Annie Dean

A strong CS leader, they say, works with the CEO, COO, and peers to fix core business problems, using customer data to make the case.

• The post takes three common complaints — selling to the wrong buyers, a bad product, and bad pricing or packaging — and lists what CS leaders can contribute to each, grounding the argument in specific behaviors rather than a general plea for a seat at the table.
• The closing is blunt: if you did all this and were still laid off, you are probably better off; if you did not, change the story you tell and focus on what you can control.

Against “we were selling to the wrong people,” the post lists ways CS can help: share success-plan data to sharpen value propositions, analyze customers with the highest and lowest lifetime customer value, give sales enablement discovery questions that screen out bad fits, work with sales ops to hold teams accountable for deals that meet the criteria, and align compensation with CAC payback goals.

• For “product was bad,” it recommends modeling the cost of not building what customers need, joining roadmap planning to validate with customers and support UAT, limiting sales demos to shipped features, and setting escalation procedures.
• For bad pricing, it calls for an annual cross-functional review using customer data and laying out the tradeoffs of usage-based pricing, per-employee pricing, and a platform fee plus services before leadership accepts the churn risk.

Read original

Rather than asking whether CS headcount can be justified, they ask what happens to expensive software development if customers never use what gets built.

• In B2B technology, building something does not mean customers will come and use it, they argue, so companies should plan resources for the work that turns a release into adoption.
• More substantial and frequent releases require more capacity; CS enablement, the post says, is the difference between low adoption of new features and a full return on the engineering team's effort.

The post spells out what added capacity pays for: training CSMs on upcoming changes, updating customer education materials, and telling customers about changes before they ship so they can prepare their own end users.

Read original

In ed-tech, the question was whether people learned and had better career outcomes; in workforce safety, whether injuries declined; in health-tech, whether people had better health and well-being outcomes.

• Not every product has such a clear correlation, Dean notes, and many customer success managers struggle to find the right measures.
• In their current social-sector role, they are building a first client success function and working out how to measure efficacy when separating causation from correlation is difficult and objective data is hard to reach.
• The post distinguishes solid data on teaching quality, subjective feedback, and small local studies from statistical proof of system-level change.

In domestic abuse cases involving children, dozens of agencies can be involved, while coercive control can play out over years amid changing circumstances such as marital status and custody.

• That makes it hard to isolate the organization's impact.
• Dean points to research from Foundations – What Works Centre for Children & Families' REACH five-year plan as a useful roadmap for good research in the field.

The measurement questions carry across sectors, but the setting has changed: from technology products with relatively clear outcome measures to social-sector work across twelve countries, where the organization cannot yet prove system-level impact statistically.

Read original

The session signals a priority: where CS sits in the revenue organization. Dean shares the stage with a revenue operations co-speaker rather than presenting alone.

The post announces a session titled “How to put the rev back in RevOps,” delivered at OpsStars with Matthew Volm, and tagged to CS ops, sales ops, LeanData, and RecastSuccess. It links to the session but does not summarize what was said on stage.

Read original

The origin story is a household that communicated in American Sign Language and growing up as the youngest of four, with three differently abled and multicultural adopted siblings. Dean credits that experience with a focus on making people feel included, heard, and supported.

Dean describes working at large technology companies and as a wingman to founders scaling their businesses, co-founding and running a company with Michi Hu Pezeshki, and being part of four exits they call successful-ish; their own company was not one of them. The post also notes that they have been talking about customer success less lately because they have been in the trenches, standing up another CSM team.

The subject matter has shifted from technology-sector customer success to social-sector client success work. Dean says their posting is a little erratic and that customer success has featured less recently.

Read original

A newcomer should start here because it lists specific moves across sales, product, and pricing rather than describing a mindset.

Annie Dean pushes back on customer success leaders who describe themselves as victims of broken segments, then walks through what the alternative looks like in practice.

• Against “we were selling to the wrong people,” the post lists sharing data from success plans to sharpen value propositions, analyzing customers with the highest and lowest lifetime customer value, arming sales enablement with discovery questions to screen out bad fits, working with sales ops on accountability for deals that meet the criteria, and aligning compensation with CAC payback goals.
• Against “product was bad,” it describes prioritizing and estimating needed engineering changes, building a model of the cost of not building what customers require, joining roadmap planning with data-driven priorities and customer access for validation and UAT, keeping sales demos to shipped features, partnering with DevOps and QA on release checks, and setting escalation procedures so bugs are handled constructively.
• Against “pricing or packaging changes sucked,” it describes an annual cross-functional review of price, packaging, and product ideas using customer data, presenting tradeoffs of models such as usage-based pricing, PEPY, and platform fee plus professional services, and adjusting comp plans and territories after leadership accepted the churn risk.
• It closes bluntly: if you did all of this and were still laid off, you’re probably better off; if you didn’t, change your story and focus on what you can control.

