How do you achieve go-to-market fit?

Every company’s growth journey is unique, and there’s no one-size-fits all solution to successful scaling. However, while there’s no cookie-cutter formula, we have (through decades of experience working with – and investing in hundreds of software companies) identified a number of areas that drive successful businesses towards GTMF. 

SUCCESSFUL COMPANIES…

1 Define who they serve (ICP, Positioning, Messaging)

2 Capture value (Pricing & Monetisation)

3 Build predictable demand (Marketing)

4 Retain and grow (Retention & Customer Success)

5 Scale through structure (Team Design)

Through every technological wave of innovation, these “accelerators” have been the keys to scaling, and this won’t change in the current age of AI. However, since our last toolkit update, AI has changed the face of all of these areas. As a result, the best practice for nailing your scaling strategy in each of these areas looks different today compared to earlier benchmarks or practices. 

In this section, we give an overview of how each area has evolved. We hope to cover the landscape of scaling strategies, with the objective of clarifying the route to scalable growth. 

Remember, AI in itself is no silver bullet. Across every GTM function, you can’t just throw AI at the problem and expect it to be solved. What separates the leaders from the rest is execution – how well teams implement, integrate, and manage these tools in practice.

While it would be tempting for leaders to leverage this set of accelerators as a “shopping list” and address each area sequentially, each requires constant testing, iteration and feedback. The accelerators are highly interrelated. Any business will be working on all of these areas concurrently. So, rather than a sequential list, we prefer to think of the accelerators as building blocks. Some will be more foundational than others, but in a scaling business, no element should be considered “complete”.

Now, let’s dive in. By “doing the work” here, you are well-placed to nail your path toward GTMF. 

As a starting point, ask yourself three questions: “Who am I for?”; “What problem do I solve?” and “Why am I different?”. Based on this you can then develop communication strategies that are tailored to your target audience. 

Most often, the biggest challenge in answering these questions sits with the first – defining who you serve. To understand positioning fully, let’s first outline the relationship between the Ideal Customer Profile (ICP), positioning, and messaging. 

You can think of your ICP, positioning, and messaging as three layers of clarity that build on one another.

1. Your Ideal Customer Profile (ICP) defines who your best customers are. It’s the segment of the market that feels the pain you solve most acutely, values your solution most highly, and, crucially, is willing to pay for it. It’s both strategic and operational, guiding everything from your product roadmap to your sales targeting. The goal is to create a clear picture of your “best-fit” customers by understanding their core firmographics: size, sector, geography, behaviours, and pain points.
   
   You will have worked with ICPs during your PMF stage, but around the GTMF stage, clearer ICPs should start to crystallise as you have more data to go on. For a deeper review of how to define your ICP, check outthis article on the ICP bow-tie, where we lay out a framework for how to define the ICP at different stages of growth. 

2. Once you know who you’re serving, positioning communicates what you offer and why it matters to them. It’s your place in the customer’s mind, how your solution stands out from alternatives and what unique value you deliver. Strong positioning gives you a narrative and a competitive stance that make your value proposition clear, relevant, and defensible. We’ll dive into this shortly.

3. Messaging is the tactical expression of that positioning, it’s how you talk about your value to each segment of your ICP. It’s what shows up on your website, in your sales decks, and throughout every customer conversation. Effective messaging translates your strategy into copy and content that resonate deeply with your audience and drive action.

These three layers work together in a continuous loop. Your ICP informs your positioning: it’s tough to accurately position a product until you know who it’s for! Positioning informs your messaging, translating your strategic stance into language that moves your audience. And messaging validates your ICP; if it resonates, you’ve likely nailed your target; if it doesn’t, it’s time to refine.

At the go-to-market fit stage, these elements should reinforce each other: your ICP sets a strategic focus, your positioning sets a competitive edge, and your messaging brings that edge to life in the market.

The power of positioning – winning in a competitive market

Positioning is all about articulating the unique value your company can deliver to a customer. Done right, positioning also serves as the input to the storytelling and messaging that underlines all sales and marketing efforts, as well as the internal communication determining how people speak about your company.

Put simply, positioning helps differentiate a company from its competitors, target the right customers, and effectively communicate the company’s value proposition. Highly focused, strategic positioning is critical to cutting through competitive noise and expanding your client base from early adopters into the mainstream. Software users and buyers are more impatient and overwhelmed with options than ever before. This is particularly true in the B2B software space, where companies have a myriad of solution providers vying for their attention. While the actual numbers vary depending on company size, multiple sources (like Tenet, Chief Martec and Zylo) report that the average mid-market business can have anywhere between 18 to 150 software vendors, with Zylo citing 275 solutions per company on average (across all sizes) in 2025. If that’s one company’s tech-stack, imagine how many businesses there are out there competing to get in the line-up. Choice overload is real: to illustrate this point, check out this illustration of the B2B MarTech landscape alone – in 2025, the MarTech space comprised 15,384 solutions organised in 49 categories.

