Pricing is one of the most overlooked B2B growth levers

Pricing is often overlooked as a growth lever. When building growth strategies, teams typically focus on acquisition, retention, and engagement – rarely considering how pricing strategy can drive significant business growth.

In this comprehensive guide, we’ll explore how pricing fits into your growth model, uncover the many opportunities beyond simple price increases or decreases, and show you how to effectively evaluate pricing experiments as part of a complete growth strategy.

Understanding growth levers

Before diving into pricing specifically, let’s establish what growth levers are and why they matter.

A growth lever is an area of your business that you’re looking to improve through experimentation. It’s something that’s holding your growth back – that layer between your North Star metric and your day-to-day activities that shows what’s actually high impact.

Growth levers help solve a common problem: experimentation can get messy. Without focus, teams try to test everything at once, spreading themselves too thin. Growth levers bring focus to one or two high-impact areas, allowing you to compare ideas like-for-like rather than across different parts of your business.

As Daphne Tideman explains: “You want to make sure that you have several experiments focusing on one lever. Maybe you have two, maybe three in a growth team, but any more than that, you’re stretching yourself too thin.”

A strong growth lever is clearly defined and brings focus rather than being too broad. For example, rather than saying “improve Meta ads,” a better lever might be “increase conversions through paid channels” – or even more specific depending on your organization’s size.

The complete growth model

To understand where pricing fits, we need to look at the complete growth model. A growth model provides:

1. Better alignment across departments: Without a unified model, each department focuses on their own metrics in isolation. A growth model shows how marketing, product, sales, and customer success all contribute to the same goals.
2. Focus and clear priorities: A good model helps you identify which areas need the most attention right now, preventing the “we should test everything” syndrome that kills momentum.
3. A visualization of how growth happens: By mapping out the entire customer journey and how different parts connect, you create a shared understanding that makes communication easier.
4. A framework for determining priorities: When you can see how each part of your business impacts others, you can make smarter decisions about where to invest resources.
5. Clarity on key channels: A complete model shows which acquisition channels, activation triggers, and retention mechanisms actually drive sustainable growth.

Traditional growth models include:

• Funnels (like the AARRR or “pirate metrics” model): Acquisition, Activation, Retention, Referral, Revenue. Funnels work well for linear businesses where customers follow a predictable path.
• Growth loops: Self-reinforcing systems where outputs of one process feed back as inputs. For example, users create content, which attracts more users, who create more content. Loops work well for network-effect businesses.
• Flywheels: Similar to loops but emphasizing momentum that builds over time. Flywheels focus on reducing friction at each stage to accelerate growth.

Each model has advantages and disadvantages. Funnels provide speed and a holistic view but remain linear. Loops and flywheels create exponential growth but take longer to build momentum.

Setting your North Star metric

Your North Star metric sits above your growth levers. It’s the overarching metric that guides your entire growth strategy.

A strong North Star metric must:

1. Help customers reach their end goal: Your metric should measure how well you’re delivering the core value customers want from your product. For example, Airbnb’s “nights booked” directly measures their promise of connecting travelers with places to stay.
2. Apply to all your customers: If your metric only applies to a segment of users, you’ll optimize for that segment at the expense of others. Your North Star should encompass your entire customer base (or the specific segment you’re focusing on).
3. Be measurable for your organization: You need reliable data collection systems to track this metric consistently. If you can’t measure it accurately, you can’t use it to guide decisions.
4. Grow frequently enough to track progress: A metric that only changes quarterly won’t provide the feedback loop you need. You should see movement often enough to know if your efforts are working.
5. Have a clear measurement frequency: Decide whether you’re tracking daily, weekly, or monthly changes. Too frequent measurements might show noise rather than signal; too infrequent and you can’t react quickly enough.
6. Allow you to react quickly to changes: When the metric moves, you should be able to identify why and take action. If the cause-effect relationship is too murky, the metric won’t drive behavior.
7. Tie directly to business growth: While customer value comes first, your North Star must also correlate with revenue and profitability. If customers love a feature that doesn’t drive business value, it’s not a sustainable focus.
8. Be impacted by the full customer journey: A good North Star is influenced by acquisition, activation, retention, and monetization – not just one part of the funnel. This ensures balanced optimization.

Your North Star metric should remain consistent even as your business evolves, unless you make a fundamental strategic shift or discover you were pre-product-market fit when you set it.

Why pricing gets overlooked as a growth lever

Now let’s focus on pricing specifically. Pricing experiments and business model adjustments often get neglected for a simple reason: many growth models don’t explicitly include them.

