Monetizely FAQ – Your Guide to SaaS Pricing & Strategy

Based on Price to Scale, the ideal level of granularity for a pricing metric really hinges on how predictable and measurable your usage is:

If your usage metric is highly predictable and easy to measure, you can afford to be more granular. This approach ties pricing closely to the value customers receive, aligning growth in usage with costs. However, it requires customers to trust the measurement and accurately forecast their usage.
If the metric is less predictable or difficult to measure, it’s generally better to bundle usage into larger units. Bundling helps avoid overly noisy or complex bills and delivers the clarity that purchasing groups often demand. Larger buckets smooth out the variances in usage and can simplify both sales and customer understanding.

To summarize, our pricing strategy book, Price to Scale, suggests starting by evaluating the predictability of your key usage metric. If it’s consistent, granular pricing per unit can work effectively. If not, consider adopting broader usage blocks to keep billing straightforward and user-friendly. This approach ensures that the pricing model not only scales with customer growth but also remains clear and accessible.

Frequently Asked Questions

What level of granularity is ideal for a pricing metric — is charging per single unit too fine-grained (leading to noisy, complicated bills) and is it better to bundle usage into larger units for clarity?

If we tie our pricing to a customer metric that grows as their business grows (like number of employees, or customers they have), how do we avoid them feeling like we’re penalizing their growth?

What strategies have you used to communicate a complicated value metric on your pricing page in a way that new visitors can quickly understand?

Has anyone implemented a two-dimensional pricing scheme (for example, a base subscription fee plus a variable fee based on another metric), and did customers find that confusing or was it accepted?

Are there analytics or tools you use to monitor how customers use the product that helped you identify the best value metric to charge on (like finding what usage correlates most with value or outcomes)?

If you realize you chose the wrong pricing metric early on and need to change it (say from per-user to per-transaction), what’s the best way to migrate existing customers to the new model without angering them?

How can we experiment with different pricing units on subsets of customers to see what works best, without causing chaos or a sense of unfairness among our user base?

For those who have implemented a price increase, how did you announce it to your customers and what kind of backlash (if any) did you experience?

What’s the best way to grandfather existing customers when you roll out new pricing — do you let them stay on their old plan forever, or migrate everyone over after a certain period?

How often do SaaS startups typically re-evaluate and tweak their pricing? Is adjusting pricing once a year a good cadence, or is that too frequent or too infrequent in your experience?

We suspect we underpriced our product at launch. Is it better to raise prices now, even with limited usage data, or wait until we have more traction? How do you figure out the right timing for a price change?

Has anyone here actually lowered their prices and seen it pay off in terms of higher volume or growth? Or does dropping price usually not bring enough new business to offset the revenue loss?

If you add a major new feature or module, do you give it to existing customers on their current plans or put it in a higher plan/new plan? How do you balance rewarding loyalty with capturing more value for new functionality?

How do you communicate and handle it if you’re doing pricing experiments (like A/B testing higher prices for new signups)? Do you worry about existing customers finding out and feeling cheated?

Any advice for conducting a pricing audit? Our pricing has gotten complicated with many SKUs and custom deals over time — how can we simplify and standardize our pricing without losing revenue?

Has anyone gone through a complete pricing overhaul (for example, moving from a freemium model to paid-only, or from flat pricing to tiered pricing)? How did you manage that transition with your existing user base?

When launching a new product or add-on module, is it better to upsell it as a paid add-on to existing customers or bundle it into a higher pricing tier? How do you determine the price of a new offering relative to your current products?

If a pricing change ends up hurting metrics (say, conversion rate plummets), how quickly do you roll it back, and do you have any stories of a pricing change that failed and what you learned from it?

What metrics do you closely watch after rolling out a pricing change (e.g., sign-up conversion, expansion revenue, churn), and how long does it take before you can confidently say the pricing change was a success or mistake?

How do you handle your sales pipeline when you’re about to change pricing? For instance, deals in progress might be based on the old pricing — do you honor the old prices for a grace period so you don’t derail those deals?

Is it fair or common to limit how long someone can stay on a grandfathered plan (for example, telling legacy customers that after 2 years on the old pricing they have to switch to the new plans), or do most companies let them stay indefinitely?

I’m setting up a process for our upcoming price review. What internal steps do you follow when re-evaluating pricing (who do you involve, do you survey customers, run internal simulations, etc.) to make sure you land on the right changes?

When did you introduce an enterprise-tier or “Contact Us” pricing option? Did you wait until big companies started asking for it, or did you proactively roll out an enterprise plan beforehand?

