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SaaS Metrics Every Founder Should Know

The SaaS industry has increased by 500% in the last seven years.

The best way to stand out is to keep an eye on the metrics that matter to you.

Why do metrics matter then and where should you start?

What makes metrics important

Keeping tabs on SaaS metrics allow you to track your company’s progress or any potential problems that may arise. It’s the fastest way to know which actions work (or don’t) and what their consequences are.

They can help you to:

  • Find behavioural patterns in customers who use your product monthly
  • Learn more about the leads you got from your latest campaign
  • Spot a growing revenue churn 
  • Understand your audience and what they want from your product

Metrics can tell lots of stories about your company’s performance.

Whether it’s about the day-to-day decisions within a team or the bigger picture and a potential acquisition, you still need data to be able to make educated decisions.

These are the key SaaS metrics to monitor to grow your company.

Nine most important SaaS metrics 

Monthly Recurring Revenue (MRR)  

The Monthly Recurring Revenue (MRR) measures your recurring revenue on a monthly basis. 

It’s one of the first metrics you need to track to predict your future growth and influence your resources or your product roadmap.

Another relevant metric to track is your MRR growth rate. This is the percentage change you notice from one month to the other in your MRR.

Ideally, you want a consistently positive MRR growth rate as an indication that your SaaS business is steadily growing.

Annual Run Rate or Annual Recurring Revenue (ARR) 

The annual run rate (ARR) refers to the recurring revenue you generate in a year. For a SaaS subscription business, it’s the annual amount of revenue you generate from all the monthly subscriptions.

It’s not enough to track your MRR to forecast your business growth. The best way to have a clear idea of how your business is performing is to keep a close eye both on MRR and ARR. 

If your company is also offering annual or multi-year contracts, use the annual run rate to predict your revenue growth year-over-year.

ARR also plays a huge part in your valuation whether it’s to secure a new round of funding or if you’re planning to sell your startup. You can use ARR to communicate your growth to investors and potential buyers to provide a more holistic view of your recurring revenue.

Customer churn 

Customer churn refers to the rate your clients cancel their subscriptions.

Your monthly customer churn can help you spot the trends on the rate your clients churn while an annual look at your customer churn can help you shape the bigger picture of your scaling growth.

A good monthly churn rate, for example, for SaaS businesses is 2-3% but the lower is always better. One ancillary metric to keep in mind that is often associated with churn is your NPS (Net Promoter Score). NPS is a simple question of “how likely are you to recommend our product to a friend or colleague?” which is answered on a sliding scale from 1 (least likely)  to 10 (most likely).

A closer look both at the customer and revenue churn can help you spot any red flags that might slow down your growth or cause financial troubles. 

Revenue churn (Gross MRR churn)

The revenue churn (or Gross MRR churn) measures your monthly revenue losses from clients who decide to leave your service or simply to downgrade a plan.

Tracking your MRR churn can help you uncover the business challenges that could affect your future success.

Go beyond the percentage of the churn. Is there a bigger churn on one specific product or pricing range? Is the churn sudden or was it happening in a series of months?

Gross margin 

Your gross margin is the revenue after deducting the costs to produce a product or service. It is also known as the Cost of Goods Sold (COGS) and it doesn’t include your operational costs like marketing and sales.

Investors are always interested in your gross margin as an indication of how efficient your business is.

A lower gross margin, for example, could also indicate a lower revenue for your operational costs and your ability to invest more in the product and the team.

Customer Lifetime Value (LTV) 

The Customer Lifetime Value (LTV) is the average anticipated revenue from an active customer in your company. The longer a customer is happy with your services, the higher their LTV.

Your ultimate goal is to keep your customers happy to stay engaged with your company as much as possible. This is a combination of a good product that adds value to them, the right pricing, and a customer success team that goes beyond the way to support them.

Customer Engagement Score 

The customer engagement scores measure your customers’ engagement with your product.

It can help your customer success team keep all customers happy while the product team can request useful feedback from the happiest customers. On a higher level, founders can look at the customer engagement score to understand how much their customers like their product and how far they are from churning.

It’s up to you to define your own scoring based on the frequency and usage of your product.

Someone who uses your product daily has a higher value than a customer who uses your product every other month.

Customer Acquisition Cost (CAC) 

Customer acquisition cost (CAC) measures how much it costs to acquire a new customer. 

