Human vs AI-Generated Content: Why the Difference Still Matters in B2B Marketing

Almost every week, someone, somewhere asks a version of the same question:

“Is AI now good enough to replace human marketers?”

Let’s face it. AI is everywhere. It writes emails, outlines white papers, suggests headlines, and produces content at a speed that would have been unthinkable just a few years ago.

But while the technology has changed fast, the fundamentals of effective B2B marketing haven’t. And that’s why the difference between human- and AI-generated content still matters, perhaps more than ever.

So, to answer the question….

Yes, AI is good enough and genuinely useful… for some things

There’s no question that AI has earned its place in modern marketing teams.

That’s largely because AI is phenomenal at accelerating workflows. It can summarise complex documents in seconds, create a long report and present it in multiple formats, or generate a serviceable first draft when you’re floundering in search of a place to start. For stretched marketing and creative teams under constant pressure to produce more with fewer resources, an AI-supported boost matters a great deal.

AI is also generally very good at handling structure. Tables, comparisons, objectively neutral rewrites and other tone adjustments are all things AI can do quickly and consistently. Used well, it helps to reduce friction in the marketing process by taking care of the more tedious, mundane tasks, which frees humans to focus on higher‑value, and often more creative, work.

Where the AI cracks start to show

The problems begin when AI is asked to do more than process information.

In real-world B2B projects, AI-generated content often *sounds* confident while actually being quietly wrong. Facts are slightly off kilter. Claims are so broad they start feeling less believable. Bold statements feel plausible but don’t quite stand up to scrutiny, especially in specialist markets like engineering, electronics, or industrial technology.

And probably, most important, AI lacks judgement. You must remember that AI is only repeating what someone wrote about something, somewhere, one day. It did not rationally and objectively arrive at its reply to your query, but it can almost make you feel as though it did.

Importantly to marketers, AI doesn’t know which detail will trigger a buyer’s scepticism, which insight might be commercially sensitive, or which message simply won’t have enough runway to land with a technical audience. AI can’t read the room. It doesn’t understand internal politics, competitive nuance, or strategic intent.

And AI doesn’t originate insight. It simply recombines what already exists. It’s efficient, yes, but it’s certainly not original.

The growing credibility issue

One of the biggest risks we see emerging from irresponsible or inexperienced use of AI is damage to credibility.

Journalists and potential product customers are being inundated with near-identical blogs, articles, and white papers. The wording changes slightly, but the structure, arguments, and conclusions have a ring of familiarity, and not in a good way. You feel as though you are being told the same thing, just in a slightly different way, whether it’s for airline tickets or bedroom slippers. In some cases, it’s patently obvious that the company name has simply been dropped into an AI-generated template and set to “spin”.

In B2B, trust underpins long and complex buying cycles, so vague familiarity that leads to loss of credibility is dangerous. When content feels generic, the brands they represent feel generic, too. And once you lose credibility, you’ve just created a credibility deficit that’s very hard to recover.

All of this is to say that human-written content has something AI can’t replicate: experience, opinion, and accountability. It shows that someone has thought deeply about the problem, formulated an informed position, and is prepared to stand behind it. The only thing AI will stand behind is itself. It is designed for self-preservation.

This isn’t humans versus machines

The biggest mistake most business professionals make is framing this debate as an either-or choice. It’s not us vs them.

The most effective B2B marketing today comes from a combined approach. Humans provide direction, strategy, and judgement about what matters, what’s risky, and what’s worth saying. AI accelerates the execution, handles the initial research, lays the groundwork, and explores the options, all of which helps to diminish unnecessary and often repetitive effort to reach the designation. AI can virtually take 50 different roads in an instant and signpost which one is likely to be best suited for you to reach your marketing campaign destination. You, then, only have to take one journey (OK, maybe two).

What we’ve found in real-world experience and conversations with global peers, especially in recent years, is that the marketers who perform best are those who understand their market deeply and can use that knowledge to brief an AI model, challenge its output, and refine its wording. The value is no longer a case of cranking out words, it’s in crafting and shaping them.

And if we get that balance right, AI won’t replace marketers. It will make the good ones more valuable than ever.

