Pricing & Revenue Strategy

Pricing is the highest-leverage lever most companies touch least often. A price change costs nothing to ship and compounds across every future customer, yet it is usually set once at launch by whoever happened to be in the room, and then defended for years by sunk-cost reasoning.

Packaging first

Before the number comes the structure: how many plans, what separates them, what meters, what is bundled. Packaging decides how much value you can capture at any price point. A well-designed ladder gives users a reason to climb it; a badly designed one makes the cheapest plan the obviously correct choice forever.

• Pick a value metric that grows with the customer's own success, so revenue expands without renegotiation.
• Keep the plan count low. Every extra option costs conversion at the decision point.
• Differentiate plans on the dimension buyers actually feel, not on internal cost structure.
• Design the annual plan deliberately: it trades cash-flow and retention against discount depth, and the right discount depends on your churn curve, not on convention.

Running price experiments that produce answers

Most pricing tests are underpowered, read too early, and measure the wrong thing. Conversion rate is not the outcome — revenue per visitor over a defined window is. A price increase that drops conversion 10% and lifts revenue 15% is a win, and a conversion dashboard will call it a failure.

• Define the read-out metric and window before launch, in writing.
• Size the test against the actual variance in revenue per user, which is far higher than variance in conversion.
• Never change price and packaging in the same test unless you accept you won't know which did it.
• Hold grandfathering policy as a deliberate decision with a modelled cost, not an afterthought.
• Watch refunds and first-renewal churn, not just checkout. Bad pricing often converts fine and then unwinds.

Revenue modelling

A monetization strategy needs a model that connects the levers to the money: acquisition, activation, conversion, expansion, churn and payback. The value isn't forecasting accuracy — it's that a model makes the disagreements explicit. When two people argue about a price, they are usually disagreeing about churn elasticity without saying so.

How I work on this

The ARPPU doubling at Smitten came from systematic pricing and packaging experimentation rather than a single repricing: testing plan structures, price points and what sat behind the paywall, then reading the results on cohort revenue instead of checkout conversion. I work on the same problem for other consumer subscription businesses — usually starting by making the existing funnel legible, because most companies discover their pricing question was actually a packaging or measurement question.

Work with me on this

Ingi Brown advises on pricing & revenue strategy and related work. Email ingi@ingibrown.com or see the full background.

Related

• B2C Monetization

  Turning consumer audiences into recurring revenue: offer design, paywall placement, trial mechanics and the analytics to prove what worked.

• Product Management

  Product strategy, discovery and delivery for consumer software — with a bias toward teams that own a commercial outcome, not a feature list.

• Innovation Management

  Running new-bet portfolios inside companies that already have a core business to protect — funding, governance, stage gates and knowing when to stop.