You can calculate it by adding your sales/marketing costs and dividing them by the number of new customers you land at a set time.

For example, if you spend $200,000 a month on marketing and sales to land 400 customers, your CAC is $500.

For a SaaS business, knowing your CAC can help you calculate your business costs and future plans on how to stay successful and efficient.

In order to stay successful, your CAC should be lower than your LTV. You don’t want to lose money on every new customer you land.

Burn Rate 

The burn rate is the capital your business is spending each month. For a SaaS business, the burn rate can affect your future funding.

Let’s say your business has $2 million in the bank and a burn rate of $300,000. This means that you have less than 7 months of cash to run the company at this rate. 

No business wants to stay on a high burn rate. It simply means that you need more revenue to remain profitable or you spend more than what you should.

If you are looking to sell a startup, then keep an eye on your burn rate and work on keeping it to the lowest possible level. 

Are there costs you want to minimize? Is there an area in the business that you’re overspending each month?

No two SaaS businesses are the same. All of them rely on metrics though to measure their success. There are hundreds of metrics to look at.

Start looking at the most important ones for your business and keep a close eye on them to stay successful.

Andrew Gazdecki is a 4x founder with 3x exits, former CRO, and founder of MicroAcquire. Gazdecki has been featured in The New York Times, Forbes Inc., Wall Street Journal, and Entrepreneur Magazine, as well as prominent industry blogs such as Mashable, TechCrunch and VentureBeat.

Building Intent Into Your MarTech Tool to Add Customer Value

Building Intent Into Your MarTech Tool to Add Customer Value

Why add intent data?

In 2011 there were just 150 MarTech companies. Today there are over 8,000 companies competing for our attention. So how do you stand out in an ever-growing crowd? 

You innovate. You provide more value for your clients. Here’s RevOptimal Founder, Will McCartney’s take.

“We define success as providing valuable solutions for our customers. With the LeadSift Intent API integration, we’re able to maintain a reliable and consistent intent input into our scoring models to maximize the value for our users.”

So how do you make sure you’re ahead of the curve while not only adding these benefits for the end-user but ensuring the quality matches the value you hope to provide?

This is where intent fits in. MarTech vendors are adding intent data directly into their tools to differentiate themselves from competitors. Intent data helps their customers identify, prioritize, target, and tailor messaging, directly to the prospects that are actually looking for help with a problem they solve. Here are just a few ways intent is being leveraged in MarTech tools:

  1. Intelligent personalization: sales enablement and marketing automation tools add personalization tokens based on a prospect’s specific intent triggers. If your customer knows a lead is engaging with sales OKRs, they can automatically tailor messaging with a surrounding value prop.
  2. Seamless enrichment: CRMs, conversational intelligence tools, and contact databases can enrich their customers’ prospect and customer data with their relevant intent data so a deeper understanding of the buyer’s journey and added actionability.
  3. Real-time prioritization: MarTech tools (like RevOptimal) allow customers to dynamically prioritize their leads based on their buying signals. This means prioritization alerts that adapt alongside the buyer’s journey for the most effective prioritization and targeting.

We sat down with Will to learn about the state of RevOptimal pre-intent features, how that evaluation process went, what implementation looked like, and the results customers are getting today. So you can make sure you’re in the A-class among nearly 10,000 other MarTech tools.

Before the integration

Before adding intent to their platform, the team at RevOptimal would work with each customer to identify their Ideal Customer Profile (ICP), build a target account list based on that definition, and then the customer could prioritize their outreach based on the ICP fit score. 

They needed a solution to elevate the prioritization solution. In-market buying signals provide actionable, real-time data so their customers can prioritize the accounts that matter most.

If you know who’s a fit, how do you determine who’s actually looking for you, so you can reach them ahead of your competition? This is where intent fits in.

When evaluating an intent vendor, three key factors played a role.

First, is data quality. “Compared to other providers, the coverage and quality for B2B SaaS companies is really strong. That, paired with contact-level data is a key differentiator” says Will.

Second, the API needed to be reliable, and performant. The cost of things moving too slowly or being error-ridden from the start is too high to risk an API they couldn’t trust. “This allowed us to service our clients quickly, and accurately”.

And I might be biased but saving the best for last was the team behind it. “We enjoy working with the team at LeadSift. We’ve found them to be great partners and helpful in supporting our mission to help our clients generate revenue”.

