This module focuses on identifying and optimizing the key growth levers that drive business outcomes. Participants will learn how to conduct market and competitor analysis, uncover bottlenecks in the customer journey, and leverage data-driven insights to unlock new growth opportunities. The module emphasizes the importance of continuous iteration and strategic resource allocation to maximize impact.

Growth levers in SaaS are the key areas or inputs that, when optimized, yield disproportionate impact on growth and revenue (Finding and Optimizing Growth Levers.pdf). In practical terms, a growth lever could be anything from a specific conversion rate, to a marketing channel, to a product feature that drives engagement. Identifying these levers early is crucial because it focuses your team on what truly moves the needle, ensuring efficient use of resources. As SaaS strategist Joel York notes, you should always ask “Where is my customer getting stuck? Where is the bottleneck?” – improving that bottleneck lever will unlock growth, whereas improving non-bottleneck areas has little effect (Identifying Your SaaS Growth Levers | OpenView Labs) (Identifying Your SaaS Growth Levers | OpenView Labs). Early identification of growth levers helps avoid hitting a growth ceiling caused by overlooked issues (for example, strong acquisition can be negated by high churn if retention isn’t addressed) (SaaS Growth Strategy | A Customer Lifecycle Approach). In short, finding your high-impact levers ensures focused resource allocation on the strategies that maximize sustainable growth (Finding and Optimizing Growth Levers.pdf).

Strategically, nearly all SaaS growth levers fall into a few fundamental categories: acquiring more customers, increasing the value of each customer (through retention or monetization), or leveraging customers to bring more users (network or viral effects). In fact, a classic framework defines the three fundamental SaaS growth levers as customer acquisition, customer lifetime value, and customer network effects (SaaS Growth Strategy | A Customer Lifecycle Approach). Early-stage startups often grow by acquiring customers, but in the long run, churn (retention) dominates growth – meaning retention and expansion must become priorities to break through plateaus (SaaS Growth Strategy | A Customer Lifecycle Approach). Companies that identify their levers early (for example, discovering that improving onboarding drives retention, or that a referral program drives low-cost acquisition) can prioritize those initiatives from the outset rather than as an afterthought (AARRR: Come Aboard the Pirate Metrics Framework | Amplitude). Dave McClure, who introduced the popular “Pirate Metrics” framework, argued that startups should prioritize scalability and monetization from the outset, not only after product development (AARRR: Come Aboard the Pirate Metrics Framework | Amplitude). In summary, knowing your SaaS growth levers early on means you can invest in the right product features, marketing tactics, and customer programs that fuel compounding growth, giving you a competitive advantage.

Frameworks for Identifying and Mapping Growth Levers

Several proven frameworks can help teams systematically identify and map their growth levers. These frameworks break down the customer journey and business model so you can spot opportunities at each stage:

The AARRR Model (Pirate Metrics)

One of the best-known frameworks is AARRR, which stands for Acquisition, Activation, Retention, Referral, Revenue (AARRR: Come Aboard the Pirate Metrics Framework | Amplitude). This so-called “Pirate Metrics” framework (named for sounding like “AAARRR!”) was introduced by Dave McClure to bring order to startup growth strategies (AARRR: Come Aboard the Pirate Metrics Framework | Amplitude). It segments the customer lifecycle into five stages and encourages you to track and optimize metrics at each stage:

• Acquisition: How you attract potential users or leads. (e.g. website visitors, sign-ups from various channels)
• Activation: The point where a user has a great first experience or reaches a defined “aha moment.” (e.g. completes onboarding or a key action that correlates with realizing value)
• Retention: Getting users to come back and continue using the product over time. (e.g. 30-day active users, repeat logins, subscription renewals)
• Referral: Users sharing the product and bringing in new users. (e.g. invitations sent, referral sign-ups – indicative of viral growth loops)
• Revenue: Monetization events. (e.g. conversion to paid plans, upsells, ARPU – how the product makes money)

By mapping your funnel with AARRR, you can identify which stage is the biggest growth lever at any given time. For example, you may find you have plenty of sign-ups but poor activation – indicating an activation lever (like onboarding flow) needs attention. Or you might have good activation but low retention – indicating a product engagement or value gap to fix. Prioritizing the weakest stage (the bottleneck) is key, because improving other stages won’t help if the bottleneck remains (Identifying Your SaaS Growth Levers | OpenView Labs). This framework ensures you examine user behavior at all stages and not just top-of-funnel metrics (AARRR: Come Aboard the Pirate Metrics Framework | Amplitude). It aligns teams on a common language (each stage has its key metric) and encourages data-driven focus on the entire customer journey. Key tip: When using AARRR, define a clear metric for each stage (e.g. Activation = user completes key setup within 7 days), then identify levers to improve that metric.

Growth Loops vs. Funnels

While the funnel model (like AARRR) is linear, modern growth teams also think in terms of growth loops – self-reinforcing cycles where the output of one cycle feeds back as input for the next, creating compounding growth (Growth Funnels vs. Growth Loops: How to Utilize Both for Your Business). A growth loop starts with an action by a user that directly leads to acquiring another user, usually with no linear “end” point. For example, a classic viral loop: User invites a colleague -> colleague signs up and invites others -> those users invite more, and so on. Other types include content loops (user content or data attracts new users, as seen in products like Notion or Canva templates) and paid loops (reinvesting revenue into marketing to acquire more users).

Growth loops are powerful because they can generate exponential, cost-effective growth when executed well. Unlike a funnel which “ends” at revenue, a loop continues to cycle. The ideal loop is self-perpetuating: each new customer generates more new customers (Growth Funnels vs. Growth Loops: How to Utilize Both for Your Business). For example, Zoom exhibited a viral loop during its rise – happy users invited others to meetings, indirectly driving new sign-ups; this loop helped Zoom grow rapidly with relatively low customer acquisition cost. Growth loops often underpinned the rapid scale of Dropbox (via its referral program loop) and Slack (via team network effects: one team member invites the whole team, and usage spreads organization-wide).

It’s important to note that funnels and loops work together. Funnels are still useful to optimize conversion at each stage, and loops can be layered on top to amplify growth. A practical approach is to use funnel analytics to spot opportunities (e.g. a high referral rate might indicate a loop potential), and design experiments to turn that into a persistent loop (e.g. formalize a referral program). As one LinkedIn growth manager put it, get the fundamentals right with funnels, then scale with loops – but continue optimizing all your growth levers in parallel (Loops vs. Funnels: A Balanced Approach to Sustainable Growth) (Growth Loops Not Funnels For Compounding Growth - Teknicks).

Jobs-to-Be-Done (JTBD)

Another framework to identify growth levers, especially on the product side, is the Jobs-to-Be-Done (JTBD) theory. JTBD shifts the perspective from what the product is to why the customer uses it. In other words, what “job” is the customer hiring your product to do? Understanding this can reveal new growth opportunities. For example, by interviewing customers you might discover an important job your product is used for (or not used for due to missing features). This insight can guide product improvements that boost adoption or retention. JTBD helps uncover unmet needs and pain points – effectively highlighting potential levers like features to build, messages to emphasize, or segments to target.

Applied to SaaS growth: suppose your analytics product’s job for startup users is “understand user behavior without SQL.” If many trial users fail to see value, JTBD interviews might reveal they actually needed easier reporting – suggesting a growth lever is to build a report template feature that increases activation and retention. By focusing on the core jobs, teams can cut through feature requests and find what truly drives engagement (growth lever for retention) or what unique value to market (growth lever for acquisition). In summary, JTBD is a qualitative framework that complements metrics: it can pinpoint why users churn or what new capability would spur expansion, thus informing your growth lever mapping with customer-centric insight. (Tip: Use JTBD to inform your North Star Metric as well, ensuring it aligns with the primary job customers seek.)