Source: ChiefMartec.com

With the emergence of generative technologies, we see a boom in new startups vying for B2B software budgets. In a recent study Battery Ventures asked CXOs how they would source generative software: if they would use existing vendors, new vendors or build themselves. Across all categories, more than 50% cited that they would abandon their current solutions for something new. Having a clear positioning is imperative.

“Positioning defines how your product is the best in the world at delivering something, some value, that a well-defined set of customers cares a lot about.”

April Dunford | Positioning Expert & Author

Positioning is about being the best at something for someone. We sat down with April Dunford for a discussion about positioning, her recommended methodology for defining it, implementing it and measuring the success of it, with a particular focus on the scale-up stage. You can watch the interview in its entirety here.

Defining and implementing your positioning

How do you go about developing your positioning? There are a number of ways to structure the process, which we have reviewed and amalgamated into a list of six key steps. For a thorough resource into positioning, check out April’s book: “Obviously Awesome”.

1. Define the working group and responsibilities

Marketing might run the project to define your positioning, but shouldn’t do so in isolation. Instead, approach and design the positioning development project as an interdepartmental exercise with support and direction from the founding / executive team. Different departments (Sales, Customer Success, Product, Support etc.) hold valuable insights about customers, making their involvement imperative to pinpoint a positioning that resonates with the audience. And, crucially, with a broad working group you ensure that the new positioning permeates the entire company, increasing the likelihood of a successful adoption among the team.

2. Find your niche

Once you have set the working group, define your target market. Start by identifying the specific segment or audience you want to target. Understand their needs, pain points, and desired outcomes. There are many different ways to segment your focus. We recommend starting with:

• Customer size
• Geography
• Industry
• Department / buyer / user
• A partner ecosystem perspective
• A specialised tech-stack perspective

3. Review the competitive alternatives and conduct customer interviews

Once you have identified a niche, conduct a competitive analysis. If your company, solution or product didn’t exist, what would your customers or potential customers do today? What – or who – do you have to beat to win a deal? What do you have that they don’t have? Engage with your existing customers or target customers through interviews or surveys and seek to understand their challenges, motivations, and the value they derive from your product or service. These insights will help you articulate the specific benefits and outcomes that resonate with customers.

4. Develop an initial value proposition

Armed with these insights, you can start defining key unique points of value.

At this point many companies focus on the features they offer. While features describe the specific capabilities or functionalities of a product, value focuses on the outcomes and benefits customers derive from using it. By positioning based on value, B2B software companies can create a stronger and more differentiated message, which connects with customers and sets them apart from other solutions.

5. Craft your positioning statement

The positioning statement should be concise, and clearly articulate the unique value you provide, the target audience you serve, and the key benefits or outcomes you deliver. It should differentiate your offering and provide a foundation for all your marketing and messaging efforts.’

EXAMPLE POSITIONING STATEMENTS

“Salesforce is the world’s leading CRM platform, providing businesses with a unified view of their customers, enabling personalised interactions, and driving growth.”

“HubSpot is an all-in-one inbound marketing and sales platform that helps businesses attract, engage, and delight customers with valuable content, automation, and analytics.”

“Zoom is a cloud-based video conferencing and collaboration solution, empowering teams to connect, collaborate, and achieve more with high-quality video and audio communication.”

6. Validate the statement and iterate 

Once you have crafted your statement, it’s time to test it with internal stakeholders, existing customers, and potential customers. Gather feedback and refine your positioning based on the insights gained. Continuously iterate and improve your positioning as you gather more data and feedback from the market.

2. Capture value: Pricing & Monetisation

Mastering the revenue equation

And so, we’re back to revenue (you can read a lot more about it here). At the Product Market Fit stage you’ve proven that customers want to buy your product – but you might not know yet how much customers are willing to pay. Especially if the product differs across customer segments.

Revenue can be defined as: Products sold x price. Mastering the pricing side of the revenue equation is crucial to achieve go-to-market fit. In a scaling company, most teams are focused on building a great product or attracting customers to buy the product. In other words, the focus is on affecting the first variable in the revenue equation. The price at which that product is then sold is an underrated lever for revenue growth. If a company can raise average price per customer without affecting the number of customers, every key SaaS performance metric improves – growth rate, CAC payback period, net revenue retention, etc. Price should be considered a critical building block of your unit economics, and therefore, the profitability of your company.

Like positioning, pricing is an enormous topic that can make or break a company’s GTM strategy – and deliver a high return on investment in product and sales. Pricing is also one of the GTM areas that will be structurally most impacted by AI-centric products. For example, as the products and services companies offer have changed in character, with software replacing work traditionally completed as a service, companies that previously sold on the basis of a usage-based pricing model may encounter challenges: with agents replacing “usage” with automation, “outcomes based” pricing may become a better commercial equivalent to customer value. 

In this chapter we will scratch the surface of this topic, and at the end share some of our favourite recommended reading if you want to dive deeper.

Picking your pricing model

There are a number of pricing models that B2B software companies most typically use: tiered pricing differentiated by product feature bundles, user-based pricing (seat licenses), usage-based pricing, and transaction-based pricing.