While some frameworks like the AARRR model or Sean Ellis’ growth model incorporate revenue metrics, popular concepts like growth loops and flywheels typically don’t include pricing as a core component. This omission means teams using these models might never consider pricing as an area for experimentation and optimization.

As Tideman notes: “The growth model includes linear channels coming in, acquisition loops, and retention loops, but it doesn’t necessarily automatically mean that you’re going to include pricing in there. It’s really hard to build that into a certain style of model.”

This doesn’t mean you need to abandon your current growth model. Rather, you should regularly consider pricing as a high-impact area that deserves dedicated attention and analysis.

Beyond price points: areas for pricing experimentation

When most people think about pricing experiments, they imagine simple price increases or decreases. But there’s a much broader range of elements you can test:

Subscription structure

• Number of tiers and what each offers: More tiers create more price points but can increase complexity. Test whether 2, 3, or 4+ tiers drive higher overall revenue. For example, adding an enterprise tier might capture value from larger customers without affecting your core market.
• Feature allocation across tiers: Which features belong in which tier dramatically impacts perceived value. Test moving key features between tiers to find the optimal balance between conversion and monetization.
• Pricing structure for each tier: Test linear pricing (e.g., $10, $20, $30) versus non-linear (e.g., $10, $25, $50) to see which drives higher tier selection and overall revenue.
• Presentation methods: How you display pricing affects conversion. Test grid layouts versus horizontal comparisons, feature-first versus price-first presentations, or highlighting different tiers as “recommended.”
• Lifetime vs. renewal options: Test offering one-time payments alongside subscriptions. Some customers prefer paying more upfront to avoid recurring charges.
• Discount strategies: Test different discount amounts, time-limited offers, or conditional discounts (e.g., “20% off when you pay annually”).
• Trial models: Test free trials versus paid trials, different trial lengths, or credit card required versus no credit card. Each approach attracts different customer types with different conversion and retention patterns.

Upsells and downsells

• Timing (initial purchase vs. later): Test offering upgrades immediately after purchase versus waiting until customers have experienced value. The optimal timing depends on your product’s complexity and value demonstration timeline.
• Offer types: Test feature upgrades, capacity increases, add-ons, or complementary products to see which resonates most with your audience.
• Sequencing: Test different paths like upsell → stop, upsell → downsell, or multiple sequential offers. The right sequence can dramatically increase acceptance rates.
• Multiple upsell paths: Test branching logic where different customer segments receive different upsell offers based on their behavior or characteristics.
• Personalization: Test tailoring offers based on usage patterns, company size, industry, or other factors. Personalized offers typically convert better than generic ones.

Average order value optimization

• Complementary product recommendations: Test different recommendation algorithms, placement, and messaging to increase attachment rates.
• Bundle configurations: Test various product combinations, bundle discounts, or “build your own bundle” options to maximize value perception.
• Volume discounts: Test different discount thresholds and amounts to encourage larger purchases without sacrificing margin.
• Free shipping thresholds: Test different minimum order values for free shipping. Finding the sweet spot can significantly increase average order value.
• Loyalty programs: Test point systems, tiered rewards, or exclusive benefits for repeat customers to drive long-term value.
• Dynamic pricing: Test adjusting prices based on demand, inventory levels, customer history, or other factors to optimize for both conversion and margin.
• Limited-time offers: Test different scarcity and urgency tactics to accelerate purchase decisions and increase order size.

The challenges of pricing experiments

While pricing experiments can drive significant growth, they come with unique challenges:

Short-term vs. long-term impact

Certain actions like discounts or price reductions may appear successful in the short term by boosting conversion rates and immediate revenue. However, these same tactics can lead to lower lifetime value and negatively impact retention over time.

This happens because discounts can attract price-sensitive customers who are more likely to churn when the discount ends. Additionally, frequent discounting trains customers to wait for sales rather than paying full price.

The solution? Measure pricing experiments over longer periods and focus on lifetime value after costs rather than just initial revenue. Ask yourself: Are those additional customers from discounts actually staying and returning? With the reduced margin, is the approach truly more profitable?

This requires patience and discipline. You might need to run experiments for 3-6 months to see the true impact, especially for subscription businesses where retention patterns take time to emerge.

Measurement complexity

Multiple factors can impact pricing experiment results, making it difficult to isolate cause and effect. This is especially challenging for smaller brands that may struggle to reach statistical significance with their customer base.

External factors like seasonality, competitor actions, or market conditions can confound your results. For example, a price increase might coincide with a competitor’s outage, temporarily masking negative effects.

