Do the facts even matter in B2B marketing?

Almost an entire November. Without sleep. In my professional life so far, I estimate I’ve spent at least 715 hours[i] researching statistics and making sure they’re accurately presented and referenced.

But sometimes I wonder… why?

So often, I encounter B2B marketing content that doesn’t disclose its sources. Or that does, but directs me towards an unsubstantiated assertion on the personal blog of a freelance HR adviser, published circa 2013.

Even when content references recent, robust research and provides a link to the original study, I’ll regularly find that – whether through a collapse of understanding or moral fortitude – the writer has misrepresented the facts.
I’ll state it plainly. Many of the claims I see in B2B marketing content are completely unsubstantiated. Many are highly dubious. Some are demonstrably wrong.

Why we need to talk about this

Now, there are many un-nefarious reasons why including references in marketing content is far from standard practice.
Marketing content needs to be many things: eye-catching, concise, effortless to read. And it’s easy to assume that by including your sources, you’ll be compromising on any one of these important attributes.

But it’s time for marketers to interrogate that assumption.
In a period when scientists worry about generative AI “hallucinations”[ii] and model collapse muddying our common pools of knowledge, I think it’s worth questioning our industry’s readiness to publish the unsubstantiated and the distorted.

I think it’s worth questioning in the pub with my professional peers, because I believe it’s in all our interests to improve the quality of the information upon which we individually and collectively base our decisions.

And I think it’s worth questioning here, on the blog of a B2B content writing agency, because I believe this is a commercial as well as ethical concern.

I think – given my lack of faith in so much of the content I see – credibility is an area in which B2B brands have a genuine opportunity to differentiate.

Exploring the issue with a representative example

To show you what I mean, I feel I need to examine at least one real-world example.

My goal here really isn’t to point fingers. After twelve years doing this job, I know too well that getting anything written, designed, signed off, and published, regardless of how well researched and evidenced it is, should often be considered a triumph.

I also know that I myself am far from without sin. I’ve definitely used statistics I didn’t fully trust because they were central to telling a client’s story. I’m sure I’ve also quoted figures without including as much context as I could.
So, I’ll keep this example quick. And then I’ll suggest some strategies all B2B content creators might benefit from adopting, myself included.

No sources = A missed opportunity

At last year’s Content Marketing Awards, this animated content piece was a finalist in the “Best Infographic (one-time)” category.[iii] It was also honoured at last year’s Killer Content Awards in the “Short-Form Content” category.[iv]
Let’s look at its first significant claim: “Currently, there are more than 171M VR users worldwide”.

No source provided in the text. No source provided in an endnote.

As explained above, I know credibility isn’t the only target B2B marketers are striving to hit. I can easily imagine a creative professional deciding that the missing source was making this visually sophisticated piece a little too busy. That it needed, on balance, to be sacrificed for clarity and punch.
I understand the rationale.

Still, this kind of omission is a missed opportunity to make me trust your brand. To make me welcome your communications, because they inform and entertain me, and help me in my professional or personal life.

And, if I remember my early-2010s copywriting apprenticeship correctly, that’s pretty much the defining goal of content marketing. The reason why content marketing is, in the words of Joe Pulizzi, “a far cry from the interruption marketing we are bombarded with every minute of every day.”[v]

Weak, old data, inaccurately presented

I go looking for the missing source for the “171 million VR users” claim. I soon find myself clicking into multiple, SEO-sired, “X stats you must know about Y” blog posts. Here’s one.

Most of these posts append a “more than” to the 171 million figure. The ones that provide a clear source almost inevitably cite the data gathering and visualisation platform, Statista.

None that I find go as far as to link to the relevant page on Statista. So, I do some more googling, and I find this data set. It shows a suspiciously identical 171 million as the forecasted number of VR users in 2018, based on a survey conducted in 2014.

That’s right. A survey conducted eight years before this publicly garlanded infographic led with 171 million VR users as evidence of a top tech trend for 2023.

Figures that are simply wrong

The second statistic featured in the infographic is: “29BN: The amount of IoT devices that will exist next year”.

Again, I try to find the source. Again, I end up back at Statista. Its latest information, released in July 2023, quotes 29.42 billion as the forecasted figure for 2030.

Not for “next year”. But for some seven-plus years into the future from the infographic’s likely moment of creation.
(Incidentally, this is almost double the actual[vi] – not forecasted – figure Statista now provides for 2023.)

I hope that’s enough of a dissection to illustrate my point.

Maybe, in the future, I’ll have time to perform an audit of claims and referencing quality across a variety of B2B content. But for now, you’ll have to take my word for it: this is far from an isolated incident.

The wider issue (and its impact on my inner child)

I’ve seen countless infographics, white papers, ebooks, and videos in my professional life that devalue credibility (and frankly, veracity) in this way.

