The Importance of Revenue Trend Analysis for SaaS Companies

SaaS vendors face unique challenges when it comes to revenue forecasting. While SaaS companies typically view their software as the product, their business depends on delivering a continuous value stream to their customers. This must be tailored to their unique needs – needs that have a habit of evolving and changing regularly. As such, SaaS revenue leaders need to adopt a strategy of continuous improvement and adaptation by investing in the right areas, from product development and customer support to sales/marketing motions and go-to-market (GTM) strategies. 

In today’s rapidly evolving SaaS market that means being agile and proactive. Regularly analyzing revenue trends is a must-have for smart decision-making regarding which areas to invest in to drive growth. It’s a vital part of the planning process as it provides greater visibility into their projected revenue growth across the entire funnel for various product lines, sales channels, geographical regions and customer segments. While no one can predict the future with certainty, analyzing the massive amounts of revenue data that SaaS companies collect can reveal trends that present either opportunities that should be capitalized on, or problems that need to be fixed before they damage the company’s bottom line. 

In another blog post we discussed what is revenue analysis, here we’re focused specifically on what is revenue trend analysis which refers to the collection of revenue-related data from multiple sources over a given period and identifying patterns by either comparing the data to previous periods or breaking it down according to different GTM motions (products, regions, segments, channels, etc.) This helps identify trends in real time, project future trends, and inform key business areas like budget allocation and product development. 

You’ll also hear the term ‘sales revenue trend analysis’ which, despite being a similar concept, is not interchangeable with revenue trend analysis. In the context of SaaS, it’s more important to talk in terms of revenue rather than just sales. The reason for this is that in the SaaS world there are various factors that have just as much impact on revenue as sales. 

Unlike traditional retail-based companies, SaaS vendors also generate revenue from follow-up activities like account upgrades, cross-sells and upsells. In addition, to ensure that they have the full picture they need to take into account activities that happened before the sale. It’s not just about a one-time product sale, but about maximizing the value a customer brings to the company during the lifetime of their engagement. Therefore, we need to map the trends in every area that can have an impact on revenue. 

There is more to revenue trend analysis than simply plotting the total volume of sales against a trend line. That’s because SaaS companies often offer various types of products, add-ons and subscription tiers across multiple customer segments in different regions. Moreover, their expense structure is also different from more product-oriented companies, since they rely heavily on service-based suppliers such as cloud infrastructure vendors. Thus, a comprehensive analysis must take a granular view, allowing teams to drill down into the data that’s important to them and break it down at multiple levels. 

There’s no simple revenue trend analysis formula since the category includes various types of revenue analysis. Some examples of revenue trend analysis include those that focus on specific lines of business, regions or customer segments, while others are categorized by period. A micro-trend analysis examines and projects performance over shorter periods, such as a week or a month, while a macro-trend analysis looks at data collected over a longer period, such as a quarter or a year. 

You might also want to carry out a revenue and expense trend analysis to see how your forecasted revenue aligns with your projected expenses. For example, you might compare bookings as they are now against where they were at the same point in the previous quarter as a percentage of quarterly targets. After all, total numbers, such as the overall revenue generated over a period, aren’t always a reliable metric when it comes to projecting the revenue trends that matter. 

Thanks to the vast amount of data collected through routine customer interactions, businesses can now identify patterns and build forecasts with an impressive degree of accuracy. Doing so makes it easier to identify new business opportunities, as well as potential problems with their revenue flows. For example, a thorough analysis can tell you which type of customers are most at risk of churning, which products or features your best customers are least likely to engage with, and which sales and marketing channels are most likely to perform well in a certain region or for a specific product. 

Let’s consider a real-world revenue trend analysis example to illustrate its importance (see chart below). Consider a SaaS company that offers three paid subscription tiers with the top two tiers bringing in high amounts of revenue per customer. In contrast, it is much more difficult to retain customers that signed up for the lowest-price tier even though it is much more popular. Moreover, the number of customers upgrading to the two higher tiers is disappointing, resulting in lots of customers with a low total contract value (TCV). 

If the company doesn’t analyze the data, then it will inevitably end up wasting its resources in the wrong area since it will make decisions based on popularity. However, by analyzing the trends and understanding how each customer segment or, in this case, subscription tier, adds value to the business, decision-makers can make informed strategic changes to their GTM motions. In this case, it might be necessary, for example, to invest heavily in upsell and cross-sell opportunities, or for the product team to optimize the different tiers and ensure that they are all sustainable. 

Some of the most important metrics to track for identifying revenue trends are bookings, annual recurring revenue (ARR) and total contract value (TCV). However, SaaS companies need to think about more than just the size of the deals they’re closing. They also need to think about retention based on which share of those deals end up recurring. In other words, they need to consider how often their customers renew or upgrade. Again, in a situation with multiple products and/or service tiers that target a broad range of customer demographics, it’s crucial to have a highly granular view of the revenue sources involved.

