Buckley Sawyer is a customer support and customer experience leader who shares practical advice on improving support operations, using customer feedback, and turning support interactions into business growth.
Practical advice on support operations, customer feedback, and turning support interactions into business growth.
Best for
A B2B SaaS support or CX platform campaign aimed at support leaders.
Not for
Brands needing priced creator placements or independently verified performance claims.
Key takeaways
Support conversations are a revenue channel, not only a cost to manage.
Customer feedback is collected far more often than it is used.
A reported support-revenue experiment added $900,000 a year while CSAT stayed 95%.
Check first: Confirm deliverables, timeline, price, substantiation for performance claims, and audience data.
Main ideas
Support conversations are a revenue channel, not only a cost to manage · Customer feedback is collected far more often than it is used · Solving the problem and delivering a great experience are not competing priorities
Buckley Sawyer is a customer support and customer experience leader whose LinkedIn posts explain how support teams can improve the customer experience, use customer feedback, and contribute to business growth.
The posts make a practical case for treating support as more than a cost center: they connect team training, AI tools, experience measures, and feedback to better service and, in some cases, revenue.
Readers can follow this work for concrete operating questions and tactics, including a first-30-days leadership checklist, a customer-feedback approach, and examples of monetizing support interactions.
They also write about job seeking and career transitions, including the emotional strain of unemployment, so the account is not limited to management advice.
Sawyer’s distinctive contribution in the posts here is to connect customer experience improvements with the practical economics of running support.
The posts move between strategy and specific actions: measure more than handle time, use open-ended feedback to find recurring problems, and align support with product and other teams.
The clearest example is a reported support-revenue experiment: they say that, at a company handling 30,000 chats and emails monthly, selected interactions generated an additional $900,000 a year while CSAT remained at 95%.
A separate tactic suggests placing attributable sales links on popular help-center pages.
These examples show the commercial argument in concrete terms, while their advice on training, AI-assisted service, and two-week before-and-after measurement keeps customer experience in view.
The posts are useful to readers looking for operational ideas they can assess, rather than broad claims that support should simply be more customer-centric.
Buckley Sawyer's writing returns to one argument: customer support is an operational and commercial system, and winning teams treat revenue potential, feedback loops, and service quality as one connected problem.
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They make the case with concrete numbers, old-way/new-way contrasts, and short diagnostic lists. Their audience is mainly current and aspiring support leaders, and they present much of the advice as a demonstration of how they would run a support organization.
Support conversations are a revenue channel, not only a cost to manage
Buckley Sawyer argues that most companies leave money inside everyday support interactions.
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With tens of thousands of monthly chats and emails already flowing through a team, small conversion rates on a fraction of those conversations can cover a meaningful share of support costs. They call this growth hacking and frame the executive pitch around offsetting support spend, not changing service quality.
In one post, Buckley Sawyer walks through a scenario handling 30,000 chats and emails a month: about 1,500 conversations, roughly 5%, led to an additional purchase at around $50 each, averaging about $0.40 per interaction and producing about $900,000 a year.
They say that equals paying for roughly 35 BPO agents or 20 US-based agents while CSAT held at 95%.
A second post describes a narrower tactic: putting attributable links to the highest-converting sales page at the bottom of the most-visited help center pages.
The path is traffic to attention, attention to options, options to a call to action, and conversion to revenue.
Customer feedback is collected far more often than it is used
Buckley Sawyer's recurring complaint is that freeform customer comments sit unused in the same platforms that hold CSAT scores.
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The fix is not a new survey but a repeatable loop: pull the comments out, surface recurring themes, and let frequency and urgency drive the priority order. They say findings create value only when shared beyond the support team and used to make changes.
The approach is three steps: export freeform comments as a CSV from Zendesk, Intercom, Salesforce, or Freshdesk; upload the text to an AI-powered word cloud tool to highlight recurring phrases, sentiment, and top complaints or compliments; then prioritize the most-mentioned issue and double down on features customers praise. Buckley Sawyer says they used this approach at two prior companies and that the findings fed marketing, product development, and support scripts.
