Маркетинг в AI-эпоху: почему старые SaaS-плейбуки больше не работают

SUMMARY

Lena Shenkarenko, ex-Product Marketing Leader at Miro and Head of Marketing at Rask.ai, discusses how AI transforms SaaS marketing, why traditional playbooks fail, and lessons from Miro's early growth and PMF signals.

STATEMENTS

Miro started in 2011, iterating on approaches before Lena joined in 2017 when the team was around 50 people and Product Market Fit was just emerging.
Early Miro emphasized maximum attention to users across all functions, with zero tolerance for suboptimal experiences in design, engineering, support, and marketing.
At Miro, everyone used the product daily, testing features and providing feedback, fostering deep involvement but potentially introducing cognitive biases.
Rapid company growth requires constant adaptation, as processes built today may need overhaul in 6-8 months due to nonlinear market and user dynamics.
Balancing flexibility with structured decisions is crucial, avoiding chaos while building scalable systems that age well.
In Miro's early stage, the team learned extensively from users about frameworks and rituals, focusing on empathy to understand workflows.
User feedback collection involved direct interactions: all relevant team members talked to users live, observed screens, and visited offices to see real usage.
Regular weekly calls with users were standard, ensuring ongoing adaptation to audience changes without relying solely on second-hand insights.
Prioritize feedback from relevant paying users aligned with the core use case, while filtering vocal minorities and irrelevant noise.
Engage silent users, like those who churn without feedback or give low NPS scores, to uncover hidden issues and improve retention.
Miro experienced hockey-stick growth from 2017-2018, but COVID in 2020 caused explosive scaling from 250-300 employees to 1,000 by year-end.
During COVID, Miro adapted by launching user education webinars, tips sessions, and a "60 fixes in 60 days" program to address backlog issues for new and loyal users.
COVID created a product-market fit with the world, shifting from tech-savvy users to broader audiences needing simple online collaboration amid remote work.
True Product Market Fit signals include sustained demand growth, strong retention, and effective monetization forming a predictable, scalable business model.
In AI startups, rapid ARR like $6M often indicates hype rather than stable PMF, as predictions based on initial growth fail when novelty fades.
AI has commoditized many tools, accelerating product life cycles and making differentiation harder amid constant innovation and big tech integrations.
Traditional SaaS marketing playbooks from pre-AI era, like standardized conferences and predictable stacks, are less relevant in the fast-changing AI landscape.
Early AI growth at Rask.ai leveraged AI hype and voice cloning tech for viral wow-effect, targeting creators and prosumers before shifting to business users.
Prosumers drive awareness and UGC but offer low monetization and retention; balance them with stable SMB and midmarket audiences for sustainable growth.
AI enables democratizing premium features for midmarket, like affordable voice dubbing, previously inaccessible due to high costs in translation and production.

IDEAS

Zero tolerance for poor user experiences permeates every aspect of a company, from product design to marketing campaigns, creating a culture of relentless empathy.
Daily product usage by the entire team builds authentic storytelling but risks internal biases that overlook how external users perceive it as just another app icon.
Startups evolve every 4-6 months during hypergrowth, forcing abandonment of "perfect" processes for adaptive, nonlinear strategies that prioritize real-time market signals.
Direct, live user interactions—screen shares, office visits—reveal raw pain points far better than filtered research summaries from dedicated teams.
Churned or silent users hold the most critical insights; proactive re-engagement uncovers systemic issues missed by vocal advocates.
COVID's remote work boom turned niche tools like infinite canvases into global necessities, but overwhelmed new users with complexity amid emotional stress.
Explosive scaling during crises demands "non-stop marathons" of fixes, education, and communication, blending product, design, and marketing efforts seamlessly.
PMF isn't a checklist but an unmistakable convergence of acquisition, retention, and revenue; doubting it means it's absent.
$6M ARR in AI often masks hype-driven spikes rather than enduring fit, as novelty wanes and competitors iterate faster.
AI floods markets with undifferentiated tools, shifting user behavior to rapid trials based on fleeting factors like price or momentary quality.
Established SaaS leaders lose ground as AI eliminates workflow stages, commoditizing features once central to differentiation.
Product life cycles have shortened dramatically with AI, from years to months, demanding constant expansion or reinvention to avoid obsolescence.
Pre-AI B2B marketing became rigid and predictable, stifling innovation; AI's chaos levels the field, forcing even veterans to learn from scratch.
Marketing generalists thrive in AI era, handling user talks, positioning, and launches holistically, unlike siloed pre-AI roles.
Delegating execution after analysis is outdated; top marketers now test demos, landers, and positioning directly to drive impact.
AI hype created "magic" perceptions around voice cloning, enabling viral demos but hard to replicate without perfect timing and quality.
Targeting prosumers accelerates awareness via UGC and ambassadorship but risks unstable revenue; they're viral engines, not reliable payers.
Midmarket SMBs represent untapped AI potential, gaining access to enterprise-grade tools at affordable scales through democratization.
Organic social requires a "mini-factory" of creatives for quick experiments, but it's slow to scale compared to paid channels.
Single-channel dependency is a vulnerability; diversify experiments across relevant formats to build resilient acquisition.
Test raw, AI-generated creatives at volume to signal winners before polishing, avoiding sunk costs on unvalidated ideas.
Founder ego often leads to building for personal taste; suppress it with user experiments to align on resonant messaging.
Cultural adaptations, like simplifying "localization" for non-experts or plain English for non-native markets, boost conversion over elegant jargon.
Speed trumps perfection in AI markets; minimum viable tests reveal demand faster than months-long campaigns.
Balanced channel strategies prevent over-reliance, ensuring growth isn't solely budget-tied or algorithm-vulnerable.

