Chris Stanczak is a talent development professional who helps organizations connect employee learning with business goals. Stanczak's work includes learning strategy, measuring program impact, succession planning, and practical uses of AI in training and development.
Most useful for practical L&D posts on learning strategy, measurement, and AI in talent development.
Best for
A B2B learning technology vendor seeking a practitioner webinar on measuring learning impact.
Not for
Consumer AI apps, general future-of-work brands, or developer tools seeking large reach.
Key takeaways
Learning spend should follow a strategy, not convenience.
Measure learning with a preponderance of evidence, including promotions and reduced turnover.
Treat AI as a learning and development co-pilot, not a technology specialty.
Check first: Confirm commercial terms, audience analytics, and past webinar figures before contacting them.
Main ideas
Learning spend should follow a strategy, not convenience · Make the case for learning with a preponderance of evidence · Treat AI as a learning and development co-pilot, not a technology specialty
Audience
2,229 LinkedIn followers · Not documented in the evidence Audience composition (geography, age, gender, seniority, occupation)
Chris Stanczak is a talent development professional whose LinkedIn posts focus on making workplace learning more strategic and useful.
They connect training to business goals, argue for measuring learning even when direct cause and effect is hard to prove, and share practical ways to use AI in learning and development.
They also describe experience building succession paths, consolidating learning management systems, and developing curricula.
Stanczak translates broad L&D challenges into concrete questions and examples.
On training investment, they ask readers to define goals, connect a program to current challenges, and decide how to measure its impact.
On measurement, they acknowledge that proving a direct revenue effect can be difficult, then point to promotions, reduced external recruiting costs, and lower turnover as evidence worth considering.
Their AI posts pair practical use cases—such as drafting training outlines and quizzes—with a note that Skills Copilot was still being explored.
This combination of business alignment, workable evidence, and candid implementation detail gives readers a practical starting point rather than a claim that every program’s impact is easy to prove.
Across five LinkedIn posts, Chris Stanczak's recurring priorities are making learning answerable to business goals, measuring its impact with defensible evidence rather than waiting for perfect proof, and treating AI as ordinary tooling for learning and development teams rather than a technology specialty.
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A fourth thread is building the talent development function itself — succession paths, learning technology ecosystems, and curricula — a playbook they describe assembling inside one company and now offer independently. The posts are mostly short conference debriefs: an observation from a session or breakout, a practical argument built on it, and an invitation for peers to respond.
Learning spend should follow a strategy, not convenience
Stanczak argues that training and conference budgets are often allocated by cost, schedule, or location rather than by a specific business need or risk.
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Buying training does not guarantee relevance: it may miss the actual skill gap or fail to fit how a team works. They propose a learning strategy aligned with business strategy and annual operating plans, tying each opportunity to team development and organizational goals and setting out how to measure the investment.
Reflecting on a conference, Stanczak describes watching "countless dollars leave companies" as employees travel to a fabulous destination but return with no changed behavior, valuable contacts, or information to share.
They offer three questions to answer before committing resources: What are our specific learning goals?
How will this training address our current challenges?
Make the case for learning with a preponderance of evidence
Rather than wait for a clear causal link between a program and revenue, Stanczak argues for a set of defensible proxies that together make the case.
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They credit the framing to a session speaker: measurement is genuinely complex, but that complexity is often used as an excuse not to measure, even when partial evidence is available and persuasive.
After the Richmond CLO Event, Stanczak shares an observation from Bjorn Billhardt, CEO of Abilitie.
A leadership program may not be provably tied to revenue growth, but the number of participants promoted after completing it can show savings on external recruiting costs.
A measurable drop in turnover can also be partly attributed to stronger leadership.
Treat AI as a learning and development co-pilot, not a technology specialty
Stanczak argues that AI is already reshaping how people learn and work, and that people in learning and development, HR, and People Ops can use it without coding skills.
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They urge readers to experiment rather than hesitate. The reported result is a shift from manual to strategic work: routine tasks are automated, knowledge-sharing becomes a cultural pillar that scales skills faster than individual training, and learning is personalized rather than delivered as generic programs.