Solving the problem and delivering a great experience are not competing priorities
Asked directly, Buckley Sawyer says the two goals are equally necessary and should reinforce each other, not compete.
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The levers they name are team training, AI for self-service and context gathering, measurement before and after a change, and continued tuning afterward. Training comes first, including product expertise, five-star service skills, and a clear sense of why the work matters.
The method is to record baseline service metrics, apply the changes, and measure again after two weeks to see the actual impact.
The metrics named are CSAT, first-call resolution, and average handle time.
Buckley Sawyer offers a free customized action plan to readers who want help getting started.
Becoming customer-experience focused is a set of specific swaps, not a slogan
Buckley Sawyer lays out seven shifts that separate a traditional support center from one that competes on experience.
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Each pairs an old practice with a replacement, making the position easy to audit against an actual team. The shifts span metrics, team structure, technology, feedback handling, and employee treatment.
The seven swaps are transactional KPIs for experience-driven outcomes such as NPS, CES, and CSAT; reactive problem solving for empowered, proactive teams; one-size-fits-all service for personalization through CRM, AI, and data analytics; feedback as a checkbox for a continuous loop that shows customers their input changed something; silos between support, marketing, product, and operations for cross-functional collaboration; reactive issue management for root-cause pain point resolution; and employee satisfaction as an afterthought for employee experience as a priority, on the reasoning that happy employees create happy customers.
AI should speed up support and sharpen analysis, not quietly replace the team
Across several posts, Buckley Sawyer presents AI as an augmentation layer with two jobs: faster self-service and better context for people handling hard cases.
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They measure it against existing service metrics rather than treating adoption as the goal, and identify human training as the most important tool in the stack.
Buckley Sawyer lists AI as a way to give customers fast self-service, gather context to troubleshoot or reproduce an issue, personalize interactions, and analyze large volumes of feedback.
One post claims implementations reduced the need for human support interactions by more than 20%.
They also argue that training helps a team solve issues faster and deliver a five-star experience, with AI helping rather than standing in.
Support leaders should lead with a diagnostic month, not a reorganization
Buckley Sawyer's answer to how a new support leader should start is a fixed list of questions to answer in the first 30 days.
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They move from measurement and structure to spend, cross-functional alignment, morale, feedback use, and quick wins. Two posts carry nearly the same list with minor wording changes, underscoring how consistently they return to it as a starting agenda.
The questions cover whether the right KPIs exist, whether the team is structured and empowered, which technology tools and processes are missing, any immediate red flags, wasted spend on tools, licenses, or overtime, alignment with product management and development, team morale, whether customer feedback is fully leveraged, and the top five quick wins for ROI, with top customer pain points as a bonus question. Buckley Sawyer supports the list with a stated background: leading departments of more than 100 people, scaling startups, building their own company, working at enterprise-level SaaS companies and companies with millions of customers, implementing AI that cut human support interactions by over 20%, an entrepreneurship award, and Help Desk Institute Support Center Director certification.
The consulting voice and the job search run side by side
Buckley Sawyer's public positioning shifts across the posts.
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The support and revenue posts sign off with service-style taglines about helping companies turn customer interactions or customer insights into growth, presenting an offer to clients.
Career posts from the same period describe an ongoing search and state that they are open to Director, VP, or Head of roles in customer support or customer experience.
Buyers considering a consulting engagement should ask whether they are available for the work or focused on a full-time role.
Alongside the CX posts, Buckley Sawyer writes about the mental health strain of unemployment, the risk of leaning too heavily on loved ones, and basics such as diet, sleep, exercise, and professional help.
They advise interviewees to show personality rather than appear like a polished robot, and post a year-end reflection expressing gratitude to former colleagues and recruiters while noting the search continues.
One post closes by addressing the C-level with a revenue result; others state openness to a leadership or consultant role.
This compact map shows how Sawyer thinks a support organization changes when it decides to compete on customer experience.
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Newcomers can start here to see the levers they treat as connected.