With AI-driven products delivering customer value in novel ways (co-pilots, agents, service-as-software), there has also been a shift toward outcome-based, workflow-based or AI consumption (token-based) pricing, as well as hybrid strategies that bridge traditional models with novel ones.

We’ve summarised commonly-commercialised pricing models below:

The default starting point for many companies is often a simple flat pricing model, usually split up by tiered access to a set of more powerful features. In the classic three-tier model, a company’s typical customer purchases the middle tier, while the least expensive tier has a slimmed down feature set to appeal to more price-sensitive customers, and the most expensive tier contains the enterprise features such as single sign-on or role-gated permissions that appeal to larger organisations.

Setting a price by the number of users of a product – a user-based pricing model – is another pricing strategy widely adopted among application SaaS products. It’s especially common among companies offering workflow or collaboration products where multiple users at the customer company work together to use a product.

For infrastructure software companies, usage-based pricing models have become the established norm over the past decade. Over the past five years, this pricing model has increasingly been applied across a broader set of industries. We also see a broad overall trend that more and more software companies are starting to experiment with a combination of licence- and usage-revenue.

Transaction-based pricing is a common strategy among FinTech companies. It refers to solutions where the company charges a fee for each time the service is used, a so-called transaction fee. For example, a payment solution company generally applies a transaction cost for the purchases it processes. More recently, as embedded financial services (where a company adds on a financial product to an underlying software product) have taken off, transaction based pricing has also spread outside the FinTech space.

Outcome-based pricing is a strategy where a company charges in line with a verified business result rather than simple access or usage. For example, a support automation platform might charge a fee per ticket resolved to an agreed quality threshold, or a sales tool might take a share of incremental revenue it helps create. More recently, as AI agents and “service-as-software” have matured, outcome-based models have developed beyond services, into a wider range of software categories.

AI consumption (token-based) pricing is emerging as a natural evolution for AI-native or AI-enabled software, where the cost to serve is closely tied to the model computation required. In this pricing model, price scales with the amount of model computation consumed in the completion of a task. This approach offers transparency for customers, while delivering a predictable margin on inference input costs (similar to a “cost-plus” model). However, because token usage does not simply correlate with the value a customer derives from a service, many companies pair token-based pricing with a minimum subscription fee or outcome-related metric to maintain predictability and alignment. As AI becomes embedded in more software categories, consumption-based pricing is increasingly finding its place alongside traditional SaaS revenue models.

As such, hybrid pricing models combining two (or more) approaches are increasing in popularity. These models typically combine a fixed or licence-based element with a variable usage or performance-based component. They’re used by software companies looking to balance predictability in revenue with flexibility for customers.

For example, a company might charge a base platform fee for access and support, with additional charges linked to usage volume, API calls, or achieved outcomes. This ensures the vendor maintains cost coverage, while aligning higher margin outcomes with customer success. Hybrid models can help smooth transitions between pricing strategies, offering an elegant way for companies to introduce new value-based or AI-linked elements without overhauling their entire commercial structure. When executed well, these models create a “best of both worlds” scenario: stable recurring revenue for the company and scalable value for the customer.

This high level overview is intended to give you an introduction to the various SaaS pricing models, but it’s often a “good enough” starting point as a company builds toward and moves beyond PMF. The exception is companies whose core insight is that their industry is ready for a business model disruption but whose core product is less differentiated: here that core insight is connected to a pricing model.

As companies start thinking about GTMF, however, it’s important to take a step back and carefully consider how the product generates value. A pricing model should be constructed in a way that as customers gain more value from a product, the price the customer pays scales. In many products, value scales with increased usage, but that’s not always the case. Map the flows of value your product generates among its users and carefully consider whether your software product’s pricing increases if the flows increase. Think about possible appropriate pricing metrics that would capture those increases. And sense check yourself: solid pricing models should feel obvious.

The case of multiple products

Some SaaS companies will go beyond perfecting a single product as they grow towards building out a portfolio of products or splitting their product into distinct modules. If each product serves a different target customer and there’s no cross-sell potential, each product can be priced separately (though we ask you to carefully question whether there’s enough target customer focus and each product is contributing enough to the whole to be worth it). If the ideal customer purchases multiple products, then the pricing of each product must work together as a cohesive whole. Simplicity in the eyes of the customer becomes an important factor which can rule out complex pricing strategies for an individual product. Net revenue retention is the North Star for these strategies: the goal of the pricing model is to maximise cross-sell.

Setting the “right” price levels

When it comes to software pricing, one thing is for sure: iteration is key.

You can consider four key steps to adjusting pricing: pricing research, setting price levels, rolling out new pricing, and measuring the impact of the pricing. It’s important to balance efforts among these. One common pricing project pitfall is overreliance on a single step. Some companies will tend towards analysis paralysis and strive to find the precise “correct” price level by searching through their customer data in minute detail or engaging in long internal projects. Some will focus on quick execution without understanding the willingness-to-pay of their different customer segments and how customers conceive of value. We advocate for a healthy mix of both analysis and execution.

