Editorial: Main Streetʼs Real Labor Problem Isnʼt Jobs, Itʼs Readiness
Ignore the headline tug-of-war over whether the economy is hot or cooling. On Main Street, the lived reality is simpler and more stubborn. Jobs are open, skills are scarce, and patience is wearing thin. In October, a third of small business owners reported they couldnʼt fill posted roles. Hiring intent ticked down. Wages ticked up. And still, too few candidates can do the work that actually needs doing.
This is not a pricing problem; itʼs a pipeline problem. Owners arenʼt refusing to pay. What they canʼt buy off the shelf is job readiness: the ability to show up, learn fast, and produce to a standard. Every unfilled shift is a missed order, a slower project, a customer you may not see again. We should stop waiting for a perfect applicant market that isnʼt coming back. The post-pandemic labor world has settled into a new equilibrium that rewards companies that build talent, not just bid for it.
The fix is unglamorous but decisive. Strip job descriptions to the 3-5 skills that matter. Replace laundry lists with 30-day ramp plans and 60-day skill checks. Recruit from overlooked pools like trade schools and veterans. Pay for persistence, not just arrival. Shift dollars from signing bonuses to 90-day milestones and stackable skill raises. And treat scheduling flexibility as a competitive weapon.
None of this absolves policymakers of their role. Local leaders can accelerate short-course credentials aligned with employer needs, streamline apprenticeships, and broker hiring compacts that turn training into jobs on a deadline. But the fastest relief is in the ownerʼs control. Redesign the hiring funnel for speed and coachability, then measure where candidates stall and fix that choke point next.
Main Street doesnʼt need perfect candidates. It needs a system that makes good ones reliably, repeatedly, and fast.
Case Study: How CMOs Are Turning AI Into a Revenue Engine
For chief marketing officers, 2025 has become the year of creative reinvention. Faced with slower growth, rising ad costs, and leaner teams, CMOs are operationalizing AI. Across industries, marketing leaders are using generative models to compress decision cycles, lower costs, and sharpen strategy.
At New York–based Black Glass, founder Katie Klumper sees the shift firsthand. Her clients use AI to benchmark spending, generate new creative, and personalize outreach with the precision that once required full research departments.
Hereʼs how leading CMOs are making it work in practice:
Track the market in real time. Guild CMO Rebecca Biestman uses AI to analyze competitor strategy and investor reports, helping her 70-person team understand where rivals are spending and what messages are resonating.
Run virtual focus groups. At ETS Global, Michelle Froah creates AI personas to test product ideas and iterate faster, replacing lengthy human panels with simulations that deliver feedback in hours.
Accelerate thought leadership. London startup Swap cut editorial production time in half. Its CMO Juan Pellerano-Rendón uses AI for research and drafting, allowing his lean 10-person team to publish two to three data-driven articles monthly.
Design smarter workflows. Former Warner Music and HBO executive Maria Weaver feeds her task lists into AI each morning to optimize her day, while Inovalon CMO Nick Panayi assigns specialized LLMs to keep projects moving.
Build community knowledge. Zola CMO Briana Severson hosts an internal Slack channel and monthly “AI show-and-tell,ˮ letting her team share discoveries. Even her own voice-typed notes become polished strategy decks within minutes through Gemini.
Stay cost-conscious. Early-stage founders like Kendra Newton of WVN rotate through free AI tool trials with clear deliverables, maximizing results before committing to paid plans.
What unites these examples is intent. By codifying “AI sherpasˮ inside their teams, partnering with CIOs to build secure workflows, and sharing proven playbooks across departments, CMOs are treating generative AI as infrastructure.
Play of the Week: Use Hyperlocal Influencers for Low-Cost, High-Trust Growth
When neighbors need a nail salon, handyman, or aesthetician, they donʼt ask celebrities; they check Reddit, Nextdoor, Yelp, or local Facebook groups. Thatʼs why “influencer-next-doorˮ partnerships are working for small, service-based businesses. Theyʼre cheap, credible, and close to the point of need.
Source where locals hang - Search neighborhood subreddits, Nextdoor threads, Yelp Elite, and community FB groups for people who already review and answer questions.
Start small and specific - Offer $100–$250 per post for 1–2 clear actions like a try-and-review plus 3-5 authentic replies that point prospects to your booking link.
Give a tight brief - Share the experience to try, key facts (hours, pricing, neighborhoods served), what to avoid (claims, private data), and how to handle comments.
Tag and track - Use UTMs/unique codes and a simple sheet to log post URLs, leads, and bookings so you can double down on the creators and forums that convert.
Make it feel native - Prioritize “reviews, recommendations, ratings,ˮ and Q&A replies over glossy ads. These channels reward helpful, conversational posts.
Stay compliant - Require “ad/partnerˮ disclosures and never condition payment on a positive sentiment. Follow each platformʼs rules.
Run sprints - Test 3-5 creators over 4 weeks, compare cost-per-inquiry, and expand only the top performers.
Treat this as word-of-mouth at scale. With a shared playbook and light guardrails, hyperlocal creators turn community trust into steady inbound for small businesses.
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Closing Note
Whether itʼs labor, marketing, or community growth, this weekʼs stories share one lesson that advantage belongs to operators who build capability.
The best owners arenʼt waiting for perfect hires, perfect data, or perfect reach. Theyʼre tightening the loop between learning and doing by training talent on the floor, codifying AI use inside teams, and turning neighbors into advocates.
Progress isnʼt coming from grand reinvention but from systems that make good decisions repeatable. Momentum compounds when you stop waiting for scale and start building it.
See you next week.
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