One post describes AI as the team's talent development co-pilot, automating trend analysis and frequently asked questions so the team can focus on higher-impact development. Another, for readers who think AI is "just a tech thing," names the tools in use: ChatGPT for generating training outlines and quizzes, with the free version described as "quite powerful"; Skills Copilot for assessing and recommending upskilling paths; and Canva for learning materials.
The two AI posts take different approaches: one recounts adopting AI across a talent development function; the other is a beginner-facing tool guide. Stanczak says they are just beginning to explore Skills Copilot and asks readers who use it to share their experience, making clear that their testing is incomplete.
Build talent development as a system, then offer the playbook elsewhere
Another priority is the machinery of talent development: clear succession paths for an organization's most critical roles, a consolidated learning technology ecosystem, and curricula built to deliver results.
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Stanczak presents a three-and-a-half-year build of this kind as a transferable playbook, not a one-company arrangement.
Stanczak describes a mission to elevate and streamline a company's talent development function and give its most critical roles clear succession paths.
They point to hands-on LMS consolidation and curriculum building, alongside a CPTD credential and a master's in organizational leadership.
Their consulting areas are executive succession and stability, learning technology ecosystem design, and fractional talent development leadership.
A career change shifts the framing. After Stanczak's position was eliminated, priorities that had been an in-house build at DLH became services other organizations could buy, moving the emphasis from internal function-building to independent practice.
Conferences prompt reflection and provide a publishing habit; they are not the learning itself
The posts follow a pattern: an observation from a session or breakout becomes a short practical argument, with named speakers credited for specific insights and a closing question inviting peers to compare notes.
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Stanczak treats the event as a prompt to pause and reflect, not as the learning itself, and turns it into takeaways others can use.
Stanczak writes that a conference offers a chance to pause and reflect on things normally "tossed into the whirlwind of the day-to-day," while criticizing trips to a "fabulous destination for a conference that doesn't produce changed behaviors."
They use the event to sharpen strategy and share takeaways.
Posts drawing on the Richmond CLO Event and the CLO Conference end by asking readers how they handle the same problem.
Answers the question: How does a seasoned talent development professional decide whether a training investment is worthwhile?
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Start here for the core problem Stanczak returns to elsewhere: learning must connect to business goals, not just fill a training budget.
Chris Stanczak argues that companies often spend on conferences and workshops without linking that investment to business strategy.
Many expect learning events to improve performance automatically.
Before committing resources, Stanczak asks three questions: What are our specific learning goals?
How will this training address current challenges?
How can we measure the impact of the investment?
The practical takeaway: identify skill gaps and connect each learning opportunity to team development and organizational success.
For brands planning a campaign
A learning technology company could use this as the starting point for a webinar on tying learning strategy to annual operating plans, with the three questions as a shared checklist.
Answers the question: What does measuring learning impact look like when direct causation is hard to prove?
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Start here for a practical alternative to perfect proof and examples of learning translated into business metrics a leadership team can understand.
At the Richmond CLO Event, Chris Stanczak highlights an observation from Bjorn Billhardt, CEO of Abilitie: measurement is complex, but that complexity can become an excuse not to measure.
For example, you may not be able to prove that a leadership program increased revenue by a specific amount.
But you can point to the number of leaders promoted after completing it, savings from reduced external recruiting costs, and a measurable decrease in turnover partly attributed to better leadership.
The post calls this a preponderance of evidence.
For brands planning a campaign
Supports a webinar collaboration on measuring learning impact. The preponderance-of-evidence framing and examples involving promotions, recruiting costs, and turnover can anchor the session and give participants a method to apply.
Answers the question: How did a talent development leader move from manual processes to an AI-assisted strategy?
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Start here for a firsthand account of adopting AI in L&D and the team-level changes that followed.
Chris Stanczak describes working at the intersection of tech and government contracting and seeing AI reshape learning earlier than most.
At the CLO Conference, AI dominated every session.