A more common mistake we see is companies that don’t change their pricing at all, or review it often enough. As a simple rule of thumb, companies should reconsider something in their pricing structure every six months. If it has been more than two years since a software company changed or reviewed their pricing, they may be overdue a change.

1. Pricing research

When you start reviewing your pricing, the first step is to undertake some pricing research. The aim of the research is to identify if and where the potential opportunities are to gain more revenue if you were to change your pricing. Sometimes, you will want to validate a relatively narrow hypothesis, and other times, it is necessary to analyse the full customer base to find broad patterns on which you can base your overall pricing strategy.

When you conduct your research, there are two things to keep in mind: (1) there will most likely be a difference in customer willingness-to-pay (WTP) between each of your customer segments, so conduct your research on a per-segment basis. (2) The intensity of research should depend on the stage of the company. A simple rule of thumb would be that the earlier a company is in its growth journey, the more acceptable it is to rely on founder gut-feel. As the company is maturing, the more worthwhile it is for a data analyst or consultant to spend their time finding additional gains.

We recommend two useful pricing research methods for companies that have found product-market fit and are starting to find their go-to-market fit:

1. Product usage analytics involves looking at key feature usage on a per customer basis as identifying patterns among customer segments that can lead a company to put certain features in certain tiers or to pull out some features as standalone add-ons.
2. Buyer research calls are structured qualitative interviews with the potential buyers of a product that help companies unlock positioning and pricing insights, best conducted by the strategic go-to-market leader in a company. For more information, please feel free to download the Oxx buyer research template.

2. Setting price levels

Next, it’s time to change the pricing levels. Unless you’re completely changing your pricing model, it’s helpful to think of pricing changes as selecting a few options from a smorgasbord of possible options. In other words, you’re changing your pricing tactics but not your entire pricing strategy.

Based on the pricing research, you should be able to make deductions about which options might have the greatest impact.

3. Roll out prices

When rolling out pricing changes, it’s helpful to do this in a few steps. A step-by-step approach allows for time to measure the impact on each group. The key is not to create too many steps. Too many steps can delay the ARR increase a pricing change can bring and can create so much project management overhead that it becomes unwieldy.

A key question that often arises is whether you should roll out pricing changes for all customers. This is a debated area: a school of thought led by, among others, Jason Lemkin suggests that the management overhead of raising prices for existing customers can outweigh the benefits, especially if you are a fast-growing small company (<$10m ARR). Instead, this school suggests that higher pricing should be implemented only for new customers, whereas the strategy for existing customers should be to grow via upsell. 

Regardless of the specific implementation, there are some communication best practices for revising pricing without increasing churn. Proactively communicate changes, and make the communication more targeted and personalised than everyday customer communication: send personal emails to self-serve customers, speak with customers who generally use digital support, etc. Be prepared to consider a discount against pushbacks but make it temporary. Finally, at renewal time, adjust commercial terms and conditions for contracts to build in the possibility to process an annual price increase in future.

4. Measure impact

Measuring the impact of pricing changes is a mix of quantitative and qualitative evidence. The quantitative is found in ARR data – churn, upsell, renewals – and customer acquisition data – changes in click-through rates on the website, lead generation, and funnel drop-off rates. The qualitative data is found in NPS scores and feedback from customer-facing teams.

In the below table we’ve assembled recommended metrics to evaluate the efficacy per pricing model, along with commentary on each of these.

Why it’s (almost) always about raising prices

There’s a cliche that as soon as a new investor comes on board, they’ll suggest a software company raise prices. As shown above, we don’t advocate companies adopt such a blunt method. However, it is true that the majority of SaaS companies raise prices as they scale, and that early-stage software companies are leaving value on the table. 

Many startups make classic “upmarket” journeys, initially selling to small- and medium- sized customers before tackling enterprise-level buyers. This is sometimes a conscious choice: it takes time to build out enterprise-grade features, acquire necessary compliance, and to have the resources to invest in year-long sales processes. But it’s worth being conscious about this evolutionary development in a business: as the positioning naturally evolves, so should a company’s approach to pricing. 

3. Build predictable demand
– Marketing as a growth system

Marketing as a revenue driver 

Marketing’s role in a SaaS company is to drive the growth system, ensuring that every euro or pound spent, every campaign launched, and every story told compounds towards sustainable, predictable revenue.

Software marketing teams have historically focused on activities directly tied to conversion – generating MQLs, SQLs, and SALs to feed into sales teams. The emphasis was on what could be measured and moved through the funnel, quickly. Harder to quantify marketing activities (for example, brand building) have been deprioritised. 

However, the best software companies recognise that differently measured marketing activities, demand gen and brand building, are not competitors – they’re two sides of the same growth engine.

In this chapter, we’ll outline why balancing long and short term strategies is essential for marketing success and generating predictable revenue, and sharing a few keys to success.

Predictability means balancing marketing strategies

Marketers have to contest with a hard truth: most of a company’s potential buyers aren’t buying today. They’re not currently “in market”, searching for a solution to a specific problem. Research from LinkedIn’s B2B Institute and the “godfathers of effectiveness” Les Binet & Peter Field shows that at any given time, only about 5% of B2B buyers are in-market – the remaining 95% aren’t buying today, but they could be in the future. 

