Either way you will want to make sure that your calculations are correct. Otherwise you jeopardize the whole effort. I’ve seen quite a few ways of calculating SaaS metrics, and here’s a list of most common reasons for them being incorrect.

Not using reliable data

Gargabe in, gargabe out. This is a well known principle in computer science. When your underlying data is trash, you cannot expect that any calculations based on this will be good, right? This also, unsurprisingly, applies to calculating metrics.

People tend to use all sorts of input data for SaaS metrics. Spreadsheets. Sales data from a CRM. Invoices.

From my experience you want to rely on invoices. Invoices are the most trustworthy source of information, because they are legal documents. This forces quality. It’s not the case with other sources. For example sales data is added by many people, with different assumptions, driven by different goals (like quarterly targets).

Lack of automation

It’s ok to do things by hand when starting. With 10-20 customers you can still manage your data by hand, using spreadsheets. With 50 it’s already getting complicated. 100 is unbearable.

Because of the repetitive nature of this task you will get sloppy. Also if you grow your business, you get even more work. The more customers, the more things to update, the more potential problems. A common mistake here is confusing New MRR with Renewal. This happens because you have to understand the whole history of the customer to correctly attribute your invoice to either of them. It means you have to look back through your whole input file.

Not identifying customers correctly

This can be somewhat a part of previous points, but is a big topic in itself. A customer is a separate entity in terms of metrics. In most cases you can calculate metrics for every customer separately and then just join the results together. This means that if you misidentify some payment, things can get ugly. If you end up with two customers (A & B) representing in reality just a single customer you will see invalid metrics. Churn from customer A and New MRR from customer B (instead of just continuous MRR for a single customer) is a typical problem.

In this example Customer A churns in June and renews in July. Customer B is treated as a new customer (new MRR) in June and churns in July. If the reality is that they are the same customer, the situation would be totally different: continuously $100 MRR and no churn/renewal. Other than that your total number of customers could also change, as well as average revenue per account.

Summary

Every business wants to have reliable metrics. It boosts confidence and trust. Empowers your decisions.

The beginnings are ok, because there is not much data. You will sort through it by hand.

Things get tough when you start growing. From my experience crossing 30-50 unique customers is a good trigger to think about this problem in a more structured way. Prepare an input dataset that you trust and automate the task of calculating metrics. It does not have to be anything fancy, but make sure you codify the rules.

Of course using a fully automated solution will make this problem easier. Fully managed solutions like Probe or automated metrics from Spreadsheets via Probe plugin take a lot of burden off your shoulders. All the details and corner-cases (and there are quite a lot of them) are already solved for you. Integrations with common invoicing software will make sure that you can rely on what you see. You get more ways to slice the data. Look at it from different perspectives.

Happy measuring! Michal, Co-founder, Probe

From time to time one of your customers will delay a payment. Maybe it’s an expired credit card or a person responsible for making a wire transfer is on vacation. One way or the other such delay in payment affects your metrics. Let’s look into one example of such delay, or past-due payment, and see what possible solutions we could apply to minimize impact on your metrics.

Consider someone paying you $5000 monthly on the 10th. It’s a big contract so they have 7 days to pay the invoice.

• 10th April – 5000$
• 11th May – 5000$

Now let’s assume it’s 12th June and they haven't paid you yet.

You ask your data analyst or revenue ops – what is our Churn? And the question is – should you include this past-due customer in your churn number or not. Technically it is a churn since 12th of April. So what should you do?

If such a situation happens to you often – for example you receive payments via wire transfer and you have net payment terms of 7 days – there is one trick to counter this situation – by introducing what we call a churn window.

You need to define a period that you, as a business owner, consider ok for the payments to be past due. During this period even if an invoice is not paid yet the customer will still be recognized as MRR. Once the period ends there are two options. Either the invoice is paid and all is ok. Or if it’s still not paid, you should treat it as a churn that happened at the beginning of the period (when the invoice was originally due to be paid).

One thing to be aware of defining a churn window is that it makes the churn metric less proactive. It might give you this warm fuzzy feeling of not having any churn, and suddenly after the churn window elapses and it turns out that your customers actually didn’t pay you, you get to see churn appearing a few days back.

Example

Continuing with the above example, if your churn window was set to 7 days, then you would not see any churn on 12th June, because the payment was due for less than 7 days.

If the user paid at any point in time, then all is ok and you recognize the correct MRR with no Churn.

If they didn’t ever pay, then you will report Churn on 10th of June, when the payment was supposed to be paid originally.

Why bother?

As you can see, introducing the churn window will introduce a bit more predictability into your metrics, especially if your payments aren’t paid on time on a regular basis. SaaS businesses which have smaller monthly payments (think under $1000/mo) might not benefit from it. Companies with less but more enterprise customers and bigger contracts are more likely to see advantages of this and get more predictability when looking at their metrics.

by Mike Co-founder @ Probe

Illustration by Violetta Barsuk from Ouch!

First I want to cover why this is important and then I will present you with 3 approaches to this problem.

Let’s dive in!

The currency of your metrics

Companies calculate and show their numbers in one target currency. This gives them the consistency much needed to be able to compare certain time periods. It means that you have to convert the money you get from your customers in multiple currencies to this target currency. It turns out that such conversion affects SaaS metrics by quite a bit.

