Dec 3, 2024 · 28m · saastr
How to Leverage Pricing and Packaging to Drive Revenue with Miro, Loom, OpenAI, and Splunk
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Monetization and product leaders from Miro, Loom, OpenAI, and Splunk examine strategic frameworks for software pricing, packaging design, de-risked experimentation, and long-term value capture.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. How this is scored →
Jason as informed peer 0.0 Guest teaching 0.0 Guest disagreement 0.0 Jason pushing back 0.0
speaking balance: gold is Jason, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 26:36 Differing views on packaging cadence
Harmon offers an opinionated boundary advising against packaging or SKU updates more frequently than every 1-2 years, contrasting with higher-frequency iteration.
Hardest push from Jason ▶ 25:33 Moderator prompt on price change cadenceSharma presses the panelists to specify exact timeframes for how frequently companies should re-evaluate and alter their pricing structures.
Biggest teaching moment ▶ 22:08 Enterprise price inelasticity reality checkHolm explains that enterprise software demand is largely inelastic unlike theoretical textbook economics, recommending starting high and discounting down.
Jason holds their own ▶ 17:37 Sharma on experimental failure mindsetSharma asserts authority by emphasizing that leaders must expect failed experiments and prioritize resilient insurance mechanisms over individual test wins.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | Jason as informed peer | Guest teaching | Guest disagreement | Jason pushing back | Why |
|---|---|---|---|---|---|---|
| Pricing as a Product Feature and the Miro Case Study | 0 | 0 | 0 | 0 | Akshay Sharma opens the panel presentation with a monologue detailing Miro's historical pricing evolutions and setting minimum user seat counts to optimize for collaboration value. The host is absent during this introductory solo presentation. | |
| Aligning Monetization Models with Company Growth Goals | 0 | 0 | 0 | 0 | Allison Harmon and Karsten Holm discuss aligning monetization with stage-specific business goals, followed by Janie Lee's deep dive into survey methodology and experimentation readiness. The panelists maintain an entirely collegial, informative panel exchange. | |
| De-risking Pricing Tests and Navigating Experimentation Pitfalls | 0 | 0 | 0 | 0 | Karsten Holm and Allison Harmon share tactics for geographic de-risking in testing, while Akshay recounts Miro's surprising paywall experiment results. The discussion is constructive and collaborative with no host pushback or guest friction. | |
| Packaging Strategy, Customer Segmentation, and Splunk's Bundling Model | 0 | 0 | 0 | 0 | Karsten Holm delivers an in-depth breakdown of Splunk's packaging shift from distinct add-ons to unified platform bundles to raise average selling price. The delivery is educational and cooperative. | |
| Price Level Dynamics, Enterprise Elasticity, and Justifying Price Increases | 0 | 0 | 0 | 0 | The panel explores enterprise price inelasticity and the necessity of clearly communicating value before price hikes. Panelists build harmoniously on each other's points regarding rapid AI price reductions versus classic software increases. | |
| Evaluating Cadence and Managing Trade-Offs in Pricing Updates | 0 | 0 | 0 | 0 | Panelists debate optimal pricing update cadences, offering differing opinions on whether core packaging should change yearly or multi-yearly while remaining universally respectful and collegial through the closing remarks. |
Statements from this episode (19)
Sharma: Treat pricing as an evolving feature, not a static decision
“First off, I want to try and make you reset your mind about what pricing is. I call it, it's another product feature. And just like other product features, it changes what your customer's behavior is. And so you should think about it the same way and use it in…”
Miro initially required a five-user minimum to ensure teams experienced full value
“When Miro was an early product, the outcome that we are trying to achieve was make sure the users love the product. And they figured out that user love happens when a lot of people come together on the Miro board and collaborate. That's when users get enough v…”
Miro set a 20-user business plan minimum to prevent smaller teams overpaying
“And so when we introduced the business plan, which had security features like SSO included in it, we set another threshold. We set 20 users minimum for the business plan, because if you were smaller than that, You could pay us the higher price, but maybe you w…”
Miro found reducing paid seat minimums to one did not hurt metrics
“And then as Vero grew and we were scaling up, we wanted the product to be available to everyone. And then we did experimentation and we figured out, Hey, we can now reduce the limits down to one user without actually hurting any of our key metrics.”