Right in the feels.

Intent implementation

Getting the ball rolling was relatively simple. Once the i’s were dotted and the t’s were crossed, RevOptimal and LeadSift’s Tech and Customer Success teams jumped in to do a technical onboarding. This helps us understand how the data will be integrated, and how we can support them along the implementation process. 

Following that comes a few weeks of API testing and ironing out parameters to make everything connect the way it needs to based on the use case. Then, connecting LeadSift intent with other analytics and data points to build the product that is now in customer hands (and pipelines), it only took 8 weeks to establish the minimum viable product (MVP).

“Implementation was easy due to the consistency and quick support. There was a time where we had trouble passing parameters, and within an hour we were on a call with the Head of Product to help us figure it out and get things running smoothly for our client”.

From a developer’s perspective, they let us know that the implementation structure was intuitive and straightforward. The ability to control pagination parameters meant they could pull intent signals with greater granularity while controlling costs. The cost structure that grows as you grow gave them the flexibility to build while saving costs, and scale as they add customers.

“That’s something that is awesome for us, being able to pull intent data as we need it, not just on an automated recurring basis”.

If you’re wondering about the endless possibilities with this data, you can see the API documentation here.

“With intent data built-in, we’re now able to inform our customers not only which prospects fit their ICP, but also which ones are likely in-market for their solutions”. 

Here’s what that workflow looks like:

The RevOptimal team works with the customer to build a training data set for their ML-based ICP scoring model. This data can include anything from CRM data, to target account lists. 

Next, they build the intent profile. This is made up of a set of signals relevant to the customer’s business solution including competitors, event attendance, hiring, and custom keywords that each play a role in the buyer’s journey.

Now that the foundation is built, RevOptimal monitors for intent signals then scores them based on fit.

From here, on any given day, customers can log into the platform and see ICP fit accounts that are showing intent in real-time, then pull the leads within those accounts to fuel their ad targeting, ABM campaigns, and outbound sales.

At the forefront, RevOptimal helps customers with account prioritization, intent data plays a key role in the machine learning models that determined when one prospect should be prioritized over another. LeadSift intent data is used as an important piece of the puzzle in uncovering revenue opportunities and prioritizing prospects for their clients. 


“ICP analytics and intent combined means our customers not only know who they want but also who wants them. That overlap is the key we’re able to uncover for our clients”.

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If you’re looking to add actionable insights for your customers, stay a step ahead of competitors, or ideally, both, what’s holding you back?

LeadSift Acquired by IDGC

Today we are announcing that LeadSift has agreed to be acquired by IDG Communications, the leader in tech media, data and marketing services. We are beyond excited to join this family.

We started LeadSift in 2012 with the hypothesis that there is a massive amount of buying intent generated across billions of public web documents every day. We quickly realized that this data, if delivered in a timely manner, could be a game changer for businesses trying to connect with their customers. (P.S. we were talking about buying intent way before it was cool.) And over the last 9 years – across multiple product pivots and 100s of customers – we have always focused (almost obsessed) over the mission of “mining information from public web sources to help businesses identify and engage their customers in the buying journey.  

Being one of the leading B2B intent data providers and working with some of the savviest marketers, we got to see how big a role intent data was playing across the entire B2B demand generation process. From identifying buyers across the buying journey to engaging with the right message across multiple channels.

Since the inception of LeadSift and our pivot to a B2B intent data platform, we have had many champions and supporters of our mission who understood the power of intent data for B2B marketers, but few have understood as quickly and succinctly as Andre Yee, Chief Product Officer of IDG Communications. (N.B. When you start discussing a product roadmap in the middle of a corp-dev call with half a dozen executives, you know you have found your kindred spirit!) Right after our first meeting, we realized the incredibly powerful future for B2B marketers we could be building together with the IDG’s proprietary first-party and the marketing tech stack they were building (acquiring Triblio and KickFire is not a coincidence).

If you’re a LeadSift customer, partner or one of our prospective customers (P.S. we should chat now seriously!) here are 3 reasons why we are super excited about the future:

1. Data is King: It is obvious the company that has the most depth and breadth of data wins the B2B demand generation space. IDG.com being the #1 Tech Media company with troves of proprietary first-party intent-data across event attendance, engagement with editorial articles, branded conversations and human verified insights has a massive head start. Imagine how scalable and actionable our intent signals will be once we integrate our 3rd-party realtime web based intent signals with this proprietary first-party intent data stream.

