Decoding the Pricing Puzzle: Navigating Streaming Platform Costs

In the competitive and evolving landscape of Streaming Platforms, where features are becoming increasingly commoditised, the pesky CFO has a bigger part to play when choosing a vendor. The problem is that direct comparisons between vendors are extremely difficult. Some offer predictability at the expense of scalability, while others offer transparency at the expense of simplicity. The rather complex nature of the technology makes it difficult to treat pricing as pure SaaS, necessitating longer discussions with potential customers to really dig into the nuances of our commercial offerings. Our transparency can sometimes get us into trouble, but we believe it is better in the long run and will lead to better relationships with our customers. 

Pricing models come in a variety of shapes and sizes which makes it tricky to compare OTT platform vendors.

  • Fixed Per-User Pricing: A fixed fee is charged per subscriber or active user. Since the vendor is taking a risk, there is often a high premium in order to cover costs in the event that you have very high activity per user. It’s simple to understand but does not scale.
  • Bucket Pricing: You pay a fixed fee each month that includes a certain amount of users or usage. It is predictable but you have to stay within the bucket in order for it to be worth it. If you grow, there could be high overage or you have to purchase another bucket that you likely will not fill. If you lose users, you will be paying for something you don’t need.  
  • Package Pricing: You like the price of the Basic Package but prefer the options in the Premium Package. Unfortunately, you can’t get the best of both worlds so you end up either disappointed by the Basic or perhaps over budget with the Premium. 
  • Tiered Usage Pricing: The most transparent and scalable option that we at Magine Pro prefer to use. You pay less on a per-unit level as you grow which increases your Gross Margin and lets you focus more of your capital on content and customer acquisition. The other benefit is that you only pay for what you use, as there are no minimum commitments or expensive overages.

Complexity in Comparing

While this diversity in pricing models aims to cater to the diverse needs of customers, it also contributes to the complexity of vendor comparisons. Several other factors also contribute to this complexity:

  • Feature Parity vs. Value: Vendors may offer similar features but bundle them differently across pricing models, making direct feature comparisons challenging.
  • Hidden Costs and Add-Ons: Additional fees for integrations, support, training, or customization can significantly impact the total cost of ownership but may not be immediately apparent.
  • Scalability and Flexibility: Pricing models often lack transparency regarding how costs will scale as the business grows or usage increases, making long-term budgeting difficult.
  • Contractual Terms: Variations in contract terms, such as billing frequency, renewal terms, and cancellation policies, further complicate comparisons.


Navigating the Pricing Maze

Despite the complexity inherent in SaaS pricing models, businesses can employ several strategies to navigate the maze and make informed decisions:

  • Define Requirements Clearly: Start by clearly defining your requirements and prioritizing features that are critical for your business. This will help you evaluate vendors based on your specific needs.
  • Request Detailed Quotes: Reach out to vendors for detailed quotes that outline all costs, including any potential add-ons or hidden fees. Ask for clarity on pricing tiers and scalability.
  • Consider Total Cost of Ownership: Look beyond the sticker price and consider the total cost of ownership over time, including implementation, support, and possible increase in headcount.


Ask and Validate

While comparing SaaS vendors based on pricing models can be challenging, it all comes down to numbers in the end. If you have a forecast then Magine Pro can help you with a Business Model so you know exactly what your costs will be over time. We will gladly go through it in detail so you feel confident and comfortable as you embark on your streaming service journey with Magine Pro.
______________________________________________________________________________________

Interested in learning more about OTT business models? Our comprehensive e-guide has you covered with all the essentials. And if you’re eager to delve into strategies for maximising revenue through content monetisation, don’t miss our white paper, ‘The Profit Playbook: OTT Revenue Growth Tactics‘.

Book a meeting with a member of the team to discuss pricing models and monetisation in more detail.

This website uses cookies

Cookies consist of small text files. They contain data that is stored on your device. To enable us to place certain types of cookies we need to obtain your consent. At Magine Pro AB, corp. ID no. 559301-7287, we use the following kinds of cookies. To read more about which cookies we use and storage times, click here to access our cookies policy.

Manage your cookie-settings

Necessary cookies

Necessary cookies are cookies that must be placed for basic functions to work on the website. Basic functions are, for example, cookies which are needed so that you can use menus on the website and navigate on the site.

Cookies for statistics

For us to measure your interactions with the website, we place cookies in order to keep statistics. These cookies anonymize personal data.

Cookies for ad-tracking

To enable us to offer better service and experience, we place cookies so that we can provide relevant advertising. Another aim of this processing is to enable us to promote products or services, provide customized offers or provide recommendations based on what you have purchased in the past.

Ad measurement user cookies

In order to show relevant ads we place cookies to tailor ads for you

Personalized ads cookies

To show relevant and personal ads we place cookies to provide unique offers that are tailored to your user data