Mike Mason

Mike heads up metric driven growth at MercuryGrove. He specializes in marketing strategies for early stage high growth internet companies.

SaaS Metrics: The Ultimate Guide to Building a Business

This post is a recap from a how-to created by Mark MacLeod . I feature some of the most impressive startup strategies we encounter at StartupPlays and share them free, here at Startupnorth.ca. Enjoy.

This guide is available in an interactive how to format Free at StartupPlays.com – Get it here

The number one focus of Mark’s investment and advisory work is SaaS companies. There are lots of reasons to focus on this segment. For one, it’s large ($21B and growing at 20% per year). In addition, it lends itself well to (metrics) and is great for investors because of the visibility and predictability that the best SaaS businesses generate.

The SaaS Terminology Cheat Sheet:

AARRR: A pirate war cry or more importantly, an acronym coined by Dave McClure to summarize the flow of SaaS users from first activation to monetization and referral.

Activation: The first time someone uses your service.

Acquisition: A new user sign up. This does not necessarily mean a paid customer. It means a new user on a free trial or permanently free version. If you don’t have a free trial or free product and the only way for someone to use your product is to pay then acquisition for you is a new paid customer. In this series “user” will refer to people that don’t pay and “customers” will be people that do pay.

ARPU: Average Revenue Per User: Total revenue / # of paying customers.

CAC: Customer Acquisition Cost. Total costs of customer acquisition / # of new customers acquired. This should be calculated both for gross new customers and net new. Net new is net of customers that you lost in the period.

Churn: The % of users / customers that abandon the service over time. This can be measured weekly, monthly, quarterly, etc. You will want to measure churn for users and churn for customers (assuming you have a free trial or freemium product).

  • Customer churn: % of paying customers that cancel their subscription.
  • User churn: % of free users that stop using the service.

CLTV: Customer Lifetime Value. The expected total revenue from a customer over their lifetime less the cost of generating that revenue less the cost to acquire that customer.

Cohort: Also called cohort analysis or class analysis. A cohort is a group of users that are grouped together based on a common attribute. That could be the month they signed up, the source through which you acquired them, the method in which they use your service (web vs. mobile vs. desktop app), etc. Say, you’re looking at cohorts based on month of sign up. You can then look at usage and monetization patterns for those users over time. For example all users signing up in January are a cohort. You can then look at the % of them that use, subscribe for, churn out, cancel their account etc. in February, March, April, etc.

Conversion: Every time a user moves forward a step in your funnel from visitor (just visiting your web site) to user (signed up) to customer (paying you money) to referrer (helping bring you new users).

  • UV conversion: % of new unique visitors that become users.
  • Active conversion: % of users that use the service for the 1st time.
  • Paid conversion: % of free users that upgrade to a paid account.

Engagement metrics: These are softer metrics that are specific to your application that don’t measure core conversion but measure specific feature uses and overall engagement with your service. Examples include # of likes, session length, # of comments, # of connections, etc.

Freemium: A goto market strategy where you have a permanently free base version of your service. This, hopefully, replaces the need for a big marketing budget and reduces friction for user sign up enabling you to acquire lots of users. From that large user base you convert a small portion to a paid premium version. There are other freemium scenarios such as free content monetized by ads but in SaaS this is the primary meaning for freemium.

K Factor: Also known as “viral co-efficient“. For every active user how many new users do they bring on. If your K factor is > 1 then your user base grows virally or exponentially. This applies well for social games and freemium services that have a built in viral aspect that introduces the game or service to new potential users.

Retention: Subsequent usage of your service. Any usage after the initial (activation use). As you will learn, retention is the most important aspect of a successful SaaS business.

Retention rate: The % of users that continue using the service over time. This can be measured weekly, monthly, quarterly, etc.

Tenure: The # of months or years that you keep a paid customer. Calculated as 1 / churn rate.

Upgrade %: The % of customers that upgrade from you basic plan to a higher plan.

The Business Model

Business model viability, in the majority of startups, will come down to balancing two variables:

  1. Cost to Acquire Customers (CAC), and,
  2. Lifetime Value of a Customer (LTV)

Successful web businesses have long understood these metrics as they have such an easy way to measure them. However there is a lot of value in looking at these same metrics for all other businesses, especially in the SaaS model.

Image source: http://www.forentrepreneurs.com/startup-killer/

Calculating Customer Acquisition Cost – To compute the cost to acquire a customer (CAC) you would take your entire cost of sales and marketing over a given period, including salaries and other headcount related expenses, and divide it by the number of customers that you acquired in that period. Use the “Cost To Acquire” sheet of the workbook to help calculate this.

Calculating Lifetime Value – To compute the Lifetime Value of a Customer, LTV, you would look at the Gross Margin that you would expect to make from that customer over the lifetime of your relationship. Gross Margin should take into consideration any support, installation, and servicing costs. Use the “Lifetime Value” sheet of the workbook to help calculate this. SaaS businesses are usually initially very high cash intensive businesses because you pay upfront to acquire a customer and the customer only becomes profitable over time. So, you have a gap in cash flow. You can grow organically by saving up enough margins from your existing customers to acquire more, but this is slow. If you want to dominate your market, you need outside capital to maximize the pace of growth (more on this later). At the seed and series A stages, I recommend startups spend no more than 6 months of revenue to acquire a customer. This is because i.) cash tends to be tight; and ii.) the startup does not have enough cohort data to know for sure how many months customers stay on average. Later, when you have more data and more cash you can be more aggressive and spend more. It’s important to do this calculation both for your overall customer base and by price plan. You will likely find your higher price customers stick around a lot longer.