So, modern B2B marketing has to balance its focus between capturing “in market” leads (the 5%), and then creating momentum for longer-term pipeline development. The best software teams build a marketing engine that makes their company impossible to ignore among the right audience, long before the buying window opens. This becomes especially important as companies mature and reach the scale-up stage, as they should afford to spend more resources on long-term strategies and as such, the awareness element of a marketing plan deserves far more weight than previously. That’s why brand is central. It shapes awareness and trust, which are the precursors to conversion. Brand investments are not just a cost-centre, but a revenue multiplier: the driver of performance marketing effectiveness, community growth, and outbound conversion in future.

TACTICS PER AUDIENCE, LONG VS SHORT TERM

To underline the swing for companies to become more focused on brand, McKinsey’s State of Marketing 2026 Europe report also noted that “brand” was the top priority for European B2B CMOs .

Focusing on finding balance

Predictability at the go-to-market fit stage comes from balancing short-term speed with long-term stability. The best teams:

• Plan several quarters ahead, ensuring today’s pipeline activity fuels tomorrow’s revenue.
• Use forecasting tools to model how changes in spend, content velocity, or outbound activity impact pipeline and ARR growth.
• Balance fast-return channels (paid search, social ads, retargeting) with compounding ones like content, community, partnerships, PR, and brand.
• Leverage AI for measurability, using it to understand how awareness and share of voice correlate with pipeline creation over time.
• Blend short-term efficiency with long-term momentum, building a growth engine that compounds.

If you can model your pipeline development several quarters ahead and explain where you expect 80% of that net new revenue will come from, motion by motion, you’re approaching true go-to-market fit.

What to look out for

Many teams confuse activity with progress. Warning flags that your growth engine isn’t yet predictable include:

• Quarterly resets: every new quarter feels like starting from zero, with little compounding effect from past campaigns.
• Volume obsession: marketing celebrates lead numbers while sales misses targets, meaning you’re optimising for inputs, not outcomes. This tends to be one of the habits you need to break as you grow and mature.
• Channel dependency: overreliance on one or two paid channels that stall the moment you reduce spend.
• Attribution paralysis: endless debates about which campaign gets credit instead of learning what drives momentum overall. Remember to zoom out. 
• Static forecasting: pipeline projections that don’t adjust dynamically to changes in spend, velocity, or buyer behaviour.

If more than one of these sounds familiar, your marketing engine is active but not yet predictable.

FROM INTEREST TO CLOSED WON PER GTM

Increasing the velocity and predictability of leads is crucial for a well-functioning GTM function in any organisation. In fact, one good sign for when the marketing function has found Go-to-Market Fit is when it can confidently predict how many high-quality leads (aligned to customer segment and target ACV) you’ll attract and whether they’ll convert.

It doesn’t matter which, or which combination of, approaches you have – regardless if your sales are product-led, inbound or outbound, driven by inside or field sales, predictability is still a main objective. Many companies use multiple marketing strategies and combine them in a unique mix that fits them and their goals. What is true is that modern B2B marketing departments are tasked with generating revenue – which also means tying their spend to revenue. As you enter the Go-To-Market Fit phase, you should challenge your marketing team to be data-driven and measure the full-funnel impact of their activities.

A few keys to success

Key to success 1: Understand buyers – and operationalise this understanding

In the insights driven world, you need to understand your buyers. If you’ve nailed your ICP and done your positioning work, you’re off to a great start. But as you put these insights into practice, you should both see results and constantly learn more information: understanding your buyer isn’t about static personas.

High-performing teams operationalise four to five key signal categories:

• Behavioural: website visits, demo requests, and pricing-page activity.
• Intent and research activity: keyword searches, competitor comparisons, and content engagement.
• Community and social: mentions in peer groups, customer review aggregators (e.g. G2), or LinkedIn interactions.
• Product usage: activation rates, feature engagement, and trial data.
• Brand visibility: presence across AI-assisted search, SEO, and structured content.
  

Signals only matter when someone acts on them. Once an account shows buying intent, modern Account Based Marketing (ABM) orchestration tools (like 6sense or Demandbase) trigger coordinated plays across SDR outreach, ads, and even in-product prompts. Ideally, marketing, sales, and product teams share a “go-to-market intelligence hub” where these signals converge, ensuring everyone acts on the basis of a shared ground truth.

Over time, this intelligence loop refines your ICP and positioning (link to these sections). Every campaign and customer interaction becomes an input for learning, building a tighter, more predictable connection between awareness, engagement, and revenue.

Every quarter, the GTM team can then review signal data to answer:

• Which behaviours correlate most strongly with purchase intent?
• Which personas show up most often in high-velocity deals?
• Which channels influence pipeline creation the most?

Key to success 2: Measure what matters

When you have reached the GTMF stage, you can’t look at efficiency as just a marketing metric – it’s a company one. The focus shifts from isolated results to shared progress: how effectively the entire GTM system turns attention into pipeline and pipeline into revenue.

