This is the AARRR (Must Read!) startup metrics model developed by Dave Mcclure. These 5 metrics represent all of the behaviors of our customers.
We want to break down these 5 metrics on your product and look at them separately, then analyze and monitor them so that we can optimize them. A successful startup is one where they are able to optimize every single one of these 5 metrics.
It's important to understand about AARRR, because only when you understand all the metrics, you will understand where exactly is wrong with your startup, so you don't guess and make the wrong assumptions. When you understand AARRR, you can become a startup doctor, because you will know exactly what or which part is wrong, and then fix it.
For example, a Chinese restaurant owner opens his restaurant in San Jose. After 3 months his business is still quite poor, so he simply blames that people in San Jose don't like to eat Chinese food (impossible!).
The truth is that many startups make the same mistake of thinking if something doesn't work, it must be everything, or they just guess the wrong reason why their business is not working. Like any website or app, a restaurant relies on many things to be optimized. It needs to have a good location. The storefront needs to look good so customers want to go in. When users are in, customers need to feel comfortable with the interior, and they need to be sold on the content in the menu. Moreover, when they go through the menu, they need to feel comfortable with the price point. Also, the user will obviously rate their experience in terms of the service, the taste of the food, etc.
So, while 1 restaurant owner will conclude that people don't like Chinese food. Another store owner that knows AARRR-fu will find out maybe it's because his storefront doesn't look interesting enough, his price point is too high, or what not.
The truth is, any part of a customer's experience and its details from walking pass the storefont, to going inside, finding a seat, ordering, eating, paying, and leaving the restaurant, are all very crucial to the restaurant's business.
Case Study: Michelin 1 star restaurant chain called Ding Tai Fong focuses on every part of the detail. They optimize everything. They are so detailed that when you are paying for the bill, the cash change they give back to you is always new so that you don't get your hands dirty. So they have someone who goes to the bank every morning to get brand new cash to start the day off. It's something as subtle as this, but this way, people love their whole experience from beginning to end and come back again or tell their friends.
Website Case Study: StartitUp is getting 1000 visitors/month (Acquisition), and our Activation (conversion) is 70%, so that we are getting around 700 users/month. Out of those 700 users, only 20% of those users are coming back after their first visit (Retention). Out of those 20% (140 users), only 10% are paying (Revenue), so that we end up with 14 users paying each month. Out of the 700 users, about 10% of those are referring out service to their friends (Referral).
When we look at the example above, we can separate each behavior and try to optimize each separately.
1. StartitUp has a good Activation (conversion) rate of 70%, which means we are dealing with a real problem and we have a real solution, and we also have a convincing landing page.
2. We want to get more signups, so we look to improve our Acquisition (visitors) by adding more acquisition channels or work on SEO to try to get more users.
3. We then look at our Retention, and saw that our Retention is pretty horrible at 20%, so we build some extra features like email newsletters and gamification to get users to come back so that we have another chance to monetize them. But we realize users are not coming back to our service because our service somehow isn't delivering the value promise we made - it doesn't solve their problem or it's not clear how to use our service. We also create a better tutorial feature to help users get started with the guide so they can properly reap the benefits from StartitUp.
4. We also see that we are not doing a very good job converting users into paying customers (Revenue), so we look at our price structure and our pricing page to see if we are not doing a good job communicating, or if we can build a stronger pricing plan with the main pricing plan that we want people to buy highlighted.
5. Finally, we check to see why we are not being recommdned (Referral) to friends and see if we can put in some social sharing features to increase the number of referrals. This could also be that our service doesn't have any referral value since it's not good enough.
However, for a startup, we don't need to focus on all of the 5 metrics during the MVP (Minimum Viable Product) phase. The 2 most important metrics we want to monitor and optimize right now are Activation and Retention (Retention is King! - If people like using your product and they return to use it, then you will be successful).
These are the 2 main metrics that will determine whether or not you have built a service that people need. A good Activation tells you that your UVP and landing page is convincing and that you successfully get the user to go through with 1 use cycle post logging in. Good Retention tells you that your MVP actually delivers the UVP to the customers.
If you plan to start charging immediately, then Revenue will be one that we want to monitor as well. Acquisition and Referral are not immediate, but they are the engines to drive new customers to your website, so do keep them in mind when building your MVP.
Important: Before you can get good Activation and Retention, which means that you have proven that your product does indeed delivers the UVP, there is no need to start getting users. The reason is because before you are sure that you have a working solution, the users you get now will leave anyways. You will be depleting your users, and it might also give you bad reviews. Therefore, before we can validate your MVP in a later section, only focus on getting "early adopters" and leave the Growth Hacking for later.
See Dave Mcclure's AARRR to learn more: http://www.slideshare.net/dmc500hats/startup-metrics-for-pirates-long-version
A great read to learn about Lean Analytics: http://www.kaushik.net/avinash/lean-analytics-cycle-metrics-hypothesis-experiment-act/
Great Tools to build engagement/gamification: