Pricing a New Product: Lessons from iA Presenter

Pricing a product remains one of the least exact sciences in development. You can polish features, refine the user experience, and prepare a flawless launch, only to stumble at the final question: how much do we charge? It is rarely a number you can simply intuit, and it is equally rare to get it right on the first attempt.

Information Architects (iA) confronted this question directly when preparing to release iA Presenter, a companion to its established iA Writer application. Because iA Presenter is genuinely new and sits beside a mature product with years of history, the company’s pricing process offers a useful case study. The team was generous enough to share the research — including posting their findings publicly — so we can trace the key considerations from initial research to final decision.

Read the Market First

Before setting any price, the iA team examined what competitors were doing. Looking at the market for presentation software reveals a wide range of models: one-time purchases, recurring subscriptions, free tiers, trial periods, and credit-card requirements. The differences are not just in the numbers but in the structure of the offers themselves.

Mapping competitors in a spreadsheet is a practical starting point. The goal is to find parallels — to understand where the bulk of the market sits so your price does not appear as a jarring outlier. As iA notes, most presentation tools fall between $5 and $25 per user, with some offering free plans supported by venture capital or advertising. Google and Microsoft bundle their tools into larger suites, which complicates direct comparison.

These outliers matter. Competing purely on price is a risky game, and a low price can undermine perceived value. The real purpose of studying the landscape is to identify where your product fits and where it can differentiate — not just to match a number.

Value Is Relative

The spreadsheet becomes most useful when it turns into a matrix rather than a simple list. Adding columns for features, user experience, and target audience helps reveal what is genuinely unique about your product. Does it solve a problem others overlook? Is the interface so much cleaner that the experience itself is the value proposition?

But iA warns that you are not only comparing against direct competitors. Customers will inevitably judge your product against whatever they already know. A hosted calendar app, for example, will be measured against Google Calendar even if the two serve different purposes. iA puts it plainly: “Customers will compare apples and oranges.” You cannot control what you are measured against, but you can anticipate it and adjust your expectations and prices accordingly.

Go Straight to the Audience

Internal debates about pricing can only go so far. At some point, you need external input. The iA team took the unusual step of asking its audience directly, publishing a blog post in November 2022 under the title “How Much Would You Charge for iA Presenter?” The post laid out the research gathered so far and invited subscribers to weigh in.

Asking customers directly accomplishes two things. It sets expectations, familiarizing users with the thinking behind a potential price before it becomes a final figure. And it generates data — structured feedback that can inform pricing experiments and reveal customer sentiment that might otherwise remain hidden.

The Three-Form Experiment

Designing a good survey is deceptively difficult. Biases creep into wording, input types, and flow. Rather than pretend to solve that problem, iA leaned into it. They divided their newsletter subscribers into groups of roughly 5,000 and sent each group a different version of the pricing form. Version after version was updated and tested on fresh audiences.

“We offered a form that required you to fill out monthly and yearly subscriptions plus ownership. […] We offered a second version that didn’t require you to fill out all fields. What happened there raised brows. The price suggestions changed. They got lower. We continued changing the form, and every time, the result changed.”

Running three versions simultaneously provided three distinct benefits:

  • Scenario testing. Instead of asking which model users preferred, each version assumed a pricing approach — subscription only, ownership with typical pricing, or a hybrid — and gathered reactions to that specific set of choices.
  • Assumption checking. The team had already formed opinions on which pricing models were most viable after researching the market. Putting three distinct models in front of real users tested those opinions against actual response data.
  • Bias revelation. Survey forms carry inherent bias, and that, iA discovered, was directly affecting results. They found, for example, some users refused to fill their assigned form simply because it proposed a subscription alone. That reaction is itself valuable signal about customer sentiment.

The findings made a clear impression on the team: changing the form changed the answers. The design of the survey was influencing the outcome as much as the pricing itself.

From Data to Decision

Combining all the responses, iA found its answer. The audience converged on the industry standard of $5 for a single license. Worked out over twelve months — and multiplied by three to make the endeavor worthwhile — the math suggests making iA Presenter a $150 application, calculated as five dollars times twelve, multiplied by three.

The result stands as a valuable reminder that pricing is a conversation, not a calculation. Research into the market, open consultation with potential customers, and careful survey design all contributed to a decision grounded in data rather than guesswork. Even when the data points clearly, pricing still carries risk — but a process built on evidence and transparency is as close to certainty as most development teams will get. The iA case shows that the discipline of asking, listening, and testing applies not only to the product but to its price. When you invite customers into that discussion, you do more than price a product — you build trust around the decision.

Pricing Tiers Versus a Single Number

Having a statistically sound price point is useful, but iA’s research also exposed a complication: no single price fits their entire audience. The survey responses showed meaningful segmentation:

  • The overall audience suggested the industry-standard $5 for a single license.
  • Perceived value varies by region — $50 for iA Writer already feels high to some, and $100 is a trivial sum in Switzerland but a significant portion of a monthly salary elsewhere.
  • Business users indicated a willingness to pay between $10 and $20 per month, per license.
  • Students expect a free tier.

iA also had the advantage of years of sales data from iA Writer. That history revealed a clear behavioral split: newer customers gravitate toward subscriptions, while long-time, “convinced” customers prefer a single, upfront purchase.

The result is that iA was not really looking for one flat rate. The data pointed toward a tiered pricing model that accounts for customer type — business versus student versus individual — as well as geography. A structure that offers different entry points is likely to capture more of the market than a single number. Even if verified students receive the product for free, that cost can be absorbed by the higher price points paid by single-license buyers and businesses.

Pricing as a Strategic Signal

What this case study illustrates is that pricing is far more than a guess or a negotiation between cost and margin. It is one of the Four Ps of Marketing, and it directly shapes how a product is positioned and perceived in the market.

Setting a price is a statement of the product’s quality and the value it adds to the market.

That is not something to leave to chance. At the same time, pricing is hardly an exact science. The real work is in gathering the right data and translating it into insights that reflect what your audience actually expects — and will pay. There are also limits to what the market will bear. A price that covers development, maintenance, new features, support, salaries, and marketing may not be sustainable if it is higher than what customers accept. Nobody wants to enter a race to the bottom.

iA Presenter is a particularly relevant example for the web design and development community because it is exactly the kind of software that community builds and uses. The company’s willingness to share its research process provides a current, real-world look at the complexity behind a pricing decision.

Whether the multi-tier strategy will hold up against more mature competitors that can afford to give their products away — Google Slides being the obvious example — remains to be seen. iA Presenter officially left beta and launched on June 1st, and the company continues to document the process on its blog and newsletter.