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CX
DATA
ANALYSIS
DECEMBER, 2019
01
CONTENTS
02 :: Executive Summary
03 :: Methodology
04 :: Member Insights
07 :: Member Growth
08 :: Prospecting Members
10 :: Recommendations
11 :: Areas for Further Study
REPORT OVERVIEW
The current makeup of its membership.
What efforts have historically worked well to attract new
members.
Which products and resources are helping convert followers to
subscribing members.
CX is a membership-based platform for non-profit leaders,
providing support through coaching, online training and digital
resources. The purpose of this report is to help CX grow a healthy
base of subscribed members by discovering:
In the end, we will propose a data-driven strategy for identifying
and converting current followers to increase CX's overall
membership base.
EXECUTIVE
SUMMARY
OBSERVATIONS: WHAT'S WORKING?
Organic Marketing - The most effective CX lead sources are organic, with paid
sources trailing significantly.
Coaching - Current coaches are doing well at maintaining premium clients.
Coach James is particularly effective, with a 2.9% churn rate.
September 2016 initiative - Almost 10% of the current member base first
encountered CX on September 16-17, 2016. This was a noticeably effective push
for attracting future members.
RECOMMENDATIONS: WHAT'S NEXT?
Target Best Prospects - Using current member information, we created a model
for finding the most likely prospects from your current database. Target these
customers directly with future marketing efforts.
Referral Program - Given the effectiveness of organic lead sources, we
recommend creating a referral system which encourages existing members to
recruit others.
Re-visit September 2016 initiative - The strategy used in September 2016 was
uniquely effective at connecting with future members. This initiative should be
explored further and replicated if possible.
Lead with key products - We have determined the five most effective
products/resources to subscription. These products should be platformed in CX
marketing.
02
METHODOLOGY
DATA SOURCES
Records of "A-List" customers who have engaged with CX products. (42,476
records)
Records of currently subscribed members. (492 records)
A table of marketing tag information linking products with "Tag Id" numbers.
The data for this study was provided by CX, containing three datasets:
METHODS
All data cleansing, visualization and modeling was performed in Python coding,
using the Pandas, NumPy, Matplotlib, and scikit-learn libraries for data analysis.
Prospect algorithm was calculated using a Random Forest model.
03
ASSUMPTIONS
Past prospect/member behavior is a reliable predictor of future
prospect/member behavior.
The overall product/membership strategy of CX will remain consistent in the
near future.
The current "A-list" has not been exhaustively tapped for future membership
opportunities.
It is important to note several key assumptions used in this analysis:
MEMBER
INSIGHTS
04
95%US-BASED MEMBERS
MEMBER
DEMOGRPHICS
OBSERVATIONS
The vast majority of members are located in the United States, with a high
concentration in Texas, California, Florida and Georgia. Several members with the
highest "lead score" are concentrated in the Upper Midwest.
LEAD SOURCE
ANALYSIS
[cxwebsite].com
Free Online Resources
[cxwebsite].com blog
ML Web [Staff blog]
Your most effective
lead sources are
100% free:
05
LEAD SOURCE
CATEGORY
ANALYSIS
Paid ads account
for <10% of
current members.
Organic referrals
are most
effective.
COACHING
ANALYSIS
Note James's low attrition rate
and high number of clients.
06
OBSERVATIONS
Internal/unpaid lead sources are most effective at finding prospective members.
Marketing dollars should be focused heavily on these channels, specifically on
website-driven content and products.
Over 25% of all current members first connected with CX through a referral, and
another 25% connected via "Direct" or "Organic" lead sources. This points to an
organic, word-of-mouth member base that could be further encouraged through an
incentivized referral system.
Coaches are doing a good job overall at maintaining their current clients. It would
be helpful to learn more about Coach James's methods, as he maintains the third
highest workload of clients with a churn rate under 3%.
MEMBER
GROWTH
07
OBSERVATIONS
For the most part, membership has grown steadily over the past five years. There
was, however, a significant jump in September, 2016. Between September 16-17,
over 30 future members contacted CX for the first time, This represents
approximately 6% of the total member base.
Given its particular effectiveness, whatever initiative was deployed during this
timeframe should be explored further to learn any strategies that can be repeated
in future marketing strategies.
NOTE: This chart represents the date each member first connected with CX, not the date of their
eventual subscription. The bump at the end of 2019 may be worth exploring, but more time is
needed to see if members who engaged in the timeframe drop off and the rate normalizes over
time.
MEMBER
DEMOGRPHICS
OVER 42,000
1.2%
490 MEMBERS
= 1,000 people
A-LIST MEMBERS
CONVERSION
RATE
PROSPECTING
MEMBERS
08
Explore
Tag Data
Build Machine
Learning Model
Target
Best Prospects
Identify
Best Features
Isolating Tag Ids and lead sources for each
customer/member in the database.