 

2. Incredible Reach: Let’s be honest, being a small startup from Halifax, N.S. we’ve always had challenges in scaling demand generation programs for really large enterprises. By merging with IDG, a company with offices across the globe, we will have a lot more resources to be able to provide global reach and support at a level that we could not previously imagine.

3. Full Cycle Demand Generation: 3rd-party intent data is one piece (albeit a very important one) of the overall B2B marketing and demand generation puzzle. But what if you could know all the information about your first-party web visitors (IDG | Kickfire), cross-reference and prioritize them with 3rd-party intent signals (LeadSift + IDG proprietary first-party data), activate them seamlessly across digital channels (IDG | Triblio) and run highly targeted lead generation programs, all from one single dashboard! This is what Kumaran Ramanathan, president of IDG Communications says: “IDG’s goal of moving to the intersection of media and MarTech is to help B2B marketers navigate the customer journey across a dynamic ecosystem by leveraging unmatched data sets. . LeadSift’s technology is further enhancing our unique intent data that drives ROI for our customers.”

What does this mean for you as a current customer and partner?

As a current customer and partner nothing changes in terms of your subscription, but you can look forward to more and better intent data that includes information from first-party websites and offline sources such as event attendance and telemarketing! Stay tuned for all the exciting product developments we have planned.

What does this mean for the LeadSift team?

We’re closer to building out the most comprehensive and actionable intent data as a service to serve the savviest B2B marketers – and we could not be happier (video/picture). Our entire team is excited to embark on this next chapter of the journey to continue to focus on our mission of “mining information from public web + proprietary data sources to help businesses identify and engage their customers in the buying journey.”

Thank you,

Tukan and Sreejata

LeadSift 360: Complete intent data. Many sources. One place.

LeadSift 360: Complete intent data. Many sources. One place.

We’ve all heard the terms “dark social” or “dark funnel” by now. Terms like this exist because so much of the buyer’s journey happens in places we can’t see. Most people aren’t waving a flag, shouting they’re in-market.

But intent data is meant to unveil those people right? 

The problem is, most intent data vendors are only providing intent signals from one source. This means you’re only getting one, small piece of the puzzle, and a few outliers could not only throw your messaging and timing for a loop, but cause you to miss the accounts that are actually in buying mode.

Introducing LeadSift 360

We’ve always had a multi-source perspective on intent, but we just took it to another level. LeadSift 360 layers more than five data sources, so you get the vastest data, scored like the stock market, so you have noise-free lead generation, directly in your sales and marketing teams’ hands.

LeadSift 360 mines the public web, including job postings, social networks, leadership changes, public forums, technographics, and any other signal on the public web, and layers it with research-based intent. This type of intent is sourced based on prospects researching and reading content on publisher websites that may signal they’re in-market.

Having more data sources means you get a 360-degree view of the buyer’s journey. The intent data essentially validates itself by being cross-referenced with multiple sources, and scored accordingly.

In practice, that means you can be confident in your timing and messaging, beat your competitors to the punch, and scale revenue.

No more black box intent data

A lot of the skepticism around intent comes (rightfully) from not knowing how it’s defined, what counts as a signal, and scoring that is only ever arbitrary secret sauce. 

So let’s break down how we’re doing things differently.

First things first, the intent data. 

Attached to every lead you get, we tell you the event that triggered the event signal. Whether that’s someone engaging with your competitor, a custom keyword, or hiring for a relevant role, you deserve to have that intel to power your messaging.

Next, scoring.

We revamped our scoring to mimic the stock market. This way, large accounts aren’t automatically, artificially inflated, and small accounts aren’t left behind if they’re truly in-market. Directly in the LeadSift platform, you can actually see why we’ve scored an account the way we have. [Note: in the platform, scores are labeled cold, warm, hot, but in the data deliveries, numbers are there for granular prioritization.]

Other research-based intent providers often send out a lot of noise. This is because the nature of that data is broad and high volume. But this can be a good thing when paired with a more narrow source. By layering research-based intent and public web signals, with trend-based scoring, you can filter out the noise and end up with clear, relevant, actionable intent leads at your fingertips. 

So, if you want to get started with noise-free intent data and scale revenue faster, you can try it free for 7 days.

