Focus on Analytics

p>HI – happy Friday – Sorry for the late note – but I wanted to just get it out and see what you think. I feel outta sorts – I feel like my current contributions might not be perfectly aligned with what the team needs right now. I think I could be more valuable if I shifted my focus towards our analytics efforts, which is an area I’m really interested in and where I feel I can make a significant impact. Get the next step of that done – then come back with that out of the way – so I can be in with a clear head.

 

Next month, I’ll be taking some time to help my mom. During this period, I’d like to dive deeply into our analytics projects. This focus shift would allow me to develop more robust insights and strategies that will ultimately benefit our overall goals.

 

I’m not disappearing or freaking out – this is something that has been running around my head for a bit. Hitting analytics a handful of nights a month – isnt' getting it done. I will still be in all the meetings – and ready to do whatever needs to be done – I just need a mental (and maybe a small pull back on some projects) shift. Remember last time I took a week and managed to get the sign-up and purchase events working? That was a solid start and really got me immersed in what we can and need to do. Just shifting my mental focus will help me contribute more effectively and align my efforts with the team’s priorities. And once it is setup it can run until we are ready for another upgrade. But it wants time and babysitting!! Some of the analytics work might actually take 3-4 weeks to get up and running with useful reports – even simple stuff like audiences it's a waiting / watching / adjusting game.

 

Thank you for understanding, and I’m looking forward to hearing your thoughts on this proposal.

 

Summary

 

Main Goals

 

NS is not a site with a shopping cart or multiple paths to purchase, we have a user make a single purchase and stay for years! Most systems are notset up that way – or even set up to track users/business like that. . Here’s what we need to do differently and what can be accomplished in a month:

 

Key Challenges and Solutions:

 

1. Tracking Long-Term User Engagement:

Retention Analysis & Churn Prediction: Improve onboarding and continuous engagement to identify early signs of churn and address them.

*CHURN**: churn is the percentage of users who cancel their subscriptions or fail to renew them within a specific timeframe.

We are redoing the join pages / emails etc. – if we could tell which users might be planning to quit (not logging in/ not watching as much and target them?)

 

2. Attribution of Marketing Efforts:

Multi-Touch Attribution: Implement models to understand the impact of different marketing channels on new sign-ups. (not looking at just 1 channel at a time or 1 event – this one is more long term but have to start trying)

3. Data Integration:

Behavioral Tracking: Use Google Tag Manager to track key user actions and integrate this data over time. (video watching / logging in – but have not made the reports)

4. Behavioral Analysis:

Engagement Metrics & Content Consumption: Track user actions and analyze content engagement to understand user behavior better.

5. User Segmentation:

Demographic & Behavioral Segmentation: Segment users by demographics and behavior to tailor marketing and retention strategies. We are hindered being porn and NOT being able to share OUR data. (This is an issue I want to map – what else can't we get)

6. Cohort Analysis:

Initial Cohort Tracking: Start basic cohort analysis to understand user value and behavior changes over time.

 

Basic Plan to Meet Marketing Goals:

 

1. User Journey Mapping:

Entry Points: Analyze where users are coming from.

Behavioral Tracking: Use Google Tag Manager to track actions leading to sign-up.

Funnel Visualization: Visualize the user journey from the first visit to sign-up.

2. Attribution Analysis:

Multi-Touch Attribution: Understand the impact of marketing channels on new sign-ups.

Content Attribution: Identify which content drives conversions.

3. Segmentation and Targeting:

Demographic Segmentation: Understand which groups are more likely to convert.

Behavioral Segmentation: Identify high-intent visitors based on their site behavior.

4. A/B Testing and Optimization: this is not hard – we just need to try it.

Landing Page Testing: Test different designs and CTAs to drive more sign-ups.(changing test on site from: watch now to start watching | change: join button colors / small things like that)

Signup Process Optimization: Experiment with processes to reduce friction and increase conversions.

