Running Pricing Experiments with Marc Boscher of Unito

Pricing has a funny way of humbling smart people. A team can build a sharp product, nail onboarding, polish the website until it sparkles, and still trip over the question that sounds deceptively simple: what should this thing cost?

That is why the topic of running pricing experiments hits so hard, especially when viewed through the lens of Marc Boscher, CEO and co-founder of Unito. Boscher’s perspective is compelling because Unito sits in one of the messiest corners of SaaS: workflow automation, cross-tool collaboration, and productivity software where customers compare your value against several other tools at the same time. In other words, this is not the kind of business where you can throw a random number on a pricing page and call it strategy. This is the kind of business where pricing needs to learn how to fight, stretch, adapt, and occasionally survive awkward meetings.

What makes Boscher’s approach worth studying is that he does not treat pricing like a one-time executive decision carved into stone tablets. He treats it like an operational capability. That shift matters. The best pricing strategy is rarely a lightning bolt. It is usually a sequence of informed bets, careful tests, customer conversations, and metric reviews that slowly move a company closer to price-to-value alignment.

And that phrase, price-to-value alignment, is the heart of the whole thing. Customers do not buy your spreadsheet of costs. They buy the outcome your product creates. If pricing reflects that outcome, buyers feel smart. If pricing drifts too far from perceived value, even a great product starts feeling like a gym membership in February: technically useful, emotionally annoying.

Why Marc Boscher and Unito Make a Great Pricing Case Study

Unito helps teams sync work across tools so updates do not die in a swamp of manual copy-pasting. That alone makes pricing more complicated than it looks. The product’s value can show up as fewer meetings, less rework, better visibility, faster execution, cleaner handoffs, or smoother collaboration between departments that would otherwise communicate like distant cousins at a wedding.

That creates a classic SaaS pricing challenge: the value is real, but it shows up in multiple ways. Some customers care about time saved. Others care about executive visibility. Others care about reducing mistakes, integrating systems, or preserving sanity between Jira, Asana, Trello, Salesforce, and everything else modern teams use when they are trying to “streamline operations” while adding five more tools.

For a company like Unito, pricing cannot simply answer, “How much does the software cost us to deliver?” It has to answer, “What is the cleanest and fairest way to charge for the value customers are unlocking?” That is where Boscher’s thinking becomes useful far beyond Unito itself. His lesson applies to almost any B2B SaaS business: when the product evolves, the customer evolves, and the market evolves, pricing has to evolve too.

Pricing Is Not a Project. It Is a Practice.

The biggest takeaway from Boscher’s approach is that pricing is not a dusty PDF you revisit every three years when revenue gets weird. It is a recurring business practice. That means you do not wait for a full-blown pricing identity crisis to start learning. You build the muscle before you need the miracle.

This is a smart stance for three reasons.

1. Markets move faster than your old assumptions

Competitors change packaging. Customer budgets tighten or expand. New categories emerge. Product-led growth changes buyer expectations. AI features distort value perception. A pricing model that looked elegant eighteen months ago can start looking like a flip phone at a product conference.

2. Products mature in uneven ways

Most software companies do not add value in one straight line. They expand across features, use cases, integrations, support models, security requirements, and buyer segments. If the product becomes more powerful while pricing stays frozen, the company undercharges. If pricing gets ahead of customer value, conversion and retention take the hit.

3. Pricing changes are risky when done blindly

Founders often fear pricing changes because they imagine one giant switch getting flipped while customers stampede toward the exit. Boscher’s answer is not “be reckless.” It is “de-risk the move.” Run experiments. Segment carefully. Survey customers. Interview them. Validate with data. Then make decisions from evidence rather than vibes.

That approach turns pricing from a gamble into a managed learning system.

The Real Goal: Reach Price-to-Value Alignment

Price-to-value alignment is one of those phrases that sounds suspiciously like consultant wallpaper until you unpack it. In practical terms, it means customers should feel that what they pay tracks with what they get. Not perfectly. Not mathematically. But clearly enough that the bill makes intuitive sense.

This is where many SaaS companies get into trouble. They choose a pricing model because it is easy to explain internally, not because it maps cleanly to customer value. Charging by seat is neat. Charging by plan is familiar. Charging by usage can be powerful. Charging by outcome can be brilliant. But the “best” model depends on what customers actually experience as value.

That is why value metrics matter so much. In SaaS, the value metric is the unit that links your price to customer benefit. It might be seats, projects, records synced, API calls, transactions, workflows, storage, or something hybrid. Pick the wrong value metric and you create friction. Pick the right one and expansion feels natural.

For a platform like Unito, a value metric tied to the tools used, items kept in sync, and feature depth makes intuitive sense because it reflects the operational footprint of the customer’s workflow. It is not just charging for existence. It is charging in relation to what the system is actually doing for the team.