How do you decide what additional value or features to include in an enterprise plan (for example, SSO, advanced security, custom integrations, dedicated support)?

If the bulk of your revenue comes from enterprise clients, is it worth keeping the low-end self-serve plans around, or do they just distract focus? How do you balance catering to small self-serve users vs big enterprise deals?

How much customization do you allow in enterprise deals? Do you end up doing custom pricing and contract terms for each large client, and if so, how do you keep that from getting out of hand?

What’s a typical way to handle volume pricing for large enterprise customers? Do you offer standard volume discounts, create custom tiered pricing for big deployments, or just do fully custom quotes for each?

Enterprise procurement often expects multi-year commitments or at least annual deals. How do you structure multi-year SaaS contracts in terms of pricing — do you lock the rate, build in a fixed annual increase, offer upfront payment discounts, etc.?

How do you anchor a high enterprise price in negotiations? Do you publish a high list price and then give discounts, or keep pricing fully custom and not list anything publicly to give yourself flexibility?

At what stage did you separate out a public pricing page for standard plans vs. having a separate section or approach for enterprise pricing? Or do you just have one page and say “Contact us for enterprise” without detail?

Any tips for dealing with the dreaded enterprise RFPs that demand pricing in a specific format or unit that doesn’t match how you normally charge? For example, if they ask for per-user pricing but your model is usage-based, how do you respond?

How do you demonstrate ROI to an enterprise customer to justify a large deal? Are there particular ROI calculators or case study approaches you’ve used to support a high price in enterprise negotiations?

Do you employ a value-based pricing approach for enterprise deals (like charging more if the client is bigger or gets more value), and how do you implement that without it coming across as arbitrary or unfair?

In enterprise agreements, how often do you try to increase the price upon renewal? Many big clients will push to lock in prices for multiple years — how do you handle negotiating price changes for long-term customers?

If your product started as a self-serve tool and later you moved upmarket to enterprise sales, how did you adjust your pricing strategy? Did you remove pricing from the website and go to custom quotes, or keep some level of transparency?

What role do things like SLAs, faster support response times, and training services play in your enterprise pricing? Do you bundle those in the enterprise price or sell them as add-ons or separate line items?

Does ending your price in a 9 versus a 0 (for example, $49 vs $50) really affect SaaS buyers’ behavior, and has anyone A/B tested charm pricing versus clean round numbers to see if it matters?

What’s the most effective way to layout the pricing page design-wise? For instance, do you use the classic three-column layout with a “recommended” middle plan highlighted, and are there specific design elements that actually improved your conversions?

How many pricing options should you show on your page to avoid overwhelming customers? I’ve seen some companies hide either the cheapest or the priciest plan by default — is that an effective strategy or does it just confuse people?

Do you present monthly and annual pricing side by side with a toggle on your pricing page, or do you show one by default? Which approach have you found causes less confusion for potential customers?

Has anyone tried using interactive elements like toggles or sliders on their pricing page (say, to adjust user count or usage and see the price update)? Do these help users better understand how pricing scales or just complicate things?

How do you simplify the presentation of a complex pricing scheme? Our pricing has multiple dimensions (like user seats and usage limits) and I’m struggling with how to display that clearly without a huge, scary table.

Has anyone added an estimated ROI or savings calculation on the pricing page (like “using our product saves X hours = $Y saved per month”) to justify the cost? Did showing that kind of info help convince customers to buy?

When listing prices, is it better to advertise as “per user” or to say “starting at $X” for a basic configuration? I’m torn because listing a low entry price could attract interest, but it might also be misleading if most teams pay more than that.

For the highest pricing tiers, have you found it better to just say “Contact us for pricing” versus listing an actual starting price or range (like “starts at $1000/month”) to set expectations?

Is there any data or anecdotal evidence on whether making the primary call-to-action on the pricing page “Start Free Trial” versus “Buy Now” (or “Request Demo”) impacts conversion rates? We’re debating what our main CTA should be.

Does adding a detailed feature comparison table on the pricing page help users make a decision, or does it just overload them with information? We’re debating if we should include a comparison grid under the pricing plans.

Should you mention competitors on your pricing page (like an explicit comparison or a note such as “half the price of X platform”) or is it better to focus on your product alone and avoid naming others?

What copy or psychological tactics have you found to work on a pricing page? For example, highlighting a “Most Popular” plan, using words like “Only $X” or “Best Value” — do these actually increase conversions?

How important is it to limit the number of choices to avoid analysis paralysis? We currently have four plans; would cutting it down to three really make a difference in reducing buyer confusion?

