6 Best SaaS Marketing Metrics for Business Growth

SHAIVI CHAPALGAONKAR | July 22, 2021

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The software-as-a-service industry is rapidly growing with an estimate to reach $219.5 billion by 2027. SaaS marketing strategies is highly different from other industries; thus, tracking the right metrics for marketing is necessary. SaaS kpis or metrics measure an enterprise’s performance, growth, and momentum. These saas marketing metrics are have been designed to evaluate the health of a business by tracking sales, marketing, and customer success. Direct access to data will help you develop your business and show whether there is any room for development.

SaaS KPIs: What Are They and Why Do They Matter?

Marketing metrics for SaaS indicate growth in different ways. SaaS KPIs, just like regular KPIs, helps business to evaluate their business models and strategies. These key metrics for SaaS companies give a deep insight into which sectors perform well and require reassessment. To optimize any company’s exposure, SaaS metrics for marketing are highly essential. They measure the performance of sales, marketing, and customer retention. SaaS companies believe in the entire life cycle of the customer, while traditional web-based companies focus on immediate sales. The overall goal of SaaS companies is to build long-lasting customer relationships since most revenue is generated through their recurring payments.

SaaS marketing technology are SaaS marketers’ greatest asset if they take the time and effort to understand and implement them. There are essential and unimportant metrics. Knowing which metrics to pay attention to is a challenge. Once you get these metrics right, they will help you to detect your company’s strengths and weaknesses and help you understand whether they are working or not.

There are more than fifteen metrics one can track but make you lose sight of what matters. In this article, we have identified the critical metrics every SaaS should track:

Unique Visitors

This metric measures the number of visitors your website or page sees in a specific time period. If someone visits your website four to five times in that given time period, it will be counted as one unique visitor. Recording this metric is crucial as it shows you what type of visitors your site receives and from what channels they arrive. When the number of unique visitors is high, it indicates to the SaaS marketers that their content resonates with the target customers. It is vital to note, however, which channels these unique visitors reach your website. These channels can be:

  • Organic traffic
  • Social media
  • Paid ads

SaaS marketers should, at this point, identify which channels are working and double down on those. Once you know these channels, you can allocate budgets and optimize these channels for better performance.

Google Analytics is the best free tool to track unique visitors. The tool enables you to refine by dates and compare time periods and generate a report.

Leads

Leads is a broad term that can be broken down into two sub-categories: Sales Qualified Leads (SQL) and Marketing Qualified Leads (MQL). Defining SQL and MQL is important as they can be different for every business. So, let us break down the definitions for the two:

MQL

MQLs are those leads that have moved past the visitor phase in the customer lifecycle. They have taken steps to move ahead and become qualified to become potential customers. They have engaged with your website multiple times. For example, they have visited your website to check out prices, case studies or have downloaded your whitepapers more than two times.

SQL

SQLs actively engage with your site and are more qualified than MQLs. This lead is what you have deemed as the ideal sales candidate. They are way past the initial search stage, evaluating vendors, and are ready for a direct sales pitch. The most crucial distinction between the two is that your sales team has deemed them sales-worthy.

After distinguishing between the two leads, you need to take the next appropriate steps. The best way to measure these leads is through closed-loop automation tools like HubSpot, Marketo, or Pardot. These automation tools will help you set up the criteria that automatically set up an individual as lead based on your website's SQL and MQL actions. Next, track the website traffic to ensure these unique visitors turn into potential leads.

Churn

The churn rate, in short, refers to the number of customers lost in a given time frame. It is the number of revenue SaaS customers who cancel their recurring revenue services. Since SaaS is a subscription-based service, losing customers directly correlates to losing money. The churn rate also indicates that your customers aren’t getting what they want from your service.

Like most of your saas KPIs, you will be reporting on the churn rate every month. To calculate the churn rate, take the total number of customers you lost in the month you’re reporting on. Next, divide that by the number of customers you had at the beginning of the reporting month. Then, multiply that number by 100 to get the percentage.

A churn is natural for any business. However, a high churn rate is an indicator that your business is in trouble. Therefore, it is an essential metric to track for your SaaS company.

Customer Lifetime Value

Customer lifetime value (CLV) measures how valuable a customer is to your business. It is the average amount of money your customers pay during their involvement with your SaaS company. You measure not only their value based on purchases but also the overall relationship. Keeping an existing client is more important than acquiring a new one which makes this metric important.
Measuring CLV is a bit complicated than measuring other metrics. First, calculate the average customer lifetime by taking the number one divided by the customer churn rate. As an example, let’s say your monthly churn rate is 1%. Your average customer lifetime would be 1/0.01 = 100 months.

Then take the average customer lifetime and multiply it by the average revenue per account (ARPA) over a given time period. If your company, for example, brought in $100,000 in revenue last month off of 100 customers, that would be $1,000 in revenue per account.

Finally, this brings us to CLV. You’ll now need to multiply customer lifetime (100 months) by your ARPA ($1,000). That brings us to 100 x $1,000, or $100,000 CLV.