The Three Layers of Pricing Experiments

Boscher’s discussion of pricing experimentation is especially useful because it nudges leaders away from thinking only in terms of “Should we raise prices?” That is the toddler version of pricing strategy. The adult version asks what exactly you are testing.

In practice, pricing experiments tend to happen across three layers.

1. Price point experiments

This is the obvious one: should Pro be $49, $59, or $79? Useful, yes. Sufficient, no. Testing price points can reveal willingness to pay, but it does not fix a broken packaging structure. If your bundles are confusing or your value metric is off, changing the number alone is like putting premium fuel in a shopping cart.

2. Packaging experiments

Packaging tests ask how features, limits, support, and product access should be grouped. This is often where real leverage lives. A good package makes it easier for buyers to self-select. A bad package makes every plan feel either insulting or suspiciously expensive.

Tiered pricing works best when each plan feels coherent, not when it looks like someone sorted features by throwing darts. Customers should immediately understand who each tier is for, why the higher tier costs more, and what practical difference the upgrade creates.

3. Value metric experiments

This is the heavyweight division. Testing the value metric means rethinking what the customer is actually paying for. Seat-based, usage-based, hybrid, or custom enterprise pricing can each be effective, but only if they align with how customers consume value. This is also where many SaaS companies discover that the model they started with was fine for version 1 of the business, but wrong for version 3.

That is exactly why pricing migrations matter. As companies grow, the original pricing model may stop fitting the product they have become.

When A/B Testing Makes Sense and When It Does Not

Founders love A/B testing because it sounds scientific and emotionally soothing. Put two prices in the arena. Let the numbers fight. Walk away with certainty. Beautiful idea. Reality is messier.

A/B testing can be powerful for parts of pricing, especially when traffic volume is high enough and the variables are narrow enough. It works well for pricing page presentation, plan framing, call-to-action language, feature emphasis, and in some cases price points for defined segments.

But major pricing changes are not always good candidates for casual A/B tests. If you are changing the value metric, introducing new packages, migrating legacy customers, or shifting upmarket, you may need more than a neat split test. You need research, interviews, segmented rollout, and strong instrumentation.

One of the smartest ideas associated with Boscher’s thinking is the use of limited geographies or controlled segments to test new pricing structures before rolling them out broadly. That kind of experimentation lowers risk without requiring a dramatic company-wide leap of faith. It gives you room to learn before the change touches every customer and every forecast.

The Metrics That Actually Matter During Pricing Experiments

A pricing experiment without measurement is just performance art with spreadsheets. To evaluate pricing changes, companies need to watch both front-end and back-end metrics, because pricing can improve one area while quietly damaging another.

Conversion rate

If fewer visitors start trials or buy plans after a change, the pricing may be signaling too much friction, weak value communication, or a mismatch between offer and buyer intent.

Average revenue per account

This is where pricing teams can fool themselves. A higher ARPA looks great until you notice that acquisition slowed, expansion stalled, or lower-intent buyers vanished. Strong pricing lifts revenue quality, not just sticker size.

Retention and churn

Retention is where bad pricing goes to confess. Customers may tolerate a poor price at checkout, but they express their real opinion over time. If cancellations, downgrades, or support complaints rise after a change, the issue may not be product dissatisfaction. It may be that the price-value equation feels off.

Expansion revenue

The best pricing models do not just convert users; they make it easy for customers to grow. Expansion is often the clearest signal that pricing is aligned with the way customers derive value.

Sales cycle friction and support volume

If prospects suddenly need a decoder ring to understand your plans, pricing has become a UX problem. Confusion is not sophistication. It is leakage.

What U.S. SaaS Research Gets Right About Boscher’s Playbook

The broader pricing conversation in U.S. business and SaaS publishing supports much of this playbook. OpenView has emphasized the power of the value metric and the rise of usage-based pricing. Stripe has highlighted how usage-based and hybrid pricing can reduce barriers to entry, connect spending more directly to consumption, and create smoother expansion paths. Harvard Business Review has long argued that tiering and freemium work only when the structure is intentional rather than accidental. McKinsey’s work on PLG and product-led sales also reinforces the idea that pricing cannot sit in isolation from acquisition, retention, and expansion strategy.

Put simply, Boscher’s approach is not clever because it is trendy. It is clever because it matches how modern SaaS businesses actually grow. Pricing now sits at the intersection of product strategy, buyer psychology, monetization design, and revenue operations. That means the team that “owns” pricing cannot operate like a secret cave council that emerges once a year with a new PDF and a headache.

