Business Impact

Feature-bundling for the Save: Why a Data Point-based Invoice Makes Sense

Last updateD on
August 10, 2021
Countly Team
Countly Team
Feature-bundling for the Save: Why a Data Point-based Invoice Makes Sense

Many a time, the choosing of a product analytics vendor can be quite an ordeal because there is no one-size-fits-all solution. The technical factors such as tech stack compatibility and integrations with the product have to be balanced with the financial health of the business. You need to find the sweet spot between where you need to go and how much money you actually have to get there. With so many things to worry about, this article will tell you exactly why getting your vendor agreements aligned with your needs and expectations is the number one factor that will help you get the most out of your investment.

Finding the Perfect Recipe

The way you combine your product or service ideas, their technical execution, and your budget is like creating a recipe. And a notable way of striking gold with your recipe is getting the vendors you need. When it comes to product analytics, the array of options is quite varied and a lot of factors must be considered. We have discussed in the past the importance of getting an extensible analytics solution that adapts to the product and business needs.

But at the end of the day, just like with any decision, this recipe for success needs to deliver the highest value for money all-around. So, how do you ensure the recipe never fails?

Knowing Your Options

As noted, there is a variety of options for product analytics. So how do you choose the one that adapts the best to your budget? Obviously, the answer will differ depending on your product or service, but for the sake of brevity and in general terms:

  1. First things first, your analytics vendor must be comprehensive enough to offer a wide range of features, so one vendor encompasses as much as possible of your present and future analytics needs. There is no easy way of forecasting what your product or service will need with time, so make sure that you always opt for well-maintained, ever-improving analytics software.
  2. Speaking of forecasting, hopefully your business always thrives. But if it ever doesn’t, shoot for a vendor that offers dynamic pricing plans for changes in your cash flow tides. That way, should there ever be an issue, a downgrade is less complicated — and less traumatizing for everyone involved — than changing vendors entirely.
  3. All your teams need to benefit from the platform that you choose, so it must be as easily accessible to everyone in the organization, regardless of the human capital rotation (i.e., it should be as simple as possible to add new members). However, data is sensitive, so access to every bit of data analyzed must depend on customizable access levels, roles, and permissions.

Now, imagine these three aspects — and many more ranging from language availability to system requirements — are covered. How do you put a price on what you need?

Saving Is the New Winning

Generally speaking, the market standard for analytics tends toward user-based or feature-based pricing. This means that, when you choose your product analytics vendor, you need to forecast the total number of users or sessions generating data or the actual features you will need to analyze such data. Planning the way you understand your users and your product with a cap on how many insights you may get, or how much ground you can cover, can easily jeopardize your operations. Imagine, for example, the impact of the pandemic in the eCommerce, ePayment, and eBanking industries and how many more clients companies in these sectors gained in the mass migration to digital operations. Lots of new clients caused user bases to register spikes and to increase the demand for features to analyze their data, two business needs that were very hard to accommodate in the middle of a pandemic.

Award podium where "data points" wins over "features" and "users/sessions".

And then, there’s the third option: data point-based pricing. Instead of basing how much you pay your product analytics vendor depending on, for example, the reporting tools or the number of apps and of dashboards, you get data point tiers with pricing schemes changing after certain thresholds. For the record, a data point is a meaningful fraction of data that can be collected and processed. The reasons why data point-based pricing makes more sense are simple:

  • It helps keep costs at bay during a spike in data points: whenever you see a surge in the number of data points being processed, you can simply turn off features like crash analytics or push notifications to contain costs. This usually works best when you set an alert for when your data point levels go over a certain limit so you avoid additional costs.
  • It helps keep the chosen analytics platform flexible: when you have more than one vendor and you get, say, crash analytics through one, just turn off this feature so it doesn’t “consume” your data points. Then, simply use those extra data points with other features that are unique to one vendor. This helps you to not pay twice for similar features between different vendors. This is a temporary solution though: as we mentioned above, unifying your vendors makes your life easier.
  • It helps you pick and choose your features: as your strategies change, you can use as many features as you may need, letting you experiment with your data all you want. And if the business needs require, roll back on any feature, whenever you need, without having to change any contracts.

But what happens when the tier threshold is exceeded?

The Service You Deserve

Making an efficient choice is to ensure that as little as possible of your investment goes to waste. Product analytics tends to be expansive and ever-evolving — definitely not for the light-hearted. So guidance goes a long way. Guidance that helps you understand if additional data points are just spikes or a permanent growth in traffic and make the decision whether to move to a higher tier or stay with the current one. Guidance that is coupled with technical support. And guidance that proactively gets you and your teams to analyze, share, and act on as much data as possible, regardless of the number of data points.

SLAs and the availability of customer success teams should be a priority in your quest to find your product analytics vendor. When you have such a vast number of possible tools to measure and handle your users’ data, they will stand by your side in your need to keep the usage relevant to your business metrics and goals.

Creating More Value for Less Money

All in all, when it comes down to choosing your vendor, get an end-to-end platform to monitor end-user analytics, behavior, segmentation, create target groups and cohorts, send push notifications (automated, trigger-based, or one-time), understand and analyze crashes and errors, collect feedback, and get all the product analytics you need to improve and innovate your web, mobile, and desktop app.

Contact your next product analytics vendor to learn how to get the most value for your money by better controlling your costs and increasing your cost-efficiency while ensuring that different teams are benefiting from valuable insights.

And don’t hesitate to request a demo so you can see for yourself how you can make your costs always justify the insights and benefits you’re getting.

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