Modern teams measure across three dimensions:

Marketers have excellent technology at their disposal, so invest time in building and experimenting with your tech stack. One of the most common reasons for revenue underperformance remains the same: not understanding clearly where the sales and marketing funnel leaks. AI now makes it possible to merge quantitative and qualitative data, tracking both conversion and sentiment, into a single GTM efficiency dashboard. Automated systems can flag anomalies like slowing activation or lower demo-to-close rates within days. But human judgment still defines the “why.”

A good feedback loop isn’t just diagnostic; it’s directional. It should:

• Identify where friction occurs (e.g., trial-to-paid drop-off).
• Recommend hypotheses (e.g., onboarding friction or misaligned pricing).
• Inform both marketing messaging and product priorities.

Predictability depends on this process of iterative feedback. Every quarter, teams test hypotheses (“What if we adjust spend, content velocity, or outreach volume?”) and forecast the impact on revenue. Static conversion rates are replaced by dynamic, data-informed learning loops that improve precision over time.

Key to success 3: Ensure you have true alignment across teams

Many teams believe they’re aligned because they share dashboards, definitions, and pipeline goals. Yet the gap between marketing and sales persists. As one SaaS CMO put it: “Department wins don’t matter if the company loses.” 

Winning quarters consistently comes down to operational precision:

• Target winnable deals. Build clear Do / Defer / Don’t rules by segment. Focus where you have a proven right to win.
• Design matching motions. Ensure campaigns reflect how sales actually sells – whether that’s ABM, product-led, or hybrid.
• Perfect the baton pass. SQLs and opportunities should come with real context, not just names.
• Run deal reviews without theatre. Use every week to identify friction, act on it, and learn fast.
• Tell one story. Every rep and marketer should be able to deliver the company’s 60-second story – and back it with proof.
  

Volume may drop when you focus like this, but win rates, velocity, and predictability typically rise. That’s alignment in practice, not just principle. GTM teams will succeed during the quarter and strengthen their foundation for the next one.

4. Retain & Grow

Winning customers takes grit, but keeping them takes discipline. Retention is about living up to your customer promises and making sure your product delivers, your pricing matches the results, and your customers’ stakeholders feel the impact. Growth built on loyalty compounds quietly, and it’s what separates good software companies from great ones. If you’re looking for predictability, retaining your core customers is key. And it starts as soon as they onboard with your product or service. 

Treat onboarding as a differentiator

Software purchasing is becoming increasingly consumerised, and end-users expectations are getting higher and higher. Quality of onboarding has therefore become a more important cross-functional area of focus, with GTM, customer support / success and product / technical teams often involved. This can be especially challenging in an enterprise where your business needs buy-in from a wide group of users or teams.

In 2025, AI is becoming a defining technology in how companies design onboarding and retention. Intelligent assistants and workflow agents are helping users navigate products, resolve issues, and discover value with less friction. But the fundamentals haven’t changed. Great onboarding must still quickly align user behaviour with real outcomes.

The shape of onboarding, and the levers that drive retention, depend heavily on your GTM motion and vertical. 

1. Product-Led Growth (PLG)

For PLG businesses, onboarding is the sale. The experience must deliver Day 0 value and make the “aha moment” feel inevitable.

• Use in-app AI agents to guide users contextually based on their goals and usage patterns.
• Personalise activation flows dynamically: a designer and a developer might not see the same onboarding journey.
• Track time-to-value, feature adoption, and usage recurrence as leading retention indicators.
• Apply predictive analytics to flag friction or inactivity early, then automate outreach.
• Design freemium and trial experiences around meaningful customer outcomes, not vanity metrics (e.g. “sign-ups”).

Retention in PLG companies is a measure of how quickly users discover recurring value. The best PLG companies are pairing product analytics with embedded AI to create self-improving onboarding loops that continually shorten the path to value.

2. Sales-led (enterprise and mid-market)

In enterprise software, onboarding is a long-tail exercise in stakeholder management. You’re not only onboarding users, you’re onboarding an organisation.

• Map stakeholders early: decision-makers, champions, and end-users all need tailored engagement. You’ll have likely started this throughout the marketing and sales process. 
• Blend automation and human touch: structured playbooks (for consistency) and hands on sessions for trust.
• Use AI-driven analytics to summarise adoption across departments and surface risk automatically.
• Tailor communications by persona with AI-generated content and insights.
• Track adoption breadth across departments, not just usage volume.
• Reinforce ROI quickly: show the economic impact and tie it to the customer’s business case.
  

Poor onboarding in enterprise contexts rarely shows up immediately, but when it does, it hurts. If the relationship starts off on the wrong foot, it’s a long climb back. And even a handful of lost customers in an enterprise software business can significantly impair ARR.

3. Hybrid or Vertical-Specific Models

Many vertical or hybrid GTM businesses blend PLG and enterprise dynamics. They face added layers of localisation, compliance, and process complexity.