North Star Metric Framework

A North Star Metric (NSM) is a single metric that captures the core value your product delivers to customers (Collection of Some of the Best SaaS North Star Metrics). Companies define a North Star to align the team on a primary objective and to ensure all growth initiatives ultimately drive that key outcome. For SaaS businesses, a good NSM is usually tied to customer value and leading indicators of revenue. For example, Airbnb’s North Star is “nights booked” (‘North Star Metric’ examples of tech industry leaders), which reflects value delivered to hosts and guests. B2B SaaS examples include HubSpot’s reported NSM of “weekly active teams” using their software (‘North Star Metric’ examples of tech industry leaders), or Asana’s focus on “weekly active subscribers”. The NSM should encompass retention and engagement, not just signups, because it’s about delivered value. It’s not a vanity metric like registered users – it must indicate that the customer has realized meaningful value (hence why active usage or outcomes are common NSMs) (Every Product Needs a North Star Metric: Here’s How to Find Yours | Amplitude) (Every Product Needs a North Star Metric: Here’s How to Find Yours | Amplitude).

Using a North Star framework means you map supporting metrics and levers that drive that North Star. For instance, if your NSM is “reports generated per week” in an analytics SaaS (assuming each report equals value to the customer), then your growth levers might map backward to things like user onboarding completion (to drive first report), feature discovery (to increase reports by each user), or workspace invites (to get more users generating reports). You still track AARRR metrics, but the NSM acts as the guiding light – if an initiative doesn’t move the North Star, you question its priority. This helps teams avoid siloed goals and work cross-functionally on the same ultimate outcome (Every Product Needs a North Star Metric: Here’s How to Find Yours | Amplitude). A good North Star also forces you to identify the key actions that lead to retention, which often surface your most important levers to pull. (One caution: an NSM is typically one-dimensional, so some companies use a secondary metric for balance (‘North Star Metric’ examples of tech industry leaders). But as a teaching tool, picking a North Star is great for focus.)

In summary, frameworks like AARRR and growth loops give you where to look in the journey, JTBD gives you why customers behave a certain way, and the North Star aligns what ultimate success looks like. Using these together, you can systematically map out potential growth levers: e.g. list metrics for each AARRR stage, tie them to your North Star, and use customer insights (JTBD) to prioritize which levers, if improved, would most increase the North Star metric.

Market and Competitor Analysis to Uncover Opportunities

Another critical input to finding growth levers is market and competitor analysis. By looking outward at the market landscape, you can identify gaps or strategies that inform your own growth initiatives. There are a few key methods:

• TAM/SAM Analysis: Understanding your Total Addressable Market (TAM), Serviceable Available Market (SAM), and Serviceable Obtainable Market (SOM) helps set the stage for growth. If your TAM is large but you’re only reaching a small niche, one lever might be expanding to new segments or geographies. Conversely, if your TAM is limited, you’ll need to maximize lifetime value or expand product offerings to grow. This strategic view ensures your growth levers (e.g. expanding use cases, entering a new vertical) align with a real market opportunity and not just squeezing more out of a tiny market.
• Competitor Benchmarking: Studying competitors can reveal which levers they are pulling successfully and where you might have an advantage. For example, if a competitor has very strong acquisition via content marketing, but weaker product engagement, it hints that focusing on retention features could differentiate you (or conversely, doubling down on content to match them might be needed). A competitor gap analysis looks at competitors’ product features, pricing, channels and identifies underserved customer needs (Finding and Optimizing Growth Levers.pdf). Those unmet needs can be your growth levers. Gong’s success is a great case in point: entering a crowded sales software market, Gong analyzed competitors like Chorus.ai and identified that while products were similar, the competitors weren’t positioning around broader analytics and revenue insights. Gong positioned itself as the leading AI-driven Revenue Intelligence platform, addressing gaps in analytics and reporting in the sales conversation space (Finding and Optimizing Growth Levers.pdf) (How Gong became 15x more valuable($7.5B) than Chorus($500M)). This distinct positioning around a gap propelled Gong to market leadership – effectively, the lever was positioning and messaging informed by competitor insight. (In fact, an analysis showed Gong’s product and tech were on par with competitors, but marketing made the massive difference, making Gong’s brand known even to those unfamiliar with the category (How Gong became 15x more valuable($7.5B) than Chorus($500M)).)
• Industry Benchmarks: It’s also useful to compare key metrics. For instance, if the industry average free-trial-to-paid conversion is 20% and yours is 10%, your conversion process is a clear growth lever to optimize. Or if competitors have higher Net Revenue Retention (NRR) than you, focusing on upsells and retention programs could unlock growth. Keep an eye on metrics like CAC, payback period, churn rates across competitors if available (sometimes from investor reports or case studies). High-performing peers set a bar that can highlight your weaknesses.
• Customer Feedback on Competitors: Sales teams often collect intel on why deals are won or lost. Those insights can surface growth levers too. For example, if you consistently hear “Competitor X’s onboarding is easier” or “Feature Y is missing in your product,” those are levers to fix (improve onboarding UX, build the missing feature) to remove friction in growth.

Overall, market and competitor analysis helps validate and prioritize growth levers. It ensures you’re not operating in a vacuum – doubling down on a lever that others have already maxed out may have diminishing returns, whereas exploiting a competitor’s weakness or a market gap can give outsized results. In the next section, we’ll look at how to prioritize all these opportunities since you’ll likely identify more levers than you can tackle at once.

Prioritization Frameworks: ICE, RICE, and Picking the Right Levers

Once you’ve mapped out potential growth levers (across your funnel, product, market, etc.), the next step is prioritization. Not all levers are equal in impact or effort, and teams have limited time. Several models help evaluate which initiatives to pursue first:

ICE Scoring

The ICE framework is a simple but effective way to score and rank potential growth initiatives. ICE stands for Impact, Confidence, and Ease (or Effort) (What is the ICE Scoring Model? | Definition and Overview). You assign a score (often 1-10) for each factor:

• Impact: If this idea works, how big might the impact be on our key metrics/North Star? (1 = minimal impact, 10 = massive, game-changing impact)
• Confidence: How confident are we in this idea or hypothesis? This can be based on data, past experiments, or qualitative insight. (1 = purely a guess, 10 = extremely certain based on evidence)
• Ease: How easy will it be to implement (or sometimes Effort is used: how much effort/cost required – ease is just the inverse)? (1 = very hard, resource-intensive, 10 = very easy/quick win)

You then calculate an ICE score – originally, by multiplying the three numbers (Impact × Confidence × Ease) (What is the ICE Scoring Model? | Definition and Overview). Some teams use a simple average instead, but the multiplication approach was popularized by growth hacker Sean Ellis (who created ICE) because it quickly highlights high-impact, easy wins (What is the ICE Scoring Model? | Definition and Overview). For example, say you have an idea “Add onboarding tutorial”. You might score it Impact=7 (decent boost to activation), Confidence=8 (from user research you feel sure it will help), Ease=6 (moderate effort). That gives ICE = 7×8×6 = 336. Another idea “Launch referral program” might be Impact=9 but Confidence=5 (unsure if users will refer) and Ease=4 (quite a bit of work), giving 9×5×4 = 180. In this case, the onboarding tutorial scores higher, suggesting it should be prioritized over the referral program (What is the ICE Scoring Model? | Definition and Overview). The highest ICE score ideas move to the top of your roadmap (What is the ICE Scoring Model? | Definition and Overview).

