Roboflow's product marketing hire is asked to build "vertical specific narratives" and "named reference stories" for industrial, logistics, aerospace and defense, automotive, energy and healthcare buyers. But 23 of the 25 industry pages show the same three unnamed stats (an automotive customer's $10 million, a logistics company's 90%, a building materials supplier's 60%), so the aerospace and healthcare buyer reads about car plants and gypsum. The logistics page labels a container-yard result "Automotive customer", and the energy page does not link Ulteig, the case study from an energy and utilities engineering firm.
First action
Build a table of the 25 industry pages and the case studies that fit each.
How to measure it
Industry-page demo request rate
- Now
- –
- Target
- +25%
- By
- 90 days
Steps
Map proof
Case studies and quotes to each industry page.
Product Marketing 2 days
Fix errors
The logistics mislabel and missing Ulteig link.
Product Marketing 1 hour
Change the template
Proof block takes industry-specific stories first.
Web Developer 3 days
Fill gaps
Closest named story, labelled, plus two /ai use cases.
Product Marketing 3 days
Brief sales
Which story to send for each industry.
Sales Development Leader 1 day
Plan new stories
One per priority vertical, with metrics.
Product Marketing 1 quarter
Measure
Demo requests by industry page.
RevOps Analyst monthly
Why it works
In two weeks, with the proof Roboflow already has: map each of the 16 case studies to its industry pages and show named results first (BNSF on logistics, transportation and warehousing; USG and Pella on manufacturing; Ulteig on energy; Wellth on healthcare); fix the mislabel; and where an industry has no story yet, show the closest named one with a clear label plus two use cases from the /ai library for that industry. Then make one new named story for each of the six priority verticals the next PMM sprint.
Enterprise buyers trust peers in their own industry. Matching proof to the page is the quickest way to make the "Vision AI platform for the world's largest companies" story believable, and it raises demo requests from pages that already rank.
Ready to use
ChecklistIndustry page proof audit
[ ] Each industry page lists only proof from its own or a clearly labelled adjacent industry [ ] Logistics page: container-yard result labelled correctly [ ] Energy and utilities page links Ulteig [ ] Healthcare page leads with Wellth [ ] Logistics, transportation, warehousing lead with BNSF [ ] Manufacturing pages lead with USG and Pella [ ] Gap industries flagged for a new named story [ ] Demo form records the industry page
Risks and how to handle them
Customers decline to be named
Use named industry and role with approved metrics.
Thin proof in aerospace and defense
Lead with relevant use cases and the security and sovereignty features.
Evidence
- HiringProduct Marketing (remote US, posted May 21, 2026): "We are moving from being known as a data labeling tool for developers to being known as the Vision AI platform that powers production deployments inside the world's largest companies." The role must "make sure every external facing surface tells a coherent story", build "Buyer facing landing pages, ROI frameworks, vertical specific narratives, customer outcomes, named reference stories", "Productize customer proof", and drive vertical strategy in "Industrial, logistics, aerospace and defense, automotive, energy, healthcare", for "$150K+ ACVs". This post says Roboflow has "raised over $63 million".Source
- Your websiteIndustry pages (checked October 22, 2026): 23 of the 25 /industries pages show the same three anonymous results: "Automotive customer, $10 million saved by automatically detecting defects on the production line", "Logistics & freight company, 90% less time spent manually tracking shipping inventory" and "Building materials supplier, 60% lower customer return rate". That includes aerospace and defense, healthcare, energy and utilities, automotive and warehousing; the aerospace, energy and automotive pages link only to the general customer stories page. On the logistics page a container-yard result is labelled "Automotive customer". The energy and utilities page does not link the Ulteig case study, whose firm works in "Power, Renewables, Water, and Transportation".Source
- Your websiteCustomer proof: 16 case studies (BNSF, USG, Wellth, Almond, Nakashima, Fletcher, Flovision, Playvision, Peer Robotics, Ogilvy Spain, StatsYuk, Field Museum, Ulteig, Blueprint Pro AI, Waypoint Transit and an equipment maintenance story). The homepage quotes BNSF ("4.8 million carloads a year"), USG ("more than 50 manufacturing sites") and Pella, and shows Rivian, Chobani, American Woodmark and Patrick Industries logos. The manufacturing report says customers "save $8 million detecting defects".Source
- Your websiteSitemap (1,690 URLs, October 22, 2026): 801 /convert format pages, 333 /ai use-case pages (for example airbag and catheter manufacturing inspection), 88 how-to-deploy, 68 train, 47 integration pages (Allen-Bradley, Siemens S7, Ignition, Kepware, AVEVA PI), 41 AI camera pages (Basler, Axis, Cognex, Keyence, Luxonis, NVIDIA Jetson and others), 36 comparison pages (Cognex, Keyence, Scale AI, Voxel51, Encord and others), 25 industry pages, 16 case studies, ebooks including a "Visual Intelligence Index 2026" and an ROI framework. The blog (1,388 posts) moved from blog.roboflow.com to roboflow.com/blog.Source