Best Practices For Pricing And Packaging Microsoft Azure
By Tony Cai, Nerdio
Microsoft Azure has had an incredible upward momentum, with a rise of 46% revenue in Microsoft’s most recent quarter. With all of these findings, it makes sense that so many businesses are looking to move to Azure, and MSPs selling Azure have not found a shortage of opportunities to do so.
Many MSPs have had experience with different ways of selling Microsoft Azure, but as the market continues to develop, the best ways to go about marketing Azure have evolved too. Whether you want to make sure your current strategies are up-to-date or feel like you need some advice on improving your Azure business and sales, here are some of the actions and strategies that deliver our partners the most success.
- Before you start, make sure you think ahead to the best-case scenario.
In an ideal world, how will you deliver Azure to your customers? There are multiple options, especially in terms of pricing. Will you charge customers at a flat rate, or will billing fluctuate? Will you bundle Azure with other managed services? These are all decisions that you should make well in advance. Beware, also, of Azure’s consumption-based pricing model, which will make pricing more variable.
- Avoid being held back by common pricing errors.
There are some simple ways to do this, such as ensuring you’re familiarized with the Active Directory identity options (Active Directory Domain Services, Azure Active Directory Domain Services vs Azure Active Directory and the pros and cons of each). Another great idea is using a pricing calculator—such as Nerdio’s free cost estimator -- to ensure you’re giving an accurate quote and quelling customer worries about lock-in and early termination fees. Maintaining the best pricing practices will help build customer trust and ensure that you’re reaping the rewards of your work.
- Keep your proposal as simple as possible.
As an MSP, a large part of your work is oriented around making complicated technology simple. That process should be implemented early in the sales process as well. Make sure you use concise language and get to the point quickly. This will not only ensure the customer is following along well but will help you remember a general outline down the line. Ensuring that you’ve taken all pre-sale considerations into account also can help with building a strong and simple proposal.
- With time, try to produce a standardized quote.
When beginning to propose Azure services to their clients, we see MSPs struggle with how much margin or what their markup should be. Think strategically, do your homework up front, and constantly evaluate your first few deployments and associated costs so that over time you can produce a standardized quote. This will help ensure that you are staying efficient. Some MSPs who have been selling Microsoft Azure for a few years have come to a point where they have their standard build, so they will offer a certain price for certain services a customer may not be able to get elsewhere. Every customer is unique, but you can consider a way to build those specific needs into your standardized quote.
- Create a more appealing proposal, but don’t forget to protect yourself in the process.
One common way that MSPs will make their proposal more attractive is by discounting the set-up costs in exchange for an agreement of a certain length. While it is good to ensure that you are appealing to a customer, it’s still important that your business is protected as well. Some simple ways to ensure this are implementing a cancellation fee and a minimum fee or user count.
Packaging and pricing Microsoft Azure can be a complicated process if you are not sure where to begin. With these tips, you should be able to enhance your proposal or build a strong one from scratch.
About The Author
With over a decade of experience working for and with managed service providers, Tony Cai is a Regional Director of Sales at Nerdio helping partners build profitable cloud and virtual desktop practices in Azure while achieving significant cost savings, optimization, and operational maturity.