Want to learn more about Humans Vs AI? Catch up on our on-demand webinar:

https://www.napierb2b.com/2026/01/human-vs-ai-machine/

 

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by David Cunningham

Using Google Ads to Generate Qualified Leads in Electronics Manufacturing

For many electronics manufacturers, Google Ads can feel like a double‑edged sword. On one hand, it promises visibility in front of engineers and procurement teams actively searching for solutions. On the other, it often delivers a flood of enquiries from students, hobbyists, or organisations that sales teams ignore because they were never a target market to begin with.

B2B marketers such as those at Napier who are working in technical and industrial markets have seen this pattern play out many times. The issue isn’t that Google Ads “doesn’t work” for electronics manufacturing, it’s that it’s frequently conceived and deployed with the wrong strategy, i.e., a focus on technical intent rather than raw traffic. Google Ads can be a powerful driver of qualified leads, but only if the message, campaign, and deployment are clearly thought out across a range of relevant criteria.

Why Google Ads Struggles in Electronics Manufacturing

Electronics manufacturing is different from e‑commerce or SaaS. Buying cycles tend to be lengthy, purchasing decisions often involve multiple stakeholders, and the products themselves can be puzzling to the non-indoctrinated. Yet many Google Ads campaigns in this space are set up using generic lead‑generation playbooks.

The biggest problem for Google Ads in electronics manufacturing is keyword strategy. Broad, high‑volume keywords might make a report look good, but they too often capture research‑driven searches rather than the genuine buyer intent the client is after. The fundamental problem is that so many agencies use search terms relating to “how‑to projects” or general learning offers that attract students and specialist hobbyists rather than engineers looking for a multi-million manufacturing partner.

Another issue is a lack of filtering. If you don’t take the time to ensure you have a robust negative keyword list, coupled with audience exclusions, your campaign will pay for clicks that were never going to result in revenue. The marketing department will celebrate the number of leads, but sales will grumble that most of those “leads” are useless wastes of time and money.

It is also important to point out that conversion strategy is often misaligned. Optimising a campaign for form fills, downloads, or generic enquiries might boost the raw number of MQLs but bear little or no resemblance to what ignites genuine buying conversations in electronics manufacturing. Sales teams don’t close deals from whitepaper downloads. They close them from RFQs and technical discussions.

What High‑Performing Campaigns Do Differently

Napier’s Digital Team has consistently seen that successful Google Ads campaigns are based on intent, not volume. An engineer researching product specifications is very different from a buyer searching for a contract manufacturer or a custom PCB assembly partner. It’s therefore important that ads, keywords, and landing pages reflect those distinctions.

Filtering is equally important. Negative keyword management keeps campaigns focused and prevents wasting money on irrelevant search results. Over time, careful keyword management alone can dramatically improve lead quality.

Conversion actions also matter. High‑performing campaigns prioritise actions that signal real commercial interest, such as “Request a Quote”, “Speak to an Engineer”, or “Discuss Your Application”.

Most importantly, performance must be measured in a way that reflects reality. Cost per click and cost per lead are useful diagnostic tools, but they don’t tell the whole story. Mature B2B campaigns must focus on producing sales‑qualified leads, RFQ volume, and pipeline contribution. These are the metrics the sales team really cares about.

Can a Google Ads Agency Help?

An agency that specialises in Google Ads can absolutely help increase qualified leads for an electronics manufacturing company, but only if it understands technical B2B markets. The right partner doesn’t just manage bids and budgets; it invests considerable time in gaining a deep understanding of its clients’ products, applications, and buying process.

When evaluating an agency, look beyond promises of cheaper clicks or more leads. Ask, for example, how they differentiate engineer searches from student searches. Ask how they define a “qualified lead” and whether that definition aligns with what your sales team has been telling you it needs.

Final Thoughts

At Napier, the measure of success for a Google Ads campaign isn’t about generating more traffic, it’s about attracting the right traffic, i.e., from the right engineers, at the right companies, at the right time. If a strategy is based on technical intent and sales alignment, Google Ads can transition from being a source of friction and frustration to a reliable contributor to real sales growth.

