategic level.

Will this technology catch on?

During my research for this blog, I came across an article exploring the use of AI to detect distress in pigs. It’s already able to do this with 92% accuracy compared to human assessment.

While it’s true that happy animals tend to be more productive, and calmer animals are easier to handle, it’s questionable whether all producers of animal products are ready to embrace such technologies. By monitoring the emotions of livestock, you also acknowledge their existence and importance. Some industry commentators believe producers will resist this shift, fearing the imposition of new regulations that diminish the profitability of their operations.

It’s grim to think that people may ignore such promising technology because it risks humanising animals and harming profits, and I can only hope it does inspire more meaningful change across the industry.

In the meantime, the solutions explored in this blog are already driving meaningful change, and while I may not like industrial farming, if AI can help the animals live out happier, more dignified lives – I’m all for it.

Five classic ways to make your B2B content budget go further

Posted on by Steve George

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.

Nature-based solutions: Technology that thinks outside the casing

Posted on by Claire Goodfellow

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.

 

 

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

Posted on by The Radix Team

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

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

Posted on by George Reith

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.

Star power: Can nuclear fusion fuel the earth?

Posted on by Claire Goodfellow

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.

Five ways B2B marketers can go the extra mile with data privacy

Posted on by Steve George

In marketing, almost everything we do is driven by customer data in one way or another. It helps us understand customer sentiment, expectations, and needs, enabling us to create relevant, high-impact campaigns and content.

But with great power comes great responsibility. Following the great GDPR panic of 2018, we all know not to put personally identifiable information into the public domain, or seriously misuse it. But beyond that, how much time do we really spend thinking about data privacy and our day-to-day role in upholding responsible data practices?

To mark Data Privacy Week, here are five things B2B marketers and copywriters can do to safeguard data privacy, without compromising on the value customer data can deliver.

 

#1) Personalise, but don’t go overboard

We’ve all come across content, ads, and offers that feel a little too targeted to us. It’s an unsettling feeling that gives people the impression they’re being monitored, rather than simply catered to.

But overpersonalisation doesn’t just put people off; it can be bad news from a data privacy perspective too. The more customer data you gather and use in your campaigns and content, the greater the risk of that data being exposed or compromised.

Encountering overpersonalised offers and content brings privacy right to the front of your audience’s mind, leading them to ask questions about what you’re gathering and why. Suddenly, a campaign that you wanted to drive sales starts driving a very different kind of engagement – changes to cookie settings and personal data visibility.

 

#2) Get rid of data and materials you no longer need

Under EU GDPR law, people have the right to have their personal data erased if it’s no longer necessary for the purpose you originally collected or processed it for. But how often do you go back and clear out old data once a campaign is complete?

As copywriters, it’s our responsibility to dispose of the sensitive data and materials our clients provide us with as soon as they’re no longer necessary for us to do our jobs. Marketers should follow the same principle. Once reference materials no longer have practical use for you, get rid of them. The less sensitive data you hold, the less there is to be compromised.

 

#3) Be cautious when using public AI models and tools

In 2023, marketers everywhere began experimenting with public AI models – most commonly, ChatGPT. But in the rush to see what they could get out of it, very few people spent time thinking about the security and privacy of what they put in.

AI models learn from the prompts users give them as well as the gigantic datasets they’re trained on. If you use sensitive data – such as your own proprietary research or details about a specific customer you want to target – as part of an AI prompt, it can leak and begin to appear in future outputs from the AI model, creating privacy issues.

Specific AI-related regulations have emerged to help account for its potential impact on data privacy. So, any marketer who wants to use public (or even private) AI models to generate content or make decisions should do so very carefully and understand the privacy risks AI can expose them to.

AI models learn from the prompts users give them as well as the gigantic datasets they’re trained on.

 

#4) Use data to answer specific questions

One of the key principles of GDPR is purpose limitation. It says that any personal data you gather should be collected for specified, explicit, and legitimate purposes. So, whenever you’re using or gathering customer data, you should start with a specific question in mind.

Plan out exactly what you want to know about your customers, and what you intend to do with that insight. All too often, people start with a scattergun approach and aim to learn everything possible about a customer and their needs. That quickly takes marketers into dangerous privacy territory, and annoys customers too.

 

#5) Champion prudent, high-impact data use

Marketers collect a lot of personal data from their customers and audience – but they’re not alone. Virtually every team in the modern enterprise uses customer data in some capacity to drive their operations and make informed decisions.

As the team closest to customer data (and the origin point for a large proportion of that data), marketing has a unique opportunity to champion responsible data practices.

By demonstrating how the right data, managed and handled in the right way, can drive business value without sacrificing customer privacy, marketers can help other functions maintain compliance.

 

Mindfulness is half the battle

It’s not rocket science. As the team closest to customer data, marketers should be the first to think about the impact of how it’s used.

The good news is that when they do, everyone wins. Organisations avoid compliance breaches, their reputations remain intact, and customer trust in their brands grows.

So, next time you’re using sensitive data to make decisions or create content, think carefully about what comes next and keep privacy in the front of your mind, so your customers don’t need to.