Creating an algorithm to help predict which
customers are most likely to subscribe to a
membership program.
Inspecting the algorithm to find a list of the
products most correlated with membership
subscription.
Creating a "prospect score" for each A-lister, and
identifying customers which have already engaged
with one of these top products.
Currently, CX is converting only 1.2% of its "A-List" customers to subscribed
members. Our goal is to use the current data of members and "A-Listers" to help
prospect and convert new members from the current database. We accomplish
this through a four-step process:.
276
CURRENT
MEMBERSHIP
PROSPECTS 10%
CONVERSION
TO PREMIUM
MEMBERSHIP
MOST
EFFECTIVE
PRODUCTS
09
"7 Topics" (Special Promotion)
"30 Keys" (Purchase)
"What's Your Corporate Culture?" (Download)
"Breaking Boundaries" (Purchase)
"$500k Breakthrough" (Click Through)
The end result of this process is a list of the top five products/resources most
closely correlated with converting an "A-List" customer into a subscribed
member. These products/resources are:
1.
2.
3.
4.
5.
Using this data, we created a "Prospect Score" for each "A-List" customer, noting
those customers who are not current members, but who have already engaged
with one of these top five products. This resulted in a list of 276 prospects for
future membership conversion.
$32K
ANNUAL
REVENUE
GROWTH=
RECOMMENDATIONS
10
Target Best Prospects - Target your current "A-List" customers who have
already engaged with one of your top five products. Based on current data, these
prospects are most likely to explore membership and provide the best return on
marketing investment.
Referral Program - Create an incentivized referral program to help engage
current members in finding new subscribers. Your network is largely organic in
nature, so this strategy would fit well with the current culture and is most likely
to be an effective use of resources.
Re-visit September 2016 initiative - Whatever you did in September 2016 was
incredibly effective at attracting prospective subscribers. If at all possible,
repeat this strategy, or explore the list of members who first contacted you
during this season to find out why they engaged.
Lead with key products - We have determined the five most effective
products/resources for converting "A-listers" to members. Platform these
products front-and-center to your current database.
Standardize Data Hygiene - Data which could help improve your marketing
effectiveness (annual revenue, parent org, staff size, etc.) is either missing or
lacks standardization in the member database. Re-assessing the info captured at
subscription, and potentially gathering information for existing members through
your coaches could result in more precise data for the future.
Based on this information, our recommendations for growing the member base are:
TUNING PROSPECTING ALGORITHM
The algorithm we created using current user data will continue to grow and
change. Tuning this algorithm over time will ensure your list of prospective
members is current and effective.
AREAS FOR
FURTHER STUDY
11
THANK YOU
Growing your business is hard work.
Understanding your data can make it easier.
We have enjoyed partnering with you in this process, and
look forward to helping you thrive in the days ahead.
*Alan E. Webber, "B2B Customer Experience Priorities In An Economic Downturn," Forrester Research, February 19, 2008
COMBINING SALES DATA
Merging this information with sales/purchase data would help determine the
effectiveness of subscriptions as a revenue stream vs. purchased products and
other sources. This could help provide more robust recommendations for
revenue growth.
CHURN PREDICTION
Preventing membership churn is 5-6 times less costly than prospecting a new
subscriber.* Obtaining data on members who have canceled their subscription
would allow us to create a churn prediction model. This would enable you to
identify those members most likely to cancel their subscription and engage
proactively to help prevent cancellation, significantly decreasing your overhead
cost per paying subscriber.

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CX Data Analysis Highlights Key Membership Insights

  • 2. 01 CONTENTS 02 :: Executive Summary 03 :: Methodology 04 :: Member Insights 07 :: Member Growth 08 :: Prospecting Members 10 :: Recommendations 11 :: Areas for Further Study REPORT OVERVIEW The current makeup of its membership. What efforts have historically worked well to attract new members. Which products and resources are helping convert followers to subscribing members. CX is a membership-based platform for non-profit leaders, providing support through coaching, online training and digital resources. The purpose of this report is to help CX grow a healthy base of subscribed members by discovering: In the end, we will propose a data-driven strategy for identifying and converting current followers to increase CX's overall membership base.