The companies that do this well build cross-functional pricing muscles. Product understands where value is created. Marketing understands how value is framed. Sales understands where deals stall. Finance understands the revenue implications. Customer success understands how pricing affects retention and expansion. When these perspectives come together, pricing gets smarter. When they stay siloed, pricing gets weird.

How to Run Pricing Experiments Without Breaking Your Business

If Boscher’s philosophy were turned into a practical playbook, it would look something like this.

Start with customer language, not internal jargon

Interview customers and prospects. Ask what feels expensive, what feels fair, what value is clearest, and where they hesitate. The best pricing insights often show up in plainspoken comments, not polished dashboards.

Define the hypothesis before touching the page

Do not test “new pricing.” Test a specific idea. For example: a usage-based entry point will improve trial-to-paid conversion for smaller teams, or clearer tier boundaries will increase mid-tier adoption. A fuzzy hypothesis creates fuzzy learning.

Segment carefully

New customers, existing customers, SMB buyers, enterprise accounts, and power users should not all be treated as one blob. Different segments experience value differently, and pricing should reflect that reality.

Protect legacy customers when needed

Not every pricing migration needs a scorched-earth rollout. Grandfathering, phased transitions, or opt-in upgrades can preserve trust while the new model proves itself.

Instrument the downstream effects

Watch what happens after checkout. The real verdict on pricing often appears in activation, support, renewal, expansion, and contraction.

Keep learning loops short

Pricing does not need to become chaos, but it should not become bureaucracy either. The goal is repeatable learning, not annual theater.

500 Extra Words: What Pricing Experiments Feel Like in Real Life

Here is the part people do not always say out loud: running pricing experiments feels less like solving algebra and more like tuning a band while the audience is already in the room. You are not working with abstract demand curves. You are working with real customers, confused sales reps, ambitious product managers, worried finance leaders, and a website team that just wants to know whether the button should say “Start Free” or “Book a Demo.”

In real SaaS companies, pricing experiments usually begin with discomfort. Maybe win rates are slipping. Maybe a lower-priced plan is attracting users who never activate. Maybe enterprise deals keep asking for custom exceptions, which is the polite business version of saying, “Your pricing page is not built for how we buy.” Sometimes the problem is even stranger: revenue is growing, but the company has a gut feeling it is undercharging relative to value. That is a good problem, but it is still a problem.

Then the internal debates start. Product thinks the premium feature should be paywalled. Sales says that will slow deals. Marketing says the message is too complex. Finance wants cleaner expansion logic. Customer success waves a tiny emotional support flag and asks whether existing users are about to be surprised in a bad way. Everyone is partly right, which is both helpful and deeply inconvenient.

The best teams handle this by turning opinion into sequence. They gather customer interviews. They look at support tickets. They review lost deals. They identify where buyers hesitate, where plans blur together, and where customers get more value than the bill suggests. Suddenly the experiment is no longer a philosophy debate. It becomes a set of testable ideas.

And then comes the humbling part: customers do not always react the way smart internal teams expect. A higher price may convert just fine if the packaging is clearer. A cheaper plan may perform worse if it attracts the wrong customers. A usage-based option may delight one segment and terrify another. A plan designed to push upgrades may instead make buyers feel manipulated. Pricing has an incredible ability to expose the difference between what a company thinks customers value and what customers actually value.

There is also the emotional reality of rollout. Even good pricing experiments make teams nervous. No one wants to be the person who “tested something” and accidentally created a churn festival. That is why Boscher’s emphasis on de-risking matters so much. Limited rollout, segmented testing, and strong measurement make it possible to learn without gambling the entire business.

When a pricing experiment works, the result is rarely dramatic in a movie-trailer way. It feels cleaner. Buyers understand the plans faster. Sales calls get simpler. Expansion makes more sense. Support sees fewer “Wait, what am I paying for?” tickets. Retention stops wobbling. Revenue quality improves. In other words, the business starts sounding less like a fire alarm and more like a machine.

That is the real experience of pricing experimentation. It is not just about charging more. It is about discovering the most believable, scalable, and customer-trusted way to monetize the value your product creates. That is harder than picking a number. But it is also far more powerful.

Conclusion

Running pricing experiments with the mindset Marc Boscher describes is not about becoming obsessed with clever monetization tricks. It is about respecting the fact that pricing is one of the strongest growth levers in SaaS, and one of the easiest to mishandle when treated as a static decision.

The companies that win do not assume they have found the perfect pricing model forever. They keep listening. They keep validating. They keep testing. They build pricing as a capability, not an event. And they remember that the real goal is not to create the most complicated pricing page on the internet. The goal is to create a pricing system that customers understand, trust, and grow with.

That is the bigger lesson from Marc Boscher of Unito. Pricing is not a line item. It is a living part of product strategy. Treat it like a muscle, and it gets stronger. Ignore it, and eventually it pulls something painful.