PRESS RELEASE: LeadSift launches LeadSift 360. Complete intent data. Many sources. One place.

HALIFAX, NS – LeadSift, a leading buyer intent data platform, is launching its newest product line: LeadSift 360.

LeadSift 360 will layer all of LeadSift’s existing intent data, mined from the public web, with research-based intent similar to that of competitors like Bombora and ZoomInfo. This will allow sales and marketing teams to have higher quality intent, and ​reach decision-makers in buying mode.

Not only will this data be layered for more data, with less noise, but each account is scored with trend-based scoring, and all scores are explained so clients can meaningfully prioritize their sales and marketing efforts.

With LeadSift 360, B2B technology companies are empowered to see the full picture of the buyer’s journey, taking the guesswork out of prospecting and creating space for tailored messaging every time.

“Being an intent data provider with our own proprietary intent signals, we are always compared to Bombora, the undisputed leader, and now more recently, ZoomInfo. And to be fair, one of the advantages some of our competitors have always had is the scale of intent signals. Millions of website visitors researching and consuming B2B topics. We had to do something about it.” says Tukan Das, CEO

“You can now get a consolidated and prioritized view of all B2B buyers across the entire web delivered to you every day. Whether they are researching the web about your competitors, reading an article about your industry, asking a question on a social media platform, making a new executive hire, attending an industry event. This means B2B tech companies can close revenue faster.” 

About LeadSift

LeadSift is an intent data provider helping B2B technology companies identify in-market customers at the contact level and reach them with relevant messaging. Moving beyond targeting by static profile elements like title or company size, LeadSift shows you who is engaging with competitors, keywords, and events that are relevant to your company from the broadest intent data sources on the market. Learn more about LeadSift.

IntentSity Score: Hear from our Director of Data Science and Engineering

We at LeadSift are launching a new way to score accounts: Intentsity Score.

At LeadSift we track over 15 different types of intent triggers for all B2B SAS. And that gives us a volume of roughly, almost about a million daily intent data points. That translates to anywhere between hundred to thousands of daily leads for a typical LeadSift customer.

And when we have leads at this large scale, the obvious question emerges is how do we know which accounts to prioritize first? And that’s where lead scoring comes into the picture. 

One way to approach this problem of lead scoring using intent data would be to base it on the net volume of intent triggers received over a period of time. The higher, the volume of intent triggers, the higher the score. 

A net volume-based scoring system suffers from bias towards larger organizations. These organizations have bigger workforces and generate higher digital footprints. And thus, they always score high.

Another problem with a net volume-based scoring system is they treat all the intent triggers the same, but fundamentally, each trigger is unique on its own. To give an example, a funding trigger might be less frequent than an account engaging with the content. And yet the funding trigger might be more valuable in deciding the likelihood to buy than a content engagement trigger. Therefore, if you simply look at the net volume, it’s very easy to miss less frequent, but high-priority triggers.

To address these shortcomings. We designed our new scoring system and we based it on two key components. The first being a statistical model that looks at trends in intent volume rather than the net volume. And the second being a rule engine that assigns higher scores upon finding less frequent, but high-priority triggers. 

Let’s take a look at each of them in more detail. The statistical model analyzes 90 days of intent data volume to quantify trends in it. It generates a baseline of usual intent volume and compares the most recent volume against the baseline to compute the intensity of the trend.

How you’d score is similar to Z-score that calculates a values relationship to the mean of a group of values. The score generated by this model is essentially a measure of the upward or downward trend in intent volume. Through this model, we can also generate insights like, “An account received X percent or higher or lower intent volume in the last 30 days than the usual 30 days volume.”

The second component of the new scoring technique is a rule-based component. In this, we look at the last 90 days data to find the occurrence of high-importance triggers. A few examples of high importance triggers are an account receiving funding, or an account seeing leadership changes, or an account entering a new partnership.

Upon finding these triggers, the scoring model factors them in to assign high scores to these accounts. This helps the scoring model to generate insights like, “An account received a high score because it received funding in the last 90 days”.

To sum up our new Intentsity Score, at its core, uses a statistical model and rule-based engines to analyze trends in intent data volume and score accounts.

A higher Intentsity Score would generally mean a higher chance of the account being in its buying journey. From a BANT sales, lead qualification perspective, the Intentsity Score addresses the need and the timing piece. 

We are very excited to launch this and would love to have you try it.

Looking to get started with intent?