Here’s a simplistic example of how metrics are affected by currency exchange rates.

Let’s look at the difference between MRR, Expansion and Contraction when calculating in dollars vs euro. We’re gonna assume there is just one customer and she pays you $100 month by month.

See that your MRR represented in € changes while in $ it stays the same.

And if your MRR is changing, then you have some expansion/contraction in € from this single customer. Wow, there’s quite a difference between how the situation looks in $ vs in €.

As the most critical metrics are affected (MRR, expansion, contraction, churn), so are others. The critical metrics serve as the building blocks to calculate other, more sophisticated numbers like Net Dollar Retention or Lifetime Value. All your numbers change.

What options do I have?

There are a few ways to deal with many currencies. Ultimately it boils down to picking how you convert the money from invoice to your target currency.

I will show you three most common approaches and discuss pros and cons of each approach.

Using exchange rate from the day you start service

The most common approach is that you convert to your target currency using the exchange rate from the day you issued the invoice. This is a very natural date to choose. You probably already have that date somewhere in the system, because it’s important to know it to correctly calculate metrics anyway.

The pros:

• Most accurate because the conversion happens at the day or very close to when you get the actual money

The cons:

• Harder to calculate sales commissions because you have to convert each sale separately to get the final value
• Requires you to keep track of exchange rates for each day

Using exchange rate from beginning/end of the month

Often you want to normalize how you pick your exchange rates so that you can operate your company more easily. For example if your sales team compensation is partially based on the value of deals won, you want to have a relatively straightforward way to calculate it.

In such circumstances you might want to convert the money based on the 1st/last day of the month the invoice was issued.

The pros:

• Simplifies calculations of sales commissions, you sum sales in specific currency and convert using one specific exchange rate

The cons:

• Less accurate because of introducing lag in exchange rates

Using fixed exchange rate

You can also predefine your exchange rates and say “from now on, we use just those exchange rates”. This has the benefit of easy comparison of your numbers without having to take fluctuating exchange rates into account.

Often it’s a matter of a deal with your investors, so things are more understandable and straightforward.

Downside of it is that you can diverge from the real numbers by a lot, depending on fluctuations of exchange rates.

The pros:

• Straightforward
• Results from different time-frames are easily comparable

The cons:

• The numbers can diverge from real money by a lot (for example in May 2021 you could buy 82€ for 100$, in May 2022 you can buy 95€ already!)

Finishing thoughts

As often there is no silver bullet and you have to weigh the pros and cons of each approach. Just make sure to stick to the chosen solution and clearly communicate it. It’s most important to have a common agreement around how the metrics are calculated so employers and/or investors have trust in the numbers.

Mike, Co-Founder @ Probe

This means two things:

1. You would expect younger cohorts to perform better compared to the older once. As time passes, hopefully, you improve the service you provide. It becomes more mature. You sell to customers that are a better fit for your product.
2. You would expect a cohort to stabilize as more months pass. Hopefully, once customers have adopted your product, they will stay with it for longer and will not churn at such a high rate as at the beginning of the lifecycle.

Here is how we can apply this to churn cohorts:

Using cohort analysis to understand MRR churn

You can use quite a few different metrics as a value for your cohort. MRR is a very good example. By calculating the MRR retention rate for each cohort you can easily understand not only where you lose the most of your money but also if you manage to grow revenue over the lifespan of the specific cohort.

Let’s take a look at the example below:

You can see that in younger cohorts, specifically Feb 2020, Mar 2020, Apr 2020 our company managed to cover all MRR churn by expanding existing customers’ MRR. Thus achieving +100% MRR retention. These cohorts have more MRR in Month 2-4 than in Month 0. This is a great sign that you are doing something right and can expand your existing customer base.

Learn more about using Excel for analytics

Alex Co-Founder @ Probe

What to collect

I will separate this information to two sets – minimal requirements and additional information that can be handy

At minimum, you have to collect information about every payment made by your customers for your service. Here is a list of attributes you will be looking for:

1. Customer ID – some unique string that can be used as an identifier for your customer. If you are in a business-to-business, tax id could be a good candidate.
2. Service Start At – a first day customer has access to your service because of this payment.
3. Service End Date – when access to the service customer paid for ends.
4. Total Amount Paid – how much money in total customer paid you in this transaction
5. Monthly amount – this is easy to calculate as Total Amount Paid / Number of Month Paid for
6. Revenue Type – if you are in a recurring revenue business, you have to separate revenue that you expect to receive regularly (recurring) from revenue that is paid only once (one-time). Usually one-time revenue is revenue the customer pays you for Professional Services engagements or onboarding.

Additional attributes that can help you to enhance your analytics:

1. Invoice ID – basically something that will help you track back to the original invoice, which has more details about this payment.
2. Product Name – this comes very handy if you are selling more than 1 product or plan. It will allow you to segment your revenue by this name
3. Any information about your customer – such as country / industry or business size – this attributes will allow you to understand your business deeper by segmenting results.
4. Original Currency and paid values in original currency – if you are receiving payments in multiple currencies, you will need to convert them into one currency. You can either select one conversion rate for all data, or use Google Spreadsheets GOOGLEFINANCE formula

Where do I store this data

If you have around 50-70 customer – Excel or Google Spreadsheet may be a good place to start with.