INSIGHTS

Cultivating company-wide user empathy as a lived practice, not just a poster value, fosters authentic products that users intuitively trust and adopt.
Hypergrowth demands embracing impermanence in processes, viewing every build as temporary scaffolding for nonlinear evolution rather than permanent infrastructure.
Prioritizing direct, frequent user dialogues over abstracted insights humanizes product development, catching nuances like frustrating pop-ups in real-time.
Silent dropouts represent the majority's unmet needs; targeted re-engagement turns potential losses into retention goldmines.
Crises like COVID amplify prepared foundations but expose scalability gaps, rewarding adaptive education over rigid feature ships.
PMF emerges as a holistic equilibrium, not isolated metrics; its absence breeds overconfidence in hype, leading to post-peak crashes.
AI's proliferation erodes tool loyalty, commoditizing features and forcing focus on ephemeral user trials over deep entrenchment.
Shortened life cycles in AI necessitate proactive pivots, treating peaks as preludes to reinvention rather than endpoints.
Rigid pre-AI playbooks stifled creativity; AI's disruption democratizes success, rewarding versatile generalists over specialized veterans.
Viral prosumers fuel initial traction but undermine economics; integrate them as awareness amplifiers for stable business segments.
Democratizing elite capabilities via AI unlocks midmarket potential, bridging affordability gaps once barred by legacy costs.
Diversified, experimental channel portfolios build antifragile growth, mitigating risks of algorithm shifts or budget constraints.
Raw testing precedes polish; validating concepts with imperfect prototypes conserves resources for proven winners.
Suppressing founder biases through user-centric experiments aligns offerings with actual resonance, avoiding self-indulgent mismatches.
Cultural and linguistic humility in messaging—simplifying for accessibility—drives broader adoption than sophisticated but opaque communication.

QUOTES

"максимальное внимание к пользователям... нулевая толерантность к плохому, неправильному опыту без разницы, о чём мы говорим."
"когда ты так много пользуешься своим продуктом... у тебя, конечно, есть некое когнитивное искажение, потому что пользователи... для них он просто один из ярлычков на рабочем столе."
"по факту, когда стартап растёт... все те вещи, которыми вы сейчас... тратите... придётся буквально через... 6-8 месяцев... перепридумать, выбросить."
"ты никогда не спутаешь... есть у тебя product market fit или нет. И как правило, если ты задаёшься этим вопросом, значит его ещё нет."
"$6M ARR больше не значит PMF... это был не продукт Market Fit, а условно какая-то волна хайпа, которая схлынула."
"AI в этом смысле всё очень сильно перевернул и поломал... условный человек с тридцатью годами опыта... пытается понять from scratch, как ей двадцатилетний выпускник."
"не надо нанимать людей до того, как мы что-то протестировали и поняли, что это может скейлиться."
"выигрывают сейчас на рынке те, кто доставляют ценность быстрее других... не протестировав изначально... намного меньшем масштабе."
"своё эго надо очень сильно принижать... нужно идти пробовать разные вещи, чтобы понять, а что нравится нашим пользователям."
"просюмеры... суперлёгкие на подъёмы... но... вышли новый... они очень легко переключатся."