ICE’s strength is its speed and simplicity (What is the ICE Scoring Model? | Definition and Overview). It forces rough estimation but doesn’t require deep analysis for each idea, which is perfect in a fast-moving growth context where you might have dozens of experiments to triage. It’s particularly useful for prioritizing experiments in growth hacking – Sean Ellis intended it for quick, iterative testing environments (What is the ICE Scoring Model? | Definition and Overview). One thing to watch out: it treats Impact, Confidence, Ease equally by default. This is usually fine, but if your team values one factor more (say you want to heavily weight Impact), you might adjust or use a weighted model. Also, because scoring is subjective, calibrate by discussing as a team to avoid personal bias in scores.

RICE (Reach, Impact, Confidence, Effort)

RICE is a variant that Intercom popularized for product feature prioritization. It stands for Reach, Impact, Confidence, Effort. The idea is similar to ICE but adds an explicit Reach factor and uses Effort (inverse of Ease) in a formula: Score = (Reach × Impact × Confidence) / Effort (What is the ICE Scoring Model? | Definition and Overview). Reach is usually a number or size of audience affected in a period (e.g. “will impact 500 users per month”). Impact is often on a 5-point scale (e.g. 3 = “medium impact”), Confidence is a percentage or high/medium/low, and Effort is typically person-weeks of work. The RICE formula will favor projects that hit many users, have big impact and high confidence, and require low effort (which is intuitive).

For growth teams, RICE can be useful if the number of users affected varies a lot between ideas. For example, one idea might improve conversion on a high-traffic landing page (Reach = tens of thousands users/month), while another improves a small upsell flow (Reach = a few hundred users). ICE alone might rate the upsell idea highly on ease and impact, but RICE would rightly boost the landing page idea due to its greater Reach. The math aside, what’s important is thinking through these dimensions. Both ICE and RICE force you to articulate assumptions: How big an impact (what metric change)? How many users or leads see this? How confident are we (do we have evidence)? How long will it take?

In practice, you can use whichever framework resonates. Many growth teams start with ICE scoring for its simplicity, and use RICE for quarterly planning or larger product features. The key is to avoid pet projects or loudest-voice syndrome – let the scoring bring some objectivity. Also remember these scores are not absolute truth; they’re guides. Always sanity-check the top results with “Does this really make sense as our next move?” and use qualitative considerations too (e.g. some initiatives are necessary for strategic reasons even if score lower).

Other Prioritization Considerations

Beyond ICE/RICE, consider these tips when prioritizing growth levers:

• Time to impact: Quick wins (low effort, fast feedback) are great to build momentum, but also have at least one or two “step change” projects that could drive major growth even if they take longer.
• Balance across funnel: You might score everything and find all top ideas are, say, acquisition-focused. Be mindful to not ignore other stages – a balanced growth engine means working on acquisition, activation, and retention levers in concert. It’s often wise to ensure at least one top initiative for each major funnel area each cycle, if possible.
• Resource alignment: Some levers require engineering (product changes), others need marketing spend, others need sales efforts. Your prioritization should factor in what team resources you have available. If engineering is swamped, maybe prioritize a marketing lever that can be done with existing content/tools, and vice versa.
• Revisit regularly: After running experiments or as market conditions change, re-score your backlog. For instance, a tactic might become more or less attractive if new data comes in (e.g. a competitor copied your feature – your confidence in further investing there might drop).

ICE scoring in action: In Section 4 of this module’s case studies, we’ll see how a prioritization matrix is applied in an exercise. For now, remember that a structured approach like ICE helps you build a growth roadmap grounded in expected impact, rather than guesswork.

Diagnosing Bottlenecks in the Customer Journey

Improving growth levers requires knowing where the bottlenecks are. A bottleneck is the point in your funnel or lifecycle that is constraining overall growth – basically your weakest link. To uncover these, use a combination of funnel analysis, data, and qualitative feedback:

• Funnel Metrics Analysis: Track conversion rates and drop-off percentages at each stage of your funnel. For example, out of 1000 website visitors, if 100 sign up (10% acquisition rate), and out of those 100 only 10 ever become active (10% activation rate), and say 5 eventually pay (5% conversion to paid), you can see which stage has the biggest drop-off. In this scenario, the activation stage (sign-ups to active users) is only 10%, which is a red flag. That’s likely the bottleneck to address before you pour more leads into the top. Tools like Google Analytics, Mixpanel, or custom dashboards can visualize these funnels. HubSpot’s marketing team famously did this analysis on their lead funnel – they looked at the MQL (Marketing Qualified Lead) to SQL (Sales Qualified Lead) conversion rate and found a significant drop-off (Finding and Optimizing Growth Levers.pdf). By identifying that as a bottleneck, they focused on improving lead nurturing and qualification, which lifted that conversion rate and ultimately revenue (Finding and Optimizing Growth Levers.pdf). (For reference, a typical MQL→SQL conversion benchmark is around 13% (How to Report on Leads, MQLs, and SQLs in HubSpot | SmartBug Media®); if you’re way below that, it’s a bottleneck worth investigating.)
• Cohort and Retention Analysis: Look at retention curves (what % of users remain active or paying over time). If you see a steep drop after month 1, then leveling off, that initial drop is your activation/retention bottleneck – maybe users aren’t finding ongoing value after the first try. If retention is fine short-term but declines gradually, the issue might be lack of new value over time or no expansion. Net Revenue Retention (NRR) is a key metric here: top SaaS companies achieve NRR > 120% (meaning upsells make up for churn) (Key growth levers for SaaS companies in 2025 | Simon-Kucher) (Key growth levers for SaaS companies in 2025 | Simon-Kucher). If your NRR is below 100%, you’re losing more than you’re expanding – signals a retention/upsell lever needs attention.
• Customer Feedback & Behavior: Numbers tell you where users drop off; feedback and user research help tell you why. Use surveys (in-app or email) to ask churned users or inactive trial users what went wrong – their answers often point directly to bottlenecks (e.g. “I didn’t understand how to use X”, “Too expensive”, “Didn’t see the benefit”). Behavior analytics (like watching session recordings or click flows) can also reveal friction points. Perhaps users always hover a certain button but don’t click “upgrade” – indicating confusion. Qualitative insight will inspire solutions: it might reveal that a missing integration is causing drop-offs (so the lever is adding that integration to retain users), or that users expect a faster result (lever might be improving product speed or communicating value sooner).
• Ask Diagnostic Questions: Sometimes a structured set of questions can guide a team’s thinking to spot issues. For example:

  • “Which stage of our funnel has the lowest conversion percentage? Why might that be?”

  • “Where do customers spend the most time or express the most frustration in their journey?”

  • “Are we attracting the right users? (If not, low conversion could be due to poor-fit leads – an acquisition targeting problem.)”

  • “Is our core value clear and reached quickly? (If not, activation is a bottleneck.)”

  • “Do we see a usage drop at a certain point in the user lifecycle (e.g. after trial ends, after 3 months)? What does that coincide with?”

  • “What do our highest-LTV customers do differently (or get more value from) than others? Are we guiding everyone to those behaviors?”

    Each answer can hint at a lever: e.g. if highest-LTV customers use feature X heavily, then driving more users to adopt feature X could be a lever for retention/expansion.