Stanczak tested tools and changed the team’s approach: AI became a talent development co-pilot, automating trend analysis and frequently asked questions and freeing the team for high-impact development; knowledge-sharing became a cultural pillar that scaled skills faster than solo training; and learning became hyper-personalized to individual needs, driving engagement and measurable results.
For brands planning a campaign
A learning technology company could invite Chris Stanczak to share this adoption story in a webinar, focusing on practical steps and the shift from manual work to strategic work.
Answers the question: What AI tools can a talent development team use without engineers?
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Start here for a practical, tool-level view with names, uses, and an honest note about what is still being tested.
Chris Stanczak argues that AI isn’t just for tech specialists and that talent development professionals don’t need coding skills to benefit.
The post lists ways AI can help: personalize learning based on skills and goals, automate scheduling and progress tracking, and enhance the experience through chatbots and AI coaching with real-time feedback.
At DLH, Stanczak used ChatGPT to generate training outlines and quizzes, noting that the free version is quite powerful; Skills Copilot to assess and recommend upskilling paths, a tool they were just beginning to explore; and Canva to create visually appealing learning materials.
For brands planning a campaign
Could support a hands-on workshop or demo-heavy webinar. The tool list—ChatGPT, Skills Copilot, Canva—gives a vendor session concrete talking points for L&D practitioners new to AI.
Answers the question: What does this person focus on professionally, and what do they claim as their proven playbook?
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Start here for career context and the specific service areas—succession, learning technology ecosystems, and fractional leadership—that connect to the rest of their posts.
Chris Stanczak reflects on three and a half years at DLH, where the mission was to elevate the talent development function, build processes, and ensure critical roles had a clear succession path.
That chapter ended when the position was eliminated.
Stanczak says they left with a proven playbook for talent challenges and are now seeking a VP, Director, or Manager of Talent Development role, along with consulting projects in executive succession and stability, learning technology ecosystem design, and fractional talent development leadership.
The post cites practical experience with LMS consolidation and curriculum building, along with a CPTD and a Master's in Org Leadership.
For brands planning a campaign
Signals openness to consulting and speaking. A vendor could approach Stanczak for a webinar on succession planning or learning technology ecosystem design, using the playbook as a practitioner case study.
Conference takeaways and peer dialogue as a recurring format4
Learning strategy before learning spend1
Measuring learning with a preponderance of evidence1
AI as a talent development co-pilot1
Plain-language AI tools for non-technical L&D teams1
Succession planning and building the talent development function1
Learning strategy before learning spend
At a conference, Chris Stanczak asks companies whether they have a learning strategy and describes watching money leave organizations through conference trips and training sessions that produce no changed behavior, new contacts, or new information to bring back.
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Training, the post argues, is often chosen based on cost, schedule, or location rather than a specific business need or risk.
Before committing resources, it lays out three questions: what the learning goals are, how the training addresses current challenges, and how its impact will be measured.
The proposed fix is a plan that ties learning to business strategy and annual operating plans, and a learning culture rather than a larger training budget.
Opens with a question to the reader, moves into first-person reflection, then closes with a numbered checklist of vetting questions.
For brands planning a campaign
For a webinar on measuring learning impact, this is a ready-made opening: the audience is already being asked to justify spend, so the session can start with the third vetting question — how impact gets measured — rather than re-arguing why measurement matters.
Measuring learning with a preponderance of evidence
Writing after the Richmond CLO Event, Chris Stanczak relays an observation from Bjorn Billhardt, CEO of Abilitie: measurement complexity is often used as an excuse not to measure at all.
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The post argues that while causation between a learning program and a business result is hard to prove, proxies can still build a case.
Examples include the number of leaders promoted after completing a leadership program, showing savings against external recruiting costs, and a measurable drop in turnover attributed in part to stronger leadership.
Together, these can make a compelling case that learning drives business results, even without a direct line to revenue.
For brands planning a campaign
A strong fit for a webinar on practical, defensible metrics. The post can anchor a discussion of promotions, recruiting savings, and turnover, or establish the framing for a session that expands on it.