HABITS

Engage directly with users weekly via calls, screen shares, or office visits to observe real workflows and gather unfiltered feedback.
Test all new features internally as a team, sharing use cases and critiques to ensure broad involvement in product evolution.
Prioritize relevant paying users' input while systematically re-engaging churned or silent ones through targeted outreach.
Launch rapid education initiatives like webinars and tip sessions during scaling to onboard diverse audiences smoothly.
Maintain a change log and internal communications to keep teams aligned on fixes and updates amid hypergrowth.
Experiment with multiple marketing channels early, testing raw concepts before committing resources to specialists.
Suppress personal biases by running user experiments on messaging and creatives, adapting to what resonates empirically.
Balance organic and paid efforts, building a "mini-factory" of creatives for quick social signals without over-reliance.
Focus on speed by validating minimum viable tests first, polishing only after confirming demand.
Democratize premium features for midmarket by simplifying access, avoiding enterprise-level complexities.

FACTS

Miro was founded in 2011, with Lena joining in 2017 when the team numbered about 50 and PMF was emerging after years of iteration.
During COVID, Miro's employee count surged from 250-300 in February 2020 to 1,000 by year-end, driven by remote work demands.
Rask.ai reached $6M ARR in its first year, fueled by AI voice cloning hype in late 2023.
Pre-AI, design tools like Sketch dominated for 4-5 years before generational shifts to Figma; AI accelerates such cycles to months.
97-98% of bloggers fail to monetize content due to lacking business methodology, budgets, and systematic approaches.
AI enables voice dubbing that once required translators, voice actors, studios, and editors, previously inaccessible to midmarket.
Post-COVID expectations linger, with growth benchmarks still inflated by 2020-2022 online surges, contributing to layoffs.
Big tech like Microsoft and Google integrate AI features, commoditizing startups with each major release like ChatGPT updates.

REFERENCES

Miro: collaborative whiteboard tool, infinite canvas product.
Rask.ai: AI voice cloning and dubbing platform.
Figma: design tool that displaced Sketch.
Lucid: competitor in visual collaboration space.
Microsoft and Google whiteboards: integrated tools entering the market.
ChatGPT: AI model causing rippling effects on startups.
Sketch: former design tool leader.
Intercom, Salesforce, Zoom: standard B2B SaaS marketing stack.
Lavable: AI product example of explosive growth.
Hicksfield, Klangi, Nanobunny: AI creation tools driven by prosumers.
Cursor: AI coding tool mentioned in adoption context.

HOW TO APPLY

Build a culture of zero-tolerance for suboptimal user experiences by reviewing all decisions through an empathy lens across teams.
Mandate daily product usage for all employees, followed by shared feedback sessions to catch biases early.
Schedule weekly direct user interactions for relevant team members, focusing on live observations to inform iterations.
Create a dedicated community team to bridge product and users, organizing events and content generation with ambassadors.
During scaling crises, compile a backlog of fixes and launch accelerated programs like "60 fixes in 60 days" with cross-team involvement.
Monitor PMF through balanced metrics: track acquisition, retention, and monetization convergence for predictable signals.
Shift from prosumer virality to midmarket stability by using UGC for awareness while prioritizing SMB procurement processes.
Experiment with 3-5 channels simultaneously at small scales, using raw AI-generated creatives to identify winners quickly.
Avoid early specialist hires; test channels with core team or part-timers first to confirm scalability before committing.
Test messaging variations empirically, simplifying terms like "localization" based on user comprehension in target markets.

ONE-SENTENCE TAKEAWAY

AI disrupts SaaS marketing, demanding user empathy, rapid experimentation, and balanced PMF over hype-driven growth.

RECOMMENDATIONS

Foster company-wide user obsession by integrating direct feedback loops into every role and decision.
Embrace process impermanence in hypergrowth, rebuilding systems quarterly to match nonlinear market shifts.
Prioritize live user dialogues over surveys to uncover authentic pain points and refine experiences.
Re-engage churned users proactively to extract insights from the silent majority.
Prepare for explosive scaling with education-focused adaptations during external shocks.
Validate PMF holistically before scaling, avoiding over-reliance on initial ARR spikes.
Target prosumers for viral awareness but pivot to midmarket for sustainable revenue.
Diversify acquisition channels early to build resilient, non-dependent growth engines.
Test raw prototypes at speed, polishing only validated concepts to conserve resources.
Suppress founder biases with user experiments, adapting messaging to cultural and linguistic realities.
Democratize premium AI features for SMBs to capture untapped affordability-driven demand.
Hire generalists in AI era, empowering them to own end-to-end from research to execution.
Avoid single-channel focus; experiment across formats relevant to your audience.
Balance organic experimentation with paid scaling for antifragile acquisition.
Focus on speed over perfection, launching minimum viable tests to outpace competitors.