After identifying bottlenecks, you then hypothesize solutions: these become your growth lever initiatives. If activation is a bottleneck, levers could be “improve onboarding UX,” “add a guided checklist for new users,” or “offer a live training webinar in week 1.” If retention is a bottleneck, levers could be “implement a customer success outreach at day 30,” “launch loyalty discounts for annual renewal,” etc. The idea is that by fixing the biggest constraint, you open up the next level of growth (Identifying Your SaaS Growth Levers | OpenView Labs). This approach is inspired by the Theory of Constraints and is echoed by Joel York’s advice: focus on improving the bottleneck, because if you improve elsewhere, the bottleneck still limits you (Identifying Your SaaS Growth Levers | OpenView Labs). In growth terms: fix that leaky bucket before turning up the flow.

Case example: In our module’s Section 3 case study, HubSpot’s team noticed a major drop from MQL to SQL (marketing -> sales handoff). By treating that as the bottleneck, they introduced lead scoring and targeted nurturing. They prioritized high-quality leads for sales and nurtured others with content until ready, which improved the MQL→SQL conversion significantly (Finding and Optimizing Growth Levers.pdf). In effect, they pulled the “lead qualification” lever and greased a stuck funnel stage.

In your own context, always be on the lookout for the one metric/stage that, if dramatically improved, would most improve overall growth. That’s your bottleneck. Find it, then fix it with creative solutions.

Growth Levers in Product-Led, Sales-Led, and Marketing-Led Models

Not all SaaS companies grow in the same way. Your go-to-market strategy (Product-Led Growth vs Sales-Led vs Marketing-Led) influences which growth levers are most important. Let’s clarify each model and give examples of levers in each:

• Product-Led Growth (PLG): The product itself is the primary driver of acquisition, conversion, and expansion. Users often can start using the product via free or self-serve channels, and the product’s value prop and usage hooks convert them to paid. Examples of PLG levers: free trial or freemium conversion rate, user onboarding experience, feature virality (invitations, collaboration features), in-app upsell prompts, and usage-based upsell (e.g. hitting usage limits prompts upgrade). Slack is a textbook PLG example – it allowed teams to sign up for free, and a key lever was the network effect within a team (as more coworkers join, Slack becomes more valuable, driving deeper adoption). Slack optimized the invite mechanism and notifications to encourage bringing colleagues in. Another example, Zoom, had a frictionless free meeting product; a growth lever was the “40-minute meeting limit” on free accounts which nudged many businesses to upgrade during the pandemic. Additionally, PLG companies focus on the “aha moment” – ensuring users reach that moment quickly is a lever (activation). Atlassian historically used PLG with low-cost, self-serve products – one lever Atlassian pulled was per-user pricing with easy self-service seat addition, making it simple for teams to expand usage (How growth levers help your business go the distance - Work Life by Atlassian).
• Sales-Led Growth (SLG): Here a direct sales force drives customer acquisition and expansion, often in mid-market or enterprise segments. The product might require more onboarding or has a higher price, so human touchpoints are key. Examples of SLG levers: volume and quality of leads to feed the sales team, efficiency of the sales funnel (MQL→SQL→Closed Won rates), sales cycle length, demo-to-close conversion, and account expansion by account managers. Salesforce in its early days (and most enterprise SaaS like Oracle, SAP) grew via aggressive sales execution – key levers were hiring more productive sales reps and arming them with lots of marketing-qualified leads. In sales-led models, lead scoring and CRM pipeline optimization are big levers (as seen with HubSpot’s case: improving lead handoff increased sales output). Another lever is sales enablement content – ensuring reps have the right case studies and ROI calculators can improve close rates. Upsells and cross-sells are crucial levers in SLG: for example, account managers at a SaaS company might systematically identify which customers could adopt additional modules and run targeted upsell campaigns. Atlassian, once it moved upmarket, actually layered sales on top of its PLG core – even then, they preserved efficiency by only having sales focus on the highest-value accounts while self-serve handled the rest (How growth levers help your business go the distance - Work Life by Atlassian) (How growth levers help your business go the distance - Work Life by Atlassian).
• Marketing-Led Growth: This model leans on marketing channels and brand to acquire and nurture customers. Think of companies that invest heavily in content marketing, SEO, events, virality in the market rather than viral product features, etc. Examples of marketing-led levers: content publishing frequency and quality (to drive organic traffic), conversion rate optimization on landing pages, webinar and event leads, PR and word-of-mouth initiatives, partner and affiliate programs. HubSpot exemplified marketing-led growth through its Inbound Marketing strategy – their lever was creating valuable content (blogs, ebooks, tools like Website Grader) to attract millions of visitors, which fed their funnel at low cost. They also built a huge email list and community; engaging that community was a lever for referrals and brand loyalty. Affiliate or partner marketing can be a lever too: for instance, a company might set up an affiliate program (paying commissions for referrals) and find that a network of affiliates drives a significant chunk of new signups. This was highlighted by a TechCrunch piece noting affiliate partnerships as an underrated lever in SaaS (3 growth levers every SaaS founder should know about | TechCrunch) (3 growth levers every SaaS founder should know about | TechCrunch). Webinars and free workshops can be marketing levers – they both acquire leads and activate them through education.

In reality, successful SaaS businesses blend these approaches. For example, a Product-Led company might still have a sales team to convert large opportunities (so they’ll have both PLG levers like virality and SLG levers like lead qualification). A Sales-Led enterprise SaaS might develop a self-service tier or strong content engine to support awareness (mixing in marketing-led levers). The mix of levers should match your customer journey: a low-touch journey lends itself to product and marketing levers; a high-touch journey means sales and relationship levers.

Diagnostic tip: Identify your primary model and check if you’re under-investing in any lever category. For instance, if you’re product-led but realize your product has no viral loop, you might explore adding one (like a refer-a-friend incentive or community sharing feature). If you’re sales-led and sales cycles are dragging, maybe a lever is improving product free trial capabilities or ROI calculators to accelerate deals (blending product/marketing into sales process). If you’re marketing-led and acquisition is great but users churn quickly, you need to borrow PLG tactics to improve product value delivery.

Ultimately, all levers – product, sales, marketing – should work in concert. Companies that master multiple growth levers achieve the best results. For example, Atlassian’s growth over 20 years came from layering levers: first product-led viral adoption, then expansion within customers via upsell/cross-sell, then later adding a sales assist for enterprise deals (How growth levers help your business go the distance - Work Life by Atlassian) (How growth levers help your business go the distance - Work Life by Atlassian). By contrast, a company that relies on just one lever (say paid ads only) might stall once that channel saturates. For a resilient growth strategy, diversify your levers across product, sales, and marketing as appropriate.

Case Studies: Growth Levers in Action

Let’s examine a few real SaaS case studies that illustrate finding and scaling growth levers:

Case Study 1: Atlassian’s Focused Growth Lever Strategy (Upsell & Pricing)

Atlassian (maker of Jira, Confluence, etc.) is famous for eschewing a traditional sales model in its early years and instead leveraging product-led growth. One of Atlassian’s key growth levers was its pricing and upsell strategy within its customer base. Atlassian offered affordable entry-level pricing and a frictionless self-serve purchase experience, which got teams in the door (How growth levers help your business go the distance - Work Life by Atlassian). Once a customer was using one product, Atlassian would expand the account through two levers: adding more users (seats) and upselling to higher editions or additional products. Crucially, they made these expansions easy and user-driven – for example, admins could add user seats with just a few clicks (no sales negotiation needed) and be billed accordingly (How growth levers help your business go the distance - Work Life by Atlassian). This led to viral expansion inside companies as more teams adopted the tools.