After the CLO Conference, where AI dominated the sessions, Chris Stanczak describes moving from hesitation to testing tools and iterating on talent development programs.
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They report three shifts: automating routine work such as trend analysis and answering frequently asked questions so the team could focus on higher-impact development; treating knowledge-sharing as a cultural pillar that scaled skills faster than individual training; and personalizing learning rather than delivering generic programs. The post ends by asking readers how AI is changing their own talent development playbook.
A first-person account of a change already made, with the reasoning behind each shift, ending with a direct question to the audience.
For brands planning a campaign
Offers a distinct webinar angle: a learning technology company could ask Chris Stanczak to discuss how AI changes impact measurement, or lead a follow-up session on adoption.
Plain-language AI tools for non-technical L&D teams
Aimed at people in learning and development, HR, and People Ops who see AI as a technology concern rather than their own, this post argues that no coding skill is needed.
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It names three uses — recommending training content based on employee skills and goals, automating scheduling and progress tracking, and using chatbots and AI coaching tools for real-time feedback — and three tools used at DLH: ChatGPT for generating training outlines and quizzes, Skills Copilot for assessing and recommending upskilling paths, and Canva for learning materials. Chris Stanczak says they are early in exploring Skills Copilot and asks readers who use it to share their experience.
A short numbered breakdown of uses followed by a named tool list, aimed at beginners and closing with an invitation to compare notes.
Ask whether the tools listed are still in use after the role change described in a later post, and whether any vendor relationships are relevant.
For brands planning a campaign
Shows tool-level fluency: Chris Stanczak can walk a learning technology audience through concrete workflows — outline generation, upskilling paths, and materials — rather than discussing AI in the abstract.
Succession planning and building the talent development function
In a career-update post, Chris Stanczak describes three and a half years at DLH spent elevating the talent development function — building and streamlining it, and giving the company's most critical roles a clear succession path — and says the position was eliminated.
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The post announces their availability for VP, Director, or Manager roles in talent development, as well as consulting work on executive succession and stability, learning technology ecosystem design, and fractional talent development leadership. It cites a CPTD credential and a master's in organizational leadership, with hands-on LMS consolidation and curriculum building as the basis for the claim.
For brands planning a campaign
Signals openness to consulting and fractional engagements, so a vendor could propose paid advisory work or a fractional role, not just a sponsored session. Chris Stanczak is also actively job-seeking, which may affect availability and how a collaboration is framed publicly.
Conference takeaways and peer dialogue as a recurring format
Across the corpus, the dominant format is the conference debrief: sessions and breakout conversations with other learning and talent development leaders at the Richmond CLO Event and the CLO Conference become a short argument with practical next steps, while named speakers receive credit for specific insights.
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Posts open with a question, use numbered lists, and close by inviting comments or connection. The focus shifts from learning strategy and measurement to AI adoption and, later, a career transition toward consulting and fractional leadership.
LinkedIn text posts with question-led openings, numbered lists, attributed quotes from named session speakers, and topical hashtags.
For brands planning a campaign
A webinar or event collaboration fits Chris Stanczak's established practice of turning event content into published takeaways, making a post-event recap a reasonable deliverable to agree on in advance. Their shift toward fractional and consulting work means the pitch should clarify whether the engagement is a one-off session or ongoing advisory.
Chris Stanczak’s posts document an employer relationship and mentions of tools and an event.
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They say they spent about three and a half years leading talent development at DLH before the role was eliminated, and name the Richmond CLO Event as the source of a learning-measurement example. They also name AI and design tools their team used at DLH.
DLH
Employment
They say they joined DLH roughly three and a half years earlier to lead its talent development function, build succession paths and consolidate the learning technology stack.
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The position was later eliminated; this is a past, not current, engagement.
They attended the Richmond CLO Event and drew a learning-measurement example from a breakout session.
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Their posts include the event hashtag but disclose no sponsorship or other commercial arrangement. Ask whether their attendance was sponsored or otherwise compensated.