To address this, extend measurement periods to gather more data with fewer customers, and supplement experiments with qualitative feedback to gain deeper insights. Consider using cohort analysis to compare similar customer groups over time, controlling for as many variables as possible.

Also, be cautious about drawing conclusions from small sample sizes. A pricing change that seems successful with 50 customers might show different results when scaled to 5,000.

Customer backlash risk

Constantly changing prices can trigger negative feedback, erode trust, and increase churn. This often happens when companies suddenly increase prices without adequate warning or special consideration for existing customers.

Price changes affect not just acquisition but also retention and brand perception. Customers who feel blindsided by price increases may leave and share negative experiences, damaging your reputation.

Best practices include:

• Communicating permanent changes well in advance: Give customers at least 30 days notice for significant price changes, explaining the rationale clearly.
• Providing clear explanations for price changes: Tie increases to added value, improved features, or increased costs in a way customers can understand.
• Treating long-term customers preferentially: Consider grandfathering existing customers at their current rate, offering smaller increases, or providing additional value to offset changes.
• Using small experiments and research to validate pricing before broader rollouts: Test with a small segment before implementing company-wide to gauge reaction.
• Testing one variable at a time rather than multiple simultaneous changes: This helps isolate what’s working and what isn’t, making it easier to interpret results.

Conducting effective pricing research

Remember: your costs don’t dictate your price. Many brands claim they can’t change pricing because it’s based on production costs or competitor pricing. But your competitors likely don’t know what to charge either, and just because something costs a certain amount to produce doesn’t mean customers will pay that price.

Pricing research helps you understand what drives value, how to communicate that value, and what price customers associate with it. Think of it as finding “price-market fit” – ensuring your pricing aligns with your channel, audience, and product to create a scalable business.

Here are three effective pricing research methods:

1. Van Westendorp Price Sensitivity Meter

This model helps find your pricing sweet spot by asking four key questions:

• At what price would it be so low that you’d question the quality?
• At what price would it start to be a bargain?
• At what price would it start to seem expensive?
• At what price would it become too expensive?

These questions create a range of acceptable prices, identifying where a product isn’t too expensive to lose customers but not too cheap to sacrifice margin.

To implement this method:

1. Identify a representative sample of your target audience
2. Present your product concept clearly
3. Ask all four questions in sequence
4. Plot the responses on a graph to find the intersection points
5. The area between these intersections represents your optimal price range

Advantages:

• Simple to implement with basic survey tools
• Captures multiple price ranges rather than a single point
• Identifies both upper and lower pricing boundaries
• Reveals psychological pricing thresholds

Limitations:

• Provides limited context about why people value your product
• Focuses primarily on price sensitivity without considering other purchase factors
• Doesn’t account for brand perception or competition
• Less effective for luxury brands where willingness to pay relates to brand loyalty
• Based on stated opinions rather than actual purchasing behavior
• Assumes rational consumer behavior when real decisions are often emotional

2. Conjoint Analysis

This method breaks down products into smaller attributes to understand how customers prioritize different features in purchasing decisions. It creates hypothetical product profiles with varying attributes and asks respondents to choose between them, simulating real purchase decisions.

Tideman explains: “It’ll look something like this on the right, where you have these three different options, and you ask people, which of these three would you choose? That will help you understand the preference over features versus pricing of it.”

To implement conjoint analysis:

1. Identify the key attributes of your product (features, pricing tiers, support levels, etc.)
2. Create different variations of each attribute
3. Generate product profiles combining different attribute levels
4. Present respondents with sets of profiles to choose between
5. Analyze which attributes most influenced choices
6. Calculate the relative value of each attribute and optimal price points

Advantages:

• More realistic simulation than simple price questions
• Identifies which product attributes matter most to different segments
• Reveals customer trade-offs between features and price
• Allows market segmentation based on preferences
• Reduces social desirability bias by making price just one of many factors

Limitations:

• More complex to implement, often requiring specialized software
• May miss external factors affecting purchase decisions
• Difficult to isolate which specific factors drive choices
• Requires careful selection of attributes to test
• Can become overwhelming for respondents if too many attributes are included

3. Gabor-Granger Method

This approach determines price elasticity by estimating how demand changes with price adjustments. The process involves:

• Selecting a range of price points to test
• Asking respondents if they would purchase at each price point
• Analyzing at which price the highest percentage would purchase
• Determining the optimal price balancing volume and margin

To implement this method:

1. Select 5-7 price points ranging from below market to premium
2. Ask respondents if they would purchase at the lowest price
3. If yes, increase to the next price and repeat
4. Continue until they say no
5. Plot the percentage of “yes” responses at each price point
6. Calculate revenue at each price (price × percentage willing to pay)
7. Identify the price that maximizes revenue

Advantages:

• Simple to conduct with basic survey tools
• Provides quick results you can implement immediately
• Cost-effective with minimal resource requirements
• Useful for new products without historical data
• Directly addresses willingness to pay

Limitations:

• Relies on hypothetical responses rather than actual purchasing
• May anchor respondents to initial price points, skewing results
• Assumes a linear relationship between price and demand
• Doesn’t capture market complexities like competition or changing conditions
• Focuses on maximizing short-term revenue rather than long-term value

Calculating the impact of growth levers

When evaluating pricing against other potential growth levers, you need a systematic approach. Create a table that includes:

1. Current KPI value: Establish your baseline performance. For pricing, this might be average order value, conversion rate at current price points, or revenue per user. Use at least 3 months of data to account for fluctuations.
2. Benchmark or potential value: Research industry standards or set realistic targets based on your own historical improvements. Don’t aim for perfection – aim for meaningful progress. For pricing, look at competitors, similar industries, or your own historical tests.
3. Impact on North Star metric if improved: Calculate how changes in this lever would affect your primary goal. For example, if increasing prices by 10% reduces conversion by 5%, what’s the net effect on revenue? Create simple models to estimate these relationships.
4. Other positive impact areas: Consider secondary benefits beyond the direct KPI. Pricing changes might affect customer perception, support load, or product usage patterns. Document these to get a complete picture of potential impact.
5. Cost (budget and resources): Estimate both financial costs and team resources required. Some pricing experiments require minimal investment (like testing different presentation), while others (like implementing new subscription tiers) might require significant development work.
6. Ease of improvement (easy, medium, hard): Based on your experience and research, how difficult will it be to move this metric? Consider technical complexity, market resistance, and internal politics. Be honest about challenges.
7. Time horizon (short vs. long term): Will this lever produce quick wins or build long-term advantage? Pricing changes can sometimes deliver immediate revenue but might take months to reveal their full impact on retention and lifetime value.

This framework helps you compare different growth levers objectively. For example, you might find that a pricing structure change has a higher potential impact on your North Star metric than an acquisition channel optimization, even if the latter seems more intuitive.

As Tideman advises: “We aren’t looking for easy areas at all with this, but we’re trying to evaluate effort versus reward to make sure that we’re focusing on impact for areas. And we also want to really challenge ourselves that we’re not just looking at short term levers, but looking also at the longer term levers.”

Defining your pricing growth lever

For each growth lever, including pricing, you need to define:

1. Clear overall KPI and goal: Choose a specific metric that directly measures success. For pricing, this might be average revenue per user, profit margin, or conversion rate at a specific price point. Set a concrete target like “increase ARPU by 15%” rather than vague goals like “optimize pricing.”
2. Measure of success: Define exactly how you’ll know you’ve succeeded. Include both the metric and the threshold. For example, “We’ll consider this successful if we increase average order value by $10 while maintaining at least 90% of our current conversion rate.”
3. Target date for achievement: Set a realistic timeline that allows for multiple experiments and learning cycles. Pricing changes often require 3-6 months to fully evaluate, especially for subscription businesses where retention effects take time to manifest.
4. At least 30 ideas in the backlog: Brainstorm extensively before starting. For pricing, this might include different tier structures, presentation methods, discount strategies, bundling options, etc. Having a deep backlog prevents you from giving up after initial failures.
5. Themes to test within the lever: Group your ideas into coherent themes like “value communication,” “tier structure,” or “upsell optimization.” This helps you learn systematically rather than jumping between unrelated tests.
6. Experiments currently running: Document active tests, their hypotheses, and expected outcomes. For pricing, be especially careful about overlapping experiments that might confound results.
7. Owner responsible for the lever: Assign clear ownership to someone who will champion this lever, coordinate experiments, and report results. Ideally, this person has both analytical skills and business understanding.
8. Supporting team members: Identify who needs to be involved from product, marketing, sales, and other departments. Pricing changes often require cross-functional collaboration.
9. Time allocated to work on it: Be realistic about the resources needed. Specify how much time team members should dedicate weekly or monthly to this lever. Insufficient allocation is a common reason growth initiatives fail.