Probe is also a perfect place for such information that can automate not only collecting this data, but also take care of all the updates and analytics on your behalf.

When it comes to keeping this information up-to-date, if the number of customers is tiny – consider doing it manually once a month. When it becomes tricky due to your scale Probe can help you.

How to calculate my metrics

Once you have all of your data in Sheets. You can use our Probe Google Spreadsheet plugin. It will take care of all the calculations for you.

All you need to do is to push this data inside Google Spreadsheet and give column headers correct names as below. It is important that headers match exactly the name specified in the list. Probe plugin uses this strings as keys to identify what data stored whee.

1. customerid – your customer id goes here
2. startedat – date when service starts for this payment
3. endedat – date when service ends for this payment
4. mrr – monthly amount contributing to your revenue

Here is the template you can view and copy to play with it.

Now all you have to do is two things: Select 4 columns with data Go to the top bar menu and click Extensions –> Probe –> Calculate Metrics Using Probe

This will automatically create a new sheet for you with basic metrics for your business.

What metrics Probe plugin supports

Here is a quick list of metric Probe will calculate with your basic data:

1. New MRR – amount of recurring revenue that came from new business – customers that you have not done business with in the past.
2. Expansion – this tells you how much money you gained due to existing customers starting to pay you more
3. Contraction – this tells you ho much money you lose due to some of your existing customers starting to pay you less
4. Churn – how much money you lost because customers left your service and stopped paying your
5. MRR – total amount of recurring revenue for a given month, it already includes new MRR as well as all the movements that may happen to your existing customers
6. LTV – this is an estimation of what is the potential amount of money you could expect to receive from a customer when he joins your service.
7. ARPU – this tells you how much recurring revenue on average you are receiving per customer. It is a useful number to know to do a quick estimation of what will it take to reach your revenue goal. Ex. if your ARPU is $100, and you want to get to $100k in MRR you know that you need to find $100,000/$100 = 1000 new customers to your service

In addition to this, you are getting a couple of charts that visualize the same data.

How to do cohort analysis

We already wrote extensively about what is cohort, how to use cohort analysis and how to read it. So go there for this additional information.

It may get a little tricky to build one in spreadsheet, but now Probe Plugin helps you with this. All you need to do is again select these 4 columns of data and click Extensions –> Probe –> Calculate Churn Cohort using probe

This will show you your churn cohort. Cohort groups customers that start using your service within the same month, then looks into initial revenue you received from this group of customers and shows you what percent of this initial number got lost as time passes.

Again, here is a more details blog post on how this works and what you should be paying attention to in this analysis.

What next

A couple of useful resources for you:

1. Analytics with Excel – a quick page to get access to this and other tips & tricks on how to do data in Excel
2. Google Sheets Probe Plugin – install it from the Google Marketplace
3. Spreadsheet Template you can copy to play with Google Probe Plugin
4. If you grow beyond the spreadsheet more – talk to us – and we will help you to automate not only data collection but also your whole analytics.

alex Co-Founder at Probe

ChargeBee

Not all of you use Stripe. We get it. From now on Probe works with ChargeBee as well! Currently, in private beta, you can use ChargeBee as a source of subscriptions data for Probe, the same way you would do with Stripe.

Once you are connected you will be able to see the same set of metrics and segment them in any way you want. Integrations connecting external data like HubSpot will also work, allowing you to segment by data from external sources.

Reach out to us at support@getprobe.io if you would like to see this integration in action.

Intercom and HubSpot

Oftentimes you want to see details of your customer when interacting with them. For example, knowing your customer’s MRR may help you prioritize their support request. We built these two integrations – Intercom and HubSpot – specifically for this use case. We enrich their interface to show you: Lifetime Value, Current MRR, and Subscription End Date. These numbers are shown when you are viewing your customer card in the products.

Additionally, for Intercom, we show a nice, small sparkline graph of the customer's MRR to show you how it changed month after month.

For more details on HubSpot integration check out HubSpot App Marketplace.

The Intercom integration is available at Intercom App Store

Google Sheets

Last but not least, Google Sheets integration. This is for all of you who track your numbers in Google Sheets.

Have your data in a format that we understand: we need columns with these headers: customerid, mrr, started (and optionally ended). Then add each of your customers’ subscriptions in a separate row. Select the prepared data and chose “Probe –> Calculate Metrics” from the menu.

We will show you month-by-month metrics for this data: New MRR, Expansion, Contraction, Churn, MRR, Lifetime Value & Average Revenue Per User. You will see this data in tabular form as well as on Sheets-driven embedded charts.

If you run a small company, with just a handful of customers, but still want to have the metrics calculated, go and use it, it’s free! The integration is available in Google Workspace Marketplace.

I hope you find these integrations useful, happy measuring!

— Mike CTO @ Probe

We have recently released quite a few product updates that our customers love. Here is a quick update on what is new at Probe and the rationale behind.

Ability to see details of each calculation

Up to that point Probe would show you just the results of calculation. We would connect your data, calculate your metric and show your MRR equals $5,000 as an example.

