19/11/2020
Lean Analytics - How to choose a OMTM?The choice of OMTM depends on the startup’s stage of development and business model. It should also be noted that the most fundamental thing about Lean Analytics is to focus on only a few important metrics in a given period of time.
Select OMTM according to stage of development
Select OMTM according to the business model:
According to Alistair Croll and Benjamin Yoskovitz in their Lean Analytics Book, there are 6 main business models which have different revenue generating mechanism and sets of analytical metrics, namely E-commerce, Software-as-a-Service (SaaS), free mobile application, media sites, user-generated content and two-sided marketplaces. In the table below, we analyze the 3 most popular business models in the Vietnamese startup community.
Business model
Revenue
Key metrics
E-commerce
From online sales
CR, CAC, Purchases per year, average shopping cart size, revenue per customer, abandonment, top keywords driving traffic to the site, Top search terms, mailing list click-through rates, shipping time….
Software service form (SaaS)
From a monthly (or yearly)
subscription that users pay
CR, CAC, LTV, attention, enrollment, stickiness, upselling, revenue per customer, churn rate, virality, Uptime and reliability…
Free mobile apps
From downloadable content, advertisements, premium features
CR, CAC, LTV, the number of downloads, launch rate, percentage of active users, percentage of paying users, virality, churn rate, time to first purchase, ...
Metrics Benchmarks
Once we have identified the OMTM, we also need to know about the benchmark for each metric to really understand the meanings behind the metrics and to see if you are doing well and outrunning other competitors in the market. Below are the benchmarks for some common metrics:
Churn rate: if you get your churn rate below 5%—ideally as low as 2%—each month, you have a reasonably sticky product.
Growth Rate: depending on your growth engine (either more users, more revenue, etc.); "A good growth rate at YC is 5-7% a week," said Paul Graham, founder of Y Combinator (YC), America's most famous startup incubator. If it is 10% a week, that is excellent. If you only reach 1%, that's a sign you haven't figured out what you're doing yet. ”
Customer acquisition cost (CAC): CAC should be less than ⅓ CLV (customer lifecycle value). On product pricing, Mr. Neil Davidson, CEO of Red Gate Software, a company providing database management solutions, said: “One of the biggest misconceptions around pricing is that what you charge for your product or service is directly related to how much it costs you to build or run it. That’s not the case. Price is related to what your customers are prepared to pay.”
MVP and the Lean Analytics Process
As illustrated above, lean startup is a process of constant building – measuring – learning. You start by building a MVP (minimum viable product) which aligns with your customers’ needs and for which they are ready to pay. Then the real lean analytics work starts and you will be measuring the impact of this new MVP (A rule of thumb is that, if you current MVP doesn’t increase order size by 30%, try something else). Finally the changes in the metrics will fuel a change in behavior (learning). You may succeed or have to build another MVP. The process will go on and on until you find the most suitable business model for your startup.
So before you launch your MVP, you need to decide on the key metrics you aim to improve and the OMTM with this MVP and the benchmark for success- success criteria. The process will be as follows:
Step 1: Identify hypotheses and prioritize them based on their risk.
Step 2: Build the MVP or any other experiment you defined to be suitable. Could be an A/B test, a campaign, an event, etc. Set up metrics for success and details on how long you plan to run this experiment.
Step 3: Learn from the results. Did your experiment succeed? What did you learn? It’s not just about hitting the success criteria or not, it’s about gaining more knowledge about your user and what they want.
And there you have it! By the end of this article, you have had a lot of information about analytics and metrics that are important for your startup. We hope this article useful to you when making data-driven decision that can drive your startup’s growth.
For part 1 of this article, please visit:
http://startup.gov.vn/Pages/chi-tiet-tin-tuc.aspx?l=Tintucsukien&ItemID=323
The choice of OMTM depends on the startup’s stage of development and business model. It should also be noted that the most fundamental thing about Lean Analytics is to focus on only a few important metrics in a given period of time.
- Select OMTM according to stage of development
- Select OMTM according to the business model:
According to Alistair Croll and Benjamin Yoskovitz in their Lean Analytics Book, there are 6 main business models which have different revenue generating mechanism and sets of analytical metrics, namely E-commerce, Software-as-a-Service (SaaS), free mobile application, media sites, user-generated content and two-sided marketplaces. In the table below, we analyze the 3 most popular business models in the Vietnamese startup community.
| Business model |
Revenue |
Key metrics |
| E-commerce |
From online sales |
CR, CAC, Purchases per year, average shopping cart size, revenue per customer, abandonment, top keywords driving traffic to the site, Top search terms, mailing list click-through rates, shipping time…. |
| Software service form (SaaS) |
From a monthly (or yearly)
subscription that users pay |
CR, CAC, LTV, attention, enrollment, stickiness, upselling, revenue per customer, churn rate, virality, Uptime and reliability… |
| Free mobile apps |
From downloadable content, advertisements, premium features |
CR, CAC, LTV, the number of downloads, launch rate, percentage of active users, percentage of paying users, virality, churn rate, time to first purchase, ... |
Metrics Benchmarks
Once we have identified the OMTM, we also need to know about the benchmark for each metric to really understand the meanings behind the metrics and to see if you are doing well and outrunning other competitors in the market. Below are the benchmarks for some common metrics:
Churn rate: if you get your churn rate below 5%—ideally as low as 2%—each month, you have a reasonably sticky product.
Growth Rate: depending on your growth engine (either more users, more revenue, etc.); "A good growth rate at YC is 5-7% a week," said Paul Graham, founder of Y Combinator (YC), America's most famous startup incubator. If it is 10% a week, that is excellent. If you only reach 1%, that's a sign you haven't figured out what you're doing yet. ”
Customer acquisition cost (CAC): CAC should be less than ⅓ CLV (customer lifecycle value). On product pricing, Mr. Neil Davidson, CEO of Red Gate Software, a company providing database management solutions, said: “One of the biggest misconceptions around pricing is that what you charge for your product or service is directly related to how much it costs you to build or run it. That’s not the case. Price is related to what your customers are prepared to pay.”
MVP and the Lean Analytics Process
As illustrated above, lean startup is a process of constant building – measuring – learning. You start by building a MVP (minimum viable product) which aligns with your customers’ needs and for which they are ready to pay. Then the real lean analytics work starts and you will be measuring the impact of this new MVP (A rule of thumb is that, if you current MVP doesn’t increase order size by 30%, try something else). Finally the changes in the metrics will fuel a change in behavior (learning). You may succeed or have to build another MVP. The process will go on and on until you find the most suitable business model for your startup.
So before you launch your MVP, you need to decide on the key metrics you aim to improve and the OMTM with this MVP and the benchmark for success- success criteria. The process will be as follows:
Step 1: Identify hypotheses and prioritize them based on their risk.
Step 2: Build the MVP or any other experiment you defined to be suitable. Could be an A/B test, a campaign, an event, etc. Set up metrics for success and details on how long you plan to run this experiment.
Step 3: Learn from the results. Did your experiment succeed? What did you learn? It’s not just about hitting the success criteria or not, it’s about gaining more knowledge about your user and what they want.
And there you have it! By the end of this article, you have had a lot of information about analytics and metrics that are important for your startup. We hope this article useful to you when making data-driven decision that can drive your startup’s growth.
For part 1 of this article, please visit:
http://startup.gov.vn/Pages/chi-tiet-tin-tuc.aspx?l=Tintucsukien&ItemID=323