For products that have varied use cases, has anyone tried a short quiz or guided questionnaire to direct users to the right plan before showing pricing? Was it effective at helping customers find the right tier or did it just add friction?

Has anyone used AI or machine learning to optimize their SaaS pricing (like dynamically adjusting prices or suggesting price points), and if so, how did it work out in practice?

What AI-driven pricing tools are out there for SaaS, and are they actually worth it for an early-stage company or would that be overkill at our stage?

Could we use something like ChatGPT or another AI to analyze our customer and usage data and suggest better pricing tiers or segmentation? Has anyone experimented with AI for pricing strategy decisions?

Are any SaaS companies doing truly personalized pricing — like showing different prices to different users algorithmically — and is that working or just too risky if customers compare notes?

How might AI help forecast the impact of a price change on things like churn or conversion? Is anyone feeding their historical data into a model to predict outcomes before making a pricing change?

Is dynamic pricing (adjusting prices in real-time based on demand or other factors) viable in SaaS or is that mostly an e-commerce thing? Could an AI theoretically manage dynamic pricing for SaaS without causing customer anger?

What data would you need to feed an AI model to have it assist in pricing optimization? We have data on usage, conversion, churn, etc. — can an AI make sense of that to suggest an optimal pricing strategy?

If you’ve tried AI-driven price optimization, have you had any mishaps (like the AI recommending something crazy high or low)? How do you put checks in place to ensure an algorithm doesn’t make a dumb pricing decision?

With AI capabilities, is it possible to do real-time segmentation and show a tailored price to each lead (say based on their industry or size)? Or would that likely backfire if customers talk and discover different prices?

Are there any open-source or affordable tools to experiment with algorithmic pricing for SaaS, or is this kind of AI-driven pricing tech mostly available only in expensive enterprise solutions?

How do you keep a human in the loop with AI pricing? For example, using AI to generate recommendations but having a person review/approve them — how do you integrate that into your pricing strategy process?

Do customers trust pricing that might change frequently? If we let an AI adjust pricing dynamically, should we be transparent about it or just quietly apply it for new users only to avoid confusing existing customers?

Are there any ethical or legal concerns with AI-driven pricing in SaaS (for example, inadvertently causing price discrimination or fairness issues)? I’m a bit worried an algorithm might lead to unfair or inconsistent prices without us realizing.

Can AI help identify the optimal price points for different plans by analyzing usage and conversion data (essentially automating price testing)?

If you’ve run pricing experiments using AI (like showing different prices to different users), how did you handle that with your customers? Did you have to explain that pricing was in beta or just A/B test quietly?

If your company offers multiple products, how do you decide whether to sell them separately or bundle them together as a suite? What factors influenced your bundling versus standalone decision?

For those with a suite of products, do you price each module à la carte and then offer a discount for buying the bundle, or do you only offer a single combined price for the whole suite?

How do you encourage customers to buy a bundle without cannibalizing the revenue from a high-priced standalone offering? We want to push a bundle deal but not at the expense of devaluing individual products.

Is it better to introduce a bundled offering right away when you have multiple products, or launch them individually first and bundle later once you see demand patterns?

How do you handle customers who only want one piece of the bundle and feel the bundle is too expensive? Do you let them purchase components individually, or insist on the bundle for certain functionality?

Looking at companies like Atlassian or Adobe that have many products, how do they structure pricing across their portfolio? Do they generally give discounts or incentives for customers to use more of their tools as a suite?

What’s a smart strategy for incorporating new features or mini-products: should we bundle them into existing plans to add value, or make them separate add-ons? I’m wary of making our pricing too complicated with add-on options.

For those who have bundled offerings, did bundling multiple products actually increase your average revenue per user (ARPU), or did it mostly just give a discount to customers who would have bought all the products anyway?

How should we display bundle pricing on our website to clearly show the value? For instance, is it effective to show what the products would cost separately (crossed out) versus the bundle price, to highlight savings?

What metrics or signs do you look at to gauge if your bundling strategy is working? I’m interested in how to measure success or failure of bundling vs selling products separately.

Does bundling multiple products help reduce churn by increasing lock-in and the value customers get, or can it sometimes backfire if one product isn’t as strong and drags down satisfaction with the bundle?

Have you experimented with bundling by offering it at a small discount versus full price to see how it affects uptake? What did you find was the sweet spot for a bundle discount (if any)?

How do you handle different usage levels of each product within a bundle? Are customers ever unhappy that they’re paying for a full suite when they’re only heavily using one of the products in it?