It is difficult to trust this number if you have no ability to see what is behind it. And it is even more painful if you are trying to figure out why the MRR number which is given to you is not matching your expectations or other source.

Therefore, we have built an ability to see details of calculations. You can see how it works on a quick demo below.

Detailed view of customer

Very often billing data can get messy. Whether it is due to refunds, same customer paying from two different accounts, or company using a couple of billing systems. Honestly we have seen quite a few of these. So when you try to understand how a specific customer contributed to your MRR it can be a challenge.

In Probe you can now access a detailed view for each of your customers. See all the subscriptions this customer has and how they are recognized over the months to come.

Segmentation

Your customer base is diverse. Different groups of customers behave differently. It is crucial to segment your metrics if you want to understand the real picture of what is going on. While one customer's segment may grow – another may stay stable and without segmentation you will not be noticing these difference. It will lead to wrong business decisions and focus on a wrong type of customers.

At Probe, you can set up any segmentation attribute and segment all the metrics by these attributes.

Access all of your customers and subscriptions

We spoke to many customers who are using spreadsheets to collect all the customers and subscriptions in one place. And for them, this feeling of control, ability to see the full list of customers or subscriptions in one place is very important. I don’t want to go into describing all drawbacks of using spreadsheets. But from now on you can access a full list of customers and subscriptions in Probe. Sorting and searching is included.

These changes give you greater control over your data. Numbers and calculations are not a black box anymore – you can always see what is inside. With this – you start to build trust and confidence in data. This is very important when you are communicating your numbers to your team or investors, and your personal credibility is on the line.

You can register for a free trial or schedule a demo with us. There is a number of smaller updates – starting from the ability to segment any metric in Probe – to manually adding new data and introducing a correction. Hope you like it and let me know your feedback.

by Alex, co-founder of Probe Illustration by Icons 8 from Icons8

At the start of each new product are just a couple of people having an idea and trying to figure out how to make it a reality. You probably speak with potential customers researching your thesis and start building the product.

Small team means everyone stays in sync. Then you start having your first customers, perhaps you raised money and your team grows. It becomes harder and harder to keep everyone focused and up to date on what is happening inside the company. Choosing correct metrics according to the stage of your company can really help you focus on the right things and measure your progress.

This article is mainly about SaaS B2B companies (Business-To-Business – if your customers are other businesses, you are in this category). If you are building a marketplace or consumer-oriented business – some things will still apply. But such areas as product adoption, marketing and sales may be a bit different for you. I also focus on a basic metrics you can start to measure when there are only a couple of people and the once you can add at a bit of a later stage of your growth.

The founders only level

You start small – just you and a couple of co-founders. You have the idea in your head and you need to turn it into a product. It seems like there is no need to measure anything at such an early stage. While you should not spend much time doing complex analysis – here are three basic numbers that will help you stay focused.

1. Total Revenue

You are here to build the business, right? Track your total revenue from day 1. The growth of this number is the most important thing defining your success. Remember that you must separate your recurring revenue from nonrecurring, report and track them separately. It is because these two types of revenue are very different in its nature. Nonrecurring revenue is usually a one time payment for a provided service – lets say training, or product implementation. You can not expect to receive the same amount of money in months to come. Comparing to the recurring revenue which is an ongoing payment. You expect to receive this revenue as long as someone stays your customer.

2. Number of conversation with prospects / potential customers

No matter how early you are – start speaking to customers from day 1. You need to have customer feedback to validate your product thesis. Set yourself a weekly or monthly goal of having a certain amount of conversations with customers. That will focus you on reaching out and speaking with your potential users and as a result you will be able to build a better product.

A certain number of conversations with potential customers will lead to actually having real customers. Early adopters who will use your product first and help you iterate on it.

3. Burn rate

Try to have an idea of your monthly costs. No matter if you raise external funding or bootstrapping. That will help you calculate your runways (see below) and answer some of the investor’s questions.

4. Runway

Runway tells you how much time you have before you run out of money. This number will keep you motivated and will help you plan accordingly.

Measuring Sales

No matter how small you are – if you want to get your first customers you must sell. At the very beginning it is the founders who are responsible for this area. Let’s see what we can track to keep everything in order.

1. New MRR

How much recurring revenue do you acquire from new customers joining your business over the period of time. This is pretty straightforward. If you set a goal of hitting a certain number of New MRR you have to track details of your Sales Process so you can estimate if you are on the right track or not. Here is how.

2. A number of Demos or Trials

Sales is a game of numbers. Depending on your product you can offer a demo or a trial period, or perhaps both. A certain number of such activities will convert to new customers. So you have to track the number of trials or demos. Set a goal for these metrics and try to grow them.

3. Conversion Rate from Demo or Trial to Won Customer

As I was saying – a certain number of demo meetings or trials will be converted to new customers. You need to understand what percentage are actually converted to a new customer. Once you have this percentage – it becomes very easy to understand how many such meetings you have to conduct to win a certain number of customers. Ex. If your conversion rate is 5% and you hold 100 meetings it should yield you 5 new customers.