CLV is crucial as it indicates whether or not there is a proper strategy in place for business growth. It also shows investors the value of your company.

Customer Acquisition Cost

Customer acquisition cost (CAC) tells you how much you should spend on acquiring a new customer. The two main factors that determine the CAC are:

  • Lead generation costs
  • Cost of converting that lead into a client

The CAC predicts the resources needed to acquire new customers. It is vital to understand this metric if you want to grow your customer base and make a profit. To calculate your CAC for any given period, divide your marketing and sales spend over that time period by the number of customers gained during the same time. It might cost more to acquire a new customer, but what if that customer ends up spending more than most? That’s where the CLV to CAC ratio comes into play.

CLV: CAC Ratio

CLV: CAC ratio go hand in hand. Comparing the two will help you understand the impact of your business. The CLV: CAC ratio shows the lifetime value of your customers and the amount you spend to gain new ones in a single metric. The ultimate goal of your company should be to have a high CLV: CAC ratio. According to SaaS analytics, a healthy business should have a CLV three times greater than its CAC. Just divide your calculated CLV by CAC to get the ratio. Some top-performing companies even have a ratio of 5:1.

SaaS companies use this number to measure the health of marketing programs to invest in campaigns that work well or divert the resources to those campaigns that work well.

Conclusion

Always remember to set healthy marketing KPIs. Reporting on these numbers is never enough. Ensure that everything you do in marketing ties up to all the goals you have set for your company. Goal-driven SaaS marketing strategies always pay off and empower you and your company to be successful.

Frequently Asked Questions

What are the 5 most important metrics for SaaS companies?

The five most important metrics for SaaS companies are Unique Visitors, Churn, Customer Lifetime Value, Customer Acquisition Cost, and Lead to Customer Conversion Rate.

Why should we measure SaaS marketing metrics?

Measuring marketing metrics are critically important because they help brands determine whether campaigns are successful, and provide insights to adjust future campaigns accordingly. They help marketers understand how their campaigns are driving towards their business goals, and inform decisions for optimizing their campaigns and marketing channels.

How to measure the success of your SaaS marketing?

The success of SaaS marketing can be measured by identifying the metrics that help them succeed. Some examples of those metrics are: Unique Visitors, Churn, Customer Lifetime Value, Customer Acquisition Cost, and Lead to Customer Conversion Rate.

Spotlight

Videology, Inc.

Videology (videologygroup.com) is a leading software provider for converged TV and video advertising. By simplifying big data, we empower marketers and media companies to make smarter advertising decisions to fully harness the value of their audience across screens. Our math and science-based technology enables our customers to manage, measure and optimize digital video and TV advertising to achieve the best results in the converging media landscape.

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Some tools used for predictive analytics are: • SAS Advanced Analytics • Oracle DataScience • IBM SPSS Statistics • SAP Predictive Analytics • Q Research { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What is predictive analytics?", "acceptedAnswer": { "@type": "Answer", "text": "Predictive analytics uses historical data to predict future events. The historical data is used to build a mathematical model that captures essential trends. That predictive model is based on current data that predicts what will happen next or suggest steps to take for optimal outcomes." } },{ "@type": "Question", "name": "How to do predictive analytics?", "acceptedAnswer": { "@type": "Answer", "text": "Define business objectives Collect relevant data available from resources Improve on collected data by data cleaning methods Choose a model or build your own to test data Evaluate and validate the predictive model to ensure " } },{ "@type": "Question", "name": "How does predictive analytics work for business?", "acceptedAnswer": { "@type": "Answer", "text": "Predictive analytics helps businesses attract, retain, and grow their profitable customers. It also helps them in improving their operations." } },{ "@type": "Question", "name": "What tools are used for predictive analytics?", "acceptedAnswer": { "@type": "Answer", "text": "Some tools used for predictive analytics are: SAS Advanced Analytics Oracle DataScience IBM SPSS Statistics SAP Predictive Analytics Q Research" } }] }

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For example, precise data integrity rules do not state or enforce accuracy, precision, scale, or resolution." } },{ "@type": "Question", "name": "What is a data integrity example?", "acceptedAnswer": { "@type": "Answer", "text": "Data integrity is the overall accuracy, completeness, and consistency of data. A few examples where data integrity is compromised are: When a user tries to enter a date outside an acceptable range When a user tries to enter a phone number in the wrong format When a bug in an application attempts to delete the wrong record" } },{ "@type": "Question", "name": "What are the principles of data integrity?", "acceptedAnswer": { "@type": "Answer", "text": "The principles of data integrity are attributable, legible, contemporaneous, original, and accurate. These simple principles need to be part of a data life cycle, GDP, and data integrity initiatives." } }] }

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Spotlight

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Videology (videologygroup.com) is a leading software provider for converged TV and video advertising. By simplifying big data, we empower marketers and media companies to make smarter advertising decisions to fully harness the value of their audience across screens. Our math and science-based technology enables our customers to manage, measure and optimize digital video and TV advertising to achieve the best results in the converging media landscape.

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