Here are some additional considerations for complex deployments:

• In regulated sectors, automation must account for approval and compliance.
• AI can help localise documentation and workflows to regional norms.
• In data-intensive applications (such as procurement or HR software), AI copilots can benchmark performance and flag adoption blockers.
• Onboarding isn’t a single event but an ongoing enablement process.
  

Universal principles

Deep thought should be given to the relative merits of free trials, demos, and freemium options. What type of behaviour does each drive? Does that align with individual user value, and with cross-team adoption? The faster users reach their ‘aha moment,’ the more likely they are to become advocates who expand usage organically and increase customer quality.
Make it as easy as possible for the first users experiencing your platform to ‘get it’ — ideally Day 0 value. That might mean structured, automated workflows like Canva’s, or a human-centric onboarding process like Superhuman’s. Track feature usage closely and be highly responsive to interactions in those critical early weeks.

While the benefits of world-class onboarding are most often considered for SMB-focussed software tooling, enterprise software businesses shouldn’t shy away from ensuring the onboarding experience is as delightful (or at least as painless) as possible.

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SMB software that might be on short contract cycles or rolling month-on-month contracts will be able to see very quickly in their retention data whether customer fit and onboarding have been successful. For them it’s also straightforward to quickly A/B test the impact of onboarding on retention and consequently work out if the strategy makes economic sense. Enterprise focussed businesses with annual or longer contracts don’t have the benefit of this short-term feedback. Nonetheless, the impact of poor onboarding can be even more damaging, as the consequences can appear more dramatically if a few large clients churn a year later.

As we touched on in the Positioning section, B2B software buyers today have more choice than ever. With so many alternatives on the market, your onboarding and early customer experience can make or break retention. Don’t give them a reason to cut you.

Regardless of your target segment, investing in onboarding is one of the most effective ways to strengthen retention and open the door to expansion. It sets the tone for your customer relationship, proving early that your product delivers on its promise and is worth the investment. In the end, that’s what builds loyalty – and lasting growth.

Double-down on Customer Success to secure high customer retention

The benefits of best-in-class retention are often underestimated. Without a doubt, the best action a company can take to rapidly accelerate towards GTMF is to support the customer success team and focus on retention. After all, the cost of acquiring new customers is broadly agreed to be around five times higher than the cost of retaining existing customers. So, if you want to boost your unit economics, don’t ignore the value of the companies in your portfolio. Below, you can see the results of maintaining strong net revenue retention (NRR) – in this example, even with no new business.

The chart shows the power of compounding – upsell and strong revenue retention can underwrite really solid levels of persistent growth.

The chart below is from a Bessemer Venture Partners survey of 174 companies, showing acquisition costs for renewal and upsell / cross-sell are a fraction of new account acquisition. The numbers speak for themselves, you need to be in the retention game.

Customer Success as a source of revenue

The rise of Customer Success as a revenue centre is transforming the way companies approach retention. There are two schools of thought regarding who should handle renewals and upsells in SaaS businesses with traditional outbound go-to-market (GTM) processes. The first school argues that a Customer Success (CS) representative, who works closely with customers to help them achieve their business objectives, is best suited for executing renewals and identifying upsell opportunities. The second school believes that a CS representative should focus on building a genuine, long-term relationship with the customer and act as a trusted advisor, without any agenda to sell.

Companies often start with a generalist approach, where employees handle multiple responsibilities. However, as companies scale, it becomes challenging to find individuals who excel both in closing deals and supporting customers. This leads to the need for specialised teams with dedicated KPIs. Maintaining alignment and a 360-degree view of the customer becomes more difficult as teams specialise and scale, impacting the value delivered to customers and increasing the risk of churn.

Despite the ongoing debate over responsibilities, Customer Success teams are gaining strategic importance, influence, and budget within organisations. According to ChurnZero’s 2022 Customer Success Leadership Study, 78.5% of Customer Success teams report into the C-suite, indicating their revenue-driving role. In larger companies, one-third of CS leaders hold positions in the C-suite. Revenue metrics, such as Net Revenue Retention (NRR) and gross revenue retention (GRR), are now the top measurements of success for CS teams. In fact, net revenue retention is one of the metrics most commonly used to measure the health of a customer success organisation.

Many customer success teams still lack the appropriate technology infrastructure to deliver insights, increase efficiencies, drive revenue, and enhance the customer experience. Only 46.3% of CS teams have a purpose-built Customer Success platform, despite six out of ten teams having a CS operations role. Luckily, there’s an increasing number of software solutions that address these challenges.

5. Scale through structure – Team design

Team design for software companies is going through significant flux as the accelerated advancement of AI technologies is allowing a greater level of efficiency across the organisation. This is exemplified with the dramatic change in ARR per FTE efficiency metrics. Best in class scaled software businesses have ARR per FTE of around $350-400k (Growth Unhinged), whilst some AI-native champions are demonstrating record levels (OpenAI and Anthropic are >$1m, Lovable >$3m and Cursor >$6m according to SaaStr). 