As your organization scales, and your sales become more sophisticated I suggest you start tracking:

1. The length of your sales cycle – how long does it take to move a customer through the whole sales process – from initial call to signing a contract? It can be days, weeks or months.
2. Number of Deals in the Pipeline – this is self-explanatory
3. Total Pipeline Worth – total sum of all the deals values that are currently in your pipeline
4. Deal to Won conversion rate – what percent of Deals that entered your sales pipeline converted to new customers.

By knowing these 4 numbers you can make a lot of estimates that help you hit your New MRR goal. For example – if your sales cycle is 6 months long you already have to start working on prospecting and finding potential companies you can sell to hit your future goals.

By knowing key numbers of your pipeline you can simply estimate what amount of revenue it can bring you:

Total Pipeline Worth / Number of Deals – will give you your Average Deal Value. And then Number of Deals * Conversion Rate * Average Deal Value – gives you an approximate estimate of the revenue that can be extracted from your sales pipeline.

Product Organization

When you are at the beginning of building your company, big chunk of your time will be spent on building the product, iterating and making it better. Because each product has to solve a real customer pain and deliver value to your customers – you have to find a way to measure if this is what is happening in reality.

Here are two numbers that will help you to get it right.

1. Total active users

First very simple way to measure if someone is using your product is just to look at the total number of active users on the daily / weekly / monthly basis. It is important to define what “active” means specifically for your product. For example if you are building a software for creating Sales Quotes – active may mean that the user has created a new quote in your system.

2. DAU / MAU Ratio

You have to make sure that your active users also stick with your product. Or in other words use it over a long period of time. DAU stands for Daily Active Users and MAU is Monthly Active Users.

One way to understand if users of your product stay engaged over the period of time is to calculate the ratio between DAU and MAU. Take the total number of unique users that were active on a given day and divide it by the total number of unique users that were active over the course of the last 30 days. The closer this ratio is to being 1 the better – cause that would mean that all the users are retained with your product.

Customer Success or understanding revenue coming from existing customers

Once you have at least one customer you have to make sure that they stay happy. At first, it can be as simple as having a conversation once in a while to make sure they are engaged. Measure product adoption on the customer level. Down the road it means building a whole Customer Success team.

From your revenue perspective – you will have to monitor movements of your existing revenue.

1. Churn MRR

You have to track how much revenue you’re losing due to customers leaving you as well as how many customers you are losing on a monthly basis. The thing is that there is a cost attached to acquiring each customer. Firstly, if the customer leaves before you’ve recovered the cost of acquiring this customer – you are losing money as a business. Secondly, when a customer leaves you – you are losing not only monthly revenue from them, but also the opportunity to get revenue in the future. It has an immense compounding effect. Lower churn means not only the customers engaged with your product but also has a tremendous impact on your business growth.

2. Contraction MRR

How much revenue you have lost due to customers starting to pay you less. Usually, because they have moved to cheaper plans of your product. I suggest you track MRR lost due to contraction separately from MRR lost due to churn. Because in case of the contraction you still have the customer. They are still paying and there is a chance to deliver them more value and retain for a long period of time.

3. Expansion MRR

How much MRR you have gained due to customers starting to pay you more. Ability to grow MRR from existing customers can be one of the biggest contributing factors to your growth.

If you have a full fledged customer success or account manager team, tracking Expansion is one of the ways you can use to measure success of this team. Because if customers are successful with your product – usually they would want to use it more and more, add new seats or users and so on. Existing customers is a huge potential for your business growth

4. Renewal MRR

How much MRR did you get due to someone coming back to your product once after they have left. Meaning of this metric can be specific to your business. If some customers come back to your product after some time it is a good sign overall. But if this is happening at a large scale it can be a sign of the product issue. As an example, your product may have more of a one-time use case and does not deliver ongoing value.

I should also mention that with time you must look at your churn by cohorts. It is the best way to understand if you as an organization make progress with time. It is also a big topic on its own – we have recently written a separate blog post about how to build and use cohort analysis.

Bringing it all together

Ok, let's recap. At this point you should have a good view inside your Sales Organization, understand your product adoption as well as what is happening with MRR from the existing customers. There are just a couple of metrics you need to measure once you have some scale to understand your whole SaaS business.

1. CAC – Customer Acquisition Cost

How much does it cost to acquire a new customer? What should and should not be included in a CAC may be a subject to a separate discussion. This number gives you an understanding of how much money you need to invest in order to reach a certain number of customers. As you will see later it is also a metric you want to minimize. Because if you are able to acquire new customers cheaper, the profitability and performance of your SaaS business will increase.

2. LTV – Life Time Value

How much money in total you can expect to receive from a customer. In order to calculate this you have to understand for how many months on average somebody stays your customer. And then what is average revenue per month for a customer. By multiplying these two number you will get your LTV. This number is especially important with relation to CAC, lets see why.

3. LTV / CAC ratio

Once you know how much it costs to find a new customer and you know how much you can expect from a customer in total, the ratio between these two become important. The higher the LTV / CAC ratio is the better. Here is a very simple example to illustrate the idea. Let's say you run Google Ads campaign. After everything is set and done you calculated that it costs you $30 to acquire a new customer. And this customer will stay with you for 18 months and pay $10 per month. Meaning its LTV is $180. LTV / CAC ration is 6. You can see that such model clearly can make money. You invested $30 to get new customer and end up with $150 profit ($180 total revenue minus $30 for recovering acquisition cost). If the ratio is equal to 1 or less it means your business it means there is a problem. You are either loosing money or not able to deliver enough value.