MEMO

In the whirlwind of AI's ascent, traditional SaaS marketing playbooks—those reliable scripts of conferences, standardized stacks like Intercom and Salesforce, and predictable growth trajectories—have crumbled. Lena Shenkarenko, who shaped product marketing at Miro from its 2017 inflection point and later led efforts at Rask.ai, a voice-cloning AI startup that hit $6 million in annual recurring revenue within its first year, illuminates this shift. Joined in 2017 when Miro's team hovered around 50, amid the first glimmers of product-market fit after years of quiet iteration since 2011, Shenkarenko witnessed a company obsessed with users. Zero tolerance for subpar experiences defined everything, from design tweaks to support interactions, embedding empathy as a core operational principle rather than mere wall art.

This user-centric ethos propelled Miro's pre-pandemic hockey-stick growth, but COVID-19 in 2020 supercharged it into chaos. Employee numbers ballooned from 250 to 1,000 in months, as remote work turned the infinite-canvas whiteboard from a niche tool for tech-savvy teams into a global lifeline for connection amid isolation. Yet, this "product-market fit with the world" strained the platform: loyal power users demanded advanced features, while newcomers fumbled with its complexity, venting frustration in a heightened emotional climate. Miro responded with a blitz of webinars, tips sessions, and a "60 fixes in 60 days" marathon, drawing on cross-functional teams to educate and iterate relentlessly. Shenkarenko notes this period's duality—exhausting yet formative, forging resilience through daily reinvention.

True product-market fit, Shenkarenko argues, isn't a debated milestone but an undeniable convergence: surging demand, sticky retention, and viable monetization forming a scalable model. Doubting its presence signals its absence. In AI's era, however, $6 million ARR often masquerades as fit, propelled by hype rather than endurance. Rask.ai's rapid rise exemplified this, riding 2023's AI fervor where voice cloning felt like magic, captivating creators with realistic dubs that once required costly ensembles of translators and actors. Viral demos sparked prosumer buzz, generating user content and ambassadorship, but Shenkarenko warns of pitfalls: these audiences drive awareness cheaply yet churn easily, lacking budgets for sustained revenue.

AI has commoditized the software landscape, flooding markets with undifferentiated tools and slashing product life cycles from years to months. Established players like Figma, once unchallenged, now face obsolescence as big tech integrates features, eliminating workflow stages overnight. Users trial apps impulsively, swayed by price or fleeting quality, eroding loyalty. Shenkarenko reflects on her Miro playbook—honed for stable B2B verticals—now shelved, as rigid pre-AI marketing stifled innovation. The chaos levels the field: veterans and newcomers alike grapple from scratch, fostering generalists who blend user insights, positioning, and launches without silos.

For early-stage AI founders, Shenkarenko urges ditching extremes: neither pure organic reliance nor budget-fueled paid floods suffice. Organic social demands a "mini-factory" of creatives for quick signals but scales slowly; paid risks tying growth to volatile spends. Diversify across 3-5 relevant channels, testing raw AI-generated variants to validate before polishing. Avoid early specialist hires—prototype with core teams or advisors first to confirm scalability, preventing misaligned talent drains. Speed is paramount: markets reward rapid value delivery, so minimum viable tests outpace months-long campaigns marred by perfectionism.

Founder ego often blinds, assuming personal appeal mirrors user needs; Shenkarenko advises suppressing it through experiments, simplifying jargon like "localization" for clarity and adapting English for non-native contexts like the Emirates. Target prosumers for virality but anchor monetization in midmarket SMBs, where AI democratizes elite tools—affordable dubbing unlocks segments once priced out. This balanced pivot, blending hype with stability, sustains beyond novelty.

Shenkarenko's journey—from Miro's empathetic scaling to Rask.ai's hype navigation—underscores AI's humbling reset. Post-COVID benchmarks linger, inflating expectations amid layoffs, but opportunities abound for adaptable teams. Marketing evolves from predefined paths to versatile reinvention, where generalists thrive by owning execution, not just analysis. In this flux, user empathy remains timeless: listen live, iterate fast, and build for resonance, not assumption.

Ultimately, AI doesn't obsolete core principles but accelerates their application, demanding humility and velocity. Founders ignoring this risk hype's fall; those embracing it craft enduring fits amid disruption's roar.