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Tip: Increase conversions by addressing hesitations in your CTAs

Source: Growth Bites

Building trust takes time. But if people are hesitant to click your CTAs, a few simple words can often ease their minds. Boost conversions by addressing concerns in the button text.

Before (and probably after) you build trust with people, they will have some hesitations. You can easily address these hesitations with slight modifications to your CTAs. Start by finding out what objections people have to a specific action you'd like them to take. You can do this by asking, surveying, or making educated guesses and testing them. Then change the text in your CTA to account for it. Here are a few examples, courtesy of the venerable Harry Dry of Marketing Examples. If they're worried about the cost, "Get started" becomes "Get started for just $X". If they're worried about adding a credit card, "Start free!" becomes "Start free! No CC required." If they're worried that filling out a survey will take too long, be explicit about how long it takes or call it a "quick survey" (if it's actually quick). Super simple, but it can help to assuage any initial fears. You can also do this in more detail in your FAQs.

AI Is Winning the Office. The Talent Isn’t Seeing the Payoff Yet.

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You’d think by now the paychecks would reflect it.

Millions of professionals use ChatGPT daily. Companies are rolling out in-house models. Training programs are everywhere. On paper, this should be a productivity gold rush.

But a new study shows the opposite: salaries haven’t moved. Work hours? Unchanged. In Denmark, one of the most digitized labor markets in the world, AI adoption skyrocketed—and the economic indicators didn’t flinch.

The research, based on 25,000 workers and 7,000 workplaces, looked at 11 occupations directly impacted by AI chatbots. The conclusion? Large language models are reshaping workflows, but not outcomes. Not yet.

So what’s actually happening? Why are so many people using AI tools, while the payoff feels MIA?

Let’s break it down.

What the Research Found: Massive Adoption, Minimal Payoff

Denmark turned out to be the perfect test lab for AI at work.
The country has a highly digitized workforce, great data infrastructure, and a culture of early tech adoption. Researchers tracked 25,000 employees across 7,000 workplaces in 11 job types—from HR and legal to software devs, teachers, and customer support.

They found what we all suspected: AI is everywhere.

47% of workers were already using AI chatbots like ChatGPT on their own. When employers stepped in—through training or encouragement—adoption jumped to 83%. A full 38% of companies built their own in-house LLMs (often based on OpenAI’s models), and 30% offered formal training. Adoption was highest in journalism, marketing, and IT; lower in fields like teaching or law.

So the tools are here. But the productivity boost? Surprisingly small.

On average, workers saved just 2.8% of their total work hours using chatbots. And most didn’t use that time for breaks—they simply shifted to other tasks. Even so, 8.4% of workers reported that AI tools led to entirely new job tasks, and the effect was even stronger in companies that encouraged adoption. The benefits—like improved quality, faster drafts, and more creativity—were 10–40% stronger in workplaces that invested in AI training and support.

But here’s the kicker. None of this showed up in paychecks or work hours.

Using matched employer-employee data, the study found zero effect on wages, hours, or employment levels—across all 11 occupations. Not even in firms actively pushing adoption. The best estimate? Just 3–7% of productivity gains are passed through to earnings. The rest gets absorbed into the system, unnoticed.

All hype, no raise. At least for now.

Why Isn’t the Talent Seeing the Payoff? Find out below

AI tools are replacing product teams (and changing who gets to build)

Source: Ben’s Bites

Building used to mean coordinating across teams — design, dev, PM, maybe even no-code help. Today? You can go from idea to working product in a browser tab. The solo builder is no longer the exception — it’s becoming the norm.

Let’s break it down:

1. Product Teams No Longer Wait on Design
Static designs used to slow down validation.

Now anyone on the team — not just designers — can spin up real prototypes instantly using tools like Lovable. That means more ideas get tested faster, and fewer sit in Figma purgatory waiting for dev attention.

2. Founders Are Shipping Without Engineers
AI tools now let solo founders build MVPs and test them without touching a line of code.

Speed matters — but so does the mindset shift: fast shipping means fast failure, which unlocks faster learning.

3. Marketers Are Building Pages, Not Just Briefs
Campaign landing pages used to take days. Now marketers prompt their way to finished funnels.

No more dev handoffs or waiting for updates — just describe the goal, launch, test, and tweak.

4. Internal Tools Are Getting AI-Built
Instead of duct-taping SaaS tools, teams are creating exactly what they need — fast and free.

Custom dashboards, approval flows, and admin panels are now a prompt away.

5. Agencies Are Moving at SaaS Speed
Agencies like Stupid Simple Apps are building 5–10 MVPs/month.
Their edge? Taste + speed. With fewer people and more iterations, they’re helping clients validate ideas faster than internal teams ever could.

The bottom line

AI has made building easy. What separates teams now is how fast they can test, learn, and ship.

The ones who know what to build — and get there quicker — will leave the rest behind.

Thank you for reading! ✌️

We look forward to sharing more with you next week. Stay tuned!

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