AI Removes Marketing Barriers in Supply Chains

In Salem, Massachusetts, October isn’t “busy season.” It’s a stress test. Picture more than a million visitors flowing into a historic town with about 3,000 parking spots. You can’t “brand” your way out of that constraint. You have to change behavior—fast, at scale, and without annoying people.

That’s why I keep coming back to a destination marketing lesson that applies surprisingly well to the AI in Supply Chain & Procurement conversation: marketing’s real job is removing barriers. In supply chains, we say “remove friction” and mean vendor onboarding, forecasting errors, late shipments, and compliance bottlenecks. In marketing, it’s the same pattern—just aimed at attention, trust, and conversion.

The real shift in 2025 is that AI-powered technology and digital services in the United States are making barrier removal practical at scale. Not theoretical. Practical. The teams winning right now aren’t the ones posting the most. They’re the ones using AI to locate the tiny points of friction that quietly kill pipeline—and fixing them before they spread.

“Remember us?” is owned media done right (and AI makes it easier)

A simple truth: algorithms are rented land. Your email list, customer community, and CRM audiences are assets you can actually control.

Ashley Judge, the executive director behind Destination Salem, describes a mindset I agree with: you’re not sending “announcements,” you’re sending a human nudge—“Hi, remember us?” That framing is gold because it avoids the biggest owned-media mistake: turning every email into a billboard.

Here’s where AI changes the game for U.S. SaaS and digital services teams: it helps you be consistent without sounding robotic.

What AI should do in owned media (and what it shouldn’t)

AI should reduce production friction, not replace your point of view.

Use AI for:

• Audience clustering from CRM and product signals (industry, account tier, feature adoption, renewal window)
• Subject line and preview text variants based on past engagement
• Content repurposing (turn one webinar into 5 emails, 8 social posts, and 1 landing page)
• Send-time optimization and frequency controls to prevent list fatigue

Avoid using AI for:

• Generic “big news!” messaging that sounds like every other vendor
• Making up customer stories, quotes, or results
• Over-personalization that feels creepy (“we saw you hovered on pricing at 2:07 AM”)

Snippet-worthy rule: If a message would feel weird as a text to a friend, it’ll feel weird in an inbox.

Why this belongs in a supply chain & procurement series

Owned media isn’t just a marketing channel. In procurement-heavy markets, it’s how you reduce risk.

If you sell supply chain software, your buyer is already managing:

• supplier disruptions
• compliance requirements
• forecast volatility
• internal stakeholders who don’t agree

A steady owned-media cadence—helpful updates, practical templates, short explainers—acts like a trust-building mechanism that shortens the vendor evaluation cycle. AI helps you keep that cadence without burning out your team.

Marketing removes barriers—so treat it like operations

The Salem story about shifting visitors from cars to trains isn’t a cute campaign anecdote. It’s an operations lesson.

When constraints are real (parking, capacity, staffing), marketing can’t be a “top-of-funnel” department. It has to function like a system designed to redirect flow.

That’s exactly what strong AI-enabled marketing ops looks like in digital services:

Barrier removal starts with a map of your journey

If you want AI to help, you need a clear definition of the journey you’re optimizing. For B2B supply chain and procurement platforms, a simplified version is:

1. Problem recognition (forecast misses, supplier delays, maverick spend)
2. Solution search (shortlists, analyst reports, peer references)
3. Evaluation (security review, integration questions, ROI model)
4. Procurement (legal, pricing, approvals)
5. Implementation (data ingestion, change management)
6. Adoption and renewal (usage, outcomes, expansion)

Now ask: Where do deals stall most often? That stall is your barrier.

Common “small barriers” that cause big losses

Judge gives a perfect example: an upside-down PDF. In SaaS, it’s the same energy:

• The security questionnaire takes 3 weeks to get answered
• Pricing pages don’t match how procurement buys
• Case studies are vague (“improved efficiency”) instead of quantified
• The demo request form asks 12 fields and converts poorly
• Integration docs exist, but they’re scattered and outdated

When you have high traffic and a long sales cycle, tiny points of friction multiply into huge revenue leakage.

How AI helps remove barriers (practical uses)

AI is most useful when it’s aimed at diagnosis + prioritization, not just content generation.

• Conversation intelligence can tag recurring objections (ERP integration, SOC 2, data residency, implementation timeline)
• Support ticket clustering can reveal adoption blockers that marketing should address pre-sale
• Website behavior modeling can show where prospects bounce during evaluation
• Automated knowledge bases can keep technical and procurement content current

Strong stance: If your marketing team isn’t regularly mining Sales and Customer Support data, you’re guessing. AI won’t fix guessing—it’ll just help you guess faster.