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by David Cunningham

Beyond 'Maximise Conversions': Navigating Google Ads Bidding and Targeting in B2B Tech

Google Ads strategy for B2B tech: A specialist guide for engineering marketers

In the specialized world of B2B technology, PPC specialists know all too well that Google's automated bidding strategies can often lead to wasted budget and a flood of low-quality leads. At Napier, we’ve seen this challenge firsthand across engineering and deep-tech campaigns. This guide is designed for those in the engineering sector who want to move past the one-size-fits-all 'maximize conversions' approach and master advanced techniques tailored for niche audiences. The focus here is on elevating your Google Ads strategy for B2B tech, ensuring you reach the right professional buyers.

Here, you'll discover how to combine audience layering with value-based bidding, ensuring your campaigns attract genuine buyers, not just hobbyists. With expert advice addressing complex queries, this resource aims to deepen trust and improve your brand's discoverability across AI platforms. Whether you're refining your lead generation or seeking actionable tips to boost campaign performance, this blog is your go-to for elevating your Google Ads strategy in the B2B tech landscape.

Why 'maximize conversions' attracts the wrong leads

At its core, the 'Maximize Conversions' algorithm is built to chase the highest number of conversions, regardless of their actual value to your business. For niche B2B tech marketers, this creates a fundamental mismatch: while you’re seeking high-value buyers with specific roles, Google’s bidding strategy is simply optimizing for volume. In our experience managing B2B engineering campaigns, this results in a disproportionate number of students, hobbyists, and other non-qualified leads, diverting precious budget away from genuine prospects.

What is 'maximize conversions' actually optimizing for?

The algorithm’s sole focus is on conversion quantity, not quality. It will always seek the easiest path to a conversion, which often means targeting audiences who are most likely to take action—even if they’re not your ideal buyer. In the B2B engineering space, this frequently results in non-buyer personas, such as students downloading whitepapers or hobbyists signing up for demos, dominating your lead pool.

The 'hobbyist vs. buyer' scenario in engineering software

Consider a typical search for “FEA software”: it could be initiated by a Director of Engineering with a substantial budget, or by an undergraduate student working on a coursework project. Because 'Maximize Conversions' cannot distinguish between these user intents, it will often favor audiences that deliver higher conversion volumes, skewing results towards student traffic rather than genuine buyers. This demonstrates how the algorithm’s priorities diverge from B2B marketing objectives and the specific needs of engineering software vendors.

You're training the algorithm with junk data

By allowing the algorithm to optimize for low-quality leads, you inadvertently create a feedback loop. Each conversion from a non-qualified lead reinforces the algorithm’s behavior, further degrading the quality of your marketing-qualified leads (MQLs) over time. The first step in breaking this cycle is to acknowledge that a different, more targeted approach is essential for success in niche B2B tech campaigns.

Layering audiences to pinpoint buyers in your Google Ads strategy for B2B tech

To tackle the challenge of attracting only genuinely qualified leads, this section offers a practical framework for Google Ads audience layering. By strategically combining targeting signals, you can exclude irrelevant users and focus your spend on those most likely to be professional buyers—such as senior engineers. The approach hinges on blending intent, demographics, and exclusions to create a refined audience profile, ensuring your ads reach the right people.

How can you target specific job roles like engineers on Google Ads?

While you can't directly target job titles on Google Ads, you can construct an effective proxy by layering targeting signals. This is the central principle of the framework, enabling you to isolate likely buyers based on their online behavior and characteristics, such as search history and engagement with industry content.

The audience layering framework

• Layer 1 – High-Intent Keywords: Start by selecting precise, long-tail keywords that signal commercial intent. For example, targeting phrases like “enterprise CFD software pricing” ensures you reach users actively researching business solutions, rather than generic searchers asking, “What is CFD?”
• Layer 2 – Custom Intent Audiences: Build audiences from users who frequently visit competitor websites, read industry publications, or engage with regulatory bodies. This indicates genuine professional interest and narrows the audience to those involved in your field.
• Layer 3 – Demographic & Company Attributes: Incorporate company size and industry data where possible. Use demographic filters—such as age and household income—to exclude typical student profiles, thereby focusing on likely professionals. Negative targeting further refines your audience, reducing wasted spend on non-buyers.

By layering these signals, you build a composite audience that mirrors your ideal customer profile. This strategic approach answers the core question: you can’t target engineers by job title directly, but with smart audience layering, you can zero in on the people most likely to be professional buyers, maximizing the quality of your leads and the effectiveness of your Google Ads campaigns.