I’m sure some of you have, too. I’m sure you’ve thought, “Wow – that’s a surprising figure.” Then followed the trail from tertiary source to secondary source to primary source… and found yourself looking at a seemingly baseless assertion in a product manager’s LinkedIn bio.

And, if you’re anything like me, I’m sure it hurt you. Just a tiny bit. I’m sure another tiny leaf tumbled from your already ravaged tree of faith in humankind.

My own tree of faith isn’t doing so well. It’s pretty constantly shaken by news articles that fashion a sensationalist headline from an innocuous aside.[vii] By interviews in which politicians steadfastly repeat “facts” that have been carefully or unthinkingly severed from all context, allowing their meaning to instantly drip away.[viii] By reports that even peer-reviewed scientific studies aren’t as infallible as you might have hoped.[ix]

If no one else cares about the facts, why should you?

You might reasonably ask: am I really telling B2B technology brands – commercial enterprises – to hold themselves to a higher standard than many online news outlets, almost all MPs, and some scientific researchers?

Yes. I am.

Because B2B tech brands aren’t reliant on the commuter’s idle click. Or the votes of an only partially engaged population. Or the results to author a career-defining paper.

No. B2B tech brands rely on sales. Often, they rely on complex, protracted sales in which multiple stakeholders collectively make a relatively high-risk investment decision.
And in this scenario, credibility is invaluable.

Convincing the hard to convince

I wish I had a way of proving it – doubly so, considering the subject of this piece – but I believe that among the business leaders who have to approve any B2B purchasing decision, there’s almost always at least one smart, sceptical individual.

I believe they roll their eyes at contextless, too-good-to-be-true statistics in marketing materials. That they scan the endnotes on the last page of my ebook, and what they see bolsters their opinion of, and trust in, my client’s brand.

I like to think that the content they admire is the content I admire. Content that’s transparent, accurate, and authoritative while also being eye-catching, concise, and easy to read.

If you can convince that person – that sceptical critical-thinker – to advocate for your solution… why wouldn’t you?

The truth is, it isn’t an either/or

You can create content that’s both beautiful and credible. And win over that hard-to-win-over CFO. (And make me feel better about our collective moral trajectory.)

How? Here are a few ideas:

  1. Expect your copywriters to get as near to the primary source of a statistic as they can. If you’re able to dig deeper than they have, flag up your concerns.
  2. If a statistic sounds too good to be true, investigate. If the copywriter’s misrepresented the facts, ask them to double-check every statistic in the piece.
  3. If a figure sounds an order of magnitude out, check the copywriter’s maths. Most of us didn’t get into this job based on our arithmetical prowess.
  4. Be aware of “zombie” statistics that a) are so overused you’d want to think twice about citing them, and b) aren’t even true. “Humans only use 10% of their brains” is the classic example.[x] (Thanks to Matt Godfrey for this tip.)
  5. Ask your copywriter to prioritise statistics from the last 18 months. If they want to use an older figure, they should be able to explain why.
  6. Ask your copywriter to use a range of referencing methods – hyperlinked text, full in-text references, footnotes, or endnotes – to minimise the impact of your content’s sources. In a thought-leadership piece on your blog, hyperlinking the text might be the neatest solution. On a landing page, however, you might include details of a source in the body copy rather than risk people clicking or tapping away before they’ve accessed your content.
  7. Really don’t want to do any of these? Consider a disclaimer. Include a little boxout at the start of your ebook saying, “We’ve not included our sources because they detract from the reading experience. If you’d like to check our working, just email us at: [email address].” (Thanks to the wonderful Irene Triendl for this one.)

Sometimes, your copywriter will need to deviate from the path set out above in order to create the best possible content piece. Because the figures that your product narrative hinges on are, in the end, only available through Statista. Or because the most recent source for that salient data point is the 2020 US census.

That’s OK. This is about your broader stance. It’s about the standards you strive to uphold, and how they reverberate across the breadth of content you create, quietly saying things like, “Hey. We’re here to educate and inform. You can trust us. We do things properly here.”

How we do it at our agency

Respect for accuracy and authority has been hardwired into our agency’s internal processes for years.

Our reviewers (aka our writing team, wearing different metaphorical hats) are taught to check and challenge the facts and figures in their colleagues’ copy, flagging anything that looks incorrect, problematically old, or poorly referenced.

Yes, we’re human, and sometimes less-than-rock-solid claims do slip through. We’re also a business, and if a client wants to use a questionable statistic despite our reservations, we’re not going to stop them.

But the fact remains – we’ve designed our processes to help us raise the bar.

What does good referencing look like?

Here’s another finalist from last year’s CMAs, also selected for the infographic category.

  • The featured statistics have a source
  • The links (at time of writing) all work
  • The research is relatively recent

And yet, it’s still a swish-looking, partially animated content piece, right?

