In this new article about the AARRR metric model, we’ll talk about the role of revenue and business models in product analytics. Every commercial enterprise has the objective of making money. When a person pays for a product or service, they are effectively rewarding the value they get from what you have created.
With the dawn of the digital revolution, business models have taken myriad forms; many favor free offerings over forcing users to pay from the get-go; some rely on commissions, others on the pure sale of services or information.
Some products or services deliver immediate value. An e-commerce site for example generates revenue from a purchase without needing to offer a free version of a product to a user. Users of e-commerce understand that they’ll only be able to experience the object they’ve purchased after paying for it.
Many dematerialized products, notably software, have moved towards freemium or trial models whereby users can experiment with a service with some limitations such as a fixed period of unlimited use or a restricted amount of functionality. Creators of these types of products understand that user buy-in comes after allowing a user to experience the core value of a product or by inducing a habit in the user.
For these products, where the value is delivered over time, often through multiple, regular interactions with your product, revenue is only achievable after focusing on retention.
Advertising models offer third parties the ability to reach communities, consortiums or user-bases directly. Most advertisers are able to price ad space based on a variety of factors that profile segments of users based on their interests, demographics and behaviors.
Platforms that propose advertising to third parties can charge for preferred access to their communities based on a variety of metrics, from reach to impressions and from conversions to display time. Prices for ad campaigns can vary by goal and audience and even by the amount of demand for specific ad placement and time.
As we previously noted, many physical products are bought outright without being experienced first. Most online commercial activity takes place in the context of e-commerce. Models that focus on selling products online mirror traditional retail models, but offer the added flexibility of measuring the cost of goods sold and selling and advertising costs in a more granular way such that margins on products sold can be calculated with a higher precision than in traditional retail.
There’s almost nothing better than knowing how much money you’ll make in the future. Subscription models are hugely popular because they offer incredible foresight into future expenses and expected revenue. Subscription businesses are based on retention, and retention’s little brother, churn. So long as a business gains more paid users than those that terminate their engagement, the business will grow.
Often subscription models will use teasers such as free, limited versions (freemium), time-restricted trials and first-time usage promotions to get users engaged at the outset. These types of products will then attempt to convert these early users into paid users within a fixed time frame or by nudging them over time to increase their usage and reliance on a system.
One of the best early examples of a successful subscription business is Dropbox. By offering new users 2GB of free storage, they were able to appeal to price sensitive individuals. As the quality of content evolved, file sizes grew and more content was stored in the cloud, Dropbox users hit their storage limits and opted for the first tier paid plans. Although the number isn’t public, there have been rumours that Dropbox is able to attain profitability with only 4% of its users as paid users, meaning 96% of its userbase is considered a loss leader.
Commission models are one of the most traditional forms of monetization. These models are most associated with middlemen. Online commerce has created a plethora of opportunities to survive based on commissions.
Companies such as payment processors, marketplace owners, transaction facilitators and peer-to-peer network facilitators all rely on commission models to generate revenue. Commission models are highly dependent on transaction volume and transaction size.
Many companies that charge commissions can afford taking small cuts of transactions if they facilitate high transaction volume. However, if transaction values are high, but volumes are low, they might favor higher commission rates. And in some rare cases, if a business operates as an effective monopoly or oligopoly, it can name its rate, as credit card companies do.
Some companies that incur high production costs and longer times-to-market will opt for a licensing model. This model was one of the first business models adopted by software companies, and one that is still extremely effective when transacting in the large enterprise world.
Companies that license software generally employ a salesforce to maintain relationships with clients. Businesses that license software might be responsible for the maintenance of their software, the implementation of services around the software or the customization of a product for a customer. In some cases, they’ll outsource these secondary aspects to service providers as is the case with Microsoft, IBM, Oracle and many other tech giants.
With the dawn of mobile applications, a restrictive, older model has seen a new day. When we think about pay-as-you-go, we think in part of our utility bills like those for electricity and water or the discount mobile carriers that were ever present in the early 2000s.
