Pricing is one of the most important strategic decisions you can make for your platform. Whether you’re building a learning platform, marketplace, or any other type of solution that you provide to your customers, it’s essential to your organizations' success to able to return a profit and maximize your revenue to keep growing.
Getting your pricing right from the get-go is crucial because it’s hard to change prices once you’ve launched. Typically, consumers are very resistant to price increases, and pricing too high can completely shut you out of the market, especially considering that many platforms need to aggregate a large number of users to be profitable.
Freemium v free trial
There’s a reason why freemium models are so popular — Mixed with a strong network effect. Freemium pricing can quickly catapult your user growth curve, and provide your platform with a low-cost stream of new users.
There’s an important distinction to make here. Freemium products are not free trials. Freemium lets users use the platform, for free, forever. Freemium users won’t have all the feature, will get capped on usage, and may have ads but they should always have access to the platform. Free forever has been seen from Invision, Intercom and other tech start-ups. Free trials, on the other hand, give you a more extensive preview of the platform, but typically access expires after 7 or 14 days.
Freemium is a pricing model in an of itself. If you’re building a platform that will attract a lot of users, in a broad category and can leverage the network effect, then you’ll want to consider going with a freemium model. Freemium can also work if you can monetize on ads. One of the best freemium platforms is Slack. They utilize the network effect and their zero cost entry to rapidly grow their install base, from there users are monetized through advanced features as Slack gains a foothold in the organization.
Freemium doesn’t mean free. And any good freemium model needs to include a way for your organization to monetize. Typically there are two ways that companies will gate a freemium platform. The first is based on usage, for example, Dropbox, once you’ve used up your 2GB, you need to upgrade to a paying plan. The second is based on features, where you’re getting additional functionality for the price you’re paying. Slack gives companies better admin tools, file storage and keeps the conversations forever when you upgrade to a paying version.
Avoid a freemium model if your platform caters to a niche, or if it's hard to offer a tiered service. A good example would be Adobe's suite of software where offering a pared-down version is more work than it's worth. Using a free trial, Adobe can let users try the full experience, and monetize them should they be interested. Imagine only having access to Photoshop with a few editing options... it wouldn't be a compelling offer.
How to price your platform
Just a quick disclaimer. Before you can begin pricing your platform, you’ll need to validate that the market needs for it. You can do this through surveys, user testing, selling a proof of concept. Optimizing pricing is impossible if your positioning is off, or if the platform doesn't meet a need in the market.
Willingness to pay
Van Westendorp price sensitivity meter
One of the most common ways to price a platform or product in a new category is the Van Westendorp price sensitivity meter. An essential tool in any pricing conversation, especially for a new category or idea where there aren’t many competitors (more on that later).
The way a price sensitivity survey works is as follows:
Get a pool of potential users (based on your buyer persona). Either 100 or 150 people should be enough. The survey has four questions.
At a price would you consider the platform too expensive
At what price would you consider the platform to be priced so low that you’d feel the quality was lacking or it was ‘too good to be true.’
At what price would the platform be expensive, but still something you’d consider
At what price would you consider the platform to be a good deal/bargain
You’ll be getting four sets of numbers, aggregate the data, get your average and median, cut out any outliers, and you’re good to go. Here’s how to interpret those numbers.
Price is too expensive. This will be the upper edge of your pricing range and should be reserved for your 'best' option, or not used at all.
Price is too low. This price is to be avoided at all costs because not only does it not optimize for the most revenue, it also damages the perception of the brand and platform. This isn't your price floor; it's your basement.
Price is expensive but still worth it. This would be your price point. The idea being you create a bit of anxiety for the customer by having pricing that is a bit more expensive than the ideal, but where you won't lose sales. It's the price where you're maximizing revenue. Plus you can always tweak downwards from here.
The bargain price. This could be used for the lowest cost tier, or as an entry-level option, and this could also serve as a point for discounting for special events (e.g., Black Friday) or the direction you can take your pricing should you find that initial pricing traction is less than optimal.
Once you've averaged out the pricing, you can start validating it with some user testing or using the Monadic Experiment below.
It should be noted that customers have a hard time conceptualizing new ideas/solutions. So for the Van Westendorp price sensitivity meter, you may want to include mockups, videos or other collateral to help customers understand how you'll provide value, and what your platform does.
The Monadic Experiment
An alternative to the price sensitivity survey would be the Monadic Experiments. This is a similar idea, with a bit more guesswork on your end because you’ll be starting with the initial pricing for your customers. There’s more bias here in such that you are anchoring price. Typically with this survey, you’ll need a larger pool of surveyees. At least 250 people for the first batch, and then possibly up to 500 more for subsequent surveys.
Here’s how to proceed. In a survey, you describe the platform or service offered — Try to keep the description around the main functionality. Then on a scale of 1-4 (from extremely unlikely to extremely likely), you ask the surveyed to rate the likelihood of paying for this solution. Going from the highest price to the lowest price, and stopping as soon as they hit the extremely likely to spend. Pro tip use Survey Monkey or TypeForm for these surveys. They allow logic to be programmed which can end the survey when someone gets to the desired result, or have options for people to leave their answers. Once the survey is complete, analyze the results. The odds are that the first time around you’ll be able to remove the highest price point and narrow down the range of pricing. The idea is to remove extremes in the pricing (too high or too low) and find the optimal price. Once a majority of your customers answer incredibly likely to at a price point, you’ve got a good idea on what the market will bear for your platform. Pricing based off the competition The odds are that you’ll have a competitor in the field already. The good news is that if their business appears to be doing well, you can model your pricing of theirs. The key here to analyze their solution v yours, what’s different, and what the estimated value of those difference are (you can use the above surveys to figure it out or calculate based on experience and conversations with customers). From there it’s a matter of adding the additional value your product brings (if any) and subtracting the features that your platform doesn’t have (if any). So the formula would be — Competitors price + your differentiated added value - their differentiated added value. Of course, it’s hard to tell how well their solution sales, so unless you have publically available data, you can attempt to augment your information on pricing by surveying your competitor(s) current customers to see how they perceive the pricing (fair, underpriced, overpriced) and what aspect of the solution brings the most value to them.