Sure, it rather stretches the definition of infographic, but that’s because of the amount of copy on the page, rather than the rigour of its referencing. And, to me at least, this content piece still feels somehow neater and easier on the eye than the example that abandoned its sources entirely.

A final thought: what would credibility cost you?

There are plenty of related issues we could drift into from here…

  • The credibility of customer proof points
  • The regulatory differences between B2B and B2C
  • The potential impacts of generative AI

…but you’ve been reading for a long time already. Thank you.

For now, I’ll leave you with this thought.

In B2B marketing, we know credibility is important. Along with originality, it’s one of the reasons the industry prizes primary research and proprietary data so highly. It’s also the reason why some B2B technology brands use independent services like TechValidate to gather and publish their customer outcomes.

So, why wouldn’t you aim to differentiate on credibility – and the quiet authority it imparts – in all the content you create?
Especially when, if you already have access to talented copywriters and designers, doing more than most of the competition could cost you almost nothing

[i] I’ve calculated this figure based on the time I’ve recorded for research, writing, and reviewing tasks in our project management system, ProWorkflow, since our records began. (Which is to say, I’ve excluded time spent interviewing SMEs, attending client calls and internal meetings, etc.) I’ve conservatively estimated that 8% of my research, writing, and reviewing time has been spent researching, writing, or reviewing claims and statistics.

[ii] Weise, Karen; Metz, Cade. When AI Chatbots Hallucinate. The New York Times. (May 1st, 2023. Updated May 9th, 2023.) Accessed February 20th, 2024: https://www.nytimes.com/2023/05/01/business/ai-chatbots-hallucination.html

[iii] Here’s the full list of finalists and winners. The “Best Infographic (one-time)” category is number 57: https://web.archive.org/web/20240107022130/https://contentmarketingawards.com/2023-winners/

[iv] OneAffiniti Wins National Digital Content Award. Atlanta Business Chronicle. March 8, 2023. Accessed March 5th, 2024: https://www.bizjournals.com/atlanta/press-release/detail/8209/Incentive-Solutions-Inc

[v] Pulizzi, Joe. Epic content marketing: how to tell a different story, break through the clutter, and win more customers by marketing less. McGraw-Hill Education, 2014.

[vi] I say, “actual”. In this case, as so often, Statista’s business model stands between me and closer analysis of the data by placing the full details of the research behind a paywall. Given how often I see “(Statista)” next to the figures provided in statistic-laden listicles, I can’t help feeling the company may be accidentally damaging “net truth” by making it even easier for time-and-money-poor copywriters to throw up their hands – and throw in a number they don’t understand.

[vii] If you think I need a reference to back this up, you clearly frequent higher-quality news outlets than me.

[viii] If you think I need a reference to back this up, please let me know where in the world you’re living. I’d also appreciate any advice on successfully applying for citizenship.

[ix] Bush, Evan. A once-ignored community of science sleuths now has the research community on its heels. NBC News. February 14th, 2024. Accessed February 20th, 2024: https://www.nbcnews.com/science/science-news/-ignored-community-science-sleuths-now-research-community-heels-rcna136946

[x] This old Wired article provides a quick synopsis: https://www.wired.com/2014/07/everything-you-need-to-know-about-the-10-brain-myth-explained-in-60-seconds/ (Unlike the writer, I have seen Luc Besson’s Lucy. If you want to watch a film in which someone learns to use a new part of their brain with amazing consequences, I’d recommend the 2012, late-life table tennis documentary, Ping Pong.)

Should content marketers be using AI-generated video?

Hand-on-heart what did you think of the video above? You can be honest – since it was largely produced by an algorithm, there’s zero chance of the director offering to beat you up.

The video was created using an online text-to-video platform called VideoGen. It cost about the same as ordering a pizza and the whole process, including the time spent writing the script and tinkering with the output, probably took around 45 minutes. The time it took an AI algorithm to generate the video itself was under a minute.

For the most part, it’s perfectly serviceable, no? Especially when you consider how time-consuming and expensive it can be to create video content from scratch. (The average cost of even simple content, like an explainer video, is around $5,400.) Unless you were looking for it, I think you’d be hard pushed to distinguish this from most other corporate marketing videos that combine stock imagery, ambient music, and voice over.

So, as 18% of businesses weave AI tools into their video production workflows, is AI-generated video content worth considering?

Understanding AI tools for video creation

AI is already transforming video production in the same way it’s transforming other complex processes, by automating and accelerating repetitive and time-consuming tasks. But we wanted to go a step further and look at the tools marketing teams without their own video production capabilities (like our own) can use to create full videos from scratch.

There’s a lot of variety in this market, in terms of both video style and content quality.