Of course there are much more details into the above calculations. But I just want to illustrate the idea how you can start to understand if you are on the right path to build scalable and healthy SaaS.

The importance of segmentation

As your company grows – chances are you will be serving different segments of the market. For example, some of your customers might be much bigger than others. Thus, it may cost you more to acquire and serve them but their lifetime value will be higher.

When at scale, it is important to use segmentation for all the metrics we have mentioned. Because your bigger customer segment may be behaving perfectly well and healthy while smaller customer segment may be unprofitable. As one example very often you will find your smaller customers churn at much higher rate compared to bigger customers.

You will not be able to see such details if you do not create appropriate segments for your customer base. You have to think what is the right way for your business to segment metrics so understand them better and make better decisions. Customer size based on number of seats or their MRR is a good place to start. Here is a great blog post about segmentation in SaaS.

Creating a rhythm in your business

It may look like there are a lot of numbers to keep track of. And certainly as your business growths you have to look at the increasing number of metrics. It is important to create a certain rhythm of looking at your data. You need to create a process that will help you keep organized. It also will help you to create a feedback loop where you first take action, then measure the result, discussing numbers and this informs you farther actions.

Monthly business review is one way to create rhythm. Depending on the scale of your business you can do it bi-weekly or even weekly. But the main idea is to have a repeatable event in your calendar where you can review the key numbers with your team, discuss what is happening and agree on the next steps. In this way even if you measure a lot of things you will have a process around that will help you to stay organized and actually convert measurements into real actions.

At Probe, we focus not only on helping you to measure your business. We also help you to create such rhythm by automating your reporting. You can add description to your data and easily share key results with your team. So that you can discuss your numbers, keep everyone aligned and convert these results into actions.

by Alex, co-founder of Probe

I worked for 8 years at a successful startup called Base CRM. It was acquired by Zendesk 2 years ago. During this time I saw the company take different approaches to many problems startups have, but one remained unchanged: unparalleled, obsessive focus on shipping new functionality. Lately, I’ve been thinking a bit more about a company as a whole because I co-started a gig called Probe, so here’s some things I think should have been different at Base.

Disclaimer I have to make: although the things I write here may sound negative it wasn’t all that bad. We still were a really successful company, did many things right, we had a great team, a product used by thousands of sales people. I’m just focusing on where we could’ve done better (myself included).

Beginnings at Base

Base’s mentality was always oriented towards product and shipping features. Even our motto said it: “It’s null till you ship it” – what better way to say that all your R&D efforts should go to releasing new stuff to production? This mentality was brought by our CEO, the person behind the idea of building a new CRM – Uzi Shmilovici. He was the most experienced person in our very young team (I joined when I was 24). His experience was definitely something that helped to instill the value of shipping new product features in our minds.

Quickly the whole organization adopted and started living by this motto. To be perfectly fair: I think there was a lot of merit in it. Being a hardcore developer at that time I still believed that what we sell is the shipped product, not the technical solutions behind it, nor the automated tests, code coverage etc. At least this is how I projected what this motto meant, and I’m quite convinced that others looked at it this way as well. I wasn’t 100% right.

Maturity and Growth at Base

Over time the company grew. More customers, bigger funding rounds, higher ambitions. Our R&D suddenly became 40, then 100 people. All of them with the “it’s null till you ship it” mindset.

Things got more and more complicated as well. CRM is a broad topic and can mean many things. It tries to embrace the basics of many different sales processes that companies have, together with a broad set of other features like email or calendar integration. It took an enormous amount of work to ship new features that fitted nicely into the existing ecosystem. Suddenly we had 1-year projects on our roadmap (nicely hidden under 3-month projects which didn’t end on time).

Additionally we landed a few huge deals, the famous customers you can’t afford to lose. It meant custom work embedded into already complicated functionality, and complexity grew fast. Big customers certainly sounded good on paper, but they came with a cost (complexity and a very hands-on relationship) that we weren’t really prepared for, and that we didn’t manage to put boundaries on fast enough.

… the difficulties started piling up fast, and before we knew it we had to deal with a lot.

We also added a lot of complication on the backend of the product. Moving to microservices meant getting rid of some problems of our legacy architecture, but it introduced us to the world of (arguably) harder ones, like keeping data consistent across services. Some we managed to cover up with money by just buying more processing power. Others we desperately needed to fix, especially those basic building blocks of our infrastructure which we knew didn’t work. One example would be a communication channel between our microservices without the at-least-once guarantee – some messages would never reach the destination endpoints, which caused problems with data-consistency.

Of course, all of this was the effect of our success. We had new customers coming in, the metrics looked good, and we quickly moved up in the market. It was all because we were solving real user problems.

But the difficulties started piling up fast, and before we knew it we had to deal with a lot.

The Difficulties

On the product side the complexity was quite overwhelming. We had a huge system with many moving parts which interacted with each other, and these interactions were sometimes hard to understand. With the added factor of custom solutions for Big Customers™, more and more flaws in the interactions started showing up.