As Atlassian’s customer base grew, they introduced a tiered edition upsell ladder: Free, Standard, Premium, Enterprise editions (How growth levers help your business go the distance - Work Life by Atlassian). They identified that different customers had divergent needs (e.g. larger customers needed advanced admin controls), so by building premium editions they could upsell a portion of users to higher-priced plans without alienating the rest. This pricing lever drove significant expansion revenue from existing customers at a low incremental cost (Finding and Optimizing Growth Levers.pdf). For instance, a small company might stick to Standard (low price), but a larger company on Standard would find value in Premium’s features and upgrade – increasing Atlassian’s ARPA (average revenue per account). Atlassian’s strategy shows how focusing on expansion levers (instead of just new customer acquisition) yielded growth: in SaaS, it’s well known that keeping and expanding customers is 5× cheaper than acquiring new ones (Key growth levers for SaaS companies in 2025 | Simon-Kucher), and Atlassian exemplified this by achieving high net retention through upsells. Result: Atlassian grew to billions in revenue with very high operating margins, since their model didn’t rely on a costly salesforce.

An interesting insight from Atlassian’s story is timing: They caution not to introduce too many editions or upsells too early (How growth levers help your business go the distance - Work Life by Atlassian). If you try to milk upsell revenue too soon, you might neglect the base product’s attractiveness. Atlassian waited until they had a large user base and diverse needs before heavily segmenting editions. Once they did, the lever was pulled hard – today they have multi-tier pricing and even a Marketplace of third-party apps (another lever to increase stickiness and revenue) (How growth levers help your business go the distance - Work Life by Atlassian). In Atlassian’s own blog, their Chief Revenue Officer describes five expansion levers they use: adding users, upselling editions, cross-selling new products, third-party marketplace apps, and services (How growth levers help your business go the distance - Work Life by Atlassian) (How growth levers help your business go the distance - Work Life by Atlassian) (How growth levers help your business go the distance - Work Life by Atlassian). These collectively increased their “share of wallet” in each customer (How growth levers help your business go the distance - Work Life by Atlassian). The takeaway is that Atlassian identified internal account growth (upsell/cross-sell) as the lever that could drive sustainable growth without proportional acquisition spend, and they optimized their business around it.

Case Study 2: Gong’s Competitor-Focused Positioning (Winning a Market with a Lever)

Gong is a B2B SaaS in the sales enablement space (conversation intelligence for sales calls). When Gong entered, there were already competitors (e.g. Chorus.ai). Gong’s team identified that to win, they needed to leverage differentiation as a growth lever. They performed deep competitor analysis and saw an opportunity to position not just as a call recorder, but as a broader Revenue Intelligence platform addressing more than what competitors did (How Gong became 15x more valuable($7.5B) than Chorus($500M)). This included building superior analytics and dashboards on sales calls and incorporating AI to derive insights (e.g. deal risk signals) that others lacked. By addressing these unmet needs (analytics and easy insights for sales managers), Gong could market itself as a must-have tool for revenue teams, not just a coaching tool for reps.

Gong’s marketing then became a lever in itself. They executed a bold content and social media strategy – you may have seen their distinctive posts on LinkedIn with sales tips and humor. This made Gong extremely visible in the sales community (How Gong became 15x more valuable($7.5B) than Chorus($500M)). So while Chorus and others were also selling to sales orgs, Gong quickly owned mindshare. They went beyond the product: Gong’s team targeted VP-level decision makers (their ICP) by tailoring messaging to them (How Gong became 15x more valuable($7.5B) than Chorus($500M)), and unleashed a stream of Gong Labs insights (data-driven studies from their platform) that gave them thought leadership. In effect, Gong created a category (Revenue Intelligence) and became synonymous with it.

The result: Gong’s valuation and market share skyrocketed, reportedly capturing 75% of the revenue intelligence market niche (How Gong became 15x more valuable($7.5B) than Chorus($500M)). They became roughly 15× more valuable than a key competitor within a few years (How Gong became 15x more valuable($7.5B) than Chorus($500M)) (How Gong became 15x more valuable($7.5B) than Chorus($500M)). The growth lesson here is that a differentiated positioning and brand can be a powerful lever, especially in crowded markets. Gong identified that lever by analyzing competitors’ shortcomings (none had claimed the broader “revenue intelligence” space or built the accompanying analytics), and then executed ferociously on it (through product features and marketing campaigns). For SaaS startups, this shows that sometimes the biggest lever isn’t a feature or metric tweak, but your go-to-market narrative. If you can define the terms of competition, you can attract more customers at lower cost (Gong’s viral LinkedIn content brought inbound interest, lowering their CAC).

Case Study 3: HubSpot’s Funnel Optimization Framework (Fixing the Leaks)

HubSpot, a pioneer of inbound marketing software, faced a classic funnel bottleneck in its growth journey. They were generating tons of leads (thanks to their content marketing machine), but the conversion from MQL to SQL and then to paying customer could be improved (Finding and Optimizing Growth Levers.pdf). HubSpot identified the handoff between marketing and sales as a critical lever. If they could increase the rate at which marketing-qualified leads turn into sales-qualified leads (i.e., truly interested prospects), they’d efficiently boost revenue without needing even more top-of-funnel leads.

To tackle this, HubSpot implemented a lead scoring system and nurturing framework. They analyzed behaviors of leads that became customers vs. those that didn’t. This data-driven approach let them assign scores to leads based on fit and engagement (e.g. job title, company size, pages visited, content downloaded). With lead scoring, the sales team only worked leads above a certain score (higher likelihood to convert), while lower-score leads got put into further nurture campaigns (targeted emails, more content to educate them) until their score improved. This ensured sales reps spent time on the best opportunities, thereby improving SQL conversion rates and sales efficiency (Finding and Optimizing Growth Levers.pdf).

They also spotted where leads were dropping off in the funnel. For example, if many leads requested a demo but then went cold, HubSpot would trigger a specific drip email sequence addressing common objections or providing case studies (to re-engage them). Essentially, they optimized each stage: marketing improved how leads were captured and educated (some tactics: personalized workflows, better CTAs to push them down funnel), and sales improved follow-up (e.g. quicker response times, tailored pitch based on score profile). HubSpot even refined their qualification criteria – ensuring the definition of MQL matched someone actually ready for sales.

The outcome was a marked increase in conversion through the funnel. In one public case study, a HubSpot user (MasterMover) achieved a 30% MQL-to-SQL conversion rate with such techniques (MasterMover) (MasterMover), far above the typical 13% benchmark. HubSpot’s own growth benefited similarly – by tightening the funnel, they could scale customers faster. This case underscores how data and process changes can be growth levers: no new feature was built, but rather the lever was operational excellence in funnel management. Many SaaS companies hit a point where pouring more leads in is wasteful; the smarter move is to increase the yield from existing leads. HubSpot’s approach of lead scoring and nurturing is now standard in B2B SaaS.

Another lever HubSpot pulled was expanding their product offerings. Initially known for marketing software, they later added Sales Hub, Service Hub, CMS Hub, etc. This cross-sell lever allowed them to increase revenue per customer (multi-product adoption) and enter new markets. Notably, they timed this after establishing their core product, similar to the Atlassian strategy of not focusing on multi-product too early. When done at the right time, a multi-product strategy can accelerate growth by unlocking new buyer personas or budget pools within the same customer base (3 growth levers every SaaS founder should know about | TechCrunch) (3 growth levers every SaaS founder should know about | TechCrunch) (HubSpot could now sell to heads of sales, not just marketing, for example).