Be critical of your success metric. For example, if you choose “average order value” as your pricing lever KPI, consider both the pros (encourages focus on upsells, easy to measure) and cons (might push for higher prices that reduce overall conversion).

Themes within pricing growth levers

Within your pricing growth lever, you’ll want to organize experiments into themes. Themes help group related experiments so you’re learning about something bigger rather than conducting random tests.

For pricing, themes might include:

• Value communication: How you present and explain your pricing to highlight value rather than cost. This includes messaging, comparison frameworks, ROI calculators, and value proposition placement.
• Discount strategies: Systematic testing of different discount approaches, including amount, timing, conditions, and presentation. This helps you understand when discounts drive profitable growth versus when they erode margins.
• Tier structure: Experiments around the number of tiers, feature allocation, and price points. This theme helps you capture maximum value from different customer segments without overcomplicating your offering.
• Upsell sequences: Testing different approaches to increasing customer spend after initial purchase. This includes timing, messaging, offer types, and targeting criteria.
• Bundle configurations: Exploring how combining products or features affects perceived value and willingness to pay. This includes testing different bundle compositions, discount levels, and presentation methods.

Themes will change more frequently than your growth levers. You’ll drop themes that aren’t yielding results after a few attempts and double down on successful ones. For example, if after 3-4 experiments your “discount strategies” theme isn’t moving the needle, you might shift resources to “tier structure” where you’re seeing promising results.

Implementing pricing as a growth lever

To effectively use pricing as a growth lever:

1. Evaluate pricing quarterly when determining growth priorities: Make pricing a regular part of your growth strategy discussions. Even if you don’t change prices every quarter, you should assess whether pricing experiments should be part of your focus.
2. Run experiments with a focus on long-term impact and customer lifetime value: Look beyond immediate conversion effects to understand how pricing changes affect retention, expansion revenue, and overall customer satisfaction. Track cohorts over time to see the full impact.
3. Consider profit implications of price decreases: Lower prices might increase volume but reduce margins. Calculate the break-even point – how much additional volume you need to offset margin reduction. For example, a 10% price cut typically requires more than a 10% volume increase to maintain profit.
4. Supplement experiments with research to test in safer environments: Use the research methods described earlier to gather insights before implementing changes. This reduces risk and helps you narrow down which experiments are most promising.
5. Choose research methods that best suit your specific situation: Different businesses need different approaches. B2B companies with few, high-value customers might benefit more from in-depth interviews, while B2C companies with thousands of customers can use quantitative methods like Van Westendorp.
6. Implement changes gradually with clear communication: When making permanent pricing changes, consider phased rollouts, clear explanations of value, and advance notice. This reduces negative reactions and gives you time to adjust if needed.
7. Treat existing customers preferentially during transitions: Consider grandfathering existing customers, offering special loyalty rates, or providing additional value to offset increases. The cost of retention is almost always lower than the cost of acquisition.

Stress testing your pricing lever

Before fully committing to pricing as a growth lever, stress test it by asking:

1. Does it align with your current focus points? If not, is that good or bad? Sometimes misalignment indicates you’ve been focusing on the wrong areas. Other times, it suggests your pricing lever needs refinement to support broader company goals.
2. Does it make sense for all teams within the organization? Pricing changes affect product, marketing, sales, and customer success. Ensure each team understands how the pricing lever connects to their work and metrics.
3. Are there ways to game the metric? Consider how teams might achieve the pricing KPI in ways that hurt the business. For example, dramatically raising prices might increase average order value but destroy conversion and retention.
4. Does it drive value for both customers and the business? The best pricing strategies create win-win scenarios where customers get appropriate value and the business captures fair compensation. One-sided approaches eventually fail.
5. Will it remain relevant as your business evolves? Consider your product roadmap, market expansion plans, and competitive landscape. Will your pricing lever still make sense in 12-24 months?

The bottom line

Pricing is one of the most powerful yet overlooked growth levers available to B2B companies. While acquisition and retention strategies get most of the attention, strategic pricing experiments can dramatically impact your growth trajectory.

By expanding your view beyond simple price points to include structure, upsells, and order value optimization – and by using proper research methods to validate your approach – you can unlock significant growth without necessarily acquiring more customers.

The key is balancing short-term gains against long-term value, communicating changes effectively, and consistently treating pricing as a core component of your growth strategy rather than an afterthought.

As Tideman concludes: “Pricing is a very, very powerful growth lever, and I really recommend making sure you’re evaluating it every quarter when you’re deciding your growth levels, because we can sometimes skip it. If our growth model doesn’t include it, it’s very easy to miss it and not focus on it.”