Understanding and reporting on uniques + repeat visitors is important to making better decisions on growth. However, it's important to not grow an unhealthy obsession on these metrics.
Choose whether monthly, weekly or daily metric matters to you.
A metric that does matter that coincides with daily, weekly + monthly windows are repeat visitors/rate of returning visitors. Overlap this with other key factors such as landing page destination + source/medium, and you can learn valuable information for optimisation.
Understanding where your users come from and where they land on your website is crucial. Knowing where they come from helps make better decisions around strategy + investment into channels that acquires more potential users/customers.
I see this view often under-utilised by marketers & founders in startups using Google Analytics. I find this one of the most powerful features of GA and I highly recommend using this more often.
Using behaviour flow you can understand essentially "end-to-end" where users land on your site, to then the other pages or destinations they visit.
I often use this view personally when I run paid campaigns for Google Ads or Facebook Ads. You can understand potential drop-offs and what encourages users to visit other pages. It helps with evaluating audience decisions and campaign optimisations.
In addition, I also use it for understanding blog content and user actions. Which piece of content performs best for conversions or where do they land after reading/landing on the post?
The importance of this metric speaks for itself. Understanding conversion rates helps with optimisation efforts on your website. You should be calculating conversion rates through these conversions;
- Form submissions
- Making a purchase
- Call tracking
- Lead Magnet downloads
- Newsletter signup
+ many other conversion types.
Make sure you're tracking sign up forms, lead magnet and content submissions across the site, especially if you're B2B or your product involves a longer sales-cycle.
Not every website visitor or lead through a form is going to be a "hot lead", so it's important that this metric gets measured and checked reguarly. Normally monthly is fine but weekly if you experience high volume of leads.
Measuring this metric helps with understanding the quality of audiences of traffic that comes to the site or the source/medium of these visitors/leads. This information helps further optimise campaigns for focusing on acquiring quality leads for the business.
Similar to the above, once a lead has come through and done their demo, how many convert then to a trial period of the product? A good way to increase this is run specific remarketing ads to those who have done demos but haven't converted into trials. You can also do then specific ads in the first 1-2 weeks of signing up for their trial.
The above is also good to understand for those who are "no-shows" for their demos.
How effective are your total efforts within product and customer service to turn trial users into paying users? How effective is your onboarding process for new/trial users? What can you do within the product to encourage activation?
All of these are important questions to ask yourself in order to convert more paying users.
Measuring your activation rate ensures you understand how users are interacting with your website or product. It can be measured in a few ways in terms of clicks, downloads, email signups, trial signups + more.
Increasing your activation rate is what leads to better retention. Knowing how users first interaction with your product can lead to long term success.
Activation rate is not something I suggest stressing over too much if you have a user base under 100.
No one likes when users churn but it's inevitable no matter what product you're running. You need to measure churn to understand how many users leave and the cost of those users.
You can calculate churn rate monthly or annually, as well as 'probability' churn rate. Here's the calculations below for your consideration + a great guide below in the orange box.
Not only is the % metric important to understand, but also 'when' and 'why'. Doing a cohort analysis can help you work out why users may churn. Then, it's about optimising areas where churn may happen, including optimisations to the onboarding process, maximise personalisation where it's possible and makes sense, in-app messages/notifications + other strategies. Consider also surveys & NPS scores where it makes sense to try capture more qualitive data through customer feedback.
They may sound similar but these two are opposites when calculating + also taking into consideration for decisions for growth. Below I share a great article that illustrates the difference between the two.
Cohort Analysis helps you analyse how users interact and engage with your product. There are two main types of cohort analysis;
- Acquisition cohorts (website/when they signed up_
- Behavioural cohorts (how they use your product)
Your cohort analysis measurements can include;
- How often do users engage within their first 14 days?
- How often to do they come back?
- When do they churn?
- Which features retain users or frequently used by users?
The article below by Appcues perfectly sums up what are cohort analyses and what you can learn from the data.
Why is this metric important to measure & improve? It's often overlooked especially with companies wanting to expand their volume of users fast, but is that always the best thing to do?
Working out ways to achieve more net revenue from your existing customers through upsells or other methods helps increase LTV of your customer base without the need for acquisition costs.
You can measure active users in two ways;
- New Active Users (Helps understand how new users engage as soon after they sign up)
- Returning Active Users (Helps understand how existing users interact with the product).
How are you currently measuring your customer experience quantitative/qualitative (or both)? NPS scores are great for understand how users are feeling about their experience with your product. You can achieve this with short surveys or even pop-up modals. The key is focusing on segmentation and trigger NPS surveys/pop-ups where they make sense.
When it comes to building a startup financial model, you can't skip measuring one of the most important metrics - your CAC. If you don't measure your CAC effectively, it could seriously come back to haunt you (I've seen i first hand with startups I've worked with). Customer Acquisition Cost (CAC) is not the same as calculating Cost Per Acquisition (CPA). The guide below I shared by Andrew Chen with Brian Balfour explains the difference between the two metrics and highlights use cases with examples including Dropbox, Hubspot + Facebook.
Coming soon :)
Coming soon :)
Coming soon :)
Coming soon :)