Chris Stanczak's posts make concise, conference-driven arguments about learning and development: training should meet a business need; its impact should be supported by defensible evidence, such as promotions, reduced recruiting costs, and turnover; and AI belongs in the everyday toolkit of L&D, HR, and People Ops teams.
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Start with the three posts that turn session or breakout observations into question-led arguments, then read the two posts that name specific tools and describe first-person shifts in AI use. A later career update traces the move from an in-house talent development build to consulting and fractional leadership, linking the strategy and measurement posts into a consistent point of view.
Budny argues that employers should build critical skills from within and link learning to business outcomes, including closing gaps in cybersecurity, data, and AI.
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That aligns with Chris Stanczak's view that learning should meet a business need, not follow a conference schedule, and that talent development works as a system rather than a set of isolated courses.
Budny writes from a workforce-development provider perspective, announcing a tech skills academy, employer visibility into developing skills, and frontline workforce themes from an industry summit. Stanczak writes as an individual practitioner about learning strategy, measurement, and AI tools.
Shahid also makes the case for learning through business outcomes.
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Their posts describe measuring behavioral change rather than completion rates, reporting time-to-productivity and retention signals, and personalizing programs at scale through personas. Those priorities overlap with Stanczak's posts on learning strategy, measurement, and AI-supported personalization.
Shahid goes deeper into instructional design, covering learner personas, facilitator preparation, assessments, and a detailed operating-model reset. Stanczak focuses on strategy, measurement, and tool adoption.
Sue Ly shares first-person guidance for L&D practitioners, including a review of a Vyond 2D animation course with takeaways for building instructional design skills and a reflection on moving from teaching into a senior curriculum and instructional design role.
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Stanczak also draws on personal experience, writing about adopting AI tools and shifting a talent development career.
Sue Ly targets teachers and career changers entering instructional design, offering tool-building and portfolio advice. Stanczak's audience is talent development leaders, and their posts focus on strategy and measurement rather than design craft.
The posts support a tightly targeted, subject-matter-led collaboration with Chris Stanczak, not a reach-based webinar.
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The only measured audience figure cited is a LinkedIn following of 2,229, observed 9 October 2026.
None of the five posts gives audience geography, age, gender, seniority, employer or job function, or reports reach, impressions or engagement counts.
A B2B learning technology company should therefore plan for a small, niche audience and judge the collaboration mainly on topical credibility and the quality of the conversation they can convene around measuring learning impact.
The posts show who Stanczak addresses, not who follows or reads them.
A 27 May 2025 post opens: "If you work in Talent Development (L&D, HR, or People Ops)..."
Other posts cover learning strategy tied to business plans and annual operating plans (10 September 2024), measuring learning value through promotion counts and reduced turnover (11 September 2024), AI in talent development with named tools including ChatGPT, Skills Copilot and Canva (27 May 2025), and AI as a talent development co-pilot (21 May 2025).
The intended audience appears to be L&D, HR and people-operations practitioners and managers, but the posts do not establish who actually engages.
For a campaign focused on measurement, the strongest topical match is the 11 September 2024 post, which quotes Bjorn Billhardt of Abilitie on using a "preponderance of evidence" and gives concrete metrics, including leaders promoted after a program and reduced turnover.
Ask for LinkedIn follower demographics or analytics, any audience survey, and registration, attendance and job-title figures from previous webinars or events on learning measurement.
LinkedIn followers
2,229
Follower count recorded on the LinkedIn profile record for Chris Stanczak · 2026-10-09
Chris Stanczak's posts don't announce a published partnership program, sponsorship offer, media kit, rate card, sponsored-content format or inquiry route.
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They do show the kind of collaboration a learning technology vendor might approach them for: they write about attending industry conferences and what came out of the sessions (the Richmond CLO Event), measuring learning impact when causation is hard to prove, and using AI tools such as ChatGPT and Skills Copilot in talent development work.
That points to a speaking, panel or webinar-style engagement rather than a paid placement.