Good, better, best
A staple of many platforms and product pricing is ‘good, better, best’ the strategy of tiering your pricing into three distinct offerings allows you to maximize revenue by capturing price incentive users and those who are more sensitive to pricing. Apple is a great example here. They typically offer three storage tiers of iPhone, iPad, and Mac. The idea being that those with lower budgets will take the least expensive option, the majority will go for the middle option (best compromise), and those who always want/need the best make the most costly choice. As you’d imagine, Apple’s profit margin on the better and best solution is higher, so they can increase their averge gross margin by making small changes to their better and best solutions (storage, processor, size). The other advantage that we see Apple utilize time and time again is starting at a price. This allows them to capitalize on the psychology of a lower starting price when in reality the average phone buyer ends up spending more overall.
When good is just okay and best is premium
Depending on your platform and your customer base, you can also leverage good, better, best pricing to further optimize revenues. Typically here you’ll play with the pricing of your lowest tier — Perhaps you’ll be offering entry on your platform with a minimal feature set for a low price. You’ll be able to advertise your solution at an attractive price, and monetize users to higher tiers as they use the platform more. On the other hand, you can offer a premium solution at the top end, this both captures the most amount of revenue from price-insensitive customers, and makes your middle tier appear like an even better value by anchoring the higher price. There's always a customer who has no budget and wants everything and the kitchen sink.
Discounting and special prices
Setting prices higher with the idea that you'll discount later should be avoided. It leads to a race to the bottom, where customers expect to receive discounts when using your platform. Eventually, you’ll be forced to offer either permanent discounts, or change your pricing. Heavy and frequent discounting damages your brand, sometimes making it hard to come back to ‘normal’ pricing. Just look at many large retail chains who ran all the time discounting and attempted to stop — Customers did not take well to it.
Similarly, if your sales team is coming to you to discount the platform, then you’re getting market feedback that your pricing is not optimal. You want your salespeople to work to close the deal, but they shouldn’t be offering discounts (especially deep discounts) for every transaction.
Discounting should be saved for special events like Black Friday, and significant milestones. A rare treat to help drum up additional business, not as a way to meet your revenue targets. Again, looking at Apple who can maintain a premium price point by rarely allowing discounts, and when they do, they tend to be conservative. Lastly, when discounting, it’s better to offer the rebate in the form of a bundle. For example, including access to your platform, plus free templates for a limited time. Bundling is a powerful way to offer additional value to your customers at a marginal cost to your business.
Pricing by persona
Depending on the type of platform you’re building, another consideration should be pricing on the persona. For example, many software companies offer discounts for students to encourage them to learn their platform and because they recognize that the value derived is lower than in a business setting. Another example is, Unbounce.com who prices for organizations and agencies. Since the personas are different, the pricing can be varied without alienating one another and maximizing value. An agency with hundreds of clients who use Unbounce for landing pages and charges clients makes way more profit than an organization which manages a few landing pages for ad campaigns — Pricing by persona should reflect the value that the persona gets from the product.
The most important aspect to remember about pricing by persona is that the feature offering needs to be differentiated based on the use case and the value that the person will get from your platform. Charging a VP more because they're a VP is a quick way to alienate the customer.
Pricing models and concepts to avoid
Cost-plus pricing is adding up all of your costs of doing business, plus the variable cost for each additional customer, and then adding your profit on top of it. This model doesn't capture the value you bring to your customer, and more often than not you'll be leaving money on the table. Cost-plus pricing is widespread in commoditized industries, say packing table, or raw materials. Where it's hard to differentiate, and competition is fierce.
Complex pricing grids and matrixes
After reading the section on 'good, better, best' you might be tempted to add even more pricing options. Don't. Many behavioral studies show that the more choice someone faces, the more difficult they find it to make a decision. Keep your pricing as simple as possible. If you have add-ons, try and propose them after the fact. Again, using Adobe as an example, they offer three options: a choice of any software, Photoshop+Lightroom, or all their software suite. Is it optimal for every customer? No. But, it keeps the friction of decision making low. In situations where complex, enterprise-level purchases happen, don't be shy to offer a 'contact us' for enterprise pricing.
Pricing is constantly evolving.
Your pricing is something which is always evolving. As you add new features, expand your offerings, or new competitors enter the market you’ll need to be flexible with pricing. The key is to be continuously gathering date on what your current and prospective customers want regarding price and the value that you’re bringing them. If your sales team is reporting price pressure from multiple competitors, then perhaps a pricing change should be considered. On the flip side, if in your customer survey’s your seeing a lot of positive sentiment around pricing, and the value that you bring, then maybe you’ll consider gradually raising prices. You can always conduct an A/B test using a limited market to see how new customers will react to prices. Many SaaS platforms do that today as they try out different pricing models to get real-time feedback on how these changes will impact revenue and profit. Finally, it isn’t often that existing customers see your pricing, typically after purchasing a few visits the pricing page. So you’ll have the latitude to experiment and try different pricing techniques for your newer customers who may not be familiar with your pricing while not alienating existing customers with pricing changes.
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