Build your first high-value audience layer

While Google Ads does not enable you to directly target individuals who have visited a competitor’s website, its audience tools allow you to reach users with similar online behaviors and interests. This approach is not about pinpointing specific site visitors, but rather about identifying broader traits common among your target professional audience, such as engagement with technical forums or industry news.

To enhance your targeting and exclude less relevant users, a practical strategy is to set age filters, such as excluding those aged 18–24 and users with unknown ages, as these segments are often associated with students who are unlikely to be qualified buyers. Additionally, refining your audience by excluding interest categories like ‘education’ can help filter out students and academics, while including categories linked to specific professional activities, which increases the likelihood of reaching individuals who are active in the workforce and more likely to be more senior decision-makers. By layering these exclusions and inclusions, you create a more focused and valuable audience for your campaigns.

How to use value-based bidding for B2B tech

Once you have established a high-value audience through careful targeting, the next step is to let Google know that these users are more valuable to your business. This is achieved by implementing value-based bidding (VBB), a strategy that allows you to assign different monetary values to various conversion actions or audience segments—even in cases where there is no direct e-commerce transaction. By using value rules and target ROAS (tROAS), you can effectively communicate to Google’s algorithm which leads are most important, ensuring that your bidding prioritizes those conversions that have the greatest potential impact on your business. This approach bridges the gap between your targeting strategy and your bidding strategy, maximizing efficiency and lead quality for B2B tech campaigns.

How does VBB work for lead generation?

VBB empowers advertisers to assign unique values to different types of conversions or audiences. This means you can inform Google’s algorithm which leads are worth more to you, even if you don’t have a checkout process. By doing so, you guide the system to focus its efforts and budget on the conversions that matter most to your business objectives.

Introducing conversion value rules

Conversion value rules are the practical tool that enable this strategy. They enable you to apply a multiplier to your base conversion value for specific audiences. For instance, you can increase the value of conversions from your target audience, ensuring Google’s bidding algorithm recognizes their higher importance and thus allocates your spend accordingly.

An example of assigning value

If your standard ‘whitepaper download’ carries a value of £50, you can set a rule whereby conversions from your ‘target buyer’ audience are multiplied by three, raising their value to £150. This enhanced value provides Google’s algorithm with a clear quality signal, encouraging it to focus on the prospects most likely to have value to your business.

Calculate your base lead value

To get started, use this simple formula: (Average Contract Value × Sales Close Rate) = High-Quality Lead Value. This calculation helps you assign an appropriate base value to your leads, ensuring your bidding strategy is grounded in real business outcomes.

Common Pitfalls and Future Outlook

Managing advanced value-based bidding strategies requires careful attention to detail and a forward-thinking approach. There are several common mistakes that advertisers make, and understanding these pitfalls is crucial for maximizing success. For example, applying value rules without sufficient conversion data can lead to unpredictable results, as smart bidding algorithms rely on a steady stream of data to operate effectively.

Mistake #1: Applying value rules with low conversion volume

Smart bidding needs data. If your campaign gets fewer than 30 conversions per month, applying tROAS with value rules can be volatile.

Start with enhanced CPC, gather data, then graduate to target CPA, and finally implement tROAS with value rules once you have a stable conversion history.

Mistake #2: Ignoring performance max campaigns

These principles are even more critical for PMax. Use your high-value audience lists as 'Audience Signals' and implement Offline Conversion Imports with value to give the PMax algorithm the data it needs to find the right engineers.

First-party data is your competitive advantage

As cookies deprecate, your ability to feed Google's AI with high-quality, offline data from your CRM will be the single biggest factor in successful B2B advertising. The framework outlined in this guide is the foundation for that future.

Key Takeaways

Audience Layering: Build composite audiences using intent, demographics, and exclusions to target professional buyers.

Value-Based Bidding: Assign higher values to conversions from desirable leads to guide Google's algorithm.

Avoid Low-Volume Pitfalls: Ensure sufficient conversion data before applying advanced bidding strategies.

Leverage First-Party Data: Use CRM and offline data to improve targeting and campaign performance.

Continuous Optimization: Monitor and refine your Google Ads strategy for B2B tech to maintain lead quality.