Sawyer lays out seven shifts for moving from traditional support to customer experience: from transactional KPIs to experience-driven metrics such as NPS, CES, and CSAT; from reactive problem-solving to empowered, proactive teams; from one-size-fits-all service to personalization through CRM, AI, and analytics; from feedback as a checkbox to a continuous loop; from team silos to cross-functional collaboration; from reactive issue management to proactive pain-point resolution; and from employee satisfaction as an afterthought to employee experience as a priority.
For brands planning a campaign
Useful for a B2B SaaS brief on moving support from cost center to retention driver. It offers a ready-made structure for campaign content around proactive support, feedback loops, and employee experience, with relevant metrics named.
It shows the audit questions Sawyer uses before proposing changes, plus the operating background they bring to a support leadership role.
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Sawyer lists the diagnostic questions they would work through in a first month: whether the right KPIs exist, whether the team is structured and empowered, what tools and processes are missing, where money is being wasted, whether support is aligned with product and development, how the team feels, whether customer feedback is fully used, and what quick wins can deliver ROI.
They add top customer pain points as a bonus question.
In the same post, they cite leading departments of more than 100 people, scaling startups, building their own company, working in enterprise SaaS and companies with millions of customers, implementing AI that reduced human support interactions by more than 20%, and holding a Support Center Director certification.
For brands planning a campaign
For a campaign about support transformation, this provides a diagnostic framework and credible specifics. A brand could build a checklist, webinar, or assessment around these questions rather than generic thought leadership.
This is the clearest example of Sawyer's signature argument: support conversations can be treated as a revenue channel, not only a cost to manage.
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Sawyer describes a support-monetization example: a team handled 30,000 chats and emails a month.
After testing several growth-hacking strategies, 1,500 conversations, about 5%, led to an additional purchase at about $50 each.
This averaged about $0.40 per interaction and produced an extra $900,000 per year, equivalent to paying for roughly 35 BPO agents or 20 U.S.-based agents, while CSAT stayed at 95%.
They frame the executive pitch as covering most customer support costs.
For brands planning a campaign
Strong for a brief about monetizing support without harming satisfaction. The numbers and CSAT guardrail make a concrete case study or lead magnet.
This small, specific tactic shows how Sawyer turns existing support traffic into commercial action.
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Sawyer suggests putting attributable links to the highest-converting sales page at the bottom of the most-visited help center pages. They describe the chain as traffic to attention, attention to options, options to call to action, call to action to conversion, and conversion to revenue.
For brands planning a campaign
Useful for a tactical campaign aimed at support and help-center teams. It can become a short how-to or checklist for low-effort revenue experiments.
It gives a concrete method for turning raw customer comments into priorities, central to Sawyer's CX work.
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Sawyer outlines a three-step process for using customer feedback: download freeform customer comments from platforms such as Zendesk, Intercom, Salesforce, or Freshdesk; upload the text to an AI-powered word cloud tool to surface recurring phrases, sentiment, and top complaints or compliments; then prioritize fixes or double down on praised features. They say they have used the approach at two prior companies.
For brands planning a campaign
Good for a brief about voice-of-customer programs or AI-assisted feedback analysis. The named platforms and steps make it easy to turn into a workshop or guide.
It shows how Sawyer connects operational metrics, AI, training, and improvement into one balanced CX approach.
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Sawyer argues that problem-solving and experience should be synergistic, not competing priorities.
They focus on team training, including product expertise and five-star service; AI augmentation for self-service and context gathering; measuring baseline KPIs such as CSAT, FCR, and AHT before and after two weeks; and continuous improvement.
They offer a free customized action plan.
For brands planning a campaign
Relevant for campaigns about AI in support that also want to keep human experience quality visible. The before-and-after measurement detail supports a test-and-learn content angle.
From support center to customer experience operating model2
Support leadership diagnostics and first-30-days framework2
Customer feedback as an operational system1
Support as a revenue channel
Several posts argue that customer support conversations are an underused revenue source.
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One describes a scenario handling 30,000 monthly chats and emails, applying conversion tactics, generating about 1,500 additional purchases at roughly $50 each, or about $900,000 per year, while retaining 95% CSAT.
Another covers placing attributable links to high-converting sales pages on the most-visited help center pages.
Sawyer frames this as growth hacking and ties it to offsetting support costs.