No Decision Paper-trail

There was little documentation about product decisions. If you’d been around for a long time (like myself), then you had a fairly good understanding of how the product worked. Anyone else had to ask around, but even the original authors of ideas didn’t have all the answers, because the situation was often complicated and involved multiple people on the team.

Insufficient Iteration

We didn’t revisit features often, either. The product specs were well thought through, sometimes crafted for months, but the truth is that almost nothing you build will be perfect the first time. (and if it is, there’s almost certainly a generous amount of luck involved). It’s normal, and there’s nothing to be ashamed of – no matter how hard we plan and research, we build with imperfect information, and we do the best we can. Sadly, we had a lot more confidence than was wise in how well our features were initially designed – some might say hubris – and we didn’t revisit or iterate on existing features.

Technology Built With More Enthusiasm Than Experience

The backend suffered as well. We moved into a world of microservices very early on, and that’s not to say that microservices aren’t a power tool (I’m still a fan of them), but you have to have expertise on how to do it well. Back then, we were inexperienced and just thinking about the outcomes and upsides, so we still pushed very hard to separate our architecture into microservices, and in many cases we did it badly. We pushed it too fast, too early, and without really learning along the way – so, in effect, we just repeated the same mistakes multiple times, rather than iteratively improving our architecture and processes as we moved forward.

We moved too slow with technical documentation as well. With a system as complex as this, it’s crucial to document your tech stack, code, and APIs Yet with the pace of shipping new things, and a pressure to deliver working solutions, we neglected documenting how things work and focused on just getting things out the door. In hindsight, we also should have standardized many more things as we moved forwards. Without coding or operating standards, the cost to introduce new solutions grew.

Lessons Learned

So far, I’ve just talked about the challenges we faced, and the pain we felt. There’s plenty you can take away just from that, but I’d like to make sure I’m also sharing some of the actual lessons I learned in the process, so that you don’t make the same mistakes.

Culture Shapes Everything

One thing it’s worth noting as a background to all of these lessons is that it’s important to recognise the huge and subtle impact of organisational culture. While some of our challenges were a result of us being a young, enthusiastic startup team, many could be traced back to the culture of “it’s null till you ship it”. That wasn’t just a saying, it was an idea that became embedded in how we thought about bugs, customers, growth and technology.

I’m certainly not saying it was a bad saying, or a toxic culture – it was instrumental in our growth and success! But I am saying that we didn’t pay enough attention to how it was shaping our organisation and our product practices. Be ready to adapt your organisation when your situation changes.

Iterate More

First and foremost: no matter how much time you put into your product design, iterate again. Your best, educated guess is not going to be enough, even if you spend 6 months perfecting it. The urge to have new functionality is huge – believe me, I know! – but make sure you spend time taking care of existing solutions. There are many improvements waiting, just look at your existing customers and what they tell you(via your support system or sales team), trust your team, and give them time to improve on solutions they previously crafted which could be delivering more value (or less friction).

Recognise – and Control – your Technical Debt

While you’re at it, gather quantitative data from your backend about errors & bugs. The complexity and friction you ignore in your software is inevitably going to haunt you when you want to try and build something new, so pay attention to your technical debt and take steps to control it. Bear in mind that some of your technical debt will be in the code, and some of it will be in the documentation or processes (or lack thereof). You need to address both, one way or another.

Beware of Money With Strings Attached

Hopefully you’ll be successful and will win big customers. However, beware of huge deals, because although the money is great, they often come with strings attached. Most likely you’re going to “pollute” your product with custom solutions which don’t really fit in, and which possibly shouldn’t even be a part of the product at all. It’s also going to force you to redesign your team structure somehow – perhaps create a Professional Services team – or else your roadmap is going to be a constant battlefield between what you want to ship and what your Big Customer™ wants. We thought these kinds of big customers would be a segway into a world of Enterprise sales, but it turned out they weren’t a guaranteed path. In fact, we lost our very first one without a clear benefit – no product improvements, and no references or stepping-stones for future Enterprise customers.

Speak up Sooner

If you are an individual contributor or a team leader of a small group of people, make sure you voice your concerns clearly. Founders are (hopefully) focused on the most important metrics and setting up strategy (and for good reasons!), but it is your responsibility to make sure they know about the things you’re responsible for. Product experience getting worse? More and more errors piling up on the backend side? Be open about it and ask for time to fix things, otherwise it’s you who’s going to have to deal with these issues all the time.

by Mike, co-founder of Probe

Originally published on www.mindtheproduct.com, 25th August 2020 Illustration by Ivan Haidutski from Icons8

The version we have launched

We decided to focus on analytics after our own experience of working in a SaaS company. We went through all the troubles from defining what to measure to building data collection stack in-house.

With Probe, we want to make it much easier to get the analytics you really need. Our MVP (Minimum Valuable Product – put simply, a minimal version of the product you launch that you believe will bring value to your customers) was a simple Slack application. You can connect it to your Stripe account and then ask for any SaaS metrics with one slack command. For example, /probe mrr would give you a chart of your monthly recurring revenue. This is the product we decided to submit to ProductHunt.