Case Study 4: Zoom’s Iterative Scaling during the Pandemic

Zoom’s explosive growth during the COVID-19 pandemic is well known – they went from about 10 million daily meeting participants to 300 million+ in a matter of months (SEO Page Title: Zoom's Tech Stack Unveiled: Scaling Secrets and Architecture Insights). Such hypergrowth could have easily led to massive failures (outages, security breakdowns) that choke further growth. Zoom’s success in this period highlights the importance of scaling levers: infrastructure scalability, iterative testing, and responsiveness.

Prior to the pandemic, Zoom had invested in a robust architecture with plenty of headroom – their data centers ran at 50% capacity, leaving room to absorb surges ([SEO Page Title: Zoom's Tech Stack Unveiled: Scaling Secrets and Architecture Insights](https://talent500.com/blog/zoom-tech-stack-scaling-architecture-insights/#::text=The%20Secret%20Behind%20Zoom%E2%80%99s%20Rapid,Scaling)). When usage spiked, one lever was technical scaling: they quickly leveraged a hybrid cloud approach, offloading overflow traffic to AWS and Oracle cloud servers (SEO Page Title: Zoom's Tech Stack Unveiled: Scaling Secrets and Architecture Insights). This flexibility ensured that even with 20-30x growth, Zoom maintained call quality and uptime. In growth terms, the lever was their ability to maintain product reliability, which kept user trust and allowed word-of-mouth to remain positive. Had Zoom buckled under load, users would have fled to alternatives, stunting its growth.

Another lever Zoom demonstrated was fast iteration on security and UX. Early in the pandemic, “Zoombombing” (uninvited participants) and other security issues arose due to the rapid influx of users using Zoom in new contexts (schools, etc.). Zoom quickly responded by pausing feature development for 90 days to focus on security improvements (like default passwords, waiting rooms). This responsiveness was crucial to sustaining growth – they plugged a potential retention killer (security concerns) just in time. It shows that sometimes the growth lever is stopping to fix foundations (quality, security) so that users stick around.

Zoom also did small-scale tests for expansion strategies. For example, they temporarily lifted the 40-minute limit for free accounts in certain regions or for educators – a strategy to boost adoption in critical segments, which they monitored before rolling out broadly. This kind of iterative scaling approach – test a change in a subset, ensure it’s manageable, then scale up – allowed Zoom to roll out changes (both technical and policy) in a controlled way (Finding and Optimizing Growth Levers.pdf). In the module PDF summary, it’s noted: Zoom focused on small-scale tests for global expansion strategies, ensuring scalability without compromising quality (Finding and Optimizing Growth Levers.pdf) (Finding and Optimizing Growth Levers.pdf). In essence, Zoom treated each potential big move (like expanding free usage or adding huge numbers of servers) as an experiment to execute carefully.

From Zoom’s case, SaaS companies can learn that operational and infrastructural levers are just as important as marketing or product features during hypergrowth. The ability to handle growth is a lever – it can differentiate those who capitalize on demand from those whose user experience collapses. Post-pandemic, Zoom’s challenge was converting free users to paid and expanding use cases (Zoom Phone, Zoom Rooms, etc.), but none of that would matter if they hadn’t first pulled the lever of scalability. As a final note, Zoom’s freemium model was itself a massive acquisition lever (free usage drove virality), but they balanced it with upsells (like large webinars, business plans) to monetize the surge. They hit an effective CAC of $0 through word-of-mouth and reinvested in product reliability – a virtuous cycle.

These case studies demonstrate a variety of levers: internal account expansion (Atlassian), market positioning (Gong), funnel optimization (HubSpot), and scaling operations (Zoom). In each case, identifying what would drive growth and then executing relentlessly on it was key. When studying your own company or product, it helps to ask: which of these situations are you in? Do you already have a big user base you can monetize more (like Atlassian)? Are you fighting competition where brand could tip the scales (like Gong)? Do you have plenty of leads/users that you’re not converting well (like HubSpot)? Or are you facing a sudden opportunity or surge that hinges on operational excellence (like Zoom)? The answers will guide you to the levers that matter most for you.

Tools & Templates for Growth Lever Optimization

To help apply these concepts, this module provides several templates you can use in Notion (or elsewhere) to map and track your growth levers:

1. Growth Lever Mapping Worksheet

Use this worksheet to brainstorm and catalog all potential growth levers across your customer journey. It’s essentially a table where you list opportunities in each funnel stage or area of the business, along with relevant data. For example:

(Numbers above are illustrative.)

You can customize the columns, but the idea is to map lever → metric → current vs. potential. This helps visualize all your options. Then you might highlight the top 2-3 levers in each stage or circle the one in each stage that seems most impactful. This worksheet is great for team brainstorming sessions. It ensures you’ve considered every part of the business (acquisition, activation, etc.) for growth opportunities. It can also incorporate external insights: e.g. in the acquisition section, note if a competitor is dominating a channel you haven’t tried, which indicates an opportunity.

How to use: Gather your team and fill this out collaboratively. Bring data for current metrics (conversion rates, etc.) so you can be concrete. Then discuss which levers seem highest priority (that’s where you’ll apply the ICE scoring next).

2. ICE Scoring Matrix Template

After listing possible initiatives or experiments, use this matrix to score them. You can maintain it as a simple table:

Sort or highlight by ICE Score. In the above example, the referral incentive (360) and signup flow redesign (336) come out on top. Those would be pursued first. You should also document any rationale or notes (perhaps in another column or a separate section). If you use a spreadsheet or Notion table, you can include formulas to calculate the score automatically.

If you prefer the RICE model, you could adapt the template to: Idea | Reach | Impact | Confidence | Effort | RICE Score. For example, assign Reach = number of users impacted in a month, Effort in person-days, etc., then use Score = (ReachImpactConfidence)/Effort. Use whichever your team finds intuitive.

This template makes prioritization discussions more objective. It’s also a living document – keep adding new ideas and re-scoring as needed. Over time, you can also add a column for outcome (once an experiment is done, was the impact as expected?) to inform future confidence scores.

3. Competitor Growth Lever Benchmarking Table

This template helps you compare your product’s growth metrics or tactics against competitors. It’s useful for identifying where you are lagging or leading. Create a table with key levers down the rows, and columns for you and each competitor:

(The above is hypothetical data.)

From this, you might observe, for example, Competitor B has very high NRR (110%) – indicating their expansion and retention lever is strong, perhaps via account management or more features to upsell. Competitor A might be winning on acquisition via paid ads but maybe spending heavily. You might realize your free trial conversion is behind Competitor A’s 20%, so you investigate what they do (perhaps they have a more aggressive sales follow-up during trials).

You can also include qualitative notes, like each competitor’s key messaging, or specific tactics (e.g., Competitor A runs weekly webinars, B offers certifications, etc.). Another way to use this template is a feature/lever matrix: list specific growth-related features or tactics (e.g., referral program, marketplace, community forum) and mark whether you and each competitor have it (yes/no or rating). This can highlight opportunities to differentiate or catch up.

Tip: Update this table at least quarterly, as competitors may change strategies. It’s particularly useful when planning – if you’re choosing between levers to pull, knowing where competitors stand can guide you. For instance, if all competitors have launched AI features and that’s boosting their growth, your AI feature lever might become higher priority.

4. Weekly Growth Experiment Tracker

Growth is iterative, and running experiments is key to optimizing levers. This template tracks ongoing tests on a weekly (or sprint) basis:

This tracker allows the team to see at a glance what’s being tested and what the outcomes are. Each experiment is tied to a focus lever (so you remember why you’re doing it). The hypothesis forces clarity on what you expect. Always define a success metric and target (even if it’s rough) before starting.