5. Retention and Engagement Strategies:

Onboarding Experience: Enhance onboarding for new members to increase engagement.

Continuous Engagement: Develop content and features that keep users engaged and reduce churn.

 

Cost-Effectiveness of Retention vs. Acquisition:

 

Retention Strategy:

 

Cost: $4,000 to retain 2% more users.

Revenue: $240,000 over 24 months.

 

Acquisition Strategy:

 

Cost: $20,000 to acquire 2% new users.

Revenue: $240,000 over 24 months.

 

Retention is more cost-effective, with a ratio of 1:5 in favor of retention. Investing in retention efforts can yield significant returns. But we need to be able to see what we actually ahve going on.

 

Conclusion:

 

This plan is basic yet thorough and can be executed within a month. With teamwork and a bit of legwork (especially in getting re-bills into the reporting), we can start seeing meaningful insights and improvements.

 


LONG ASS PROPOSAL

 

Main Goals

NS is not a site that has a shopping cart – multiple ways or paths to purchase – which is what it seems like everying is set up for AND google Ads is out of our reach So what do we need to do that other sites may not? With sign_up and purchase we have dipped out feet into this – but we need to find the parts we want to track and create ways to track them.

 

Key Challenges and Solutions:

 

1. Tracking Long-Term User Engagement:

 

Retention Analysis & Churn Prediction: By improving onboarding and continuous engagement, early signs of churn can be identified and addressed, laying the groundwork for deeper retention analysis.

 

2. Attribution of Marketing Efforts:

 

Multi-Touch Attribution: Implementing multi-touch attribution models and content attribution can be started within a month to understand the impact of different channels on new sign-ups.

 

3. Data Integration:

 

Behavioral Tracking: Using Google Tag Manager to track key user actions provides a basis for integrating behavioral data with other data sources over time.

 

4. Behavioral Analysis:

 

Engagement Metrics & Content Consumption: Tracking user actions and analyzing content engagement can be set up initially to begin understanding user behavior.

 

5. User Segmentation:

 

Demographic & Behavioral Segmentation: Segmenting users based on demographics and behavior can start within a month to tailor marketing and retention strategies.

 

6. Cohort Analysis:

 

Initial Cohort Tracking: Basic cohort analysis can begin to understand user value and behavior changes, forming the basis for more detailed longitudinal studies.

 

7. Measuring Success:

 

Key Performance Indicators (KPIs): Identifying and tracking initial KPIs related to acquisition and retention can be established, setting up for balanced metric tracking.

 

8. Technical Challenges:

 

Data Storage and Processing: Setting up initial data tracking and reporting processes can help identify future scalability needs.

 

9. User Privacy and Compliance:

 

Data Privacy Regulations: Ensuring compliance with data privacy regulations can be integrated into the initial tracking setup.

 

10. Reporting and Visualization:

 

Actionable Insights & Customization: Creating basic reports and dashboards to provide actionable insights for different stakeholders can be started.

 

11. Resource Allocation:

 

Prioritizing Efforts: Using insights from initial data to prioritize efforts for both acquisition and retention can be managed within the first month.

 

So it looks like a long list – but it is all connected – and I feel as though it is connected to what we ALL are looking for:

 

Basic Plan – that should meet marketing goals + help set us up to continuously take in new data that we can use for analysis that makes sense to us.

 

1. User Journey Mapping:

 

Entry Points: Analyze where users are coming from (e.g., referral sites, search engines, social media).

Behavioral Tracking: Use Google Tag Manager to track user actions on key pages leading to sign-up.

Funnel Visualization: Create a visualization of the user journey from the first visit to the sign-up.

 

2. Attribution Analysis:

 

Multi-Touch Attribution: Use multi-touch attribution models to understand the impact of different marketing channels on new sign-ups.

Content Attribution: Identify which content pieces (blogs, videos, landing pages) contribute most to conversions.

 

3. Segmentation and Targeting:

 

Demographic Segmentation: Segment users based on demographics to understand which groups are more likely to convert.