Buyers should ask directly about availability and commercial terms before building an engagement into a campaign.
Strong fit, with conditions, for a B2B learning technology vendor seeking a practitioner webinar on measuring learning impact.
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A learning analytics or measurement platform could work with Chris to host a live webinar and follow-up LinkedIn recap for L&D, HR, and People Ops practitioners and managers, aiming to generate qualified conversations rather than mass registrations.
The measurement theme is already central to their posts.
The Richmond CLO Event post relays Bjorn Billhardt's argument that complexity is often used as an excuse not to measure, then offers practical proxies: leaders promoted after a program, savings from reduced external recruiting, and reduced turnover partly credited to better leadership.
The learning strategy post offers a companion frame: before spending on training or conferences, ask what the learning goals are, how the training addresses current challenges, and how impact will be measured.
The AI posts add a secondary angle, showing tool-level fluency with ChatGPT, Skills Copilot and Canva in talent development, and describing AI as a co-pilot that frees time for higher-impact work.
The format also fits: their recurring pattern is conference debrief followed by practical next steps, making a post-event recap a natural deliverable.
Before planning, confirm commercial terms directly; the posts provide no sponsorship formats, rate card, media kit, or inquiry route.
Audience information is limited to 2,229 LinkedIn followers observed 9 October 2026, with no demographics, reach, engagement, or webinar history.
In the career-update post, Chris says the DLH role was eliminated and they are seeking VP, Director, or Manager roles, plus consulting work in succession, learning technology ecosystem design, and fractional talent development leadership.
Confirm availability and engagement structure before planning a long program.
Judge the collaboration on topical credibility and conversation quality, not reach.
Frame tool and employer references as descriptions in the posts, not current vendor endorsements.
When to choose a specialist
Poor fit for a consumer AI app, a general future-of-work brand, or a developer-tools company seeking a high-volume sponsored webinar or paid social placement with large reach and a product-led coding demo.
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The brief calls for registration targets in the thousands, a general business or developer audience, and a creator who can demo coding workflows or review consumer apps.
Chris's posts do not match that audience or content.
They address people in talent development, L&D, HR, and People Ops; the AI tool post explicitly tells that audience no coding skill is needed.
The topics are learning strategy, measurement proxies, AI adoption in L&D, and a career update—not software engineering, consumer app reviews, or broad future-of-work commentary.
The only audience figure stated is 2,229 LinkedIn followers observed 9 October 2026, with no demographics, reach, engagement, or past webinar data, so the posts provide no basis for a reach-based campaign.
The commercial structure is also unconfirmed: the posts provide no sponsorship formats, rates, media kit, or inquiry route.
A campaign promising direct causal ROI at scale would conflict with Chris's own measurement position, which argues for a preponderance of evidence and proxies when proving causation is difficult.
The career-update post says the DLH position was eliminated and they are seeking a senior talent development role or consulting work; confirm availability before proposing an always-on influencer program.
This is not a poor fit for a niche measurement webinar; it is a poor fit for a broad-reach consumer or developer campaign that needs numbers the posts cannot support.
A worked campaign example
Worked campaign angle for the good-fit brief: a learning technology vendor wants to collaborate on measuring learning impact.
Frame the session as 'Beyond Causation: Building a Preponderance of Evidence for Learning Impact.' Make it a practical measurement clinic for L&D leaders, not a product demo.
Chris can host as a practitioner voice, with the vendor supplying a worksheet and follow-up consultation route.
Pre-event LinkedIn post: open with the question from the learning strategy post, 'Does your company have a learning strategy?', then list the three resource-commitment questions and invite readers to bring one program they cannot currently defend.
Live 45-minute webinar arc: first, use the learning strategy post to show why measurement starts before the training purchase, not after.
Second, draw on the Richmond CLO Event post and the preponderance-of-evidence argument: acknowledge that direct causation is hard, then walk through proxies such as leaders promoted after a leadership program, reduced external recruiting costs, and a measured drop in turnover partly attributed to stronger leadership.
Third, run a short worked example in which participants map one program to two proxies and one business decision it informs.