At week’s (or experiment’s) end, log the result and decide next steps: iterate, roll out, or scrap. For example, if the onboarding tutorial didn’t move the needle enough, you might try a different approach or concede that lever might need a bigger change. If an experiment succeeds (hits or exceeds target), you then decide to implement that change permanently or scale it up. If it fails, document learnings and perhaps deprioritize that lever for now.

Using a weekly tracker instills a culture of experimentation. It ensures continuous progress on optimizing levers, rather than set-and-forget. It’s also motivating to see wins accumulate over weeks. In Notion, you could make this a database with properties for each column, making it easy to filter by focus (e.g., show all experiments related to retention).

Note: Make sure to not run too many concurrent experiments on the same segment of users if they might interfere. Also, ensure statistical significance where applicable for A/B tests. The tracker can include a “Status” (Running, Analyzing, Completed) as well.

All these templates are meant to be practical tools. They can be downloaded or duplicated into your own workspace. By using the Growth Lever Mapping worksheet, you prioritize systematically; with the ICE matrix, you choose smartly; with competitor benchmarking, you stay informed; and with the experiment tracker, you execute and learn rapidly. Together, they form a toolkit for ongoing growth optimization.

Metrics to Evaluate Lever Effectiveness

To know if a growth lever is truly driving improvement, you need to measure the right metrics. Different levers will move different metrics, but here are key SaaS metrics by area and how to use them:

• Acquisition Metrics:
  • Website traffic and conversion rate: If your lever is an SEO campaign, track organic visits and the conversion rate to sign-ups.
  • Cost Per Acquisition (CPA/CAC): For paid channels, measure how much it costs to acquire a customer. If you optimize an ad targeting lever, a falling CAC indicates success (assuming quality holds).
  • Lead Volume and Quality: Track number of leads from each channel and their downstream conversion. An increase in high-quality leads shows, say, your new content strategy lever is effective.
  • Channel mix: Keep an eye on which channels are growing. For example, if referrals (viral) jump from 5% to 15% of new users after a referral program launch, that’s a clear signal of lever effectiveness.
• Activation Metrics:
  • Activation Rate: Define what “activated” means (e.g. completed onboarding or performed key action X within first week) and measure the percentage of new users who reach it. If you redesign onboarding and activation rate rises from 40% to 60%, that’s a huge win (How to Report on Leads, MQLs, and SQLs in HubSpot | SmartBug Media®) (How to Report on Leads, MQLs, and SQLs in HubSpot | SmartBug Media®).
  • Time to Value: How quickly do users reach their first aha moment or valuable outcome? Shortening this (in days or sessions) is often a lever. Metrics like “% of users achieving [key action] in first 1 day/1 week” can quantify it.
  • Free to Paid Conversion: For freemium/trial models, track the conversion rate from free to paid within a certain time. If an in-app upsell experiment works, you might see trial conversion go from, say, 12% to 15%. That percentage and its trend are your gauge.
  • Onboarding Drop-off: If your funnel is multi-step (sign-up -> onboard -> first use), measure drop-off at each step. A lever aimed at step 2 is successful if drop-off between step 1 and 2 decreases.
• Retention Metrics:
  • Churn Rate: This is the inverse of retention – % of users or customers who cancel or stop using in a given period. A reduction in churn (monthly or annually) indicates retention levers (like new features, better support) are effective. For instance, if monthly churn drops from 5% to 3%, that’s a retention lever payoff.
  • Retention/ Cohort Curves: Plot cohorts of sign-up months and see what % remain active or paying over time. Healthy retention shows curves flattening out (indicating long-term users). A retention lever like a re-engagement email might cause a cohort’s curve to flatten higher than before.
  • Net Revenue Retention (NRR) / Expansion Rate: Measures how revenue from a cohort grows or shrinks, including upsells. If you implement an upsell strategy and NRR increases from 100% to 110%, it means upsell revenue is outpacing any lost revenue (Key growth levers for SaaS companies in 2025 | Simon-Kucher) (Key growth levers for SaaS companies in 2025 | Simon-Kucher). This is a powerful metric – top companies focus on NRR as mentioned (120%+ best-in-class (Key growth levers for SaaS companies in 2025 | Simon-Kucher)). Even if user count churns, NRR can be >100% if expansions make up for it.
  • Engagement Metrics: These can serve as leading indicators for retention. E.g., DAU/MAU (daily active over monthly active) to see stickiness. If your lever (say, a new feature) is effective, DAU/MAU might rise (users coming back more frequently). Or track WAU (weekly active users) after certain changes.
  • Customer Satisfaction (indirect): NPS or CSAT scores can be higher if a retention lever like improved customer support is working. While not a direct growth metric, a rising NPS often correlates with better retention.
• Referral/Viral Metrics:
  • Referral Rate: How many invites or referrals per user. If you launch a referral program, track the % of customers who refer at least one other, or number of referrals sent per 100 users. Also track referral conversion (how many referred actually join). An upward trend means your program or viral feature is working.
  • Viral Coefficient: In some cases, you can calculate k = (average invites sent * conversion rate of invite). If k > 1, you have true viral growth. Even if not >1, increasing it from 0.2 to 0.5 significantly lowers your effective CAC. Monitor this if applicable.
  • Organic Growth Share: Simply, what portion of new users are coming unpaid/organically (including referrals/word-of-mouth) vs paid. If your lever is “add sharing to social media”, you might see organic sign-ups climb relative to paid.
• Revenue & Unit Economics Metrics:
  • Monthly Recurring Revenue (MRR) / Annual Recurring Revenue (ARR): The ultimate growth metric for revenue. Are your levers moving the needle in total MRR/ARR? Break it down further into New Business MRR, Expansion MRR, Churn MRR for clarity. For example, after an upsell campaign, Expansion MRR should show a jump.
  • Average Revenue Per User (ARPU) or per Account (ARPA): If you tweak pricing or packaging, ARPU is the metric to watch. A successful price increase or cross-sell will lift ARPU. But watch customer acquisition alongside it (price lever could backfire if ARPU up but significantly fewer customers).
  • CAC Payback Period: How many months of revenue to recover the customer acquisition cost. If you implement cheaper channels or improve trial conversion, you might reduce CAC payback from, say, 12 months to 9 months – meaning you recover costs faster and can reinvest sooner (Every Product Needs a North Star Metric: Here's How to Find Yours). This metric combines acquisition and monetization efficiency; investors love to see it improve.
  • LTV:CAC ratio: Relatedly, Lifetime Value (LTV) to CAC should increase if retention or monetization levers are effective (LTV goes up) or CAC goes down. For a SaaS, aiming for LTV:CAC of 3:1 is a common rule of thumb. If you increase prices or retention (LTV ↑) while holding CAC stable, this ratio will rise.
  • Gross Margins: A bit operational, but if you have levers around cost optimization (say migrating to cheaper infrastructure, or reducing cost-to-serve), your gross margin will improve. High gross margin means growth is more profitable. This became important in recent years as investors pushed for profitability – e.g., focusing on more profitable customer segments is a lever that might sacrifice some growth but drastically improve margins.
• Engagement & Product Metrics:
  • If your lever is introducing a new product feature aimed at growth, define a metric for its usage. For instance, if you add a “Team invite” feature, measure how many invites are sent, and subsequent effect on new user acquisition. If you create a community or content hub, track active members or contribution volume, and link that to retention or acquisition.
  • Jobs-to-be-Done metrics: If you identified certain key actions (jobs) that correlate with retention, track the % of users performing those jobs. You might say “invoices created” is a core job in accounting software – measure average invoices per user, and see if levers (like templates or reminders) increase that.