This change is due to the heightened level of automation possible as labour is replaced with software, and it has shifted the hiring profile for fast-growth software businesses towards “more hybrid and generalist profiles – at the intersection of domain expertise and AI” (quote attributable to Fin). At its most extreme, it has led to discussion over the possibility for solo-founder unicorns to emerge. 

Interestingly – the evidence so far for most scaleup software businesses is more mixed on deliverability of these savings. Research from A16Z shows that software businesses with $5-20m ARR have roughly the same number of median employees as the 2022-2024 average (~65); though more scaled businesses are seeing significant operating leverage – with reduction in the number of median employees of 42% ($20-50m ARR); and 59% (>$50m ARR). 

In our view – consistency in the median masks significant variation, as we are seeing top scale-up stage businesses grow significantly faster, more quickly, with leaner teams. Team leads usually exhibit more ‘hybrid’ profiles and have higher degrees of technical capabilities and ‘systems thinking’ than in the old-world, which results in slower pace of junior hiring and more operational efficiency generally. 

Having said this – despite the advancement in AI tooling that’s being deployed particularly in R&D, CS and the GTM stack, some of the traditional lessons on structuring the human part of the GTM team have remained quite consistent.

Specialise revenue-generating team roles

If you are looking to increase efficiency within the team, evidence from organisational research shows that employee performance improves as a result of an appropriate degree of role specialisation. It’s a fairly logical conclusion; if you are juggling multiple projects and responsibilities, the likelihood of pushing them all forward at a fast pace decreases. Often you will make progress, but slowly and with small steps. With fewer responsibilities, you would be able to execute with a higher focus and make progress at a much faster pace.

To transpose this into our B2B SaaS arena, some people have even laid out a roadmap for the precise GTM hires that a SaaS business needs at each stage in their development in order to time the level specialisation needed depending on where in the journey the company is. We don’t think it’s practical to be quite so prescriptive and mechanical about it, but have seen repeatedly that reviewing resourcing in the following areas lead to superior performance. The first three examples below typically refer to the traditional outbound GTM/sales process. Examples four through six refer to some of the different approaches required to succeed with new user-focused (rather than buyer-focused) GTM approaches, through marketing, product or community led growth strategies.

If you are looking to increase efficiency within the team, evidence from organisational research shows that employee performance improves as a result of an appropriate degree of role specialisation. It’s a fairly logical conclusion; if you are juggling multiple projects and responsibilities, the likelihood of pushing them all forward at a fast pace decreases. Often you will make progress, but slowly and with small steps. With fewer responsibilities, you would be able to execute with a higher focus and make progress at a much faster pace.

Commercial team lines are blurring as many businesses pursue hybrid top down and bottom up GTM approaches, and cross-functional teams become more common. Two examples include a customer segment pod approach (combining sales and customer success into teams per customer segment) or establishing a growth team (combining marketing, engineering and product).

Our advice is to segment your customers into reasonably homogenous core groups, and design tailored GTM processes and team structures around the different acquisition journeys of clients. As your business scales, it’s normal to see increasing specialisation across different stages of the acquisition funnel, as well as specialisation across ‘styles’ of commercial teams. When specialisation increases, this can create an increased range of natural career paths for higher internal mobility. This is a very valuable spill-over benefit that can have huge cultural positives.

Right-size the GTM team leads, at the right time

Continuing on the topic of resourcing and team building, ”I’m looking for a great VP of X” quickly followed by ”any advice on what profile I should look for?” are two of the more common questions companies ask us. The simplest advice is to look for an individual who can bring you a playbook for success, but with the curiosity and drive to rewrite that playbook for your company’s unique GTMF journey.

It’s important to right-size these leaders. What do we mean by right-sizing? Finding a candidate that has the experience and career goals that match with your journey. Ideal candidates have just completed a scaling journey similar to the one you’re embarking upon, in the same role. Beyond these rare gems, look for individuals with high potential who have experienced a company achieving GTMF, even if they were, for example, the head of sales reporting into the VP of Sales. A key factor here is the recency of their experience – we generally see less impressive results from recruits who haven’t operated in a company of similar size for over a decade, no matter the companies they have worked for. The B2B SaaS world moves, and changes, quickly, as do the processes at these companies. 

Below we go through a number of typical role profiles. While these are the classic titles you would be looking for, you may instead (or in addition if your budget allows it) seek out a VP Customer Success, VP Partnerships or a VP Growth depending on your GTM motion and company. Most importantly, it’s absolutely critical that all of your commercial leaders maintain excellent alignment.

Hiring abroad?

Geography can be a confounding variable when determining which roles to create or prioritise. Companies often struggle to determine the right level of early international commercial leaders. Is it better to hire a senior US-based CRO as #1 hire to build the team? Should a co-founder relocate and bring in local Head/VP level individuals? Do you start with mid-level employees in a satellite office and manage remotely? Can you scale a company internationally entirely from your HQ?  These are challenging questions to grapple with, and often idiosyncratic cultural factors, founding-team dynamics and senior capabilities play crucial roles in determining the best strategy. We typically see that a co-founder relocating or scaling from HQ tends to work best to establish a strong beachhead customer base, after which a company typically transitions to a local, senior leader.

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