Fourth, bring in the AI posts carefully: AI can automate trend analysis and FAQs, personalize learning, and recommend upskilling paths, but it does not remove the need for human judgment about which measures matter.
Close with a worksheet: a one-page measurement memo naming the program, two proxy metrics, the memo's audience, and the next review date.
Post-event recap: use the conference-debrief style in Chris's posts, with three takeaways and a link to the worksheet.
The vendor can host the registration page and deliver the worksheet and follow-up consultation, but should not present unreviewed product features as working.
This approach uses the strongest measurement content, matches the named practitioner audience, offers the vendor a qualified conversation rather than a mass-registration promise, and produces an inspectable asset.
Before launch, confirm commercial terms directly because no sponsorship offer or rate card is documented; confirm availability given the active job search and consulting interest; keep claims about tools and past employers to what the posts state; and assess results by session conversation quality and worksheet completion, not follower count alone.
A stronger fit for the same measurement-impact webinar when the vendor wants a concrete L&D operating-model turnaround rather than a conference-style measurement argument.
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The posts describe a platform launch that reached 13.8% engagement, a shift from completion rates to behavioral change, a 90-day adoption check, a quarterly Talent Radar for emerging, proven, and hype tools, and upward reporting on time-to-productivity, retention signals, and capability gaps tied to business outcomes. They also cover persona-led training design, making Shahid Ahmed ST the stronger choice if the session should teach how to design and measure learning for distinct learner groups.
The posts focus on internal L&D transformation and instructional design.
They offer no ready-made conference debrief, executive case for measurement, or webinar format.
A vendor would need to adapt the operating-model story into a measurement-platform webinar.
Ask for audience size, engagement, webinar history, and commercial terms.
A stronger fit when the vendor wants to connect measurement to a workforce-development platform, skills academies, frontline talent, internal mobility, retention, and career pathways.
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The posts describe Tech Skills Academy, 15+ configurable career pathways, 100+ industry-aligned programs, a single data-driven platform, and employer visibility into skills developing across an organization. They also report ASU+GSV observations that education should connect to retention, internal mobility, and clear career progression rather than stand alone as a benefit.
The posts focus on organizational strategy, products, and conference reflections.
They do not demonstrate a practitioner measurement method, proxy metrics, or a live webinar format.
For a campaign centered on measuring learning impact, Chris Stanczak's Richmond CLO Event post offers a directly reusable measurement argument; Patrick Budny's material would need reframing from platform strategy to impact measurement.
Ask for audience size, engagement, webinar history, and commercial terms.
A stronger fit only if the vendor shifts the collaboration toward practical instructional-design tool training, especially for people moving into L&D from teaching.
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The posts cover a transition from high school art teacher to curriculum and instructional design work, five things Sue Ly values at VSP Vision, and a detailed review of a Vyond 2D character animation course, including course structure, instruction quality, and hands-on project takeaways.
Sue Ly is not the closer alternative for the stated measurement-impact webinar.
The posts focus on instructional design tools, career transition, and workplace culture, not learning measurement, business outcomes, or campaign-impact arguments.
A vendor seeking a measurement webinar would find weaker topical evidence and need to shift the session toward tool skills, animation, or portfolio building.
Ask for audience size, engagement, webinar history, and commercial terms.
This profile is built from five LinkedIn posts written by Chris Stanczak and reviewed as full text.
The posts cover learning strategy, measuring learning impact, AI adoption in talent development, practical AI tools, and a career update.
They do not carry publication dates, so topics are grouped by argument rather than by a dated timeline.
The similar-creator comparisons in the discovery section draw on posts from three other creators dated June 2026, May 2026, November 2025, April 2026, June 2024, and July 2024.
Research gaps remain: no videos, articles, transcripts, engagement or reach data, audience demographics, webinar history, or documented sponsorship terms were available.
Claims about employers, credentials, and tools rest on what the posts state.
The page targets general name searches and the common modifiers around talent development, learning measurement, and AI in learning and development.