Real-world-style numbers, step-by-step breakdowns, and executive-facing framing.
The figures come from Sawyer's own posts; ask for independent verification before treating them as performance results.
For brands planning a campaign
For a B2B SaaS campaign focused on support revenue, Buckley Sawyer can speak to concrete monetization mechanics: help-center placement, conversion attribution, and CSAT guardrails. They also show how to frame the business case for executives.
From support center to customer experience operating model
A seven-step post contrasts old support practices with new CX practices.
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The old side includes transactional KPIs, reactive problem solving, and one-size-fits-all service.
The new side includes experience-driven outcomes such as NPS, CES, and CSAT; empowered, proactive teams; personalization through CRM and AI; continuous feedback loops; cross-functional collaboration; root-cause resolution of pain points; and employee experience.
A second post answers how to balance problem-solving and experience: train teams on the product and on five-star service, use AI for self-service and context, measure baseline KPIs before and after two weeks, and keep improving.
Old-way-versus-new-way contrasts, numbered steps, and named KPI examples.
The posts are general playbooks and are not tied to a named employer or client.
For brands planning a campaign
Useful for a support-to-CX transformation campaign. Sawyer can articulate transition steps, metric choices, and organizational enablers for a B2B SaaS audience.
One post explains exporting freeform customer comments from platforms such as Zendesk, Intercom, Salesforce, and Freshdesk into CSV files, using an AI-powered word cloud to surface recurring phrases, sentiments, and top complaints or compliments, and then prioritizing what matters by frequency and urgency.
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Sawyer argues that most companies passively collect feedback but do not really use it.
Tool-specific steps and an AI-assisted feedback analysis process.
Ask for a case study or technical details if the campaign requires code or integration specifics.
For brands planning a campaign
Fits a voice-of-customer or CX analytics campaign. Sawyer can show concrete steps from data analysis to prioritization to cross-team use, helping a brand demonstrate practical support improvements.
Across posts, AI appears as a way to speed self-service, gather context for troubleshooting, personalize interactions, analyze customer feedback, and reduce human support interactions.
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One post claims implementation reduced the need for human support interactions by over 20%.
Another says training remains the most important support tool.
Sawyer links AI use to baseline metrics such as CSAT, first-call resolution, and average handle time.
Ties AI adoption to baseline metrics and team training rather than treating it as a standalone tool.
A self-reported 20% reduction in the need for human support interactions.
For brands planning a campaign
A B2B SaaS AI support campaign can use Sawyer for practical augmentation angles, including how to measure AI against service metrics and keep team training central.
Support leadership diagnostics and first-30-days framework
Two nearly identical posts list ten questions a support leader would answer in the first 30 days: whether the right KPIs are in place, whether the team is structured and empowered, what technology or systems are missing, which processes need improvement, any immediate red flags, wasted spend on tools or overtime, alignment with product and development, team morale, use of customer feedback, and top quick wins.
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A bonus question asks about top customer pain points. Sawyer supports the list with claims of having led departments of more than 100 people, scaled startups, built their own company, worked at enterprise SaaS companies, implemented AI, won an entrepreneurship award, and earned Help Desk Institute Support Center Director certification.
Numbered diagnostic questions, a bonus item, and an experience summary.
The two posts repeat the same list with minor wording changes; ask for verification of credentials if they are central to the campaign.
For brands planning a campaign
Useful for an executive-audience or leadership-content campaign. Sawyer can frame a diagnostic agenda for support leaders and connect it to operational ROI.
Several posts address job search and career transitions.
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One covers mental health during unemployment, the risks of leaning too heavily on loved ones, basic routines such as diet, sleep, and exercise, openness to therapy or medical help, and daily self-improvement.
Another advises showing personality in interviews rather than appearing like a polished robot.
A third reflects on 2024, expresses gratitude, and describes an ongoing search.
They state they are open to Director, VP, or Head roles in Customer Support or Customer Experience.
Personal narratives and advice lists.
This material is not directly about B2B SaaS support operations and may dilute a support-revenue campaign without framing.
For brands planning a campaign
This context matters for availability and tone. For a brand campaign, Sawyer may fit practitioner-perspective content, but they are positioned publicly as an active job seeker rather than a vendor or agency owner.