Let your audience segment itself (AI makes this way more powerful)

Destination Salem created a personality quiz that routes visitors into personas like “Cultural Connoisseur” or “Muggles Seeking Magic,” then generates a personalized itinerary.

B2B teams sometimes roll their eyes at quizzes. I think that’s a mistake. The mechanics are sound:

1. Ask prospects a small set of questions they’re happy to answer
2. Use answers to route them to the right recommendations
3. Capture structured intent data you can act on

A B2B version for supply chain and procurement

If you sell supply chain AI, supplier risk tools, procurement automation, or logistics software, your “quiz” can be a short assessment:

• Primary goal: cost reduction, resilience, compliance, speed, working capital
• Current systems: ERP, TMS, WMS, eProcurement suite
• Data maturity: spreadsheets, BI, data lake, real-time feeds
• Timeline: this quarter, 6 months, next fiscal year
• Top constraint: change management, integrations, budget, staffing

Then route to:

• a tailored demo path
• a relevant case study
• an implementation checklist
• an ROI model aligned to their goal

Where AI fits

AI can:

• detect patterns across responses and create smarter segments than static personas
• recommend next-best content for each segment
• create sales assist briefs (“This account is resilience-led, ERP-heavy, integration-risk sensitive”)

This is barrier removal again—just earlier in the process. You’re preventing “wrong demo, wrong story, wrong proof” from wasting everyone’s time.

Bridging brand value to hard numbers (without hand-waving)

Leaders still get pinned with the same question: “How do we justify brand investment with real financial outcomes?”

Destination marketers live this tension—fantasy and imagination drive visitation, but tax revenue and seasonality are what matter. B2B isn’t that different. Brand works because it changes what the buyer believes before the first sales call.

A practical measurement model that works in SaaS

Here’s the model I’ve found most defensible for stakeholders who want numbers:

1. Define the economic event you’re trying to influence (pipeline creation, win rate, ACV, retention)
2. Pick leading indicators brand can realistically move:
   • direct traffic growth
   • branded search volume
   • email list growth and engagement
   • demo-to-opportunity conversion
   • sales cycle length by segment
3. Connect to lagging indicators:
   • influenced pipeline
   • win rate uplift in branded vs non-branded cohorts
   • churn reduction for customers exposed to enablement content

Then set a timeline. Brand isn’t instant-response. But it’s also not mystical. If you can’t see movement in the leading indicators, your “brand” work is probably just content without strategy.

AI makes attribution more honest (not perfect)

Multi-touch attribution still has flaws. AI helps by:

• unifying identity across touchpoints (within privacy constraints)
• modeling likely influence when tracking is incomplete
• identifying which messages correlate with faster progression

You still need judgment. But you can replace “trust me” with “here’s what changed, and here’s what followed.”

A 30-day AI plan to remove barriers (steal this)

If you’re responsible for growth in a supply chain or procurement tech company, here’s a realistic month-long sprint.

Week 1: Find friction with data you already have

• Pull the top 50 sales calls and summarize objections by theme
• Cluster the top 200 support tickets by category
• Identify the 3 pages with the highest traffic and highest bounce

Deliverable: a ranked list of 10 barriers with evidence.

Week 2: Build “barrier-buster” assets

Create assets aimed at the friction points:

• security + compliance one-pager
• integration overview (with realistic timelines)
• ROI calculator aligned to procurement language
• implementation checklist that reduces fear

Use AI to draft structure and variants, then edit with real specifics.

Week 3: Deploy owned media sequences

• 3-email “Remember us?” sequence for each segment
• one monthly customer story (quantified)
• a short newsletter that’s actually useful

Week 4: Add self-segmentation

• launch a short assessment (5–7 questions)
• route to a tailored landing page and demo track
• feed segment labels into CRM for sales routing

Success metric: higher demo-to-opportunity conversion and fewer “wrong-fit” demos.

What to do next

Marketing that removes barriers is closest to what supply chain leaders already respect: systems thinking. If you treat marketing like a set of operational constraints—then use AI to spot friction, prioritize fixes, and personalize at scale—you’ll see measurable lifts in pipeline efficiency.

If you’re planning your 2026 roadmap right now, take a hard look at where your buyer journey is still built on assumptions. Where are prospects confused? Where do approvals stall? Where does adoption fade after implementation? Those are barriers, and they’re expensive.

What’s one barrier your customers hit repeatedly—something your team could fix “purely out of love for the user,” even before it shows up in a dashboard?