The key with metrics is to tie them back to the lever and goal. At the start, define what success looks like in metric terms. For example, “We will consider the onboarding revamp successful if Day 30 retention of new users increases by 5 percentage points”. Then instrument that metric. Sometimes you’ll need to create new tracking if it’s a new behavior.

Also, use leading indicators where possible. If your ultimate goal is ARR, you don’t want to wait a year to see if a lever worked. Instead, identify leading metrics: e.g. for ARR, leading indicators could be pipeline volume, conversion rates, user activation rates, etc. Similarly, for retention, leading indicators might be weekly product usage or user satisfaction after onboarding. By measuring these, you get quicker feedback on lever effectiveness.

Lastly, ensure you are segmenting metrics appropriately. A lever might work great for one segment (SMBs) but not enterprise, and an average metric could mask that. So slice by user cohort, plan type, source, etc., when evaluating impact. It’s common to do an A/B or cohort analysis to isolate the effect of a change.

In summary, choose a primary metric (or a small set) for each lever initiative and track it religiously. If the metric moves in the desired direction (with statistical significance if applicable), you have evidence your optimization is working. If not, dig in to understand why – maybe the lever needs a different approach or wasn’t as high-impact as assumed.

Answer Key

1. B – A growth lever is an area that disproportionately drives growth if optimized (Finding and Optimizing Growth Levers.pdf). (A is wrong because gimmicks don’t guarantee growth; C and D are unrelated humorous options.)
2. C – Retention is often the most crucial for long-term success (3 growth levers every SaaS founder should know about | TechCrunch). Acquiring users only to lose them is a leaky bucket; strong retention (and expansion) creates compound growth. Activation is very important early on (since it feeds retention), but the question asks long-term. Referral is powerful but usually supplement to a good product/retention base.
3. A – ICE = Impact, Confidence, Ease scoring (What is the ICE Scoring Model? | Definition and Overview). (It’s a prioritization framework, not a brainstorming method or interview, and not specifically technical.)
4. B – NRR >100% (rising from 90 to 105%) means expansions/upgrades outweigh churn – existing customer base is growing in value (Key growth levers for SaaS companies in 2025 | Simon-Kucher). (90% meant they were shrinking from churn, now 105% means net growing.)
5. C – PLG relies on product and virality, not heavy outbound sales. (A, B, D are classic PLG levers; C is more sales-led lever.)
6. B – They have an activation problem (users not creating content, thus not activating and later churning). The lever is to improve activation (maybe onboarding or UX to get them to create content). Getting more users won’t help if half don’t activate; referral won’t work if they don’t find value; pricing likely isn’t the root issue if they haven’t even used the product meaningfully.
7. B – Activation lever success is measured by early usage and retention: how many complete onboarding, how quickly they get value, short-term retention. (A is acquisition metrics, C is financial metrics, D is satisfaction which is more qualitative.)
8. False. NSM should correlate with customer value and leading indicators of growth, not necessarily be revenue (Every Product Needs a North Star Metric: Here’s How to Find Yours | Amplitude) (Every Product Needs a North Star Metric: Here’s How to Find Yours | Amplitude). Many companies choose a usage metric (e.g. Spotify: time spent listening) as NSM.
9. Idea C should be first (highest ICE). It implies that based on team’s scoring, C had the best combination of high impact, high confidence, and relatively easy. Therefore it likely offers the best ROI to pursue immediately. Idea D is nearly as good and could be next.
10. B – With a statistically significant improvement (12% vs 10% with 95% confidence), the new pricing page is a proven better variant. The logical step is to roll it out to all users to reap the conversion benefit. (2 percentage points is actually a 20% relative lift – quite meaningful in conversion terms). You’d monitor post-launch. No need to run longer if significance achieved; and it’s not a failure but a success.

Scoring: 10 correct – Growth guru! 8-9 – Excellent understanding. 6-7 – Good, but review some concepts. <6 – Recommend revisiting certain module sections and frameworks.

Additional Resources & References

For further learning and tools on SaaS growth, check out these resources:

• “Startup Metrics for Pirates” by Dave McClure (Slideshare) – The original presentation introducing AARRR metrics (Pirate Metrics For Product-Led SaaS - The AARRR Framework For SaaS). Great for understanding the basics of funnel metrics.
• Reforge Blog – Growth Loops – Growth Loops: Transcending AARRR Frameworks by Brian Balfour. (Reforge, 2017) – Explains the concept of loops vs funnels with examples from top tech companies (Growth Loops: Transcending AARRR Frameworks - Reforge).
• OpenView Labs – Product Led Growth – OpenView’s guides on PLG with case studies (e.g., “PLG Primer” and Benchmarks reports). OpenView Partners also has articles on identifying SaaS growth levers.
• Sean Ellis – Hacking Growth (Book) – A practical playbook on growth experimentation from the godfather of growth hacking (introduces frameworks like ICE in detail).
• Lean Analytics (Book by Alistair Croll & Ben Yoskovitz) – Deep dive into metrics that matter at different startup stages (with SaaS examples). Helps in selecting North Star and supporting metrics.
• “Only 3 Levers to Grow SaaS” – Joel York’s Chaotic Flow blog – Explains the three fundamental levers (acquire, retain, monetize) and how they interplay (SaaS Growth Strategy | A Customer Lifecycle Approach). Also look for his concept of the SaaS growth pyramid.
• HubSpot Academy – Inbound Marketing Course – Free course that shows how to leverage content and funnel nurturing (relevant to marketing-led growth levers).
• Mixpanel & Amplitude Blogs – They often publish analytics how-tos (e.g., Amplitude on North Star Metric (Collection of Some of the Best SaaS North Star Metrics), Mixpanel on cohort analysis) which are useful for measuring lever impact.
• Lenny’s Newsletter (Subscription) – Popular newsletter by Lenny Rachitsky, frequently covers growth case studies, product-led tactics, and metrics in SaaS (with contributions from experts).
• ProductLed.com – Articles and webinars specifically about product-led growth strategies (e.g., using JTBD in PLG, user onboarding tactics).
• SaaStr Blog and Videos – SaaStr by Jason Lemkin has tons of SaaS growth advice, including on pricing, retention and metrics benchmarks at various ARR scales.
• Templates & Tools:
  • Miro / FigJam templates for Growth Experiments and ICE scoring (the Miroverse link has an ICE Prioritization Matrix template).
  • Analytics tools: Mixpanel, Amplitude, Google Analytics, Heap – for instrumenting the funnel metrics. Many offer free tiers for startups.
  • CRM & Marketing Automation: HubSpot (for lead scoring workflows), Segment (to pipe data), Customer.io or Braze (for lifecycle messaging) – these help operationalize some levers like nurturing and re-engagement.
  • A/B Testing frameworks: Optimizely, VWO, or built-in tools in Mixpanel/Amplitude Experiment – essential if you plan to systematically test changes on website or in-app.
• Case Study Libraries:
  • YC’s Startup Library and First Round Review often have articles on how startups unlocked growth (e.g., Airbnb’s referral program, Slack’s enterprise adoption strategy). These real stories can inspire lever ideas.
  • GrowthHackers.com archives – searchable forum of growth experiments and results shared by practitioners.

Leverage these materials to deepen your understanding and stay current on growth trends. Remember, SaaS is dynamic – the best practices evolve, and continuous learning is itself a growth lever for your career! Good luck, and happy growth optimizing 🚀.

Case Study 18.1: Growth Levers in Action