Posts typically use a bold hook, numbered or emoji-numbered lists, old-way versus new-way contrasts, specific dollar or metric examples, and a closing question to the audience.
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Hashtags cluster around customer support, CX strategy, support monetization, customer experience, and job search. Some posts repeat the same ten-question leadership list with only minor wording changes.
Listicles, contrast structures, and metric-led hooks.
Repetition across posts poses a risk for a multi-part campaign.
For brands planning a campaign
Sawyer can produce structured, list-driven educational content. For a multi-part campaign, ask for original examples to avoid repetition across posts.
In ten posts, Buckley Sawyer names no sponsor, affiliate, client, or disclosed partnership.
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Zendesk, Intercom, Salesforce, and Freshdesk appear as tools where support teams store feedback and run help centers, cited in descriptions of methods they used at past employers—not as advertised or disclosed commercial relationships.
They say they built their own company "from the ground up," led support departments of more than 100 people, and worked at enterprise SaaS companies, but do not name the business or employers.
Ask for those names to assess potential company or employer ties.
They also state that they are certified by the Help Desk Institute as a Support Center Director, a credential rather than a commercial tie.
Buckley Sawyer treats customer support as a commercial system: support conversations can generate revenue, customer feedback should drive priorities, and AI works best when it speeds up service and analysis rather than replacing trained teams.
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Numbered playbooks cover the shift from support to customer experience, a first-30-days diagnostic for support leaders, and feedback workflows using tools such as Zendesk, Intercom, Salesforce, and Freshdesk. A parallel strand offers job-search and career-transition advice, revealing the practitioner voice behind the operational writing.
Works where support and revenue operations meet: routing support inboxes, using AI for first-pass responses, and turning repeated service work into a defined process.
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Orlando G. focuses on HubSpot implementation and RevOps execution, showing how to build ticket queues and AI-assisted handoffs. Sawyer covers monetization numbers, CX strategy, and leadership diagnostics.
Makes customer feedback actionable through AI, connecting NPS, CSAT, and review data to analysis tools so teams can act on what they already collect.
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Ward writes from a product and vendor leadership position, announcing AskNicely tools and customer proof. Sawyer offers practitioner playbooks and diagnostic frameworks, often with self-reported revenue examples.
Explains customer success and CX concepts through practical questions, showing how to connect post-sale work to the outcome a customer actually bought.
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Okoyenta centers the customer success manager role, sales handoffs, and definitions such as CSAT. Sawyer focuses on support operations, support-to-CX transformation, monetization mechanics, and leadership diagnostics.
The posts suggest a content fit for B2B SaaS teams working on customer support, customer experience, customer feedback, and support-driven revenue.
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For campaigns targeting specific roles or industries, ask for documented audience survey results or another source identifying followers’ professional attributes.
Buckley Sawyer's posts do not specify sponsorship or brand-partnership formats.
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There is no published media kit, rate card, or sponsor policy, and none of the posts describe a paid partnership or sponsored placement.
They do advertise consulting and advisory work: several posts invite readers to message them for a free customized action plan, while others say they are open to a consultant or leadership role in customer support or customer experience.
These are service offers to companies, not creator sponsorship packages with defined deliverables, timelines, or pricing.
Buyers seeking a sponsored placement should ask directly what Sawyer would offer rather than assume a rate, content format, or review timeline.
A B2B SaaS company selling a customer support or customer experience platform can use Sawyer for practitioner-credible content that helps support leaders shift from cost-center thinking to revenue and experience outcomes.
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Their posts name the levers support leaders pull — experience-driven metrics such as NPS, CES, and CSAT instead of handle time alone, proactive pain-point resolution, continuous feedback loops, and alignment with product and development — and connect them rather than presenting separate tips.
A signature argument comes with a worked example: a team handled 30,000 chats and emails a month; about 5% of conversations produced an additional purchase of roughly $50 each, which they total to about $900,000 a year while holding 95% CSAT.
They also offer a specific tactic for this audience: add attributable links to a high-converting sales page at the bottom of the most-visited help center pages.