Tipping the Balance – Tactics for Optimizing your Model

If you are building a data driven company then i.) your entire team should have daily access to key stats (just put up Geckoboard on a big monitor and connect everything to it); and ii.) each team member should own a metric.

Brainstorm – with your team – 5 ideas/strategies around the two key elements (Monetization and CAC) with help from the examples given. Calculate Your Monthly Recurring Revenue (MRR) And Average Revenue Per User (ARPU) – Monthly Recurring Revenue (MRR) is calculated by multiplying the total number of paying customers by the Average Revenue Per User (ARPU). This is usually a key indicator of profitability. Use the “Monthly Reoccurring Revenue” sheet of the workbook to help calculate this.

Look at your CAC ratio monthly: this is the new Monthly Recurring Revenue (MRR) you added in the month * gross margin / the customer acquisition costs incurred that month. You can read more about this important ratio here.

This and more is available in a step-by-step interactive format at StartupPlays.com

Creating a Referral Engine for Your Startup

This post is recap on some of the highlights from a how-to created by Ilya Lichtenstein of mixrank.com. I feature some of the most impressive startup strategies we encounter at StartupPlays and share them free, here at StartupNorth.ca. Enjoy.

We recently did some work with a brilliant young guy named Ilya Lichtenstein from Mixrank.com, a company which has seen early investments from 500 Startups, Y-Combinator, and Mark Cuban. While in college Ilya was working side jobs with startups and getting deep into the affiliate marketing world. He grew a $300 investment into six figure revenue numbers in his first year. He has applied the behaviours and characteristics of major affiliate programs and adapted them to  smaller scale customer referral programs for startups, this is his “best practice manual for building a customer referral program”:

Major Affiliate Programs

Websites like Amazon and Netflix have elaborate affiliate networks anyone can join and receive an affiliated commission from a signup or purchase on their websites. This works because these companies have determined some of their most important baseline metrics, things like:

  • Cost per acquisition of a customer
  • Lifetime value of a customer
  • On page conversion rate
  • Variants between traffic sources
  • Cost of buying traffic within the industry
They use these metrics to determine what affiliate commissions they can set for the business to turn the channel into a profitable one. If affiliates can purchase traffic at a cheaper price than the payout (typically between $0.50-$4.00 per click) then the program is sustainable. You’ll need to determine what these numbers are for your startup, even if you ball park it, here is an excel template that will help you do it.

How Building your Referral Engine is Different

A customer referral engine is a lot like an affiliate program only scaled down and involves much higher participant engagement. Building a referral program is not for the light of heart but has massive payouts for everyone involved. When creating a referral engine you won’t want to label participants “Affiliates”, but instead something like “Partners”. Your “Partners” will be composed of two segments:

  1. Existing Users
  2. Content Producers within your Niche

Existing users are easy advocates since they’re already familiar with your brand and understand your offering. Incentivizing them to tell others what they may already be telling people is a win-win.

Content Producers within your niche have clout and often an engaged audience on the web, they may even be looking to monetize their content and this provides them with a non traditional medium that has higher revenue potential and that sucks a lot less than one site ads.

Compensating your Partners

As an early stage startup your base metrics probably wont warrant a direct flat fee compensation for a new lead, you’ll be compensating partners in your referral program based on a percentage of or flat fee per paid conversion. Be careful to avoid revenue share in perpetuity, this may hurt you down the road when approaching investors. Major Affiliate programs will payout anywhere from  $30-$40 for a credit card submit on their site (this is what you’re aiming for). If you have the ability to set up coupon codes on your website, give your partners a custom coupon code, this instantly creates a value add for their audience and makes it easier for them to share with people they know. (People LOVE sharing deals)

  1. You’re an e-commerce vendor: Give partners a commission on each sale they drive.
  2. You’re a SaaS vendor: Give partners straight cash per transaction, if your offering is tiered your affiliate commission can be as well.

When you setup an affiliate program you are effectively sharing the risk and the reward.

If your sales funnel is: visit page -> email submit -> purchase

You can compensate affiliates for either the page visit, the email submit, or the purchase. You will need to compensate the affiliate more for actions that are further into the funnel, as you are placing the risk on the affiliate to convert the user. If you compensate them at the start of the funnel, you can pay them less and the risk is on your side to convert them.

You will need to determine the right risk / reward ratio to determine which action will be most profitable – and attractive – for both you and the affiliate.

Tracking Referrals

You need to use a third party to track referrals, this guarantees no foul play on your side ands building confidence in your program into your program. It also helps limit fraudulent activity, you can review partners as they apply, and send payouts once customer payment has been confirmed on your end.

Here are some third party services you can use to set up a program like this:

  1. Zferral – I prefer Zferral to others because of its ease of use, and support. If you’re having issues with setting up you can use their support centre to screencast your issue and have it resolved within a few hours.
  2. HasOffers – Custom referral programs, easy setup.
  3. LinkTrust – This is a costly alternative, but is the undisputed gold standard within the industry.

White Glove the Entire Program

Send your partners a monthly recap, keep them updated on how other partners are doing, and how the program is a smashing success! It will keep them involved and give them a benchmark for how well they can do, and how much money they can make by being part of your program.

The customer referral engine is a win-win channel for driving online sales generally untouched by most early stage startups. If you have a startup that could benefit from a referral program, talk to us in the comments!

photo credit – armando cuéllar