How to automate revenue monitoring

Effective revenue monitoring means monitoring all the metrics and KPIs that impact your revenue. Here’s how automation will help you stay on top, whatever revenue models you use.

Revenue is the ‘mother of all metrics’ for a very significant reason: Because all the data, metrics and KPIs you monitor ultimately stand to impact your revenue. If your site is experiencing downtime, this can hurt your revenue. If a specific item is under-performing, this can hurt your revenue. If your campaigns aren’t working, this can hurt your revenue.

However, monitoring metrics that could ultimately make significant changes to revenue is a huge, resource-heavy challenge for every business today. There’s just so many metrics that go into revenue, and keeping on top of all the fluctuations within those metrics is a huge task.

Fortunately, it’s a problem that can be easily solved with AI automation. But, before we dive into the exciting opportunities that automated KPI monitoring open up, let’s first take a look at the four of the most common revenue models and the unique challenges they present for revenue monitoring.

Exactly what it says on the tin. A single payment is a one-time only payment for a product, or a number of products, that’s agreed upon in advance. For example, an electronics company might sell a TV for a single, one-time payment and collect $1200.

Single payments are product-based and are very sensitive to fluctuations in metrics such as:

To demonstrate the impact an under-performing metric can have on revenue, let’s look at the example of a cosmetics company. This company might make $200 million in a year and have an average order value (AOV) of $30. This means that they are processing hundreds, even thousands, of sales every single day. With such a huge volume of sales, it becomes incredible difficult to monitor potentially under-performing metrics. So, if a certain product isn’t selling as well as others, as a result of the sheer amount of data being processed this is likely to fly under the radar. Yet the company could be missing out on thousands in potential revenue by not investigating why this product is under-performing.

Here’s an example of the Financial Times ‘ subscription plan, allowing access to an unlimited number of articles for paying customers.

While subscription models don’t fluctuate as much as a single-time payment, they still come with their own complications. A subscription revenue model relies on monitoring metrics like:

Micro transactions, or MSX, are most common in the gaming world. Micro transactions are a digital-only revenue model where users can make a one-time, online purchase of virtual goods in-game.

Here’s an example of some micro transaction payment options in the freemium game Candy Crush.

Much like single payments, micro-transactions are also product-based and therefore require monitoring KPIs such as:

This fourth revenue model tends to be the most complex. Companies using it focus on connecting buyers and service providers rather than creating a product or service of their own. This revenue model finds an audience interested in a product or service and directs traffic towards it. Common examples are travel agencies like Tripadvisor, or e-commerce marketplaces like eBay. Money is made through this model by affiliations, partnering, ads or a mix of these three.

Affiliate, partner or ads revenue models are vulnerable to similar challenges as marketing campaigns, like:

For example, if eBay experienced a 50% drop in traffic to a particular product, this would be hard to detect among the millions of products available on the website, but will probably halve the number of conversions for that particular supplier. Because it’s difficult to monitor so much data for so many partners, organisations using this revenue model tend to focus on monitoring metrics of their top partners — and experience a high level of churn from smaller partners as a result, losing thousands in potential revenue each year.

Many companies today also use a blended approach where they utilise a mix of these four revenue models in order to meet the needs of the largest amount of customers. Amazon, for example, mostly utilises the affiliate marketing model to market other companies’ products. But they also sell many of their own products for single payments, as well as operating a subscription model for their delivery and Prime video services.

Blending revenue models might be an effective way of supercharging revenue, but it creates even more opportunities for unruly metrics to damage your bottom line.

Revenue monitoring is a complex ecosystem, where anomalies and fluctuating metrics can at any point devastate a company’s profit margins. But, with so many metrics that can potentially impact revenue to monitor (and companies using a mix of of revenue models to boot), it can be incredibly difficult to stay on top of all the KPIs affecting revenue.

There are three crucial requirements to ensuring you are able to fully monitor the metrics impacting revenue:

Luckily, today we have automated KPI monitoring technologies to streamline the process of monitoring revenue and ensure your profit is protected from anomalies and fluctuating metrics at all times.

The millions upon millions of pieces of data that make up the metrics that impact revenue might be difficult for humans to keep track of, but analysing large datasets is exactly where AI flourishes.

In addition to finding many more digital performance opportunities that helped our users supercharge revenue.

Or contact us at hi@millimetric.ai to learn more about our bespoke Enterprise model that offers full customisation to suit any workflow, agency-style consulting from our team of specialists and fully-supported set up to make the integration process easy — saving you time and money to drive better performance.

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