Their three-step feedback workflow names Zendesk, Intercom, Salesforce, and Freshdesk, tools a B2B SaaS support buyer uses.
A first-30-days diagnostic covering KPIs, team structure, missing systems, wasted spend, product alignment, morale, feedback use, and quick wins gives a campaign a ready-made assessment structure rather than generic thought leadership.
The content fits B2B SaaS support, CX, and customer-feedback teams.
The posts don't establish who follows them; ask for audience data if a match to a specific role, seniority, or region is essential.
When to choose a specialist
Two campaign needs require clarification.
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First, the posts document no sponsorship formats, media kit, or rate card, and no post discloses a paid partnership or sponsored placement.
They advertise consulting and advisory work instead: invitations to message Sawyer for a free customized action plan, and stated openness to a consultant or leadership role in customer support or CX.
A brand seeking a priced, scheduled creator placement should ask Sawyer to define the deliverables, timeline, and price.
Second, the figures they cite — $900,000 a year, 95% CSAT, and a reduction of more than 20% in the need for human support interactions — are self-reported, not independently verified.
The posts also don't establish the audience's roles or industries.
Ask for substantiation and audience data before relying on performance claims or a precise buyer match.
Consumer-facing or broad-reach lifestyle campaigns are a poor fit: the posts cover support operations, CX strategy, customer feedback, AI in support, and Sawyer's job search, not consumer products or lifestyle.
A worked campaign example
A worked angle for a campaign aimed at B2B SaaS support teams: a support platform runs a three-part series with Sawyer on treating support conversations as a revenue channel, then offers the series as one working resource.
Part one uses their $900,000 example to frame the opportunity and the CSAT guardrail, showing how an extra purchase can come from conversations a team already handles.
Part two walks through the help-center link tactic and how a support team can attribute its clicks.
Part three uses their three-step feedback workflow — collect freeform comments from Zendesk, Intercom, Salesforce, or Freshdesk; run an AI word cloud to surface recurring phrases, sentiment, and top complaints; prioritize by frequency and urgency — to show how a support team decides what to fix first.
The companion resource is a support-revenue audit built from their first-30-days diagnostic questions.
The brand supplies a completed example from its own customers plus a blank version a support leader can fill in at their own company, so the tool stands on its own outside the series.
Where the angle leans on Sawyer's numbers, label them as Sawyer's reported figures, not audited results, and confirm with them that the figures still reflect their current position before publishing.
The posts document no sponsorship or service format, so agree the deliverables, usage rights, and timing in writing before the campaign starts.
Choose Tony Ward for a campaign about using AI to turn customer feedback into action.
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In one post, they describe bringing NPS, CSAT, and review data into Claude so teams can ask questions across customer information; in another, they introduce agents that surface CX trends and help teams respond to feedback. These examples give a brand a direct feedback-and-AI story.
The examples focus on AskNicely tools and feedback workflows.
For a story about support-led revenue, help-center conversion, or a broad support-leadership diagnostic, Buckley Sawyer’s posts are a closer fit.
Choose Anurika Okoyenta for a campaign about post-sale customer outcomes.
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Her post urges customer success managers to learn why a customer bought, validate the intended outcomes during handoff, and avoid defaulting to feature demonstrations.
A separate post explains how CSAT can help teams spot satisfaction, risk, and potential advocates.
Together, these ideas suit a campaign about onboarding and customer success planning.
The examples emphasize account outcomes and customer success, not support-team operations, help-center conversion, or support-led revenue.
Ten LinkedIn posts attributed to Buckley Sawyer were observed on October 9, 2026.
The posts cover support-to-customer-experience transformation, support monetization, customer feedback workflows with tools such as Zendesk, Intercom, Salesforce, and Freshdesk, AI in support, a first-30-days support leadership diagnostic, and job-search and career-transition reflections.
The posts do not say when individual posts were published, so this page does not assert those dates.
Performance figures such as a reported $900,000 annual support-revenue example and a reported 20% reduction in the need for human support interactions are self-reported in the posts and are not independently verified.
No books, shows, other channels, media kit, rate card, sponsor disclosures, or audience data are published in the posts here.