Will My Embedded Analytics Solution Integrate Well With My Billing Strategy?

Our previous chapter explored how embedded analytics solutions should scale to suit your future user base size. In this chapter, we’ll break down how to ensure that your chosen embedded analytics solution aligns with your established billing strategy.

Does the embedded analytics solution integrate with my billing strategy?

Definitions

In this chapter, it might help to brush up on the following definitions:

Expired user – This is a user who abandons an application, subscription, or contract.

Here’s What You Need To Know

Does the embedded analytics solution match our billing model?

Your application or product likely already has an established billing model in place. Consider the following aspects of your current billing model:

• Does your billing model offer a freemium or free trial model? If so, will this be a long-term or permanent aspect of your billing model?
• Is your embedded analytics solution of choice going to affect the cost of your product or interfere with your freemium or free trial model?
• Will it be necessary to purchase a large volume of users through the BI tool to account for your freemium or trial users? (Keep in mind that this will come at your own cost.)

Ideally, your embedded analytics solution should be easy to integrate with a freemium model. However, in many cases, you will be required to purchase a surplus of users to account for your free trial users. It’s recommended to measure your free trial user base over several months to get a general idea of just how many accounts you will need to buy and whether or not your free trial model is worth it post-integration.

Just as well, you’ll need to consider your billing timeline. Whether you bill monthly, quarterly, or yearly, your embedded analytics tool should be able to blend into your established timeline. For those who pay by the user, consider whether or not your costs will be prorated if you add or remove a user.

The last thing you want is to be charged a full-term amount– if there’s no way around this, it may be worth looking into an alternative solution.

The tiniest details of your billing framework can make or break the efficiency of a BI tool.

You’ll also need to consider your perpetual or subscription model. For apps that offer a perpetual model, your customer will pay a one-time fee and be able to use your app for life. For apps that offer a subscription model, your customers will need to pay a regular monthly (or quarterly, or annual) fee to use your software.

If your users can buy your product once and keep it forever, will that model affect your chosen embedded analytics solution? Your chosen tool may offer a perpetual license, but not every solution will.

Does the embedded analytics solution match our billing roles?

It is important to remember that the roles within your billing model matter. Consider whether or not your application offers multiple pricing tiers. Within each tier, do your customer have the option to choose which modules they want, such as dashboards, reports, data access, and other bells and whistles? If your application takes a very bespoke approach to billing and subscriptions, your embedded analytics solution will need to align with the customizable analytics needs of your users.

You have to understand that you can use your chosen solution with every tier and each customizable option. The costs must be compatible. In many cases, a BI solution will offer an “all in one” price point for SaaS applications with highly customizable subscription packages. Ask your sales agent about potential cost increases and what scenarios could lead to an increase. Also, consider the possibility that your tier features may change as you scale. Will your BI solution become more expensive if your lower tiers are given more features?

What happens to expired users?

Expired users are unavoidable when it comes to SaaS applications. Many apps will allow end-users who abandoned the product to return, restart their contract, and access their old data within a certain amount of time. Just as well, you may want to offer a subscription “pause” feature as an alternative to outright canceling a subscription. Consider how this could affect the cost of your embedded analytics solution. Because there are licenses involved, will a contract termination or user deletion reduce the cost of your BI? Or will it be non-refundable? Also, consider the extra costs associated with storing abandoned user data for a certain amount of time.

Conclusion

In the end, you’ll need to consider your established billing model and whether or not your BI tool of choice aligns with that billing model.

Consider your user costs, billing timeline, subscription models, customization options, tier scalability, and expired users.

You have reached the end of this complete buyers’ guide for embedded analytics. This one is the last chapter, but we added a bonus because we want to help you in your journey towards embedded analytics. We know it can still be a bit hard for you to understand, so we will introduce you to someone who can help you out with it. Curious? Hop on to the next part to find out!