For brands planning a campaign

For a brief about customer success and revenue operations alignment, this is the clearest evidence of what an advisory engagement would cover: diagnosing which of three failure modes a company has, then identifying the cross-functional interventions that make CS a partner rather than a complaint channel. It’s a post, not a talk, so use it to shape a proposed session and ask for the underlying case details and results.

It takes a minute to read and lays out the business case in Dean’s own terms.

The argument is that software development is expensive and unused software wastes that money.

• Dean says that in B2B technology, building it doesn’t mean customers will come and start using it, and that resources should be planned to train CSMs on coming changes, update customer education materials, and communicate changes to customers before release so they can prepare their own end users.
• The more substantial and frequent the code releases, the more resources are needed.
• The post frames CS enablement as the difference between low adoption of new features and full return on the engineering team’s effort.

For brands planning a campaign

Use this as the one-slide business case for a CS enablement engagement tied to a product release calendar. The post asserts a relationship between release cadence and enablement capacity but doesn’t show a sizing model, so ask for one.

Start here if the question is measurement rather than tactics: it works through the difficult version of the problem instead of citing easy metrics.

Dean traces efficacy measurement across sectors: in ed-tech, did people learn and have better career outcomes; in workforce safety, did fewer injuries occur; in health-tech, did people have better health and well-being outcomes.

• The post notes that not every product has such a clear correlation and that many customer success managers struggle to find the right measures.
• In their current social-sector role, Dean is building a first client success function for 2026 and working out how to measure the efficacy of products and services, where separating causation from correlation is hard and objective data is hard to access.
• In domestic abuse cases involving children, dozens of agencies can be involved, and coercive control can play out over years amid changing dynamics such as marital status and custody.
• Dean says the organization has robust data on the quality of its teaching and a large amount of subjective evidence that the material is meaningful and helpful, plus some small local studies, but that it’s difficult to statistically prove impact on system change across the 12 countries where they work.
• The post points to research from Foundations – What Works Centre for Children & Families' REACH five-year plan as a useful roadmap for what good research in the field can look like.

For brands planning a campaign

This is the strongest evidence for an engagement about measuring product efficacy: Dean works through weak attribution, long time horizons, and multiple agencies rather than claiming clean proof. Ask for a session on designing an efficacy framework when attribution is weak, applied to your own success-plan data.

It points to the speaking context; ask for the session itself.

Dean announces a session at OpsStars with Matthew Volm titled “How to put the rev back in RevOps,” tagged to CS ops, sales ops, LeanData, and RecastSuccess. They say it covers what customer success wishes marketing ops, sales ops, and general RevOps knew; the substance is in the session.

For brands planning a campaign

Confirms Dean has presented on CS and RevOps alignment to an ops audience and can be paired with a revenue operations co-speaker. Ask for the recording or slides before promising specific content from that session.

Useful background before reading the work.

Written on reaching 7,000 LinkedIn followers, this is the closest thing in the set to a career narrative.

• Dean says English was not their first language despite being born in the United States, that their family communicated in ASL at home, and that they are the youngest of four, with three differently abled and multicultural adopted siblings.
• They credit these experiences with shaping their focus on making people feel included, heard, and supported, and on clearing obstacles so others can move forward.
• They describe a career that looks fragmented on paper but has one thread: helping people build better lives through learning and technology, and helping organizations create the conditions for people to thrive.
• They have worked at large technology companies and as a wingman to founders scaling their businesses, co-founded and ran a company with Michi Hu Pezeshki, and been part of four exits they call successful-ish, while their own company was not one of them.
• Dean says they talk about customer success less lately because they have been in the trenches standing up another CSM team.
• On the personal side, they married their high school boyfriend at 18, have been together nearly 30 years, have two children aged 24 and 15, feel the squeeze of the sandwich generation, and garden and paddle board despite not being especially good at either.
• It ends by inviting readers to share a fun fact.

For brands planning a campaign

The best source for a short speaker bio or introduction.

• The wingman-to-founders work and four exits give a brand hooks beyond CS tactics, such as a session on building a CS function inside a scaling startup.
• Since it’s self-description, verify employers and exits against other sources before publishing a bio.