Conclusion

To achieve higher-quality leads and maximize ROI, B2B technology marketers should implement a Google Ads strategy for B2B tech that combines audience layering with value-based bidding and first-party data. This approach ensures campaigns are future-proofed and focused on meaningful business outcomes.

FAQ

What is the most effective way to optimize Google Ads for B2B tech lead quality?

The most effective method is to combine audience layering with value-based bidding, ensuring your campaigns target professional buyers and assign higher value to desirable leads using conversion value rules.

Where can I find tools and resources to implement Google Ads strategy for B2B tech?

Resources such as Google Ads Help Center, Napier’s B2B marketing guides, and industry forums provide frameworks and step-by-step instructions for setting up advanced audience targeting and value-based bidding.

How can I start implementing value-based bidding for my B2B tech campaigns?

Begin by calculating your high-quality lead value, then use Google’s value rules and tROAS features to assign higher values to conversions from your ideal audience. Monitor results and adjust as your data grows.

How does Google Ads strategy for B2B tech compare to traditional B2C strategies?

B2B tech strategies focus on layered audience targeting, lead quality, and value-based bidding, while B2C often prioritizes conversion volume and broader targeting. This makes B2B approaches more specialized and data-driven for niche audiences.

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by David Cunningham

Why is Traditional Lead Generation Failing B2B Tech Companies?

The long-standing tradition of wide-net marketing is increasingly ineffective for B2B technology firms. Why? Because the traditional market they are often chasing is not as easy to identify as it once was. Therefore, using traditional strategies to try to reach them often result in unsustainably high costs to generate a large number of low-quality leads that rarely match the high-value opportunities that sales teams want. This wastes the sales team’s time, which costs money, and quite a bit of it.

A disconnect between marketing, which typically focusses on marketing qualified leads (MQLs), and sales, who typically prioritise sales qualified leads (SQLs), is often a source of friction. When marketing delivers a high volume of seemingly unfocussed leads and sales teams spend valuable time working through unsuitable prospects, it erodes alignment, diminishes efficiency and, overall, makes everyone grumpy.

Ultimately, these shortcomings are why traditional lead generation methods are short-circuiting what modern B2B technology marketing and sales needs to propel a business forward.

Can account-based marketing improve lead generation for B2B tech companies?

Account-based marketing (ABM) is a targeted growth approach designed to address the shortcomings of traditional B2B lead generation. Instead of a net cast wide, ABM focuses marketing and sales resources on a select group of high-value target accounts. The process of identifying those targets is consistent and straightforward. First, you simply identify the most valuable accounts; you then engage them with highly tailored marketing and sales initiatives; and once landed, you expand and deepen the relationship from the inside to identify and explore additional opportunities within those accounts.

The ABM approach, done right, has many advantages, for example:

Personalised outreach ensures that messaging resonates with the specific needs and priorities of each target. This makes your approach more meaningful and “sticky”.

Focusing on accounts that are most likely to benefit from your solutions increases the likelihood that leads will progress through the conversion funnel and ultimately convert.

Resources are allocated to target only the most promising prospects, thus greatly reducing the amount of money squandered on low-quality leads.

Because effective ABM demands close collaboration between sales and marketing, it ensure that both teams are working towards the same high-value opportunities. This has the additional benefits of reducing internal friction and enabling both parties to jointly celebrate successes.

Overall, by shifting the focus from quantity to quality, those who adopt the ABM approach deliver more relevant leads, shorten sales cycles, and ensure that marketing and sales are working in harmony.

What does a successful ABM campaign look like?

A successful ABM campaign looks a lot like ABB Electrification’s collaboration with Napier.

To boost awareness and generate demand for its products and expertise within the food and beverage (F&B) sector, existing Napier client, ABB Electrification, leveraged the expertise of F&B specialists to create a series of eBooks that were distributed using popular, interactive Turtl documents. This ensured that the content was both relevant and engaging for the specific audience at which it was aimed.

The campaign involved strategically gating the eBook content behind Salesforce Marketing Cloud Account Engagement (formerly Pardot) landing page forms, with a robust, lead-nurturing flow to follow up. Carefully selected paid LinkedIn and Google Ads campaigns drove traffic to these landing pages, with LinkedIn’s one-to-many ABM targeting individuals based on firmographic and demographic criteria to maximise relevance and impact.