Behavioral Segmentation: Segment users based on their behavior on the site (e.g., pages visited, time spent) to identify high-intent visitors.

 

4. A/B Testing and Optimization:

 

Landing Page Testing: A/B test different landing page designs, copy, and CTAs to see which variations drive more sign-ups.

Signup Process Optimization: Experiment with different sign-up processes to reduce friction and increase conversions.

 

5. Retention and Engagement Strategies:

 

Onboarding Experience: Enhance the onboarding experience for new members to increase early engagement and satisfaction.

Continuous Engagement: Develop content and features that keep users engaged and coming back, reducing churn.

 

 

Our secret weapon – rebills as a major revenue stream.

While I do grasp that tracking new users is very important – I can't help but feel that if we had the whole picture it would also aid our efforts. If we could RETAIN 2% let's say – what would that same effort (to gain 2% more) actually cost us?

The overall ratio that I found seems to be – 1:5 or even 1:7. For every dollar spent on retention efforts, you might need to spend five to seven dollars on acquiring new users.*

We just don't have this now – I"m not saying we STOP our work to get new users – I just want to get the rebilled users into the mix so if there is an easy way to keep them we do.

 

Hypothetical - 

	•	Cost to Acquire a New User (CAC): $100
	•	Cost to Retain an Existing User: $20
	•	Current Monthly Revenue per User: $50
	•	Average User Lifetime: 24 months

Retention Strategy:

	•	Cost to Retain an Extra 2% of Users:
	•	If you have 10,000 users, retaining an extra 2% means keeping an additional 200 users.
	•	Total cost for retention: 200 users * $20 = $4,000
	•	Revenue from Retaining 200 Users:
	•	Monthly Revenue: 200 users * $50 = $10,000
	•	Over 24 months: $10,000 * 24 = $240,000

Acquisition Strategy:

	•	Cost to Acquire 2% New Users:
	•	Acquiring 2% new users = 200 new users
	•	Total cost for acquisition: 200 users * $100 = $20,000
	•	Revenue from Acquiring 200 New Users:
	•	Monthly Revenue: 200 users * $50 = $10,000
	•	Over 24 months: $10,000 * 24 = $240,000

Conclusion:

	•	Cost for Retention: $4,000 to gain $240,000 revenue
	•	Cost for Acquisition: $20,000 to gain $240,000 revenue

In this scenario, retaining 2% more users costs significantly less ($4,000) compared to acquiring 2% new users ($20,000), while generating the same revenue ($240,000). This illustrates a cost-effectiveness ratio of 1:5 in favor of retention.



 

ROUGHLY::

  • Cost of Retention:: 4,000 to gain $240,000
  • Cost of Acquisition: 20,000 to gain $240,000 in revenue.

Which of course we can't know yet – but hopefully with a bit of work we can start to see how that could work for us. – Then we can plan how to keep them – which MIGHT BE EASY –

 

Invest in Retention Efforts:

• Enhance customer support and engagement.

• Personalize user experiences.

• Implement loyalty programs and incentives.

• Regularly gather and act on user feedback.

Measure and Optimize:

• Continuously track retention metrics and customer satisfaction.

• Use A/B testing to find the most effective retention strategies.

 

We discussed getting this working – but I feel like it might take a bit of legwork to sort out the best path and for sure – teamwork to pull it off – but once done – we will have it. (if you could bottle whatever the falcon customers drank and give it to everyone – we would be golden. lol. )

 

Conclusion:

 

This is really a basic but I hope thorough plan – that can be undertaken in a month. All systems go!! Some things that I keep comign back to – We need more audineces – we should be setting up cohorts. The funnels – they exist – how much better can we make them OR are they just a gateway to uisng big data – which Ithink we get us better answers. OR is there something that can assemble these resports for us that is imporessive enought that it seems worth it. Also – A/B testing (like on tubes) – is not difficult – and we should really do it.

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