What is ProductHunt and our goal for the launch

If you are not aware of ProductHunt – it is a community for discovering new products. Each member can submit a new product, and then other members can upvote your submission if they like it. Products that have the most upvotes are being promoted by the platform.

Top 5 submissions with the most upvotes launched on a given day will be featured in the ProductHunt newsletter. This newsletter has quite a big audience and being there simply increases your chances to get new customers. We aimed to find early adopters via launching on ProductHunt. Probe is a business to business product. It means that our potential customers are early-stage SaaS companies. We thought that ProductHunt may be a good place to find such companies. We also aimed to be in the top 5 of the products launched this day.

Planning the launch

There is quite a lot of information about launching on ProductHunt. We have followed the official blog post.

When launching on ProductHunt you have to take care of 3 things:

1. Decide on the scope of your product and ship it
2. Prepare design and marketing materials for ProductHunt submission
3. Build community and have means of promoting your product submission

While the first two things are pretty straightforward, the last one is not so much so. And here is where we failed big time.

First of all no matter what you launch, if you hope that you simply put your submission out there, and it will end up in the top 5 of the day, most certainly this is not going to happen. If you wanna get there, you have to come up with a plan to promote your listing and get the upvotes.

To be in the top 5 products launched on a given day, you have to have around 500 Upvotes. We found this number by monitoring ProductHunt for a week and documenting the number of Upvotes the most popular products had.

So we had to come up with a plan of building a community, prior to the launch, that will give us a chance of reaching 500 upvotes.

We have a team of three working on Probe. Each of us went through Facebook and LinkedIn and added everyone we felt comfortable asking for feedback and help to one huge spreadsheet. We ended up having around 450 people on this spreadsheet. That gave us a good chance to get to 500 Upvotes and reach our goal.

Two-three weeks prior to the launch we have started to reach out to our community. We ask people to follow my ProductHunt account and give us feedback once our submission goes live.

The day of the launch

Choosing a day to launch on ProductHunt is important. There is a bit of luck involved. If a big company decides to launch on the same day as you, they will collect a huge amount of upvotes and will end up in top products of the day, taking one of the places. But nothing you can do here. You can also choose to launch over the weekend – then the top 5 is formed not from the given day but from the whole weekend.

We have decided to launch it on Monday. Our submission was scheduled to go live at 9 am CET time. Once the listing was up – the first thing we did is to share our listing on social media, and second – we started to reach out to our community. We ask to check out the submission and give us an upvote.

At first, everything was fine. Our submission was visible on the main web page. Somewhere in the middle of the day, we found out that the submission disappeared from the main product hunt page as well as from the search results. It was accessible only via direct link. Something was off.

ProductHunt’s response

After reaching out to ProductHunt support, we found out that their algorithm identified some suspicious activity on our submission and flagged it. That led to its disappearing from the main page and search results. When we tried to clarify why exactly did this happen – we were told that unfortunately the exact reason can not be given because it may expose details of how the product hunt algorithm works. The only thing we were told is that next time we have to be careful with fake comments.

Frankly, it was devastating to put a lot of work into launch preparation and seeing it all go south.

Launch outcome

The bottom line of the launch was that no new trial accounts came via ProductHunt. We have spent about a week putting everything together, from finishing touches on the product scope to reaching out to people and building a community and this outcome really was something we did not expect.

ProductHunt does tell you not to ask for upvotes but to ask for feedback. To be fair, we did ask our community to support us and give an upvote. We felt like these were not random people, but someone who was willing to help, everyone was invited by us, that is why we thought it is OK to do so. Perhaps we were wrong here.

Is ProductHunt worth a try

Thinking about this now, and after speaking to some startups and friends who also launched on ProductHunt I think it was a mistake to have high expectations about the launch event overall.

There is a big difference between launching a product in a business-to-business (b2b) space vs business-to-consumer (b2c). In my opinion, b2c products are a better fit for ProductHunt launch. Due to the fact that potential customer definition in the consumer segment is broader.

I'm not saying that ProductHunt is not worth your time. We broke some rules and it did not work for us. But I still think that it may be a good idea to pursue this path. It can definitely expose your product to potential customers, and you can get valuable feedback.

Do and Dont’s on ProductHunt

If you decide to launch on ProductHunt here is a list of things we would do differently next time:

1. If you decide to build your community – do it earlier. Also, ask your community not only to register on ProductHunt and follow your account but check other products as well.
2. ProductHunt tells that there is no difference between submitting a new product yourself or asking a person with a more mature account to do so. In reality, once the maker submits a new listing – each follower of the account receives a notification. So if you have an opportunity to be launched by a more mature account, with a bigger number of followers, it increases your chances to be in the top 5.
3. Be careful when promoting your posting – to my knowledge everyone I know who performed a successful launch without a huge user base, had a plan for promoting their ProductHunt posting. When building such a plan, try to spread your activities over the course of a full day while your post is active.
4. Don't stop after launching on ProductHunt, look beyond. There are many other platforms you can use to get visibility for your product.

Keep in mind that launch is just one milestone on your journey. We all wish for it to be big and successful. Whatever it turns out to be for you, successful or not, there is more work ahead. Keep going.

by Alex, co-founder of Probe