The campaign’s results exceeded expectations. it achieved more than 60 million impressions across LinkedIn, Bing, and Google, garnered 1.4 million views on the campaign’s Pardot landing page, and generated more than 2,700 high-quality leads. This is a clear demonstration (to all parties) how combining personalised content with precise targeting and close sales-marketing coordination delivers outstanding outcomes.

How do you implement an ABM strategy for lead generation?

Fundamentally, an ABM strategy requires a structured, step-by-step approach that ensures your efforts are focused on attracting and engaging high-value prospects. Following is an actionable guide to help you launch an ABM programme for your business.

Start by bringing your sales and marketing teams together to set shared objectives and clearly define your Ideal Customer Profile (ICP). This alignment at the very beginning is crucial for identifying and pursuing the right opportunities, and for ensuring that both teams are working in unison toward common goals.

Utilise the ICP you’ve just created to list companies that are most likely to offer the highest potential value. This approach shifts the focus from quantity to quality by prioritising the accounts most likely to convert and deliver long-term business value.

Identify and implement the essential technology tools you’ll need, such as customer relationship management (CRM) platforms, marketing automation systems, and intent data solutions. These tools are designed to help you manage campaigns efficiently and track engagement throughout the buyer’s journey.

Be sure to carefully craft tailored content with messaging that directly addresses the unique challenges and objectives of your target account. Personalisation has been well documented to increases relevance, foster deeper engagement, and help your brand stand out.

Once you’ve launched your ABM campaign, carefully monitor key metrics such as account engagement, pipeline velocity, and deal size. By regularly analysing performance data, you can refine your strategy and demonstrate the positive, tangible impact that your ABM efforts have on the business.

The overall aim is to firmly establish a strong foundation for ABM-driven lead generation. You achieve this by ensuring your sales and marketing resources are concentrated on best-fit prospects, which maximises the return on your marketing investment.

What are the common mistakes to avoid in B2B tech ABM?

B2B tech companies need to avoid a few common errors that many embarking on the ABM journey will make. This will enable you to establish and maintain a more effective and sustainable ABM strategy.

Always remember that ABM is not a quick fix. To be effective, it must be a long-term, strategic approach designed to grow deep and meaningful relationships that drive positive business outcomes for all parties. If you see ABM as a one-off campaign, it undermines its effectiveness and limits your results, often to the point of not being worthwhile, which you don’t want to have to explain to the boss. Success requires ongoing collaboration between sales and marketing, regular analysis and refinement of target accounts, and persistent yet unobtrusive engagement.
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On a personal note:

Dear Jane. I’m writing to tell you that simply addressing contacts by name is not enough. ABM demands genuinely bespoke messaging, using content that speaks to the specific opportunities, challenges, goals, and context of each specific account. Without this degree of personalisation, you will sound superficial and miss opportunities.

So, Jane, I am delighted to hear that your daughter graduated with honours. I’m sure she’ll follow in your footsteps as a vital member of her professional community. Speaking of professional communities, are you aware of the webinar we are hosting on personalisation….
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Many companies focus ABM efforts solely on new business acquisition. That’s a mistake. ABM is for that of course, but it is equally vital for growing revenue within existing customer accounts. By ignoring post-sale opportunities, you risk losing out on the potential for upselling, cross-selling, and strengthening customer loyalty. ABM is multi-faceted, not a one-trick pony.

There’s nothing wrong with tracking your success (or lack thereof), but use the right ones, in the right way. Contrary to popular belief, vanity metrics such as email opens or click rates do not reflect the real impact of ABM. In fact, they can give you a false sense of success that will not be reflected in bottom-line results, potentially making you look a bit foolish at best, or an unacceptable drain on resources at worst. What you must do instead is measure real-world business-impact metrics like pipeline generation, deal size, demonstrable levels of account engagement, and customer lifetime value. These indicators provide a far more honest and crystal-clear picture of programme effectiveness and ROI than any number of often irrelevant clicks.

Don’t let your ABM campaign fall victim to tradition. Campaign the modern way, by inviting to the dance the ones that invited you to theirs.

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by David Cunningham