Finance leaders may be mostly interested in topline metrics, as will potential investors. However, it’s not enough to solely track these metrics since they’re not directly relevant to the day-to-day operations of sales, marketing and product teams. All they do is give a broad picture of how the business is performing on the balance sheet. 

We can take average revenue per account (ARPA) as another revenue trend analysis example as it should also be tracked as it helps align incentives and pricing with the broader needs of the business. As can be seen below, even if ARR is increasing because the company is onboarding more customers, ARPA could still be going down due to strategy changes or increased customer acquisition costs (CAC). 

These factors are largely beyond the control of the finance department, which is why it’s important for teams that are closer to the product or the customer to track, understand and act upon them. Regardless of who is analyzing the data, such changes always need to be based on informed decisions, and that’s exactly where revenue trend analyses come in. 

While every business leader understands the importance of ARR, these high-level metrics are not particularly actionable. What really matters to the revenue organization, including sales, marketing, customer success and product, are actionable insights that are relevant to their specific processes. In other words, they need to understand the composition of all topline metrics. 

As a company matures, its various revenue streams will come to represent differing shares of ARR, with renewals and upsells growing vs new revenue. Truly understanding those revenue streams is where the real potential lies. Equipped with these insights, teams can make granular changes to practically every facet of the business and its products, albeit without having to depend on pure guesswork or instinct. 

With any process, there’s an expectation as to how things should perform. For example, sales representatives are often expected to meet certain sales targets, while product teams might be expected to meet certain adoption rate targets when rolling out new software versions and features. However, there’s little value to be had in simply tracking performance levels for their own sake. It’s important to understand the root causes and why certain targets aren’t being met or for that matter, why certain targets are being exceeded. 

Analyzing revenue trends helps you answer such questions, especially if it’s done on a granular level. For example, when reporting disappointing ARR results, it’s important to understand exactly where the problem is occurring and how. With accurate trend mapping, teams can home in on specific areas, such as customer segments, regions served or products, and see exactly where the fault lies. 

Sometimes, problems are not immediately obvious. As we mentioned previously, ARR might be increasing, and leaders might be delighted with the way things are going. However, if CAC is rising rapidly due to increasing marketing and sales costs in certain regions, they could be in for an unpleasant surprise further down the line. In other situations, there may be positive underlying trends that are even better than topline metrics like ARR suggest. Seasonality is another factor that is important to track but may be misleading for high growth startups which should be looking at growth relative to the previous periods, rather than at simple year-over-year trends. 

Another trend analysis example is customer lifetime value (LTV) which, as a main driver of growth, should also be broken down by specific parameters. By analyzing it in depth, you can get a far more comprehensive picture than just knowing how much revenue a given customer is likely to generate over the course of their relationship with you. Retention is a key consideration when it comes to maximizing LTV so discovering positive or negative trends for gross dollar retention (GDR), net dollar retention (NDR), and cohort development will help identify problems and opportunities earlier. 

After answering the question ‘what is revenue trend analysis’ and reviewing the benefits of tracking revenue trends on a regular basis, it’s likely clear how this proactive approach helps revenue leaders achieve their goals. Even if an overarching trend looks positive, a deeper look can identify negative trends that could impact the bottom line in the foreseeable future. Provided you know about those trends, you can leverage them for new opportunities or alternatively, fix the underlying problem before it can seriously impact the company’s results. 

First you need to have a clear understanding of which metrics are important to your business and its constituent teams, as well as the right tooling to track them. Then revenue trend analysis will be able to provide vital information about how your business is performing. In a constantly evolving, highly competitive and often unpredictable sector like SaaS, that’s a huge advantage to have on side. 

There are multiple ways to start analyzing revenue trends, but the easiest way is to utilize a fully automated revenue analysis solution. The right platform will provide hundreds of precalculated metrics displayed using clear visualization, and then enable anyone to easily drill down into those metrics at a highly granular level. Breakdown options should include any parameter used in your CRM system so you can quickly identify any friction points and risk indicators in your revenue stream and proactively resolve them to ensure optimal flow. 

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• Customer acquisition cost (CAC) 
• Customer lifetime value (LTV) 
• Annual Recurring Revenue (ARR)

• Conversion rate 
• Pipeline health 
• Quarterly forecast
• Net Revenue/Dollar Retention Rate (NRR/NDR) 
• Funnel leads and velocity rate 

• Active user count 
• Behavioral metrics 
• Net promoter score (NPS) 

• Employee turnover rate (ETR)
• Time to productivity 
• Employee experience metrics