One post works through three scenarios—selling to the wrong buyers, a weak product, and poor pricing or packaging—and lists what the CS leader can do about each: share success-plan data to sharpen value propositions; analyze highest- and lowest-lifetime-value customers to give sales enablement disqualifying discovery questions; work with sales ops on accountability for deals that fit; align compensation to CAC payback; model the cost of not building needed product changes; feed roadmap planning with customer validation; and set escalation procedures so bugs reach customers less often. The post also tells laid-off CS leaders who did this work that they are 'probably better off' and urges them to change the story they tell rather than play the victim.

A scannable LinkedIn checklist pairs each failure with a concrete contribution under a cross-mark, showing specific behaviors rather than making a general plea for a seat at the table.

Annie Dean acknowledges the post may 'catch heat' and argues bluntly that some CS leaders who did the work and were still laid off may simply be better off elsewhere—a pointed position, not a neutral endorsement.

For brands planning a campaign

A good fit for a customer success platform, sales enablement, or RevOps vendor looking for a speaker to frame CS as a revenue and product-feedback function.

• A talk could build on the three failure scenarios and cross-functional fixes.
• The post is an argument, not a case study with named clients.

Examples: Source 1

The post is a short announcement that tags LeanData and RecastSuccess and links to the session, rather than summarizing what was said on stage.

Annie Dean's post gives only the session topic. Ask for the session arguments and examples before attributing anything beyond that framing to it.

For brands planning a campaign

A joint CS-and-RevOps session or panel is the natural format, and co-presenting with a RevOps figure is consistent with Annie Dean's previous appearances. Ask for the session outline; the posts do not describe its content.

Examples: Source 1

The post spells out what added capacity pays for: training CSMs on what's changing, updating customer education materials, and telling customers about changes before they ship so their end users can prepare.

• More substantial and frequent releases require more resources.
• In this framing, CS enablement turns engineering effort into adoption and a full return on that investment.

Reverses the usual budget question: instead of asking whether CS headcount can be justified, it asks what happens to engineering spend if adoption never follows.

For brands planning a campaign

Strong fit for onboarding, in-app adoption, or customer-education vendors, and a concrete argument to reuse in a webinar or talk for product and CS leaders setting headcount. The claim is a business rationale, not a measured result; pair it with campaign data.

Examples: Source 1

Now working in the social sector, they are standing up a first Client Success function for 2026 and working through how to measure efficacy in a genuinely complicated context: domestic abuse cases involving children, dozens of agencies, coercive control experienced over years, and changing circumstances such as marital status and custody.

• The post distinguishes solid data showing that the learning programs teach well, along with subjective feedback and small local studies, from statistical proof of system change across the twelve countries where the organization works.
• It points to the REACH five-year research published by Foundations – What Works Centre for Children & Families as a model of good research in this field.

Annie Dean says the organization cannot yet prove system-level impact statistically, and identifies correlation versus causation and access to objective data as unresolved problems.

For brands planning a campaign

Relevant for research, evaluation, or impact-measurement vendors, and for anyone briefing a talk on measuring outcomes when attribution is hard. The candid gap analysis is the selling point; ask for a finished case study with a clean number before presenting one.

Examples: Source 1

The post covers an ASL-speaking household and growing up as the youngest of four with three differently abled and multicultural adopted siblings; work at big tech companies and as a wingman to several founders; co-founding and running a company with Michi Hu Pezeshki; being part of four successful-ish exits while their own company was not one; and currently standing up another CSM team. They also say they post a little erratically and have been talking less about customer success lately because of time spent in the trenches.

Uses a follower milestone to introduce a personal reintroduction, mixing professional history with family and hobbies such as gardening and paddle boarding.

For brands planning a campaign

Useful for employer brand, inclusion, or founder-support campaigns where a personal narrative carries weight.

• Annie Dean says they post erratically and have recently talked less about customer success while spending time in the trenches.
• Ask about publishing cadence and current subject matter before planning a campaign around regular CS content.

Examples: Source 1

The post tags LeanData and RecastSuccess as hashtags.

View example

The post focuses on measuring whether those programs make a difference.

View example

Likas argues that leaders do not know where their team's time goes and that packed calendars are not a quality measure.

• That mirrors Annie Dean's argument that CS leaders should bring customer evidence, not complaints, into business decisions.
• Both write scannable LinkedIn posts that turn a planning problem into a short set of questions.

Likas writes about the sales and RevOps system itself — AI pilot design, meeting-quality analysis, product-centered operating models — and promotes Nektar, the company behind the meeting-data argument. Annie Dean writes about customer success as a cross-functional partner and whether a product helped the people it was built for; the posts contain no comparable vendor pitch.

Read original · Original 2

Aleman's post on hiring ten reps to add ten quotas and Annie Dean's post on scaling CS headcount with product and engineering make the same point: the spreadsheet assumes capacity that does not exist until someone does the enabling work. Both write blunt, example-first paragraphs for operators rather than executives reading a summary.