Holm: Value metrics are much harder to change later than pricing numbers
“The numbers you can play with, the metrics, things like that are really hard to change after the fact. So being clear around how you want to capture value and having it a fair value exchange, meaning the customer agrees that is also the way to capture value an…”
Lee: Enterprise companies lack the funnel volume for precise pricing experiments
“It's really, really hard to have enough volume so far down the purchase funnel to actually run an experiment that gives you really precise results. And even if you do, it'll take you a really long time to get enough data on things like churn that actually will…”
Lee: Changing core package pricing is riskier than launching new products
“When you're rolling out a completely new product, worst cases, no one buys it, which is obviously really bad, but you're not actually detracting from your bottom line. Whereas if you're changing an existing package that You already have the majority of your cu…”
Loom reserves pricing experiments exclusively for its highest-risk, highest-impact changes
“We rarely are running experiments like on a quarterly basis on pricing. These are really reserved for our highest impact, biggest risk changes.”
Loom appeases angry customers with the most generous version of pricing experiments
“Being on the receiving end of pricing and packaging experiments can be really frustrating if you find out. And so we've had a philosophy of, hey, if someone finds out or if someone is really unhappy, how do we just give them the most generous version of our po…”
Holm: Pricing changes are a one-way door that is difficult to reverse
“Pricing is one of these things. Once you have it out there in the market, it's really hard to roll it back in, right? It's like a one way door, right? Once it's out there, tough to reel it in.”
Harmon: Never test a pricing change you are unwilling to roll back
“I feel like there's general growth wisdom, which is don't test something you wouldn't ship. And I think that's really true with pricing and packaging. But the contrapositive or inverse is also true, which is don't test something you wouldn't roll back.”
Miro saw a 15% conversion lift by paywalling GIF playback
“One example at Miro was GIFs were very popular, and there was a limitation on free plans to play GIFs. Putting a paywall there, we thought would convert a little bit. The conversion was very big. It was 15%.”
Miro's conversion rates fell when free users tested premium business features
“The most popular features, which were the drivers of conversion from starter to business plan, they said, let's pick those two or three features And allow starter plan users to test them out, and they'll see more value, and they'll upgrade. The reverse happene…”
Bundling add-ons increased Splunk's user adoption and average selling price
“And so we're running some interesting pilots there that ultimately showed two things. A user adoption was much, much higher because people felt like they can experiment without any real risk and commitment. Number one. And number two is the ASP for the platfor…”
Holm: Enterprise software is inelastic, so vendors must set high initial prices
“In enterprise sales or enterprise software, it's not super elastic. That's the bottom line. Splunk may be one of the more elastic enterprise products than others, but you're not going to wake up one more, one day and say, oh, let's buy a bunch of Oracle today.…”
Harmon: OpenAI frequently lowers prices with upgraded models without raising them
“OpenAI has certainly done that many more times than twice a year. We typically launch a model and then weeks or months later launch another version of it that's even better and lower the price and then lower the price again. I think that really speaks to the s…”
Harmon: Avoid overhauling packaging or adding SKUs more than every two years
“I feel like you can make tweaks and small or medium changes as frequently as you want and as your business commands, but I wouldn't Change your packaging, add a skew, overthink something more frequently than every one to two years.”
OpenAI has kept the ChatGPT Plus subscription unchanged for over a year
“ChatGPT Plus has been our ChatGPT subscription for over a year now, and so that's an example of something we haven't changed that I think I'm proud of and we've been thoughtful about where and when We'd change that, but it has stayed the same in the market, wh…”
Holm: Pricing model shifts create friction that must be offset by volume
“Every single time it's a trade off, right? Because whatever you change to, it has no linear correlation to the old model. So there are always going to be some winners and losers in this. The winner's going to take their wins. They're not going to give you the …”