Some programs use prompts to generate “original” footage  (welcome to the uncanny valley, please mind the hands). Others provide digital avatars that will read your script like some sort of slightly unsettling Red Dwarf throwback.

We created our video with VideoGen, because we wanted a video that wasn’t so obviously AI-generated. (And, let’s be frank, because it was quick and cheap.) And because its own marketing hails it as “the most powerful AI video generator ever!” All VideoGen asks is that you enter a script into a text box. The AI then uses key words from your text to pull images from a stock footage library, while a computer-generated voiceover reads it aloud.

The process is more “sortamated” than automated, as it rarely gets everything right first time. As you can see from the first version of our introductory video below, you’re often met with irrelevant imagery, inappropriate music, mistimed transitions and a host of other not-quites. At one point the program insisted on putting a “like and subscribe” page for YouTube directly in the middle of the video, which felt hopeful at best – like AI’s version of *shrug* “maybe this’ll do”.

All of this means, even with one of the most basic tools around, marketers are destined to spend a fair amount of time using a software interface to fine tune their creations.

The dangers of undifferentiation

As I put various iterations of our script through the program, I began to get an odd sense of déjà vu. It quite quickly became apparent that I was being fed the same stock footage over and over – same clip, different day. Despite the service boasting a library of 500,000 videos to choose from.

This seemed far from ideal when the last thing you want your marketing to be is generic and derivative.

And that’s a problem that extends beyond stock-footage-dependent tools like VideoGen. Even if you use a tool that generates images from scratch, you’re likely to encounter a “look” that can be attributed to that particular program. Much the same way lots of people can instinctively tell when something has been written by Chat-GPT.

For me, this is a good enough reason never to use AI-generated video for customer-facing marketing content. Above all else, you want that content to be both unique and specific to your brand.

But there are some scenarios where it could save marketers time and money, with far fewer risks. Given many people find video content much easier to engage with than the written word, AI-generated videos could be a cheap and effective addition to the usual package of sales enablement collateral.

Equally, by providing a way to create rough prototypes of video content, they’re likely to help marketers better convey their ideas when briefing in their human video production teams.

Cutting edge or cutting corners?

Marketers have spent decades talking about the importance of personalised journeys and tailored content. And in recent years, the rise in data analytics has made engaging with prospects as people, not percentages, much more achievable.

In many ways, presenting your audience with AI-generated content runs counter to this trend. Yes, you could argue it creates the opportunity to cost-effectively spin up multiple videos, within a small window of time, and speak more directly to specific audience segments – or even specific individuals. But if they can tell it’s been made by AI – and they can, even when it’s been done well – how will that affect their perception of your brand? Toys “R” Us recently provided the world with a great example of how AI-generated content can backfire.

This won’t be true in every case. In some instances and industries, creating video content that shows you’re operating at the cutting edge of AI experimentation could have the opposite effect, impressing your customers and prospects and positioning you as a trailblazer. But whatever your brand and your target audience, the decision to use AI-generated video isn’t one to be taken lightly.

What you won’t get from AI-generated videos

As marketers, we strive to create moments of resonance – genuine, human reactions. Most often, this happens when we break with the long-established formula. When, instead of slotting the same old ideas together in the same old ways as everyone else, we find more surprising (and usually, more human) messages and media.

Those moments require, perhaps more than anything, a sophisticated understanding of human relationships and emotions. Something that can’t be quantified or taught, but is instead just inherently understood – by people, but not by algorithms or machines.

Talking this blog post through with my colleagues, I kept finding myself coming back to the ending of Mike Nichols’ The Graduate (1968). In the final scene of the film, Dustin Hoffman and Katherine Ross’s characters sit at the back of a bus having fled from Ross’s wedding.

There’s a pivotal moment here – what in screenwriting parlance is called a beat – that’s dragged out over several heavy seconds, as we slowly see the enormity of our characters’ actions dawn on them. You’ve probably seen it, so I won’t go on. But this moment, for me, is the perfect example of a human artist’s ability to connect with an audience by understanding the human condition – and being led by what felt right.

Nichols intuitively knew how long that wordless moment needed to be. He understood what his characters were thinking in those seconds, and how the audience would understand those thoughts, too. If you asked AI to edit that film, it would almost certainly be six seconds shorter, and 100 times worse. It would be technically correct. But at the same time, entirely wrong. It’s in this intangible space – in those insightful, empathetic six seconds – that humans will continue to show their creative superiority.

In time, I have no doubt that a healthy balance will be found between marketer and machine – one in which AI simplifies and accelerates processes and leaves more room for such human creativity to flourish. We’re already seeing the fruits of that fertile middle ground. But relying on AI to be creative on your behalf will always feel like cutting corners to me. And when its source material is solely things people have created in the past, you’re removing any hope for originality.

For now then, we should continue to put people in charge of talking to people. And only allow technology to lend a hand.