Nowadays, many mobile applications favor nudging users to pay for upgrades or temporary access to features during their usage. In doing so, they don’t burden users with purchasing decisions at any specific moment. Instead, they favor proposing a paid option at critical moments along the user journey.
These models push users to make micropayments (e.g. smaller payments for access to limited parts of a product or a service). By combining several micropayments per user, some businesses are able to build effective monetization strategies without explicitly placing the user in the context of a heavy purchasing decision.
Much of the innovation over the past 2 decades has been driven by the productization of services, effectively scaling ubiquitous or semi-ubiquitous services and off-the-shelf products.
It’s worth noting that many of today’s most successful companies are profitable thanks to what now seems like old school service models. Not every company needs to achieve massive economies of scale. Of course, productizing and industrializing makes an offer more efficient, but in many cases, providing custom services can not only be lucrative, but just as valuable for end users or customers.
As an example, many open source movements from Linux to Red Hat and WordPress have spurred the growth of consulting agencies, service providers and experts that work on behalf of clients using these technologies. Similarly, even companies that have developed licensed software find it important to provide service work directly to their customers not only as a supplementary revenue stream, but also because such a way of functioning keeps them aware of their clients’ needs and the way their market evolves.
Pricing and Packaging
No one can tell you how much your product is worth. You might conduct interviews and get feedback from potential customers about their willingness to pay for your product. You might look at competitors to price your product relative to a benchmark. You may even read industry reports that attempt to explain what decision makers are ready to pay for.
The best way to determine your price, however, is by testing the value of your feature set. If you’re running a B2B company, you likely have a pipeline of prospects. To test pricing for an enterprise product, you may want to first segment your potential customers based on their needs, and then perhaps based on their expected purchasing power (i.e. company size, number of employees, market, etc.).
Once you have a clear way of grouping your prospects together, you can try pitching them similar packages of feature sets at different prices. With enough feedback and a few rounds of negotiation, you’ll likely have a more developed idea of what your contacts are willing to pay for your product.
For B2C companies, the process of testing is similar, but requires packaging features together and presenting them to a user online, without necessarily connecting with them personally. By collecting data from your pricing page and comparing the number of clicks or signups on a particular offer, you’ll be able to determine, at least from the presentation of your tiered packages how much demand there is as well as how users break relative to the proposed offers you’ve published.
Some companies like Intercom, will change the way they package features and the associated pricing on a regular basis in order to optimize revenue generation at a given point in time, but also to remain relevant vis-à-vis its competitors as the market evolves.
Revenue is measured in the same way as acquisition, activation and retention, through funnels. There can be different entry points to the revenue funnel from various places in a product.
In e-commerce for example, a user may proceed to checkout directly from a product page, or may continue to checkout after adding multiple products to the shopping cart.
When a product uses usage limitations that cause roadblocks for users, the product might propose an upgrade when the blocking point is hit.
In any case, a revenue funnel begins when a user encounters an opportunity to proceed down a path to a purchase. The beginning of these paths can be embedded throughout a product, proposed at random points in the usage of a product, occur through promotional advertising campaigns or appear when a user reaches a limit.
There are usually multiple steps through which a user must proceed before committing to a purchase. In this case, the longer the user takes to make a purchasing decision, the more opportunity exists for the user to doubt her decision. Some companies like Amazon have done so well at optimizing the revenue funnel that purchases for existing users can be made in just one click.
One of the biggest obstacles for companies regarding the revenue funnel implicates payment processors that often provide less than optimal experiences that lie outside the control of the product developer. Choosing your payments processor and how you allow people to pay can make a significant difference in the number of users that complete your funnel. Making the experience fluid and reducing the number of steps at this point are key to ensuring the efficacy of your revenue funnel.
In our next article about the AARRR metric model, we’ll talk about retention, the metric that represents value of recurring users through the frequency of their interaction with your product.
Want to learn more about how to implement product analytics for your company? Download our paper, “The 3 components of behavioral analytics for products.”