Aleman stays on sales capacity and forecast risk — ramp curves, territory cuts, pipeline inspection, board surprises — with examples rooted in sales-floor mechanics. Annie Dean focuses on customer success, adoption, and outcome measurement, with examples of cross-functional contributions to product roadmap, packaging, and buyer fit.

Read original · Original 2

Brady argues that fixing attribution and data hygiene first still delivers leads to reps who cannot convert them, and that dashboards surface symptoms while behavioral patterns cause outcomes.

• That is close to Annie Dean's argument that CS leaders should bring customer evidence into decisions instead of reporting on them.
• Both write long-form LinkedIn arguments that pose a question and answer it with a chain of concrete consequences.

Brady writes about sales enablement and pitches a revenue-intelligence product, naming Luster and Predictive Enablement.

• Their posts run longer and stay within the sales cycle.
• Annie Dean writes about post-sale customer success, with posts that mix shorter checklist posts and a personal reintroduction.

Read original · Original 2

A strong example is an account-level analysis of a top-1,000 customer set, segmenting churned, renewed, and expanded accounts and comparing where influential stakeholders engaged, then rebuilding playbooks around the meeting types the data links to outcomes.

• Another post applies the same operating-model lens to AI and transformation work: pilots succeed with dedicated resources and contained use cases, so a successful pilot proves little about real conditions.
• The useful move is to understand how work gets done today, where the friction is, and what the company is willing to change before deciding where AI belongs.
• Pick this alternative if the engagement should end in a measurement layer or an operating-model decision, and if the company already has or plans to buy granular engagement data.

The measurement argument arrives attached to a product.

• In the post, the method runs through Nektar, which the post says provides granular meeting and stakeholder insight, and closes by inviting readers to send a direct message to learn how Nektar can help with planning season.
• Buyers seeking tool-neutral advice should expect a session shaped around evaluating that capability.
• Their posts do not address customer success team building, CSM enablement, or CM training against product releases—the core need for a campaign aimed at them.
• Buyers trade subject match for stronger revenue-engagement analytics and give up the cross-functional CS narrative.

Examples: Source 1 · Source 2

One post directly critiques adding headcount to a revenue target: ten new reps at a $1M quota is arithmetic, not capacity, because ramp curves, pipeline supply, front-line manager span, and territory carved out of the patches of reps already carrying the number all change the outcome.

• Another argues that boards tolerate a miss but not a surprise, and that risk signals should come from observed behavior rather than a rep voluntarily marking a deal at-risk: close dates pushed twice, late-stage opportunities with nothing on the calendar, buyers who used to reply same-day going quiet, or legal not having seen paper two weeks out.
• This is a good fit when the deliverable should be pipeline inspection rules or a written critique of next year's hiring plan, and the audience is sales and RevOps leadership.

Both posts focus on sales and forecasting.

• Their posts do not address customer success, onboarding, adoption of newly shipped features, CSM enablement, or measuring product efficacy, so a session on scaling CS and aligning it with RevOps would draw on adjacent forecasting material rather than demonstrated work on the topic.
• Buyers trade subject match for sharper forecast mechanics.
• Their posts also offer no evidence of a workshop, teaching, or speaking format; agree on the format directly against the buyer's agenda.

Examples: Source 1 · Source 2

One post follows a prospect conversation in which “we need a quarter or two to fix data, lead routing, attribution, and CRM adoption” gets carried forward two quarters, leaving the company with a perfect system delivering leads to reps who still cannot convert them, a longer sales cycle, stale collateral, and an account management team hiding behind organizational change instead of closing proficiency gaps.

• Another post makes the same case about revenue leaks: companies with full stacks of CRM, LMS, CMS, call intelligence, and AI tools still report missed quotas and pipeline surprises because the tooling surfaces symptoms and stops at visibility.
• This is the better choice when the campaign shifts toward sales enablement and rep proficiency, or when the session needs a behavioral revenue-intelligence framing that predicts risk before pipeline deteriorates.

Their posts argue from the sales and enablement seat, not from customer success.

• They do not describe CS enablement sizing against release cadence, a product-release communication plan, or a method for measuring efficacy when causation is hard to isolate—the focus of a campaign aimed at them.
• The likely internal sponsor is sales enablement and revenue leadership rather than customer success leadership.
• The posts also speak on behalf of a platform, Luster, and name Predictive Enablement as its category, so a session may carry tool framing.
• Ask directly about audience and session format, and whether they offer teaching or workshop engagements; the creator describes a background as a salesperson rather than an advisory practice.

Examples: Source 1 · Source 2