  • 3. EXECUTIVE SUMMARY OBSERVATIONS: WHAT'S WORKING? Organic Marketing - The most effective CX lead sources are organic, with paid sources trailing significantly. Coaching - Current coaches are doing well at maintaining premium clients. Coach James is particularly effective, with a 2.9% churn rate. September 2016 initiative - Almost 10% of the current member base first encountered CX on September 16-17, 2016. This was a noticeably effective push for attracting future members. RECOMMENDATIONS: WHAT'S NEXT? Target Best Prospects - Using current member information, we created a model for finding the most likely prospects from your current database. Target these customers directly with future marketing efforts. Referral Program - Given the effectiveness of organic lead sources, we recommend creating a referral system which encourages existing members to recruit others. Re-visit September 2016 initiative - The strategy used in September 2016 was uniquely effective at connecting with future members. This initiative should be explored further and replicated if possible. Lead with key products - We have determined the five most effective products/resources to subscription. These products should be platformed in CX marketing. 02
  • 4. METHODOLOGY DATA SOURCES Records of "A-List" customers who have engaged with CX products. (42,476 records) Records of currently subscribed members. (492 records) A table of marketing tag information linking products with "Tag Id" numbers. The data for this study was provided by CX, containing three datasets: METHODS All data cleansing, visualization and modeling was performed in Python coding, using the Pandas, NumPy, Matplotlib, and scikit-learn libraries for data analysis. Prospect algorithm was calculated using a Random Forest model. 03 ASSUMPTIONS Past prospect/member behavior is a reliable predictor of future prospect/member behavior. The overall product/membership strategy of CX will remain consistent in the near future. The current "A-list" has not been exhaustively tapped for future membership opportunities. It is important to note several key assumptions used in this analysis:
  • 5. MEMBER INSIGHTS 04 95%US-BASED MEMBERS MEMBER DEMOGRPHICS OBSERVATIONS The vast majority of members are located in the United States, with a high concentration in Texas, California, Florida and Georgia. Several members with the highest "lead score" are concentrated in the Upper Midwest.
  • 6. LEAD SOURCE ANALYSIS [cxwebsite].com Free Online Resources [cxwebsite].com blog ML Web [Staff blog] Your most effective lead sources are 100% free: 05 LEAD SOURCE CATEGORY ANALYSIS Paid ads account for <10% of current members. Organic referrals are most effective.
  • 7. COACHING ANALYSIS Note James's low attrition rate and high number of clients. 06 OBSERVATIONS Internal/unpaid lead sources are most effective at finding prospective members. Marketing dollars should be focused heavily on these channels, specifically on website-driven content and products. Over 25% of all current members first connected with CX through a referral, and another 25% connected via "Direct" or "Organic" lead sources. This points to an organic, word-of-mouth member base that could be further encouraged through an incentivized referral system. Coaches are doing a good job overall at maintaining their current clients. It would be helpful to learn more about Coach James's methods, as he maintains the third highest workload of clients with a churn rate under 3%.
  • 8. MEMBER GROWTH 07 OBSERVATIONS For the most part, membership has grown steadily over the past five years. There was, however, a significant jump in September, 2016. Between September 16-17, over 30 future members contacted CX for the first time, This represents approximately 6% of the total member base. Given its particular effectiveness, whatever initiative was deployed during this timeframe should be explored further to learn any strategies that can be repeated in future marketing strategies. NOTE: This chart represents the date each member first connected with CX, not the date of their eventual subscription. The bump at the end of 2019 may be worth exploring, but more time is needed to see if members who engaged in the timeframe drop off and the rate normalizes over time. MEMBER DEMOGRPHICS
  • 9. OVER 42,000 1.2% 490 MEMBERS = 1,000 people A-LIST MEMBERS CONVERSION RATE PROSPECTING MEMBERS 08 Explore Tag Data Build Machine Learning Model Target Best Prospects Identify Best Features Isolating Tag Ids and lead sources for each customer/member in the database. Creating an algorithm to help predict which customers are most likely to subscribe to a membership program. Inspecting the algorithm to find a list of the products most correlated with membership subscription. Creating a "prospect score" for each A-lister, and identifying customers which have already engaged with one of these top products. Currently, CX is converting only 1.2% of its "A-List" customers to subscribed members. Our goal is to use the current data of members and "A-Listers" to help prospect and convert new members from the current database. We accomplish this through a four-step process:.
  • 10. 276 CURRENT MEMBERSHIP PROSPECTS 10% CONVERSION TO PREMIUM MEMBERSHIP MOST EFFECTIVE PRODUCTS 09 "7 Topics" (Special Promotion) "30 Keys" (Purchase) "What's Your Corporate Culture?" (Download) "Breaking Boundaries" (Purchase) "$500k Breakthrough" (Click Through) The end result of this process is a list of the top five products/resources most closely correlated with converting an "A-List" customer into a subscribed member. These products/resources are: 1. 2. 3. 4. 5. Using this data, we created a "Prospect Score" for each "A-List" customer, noting those customers who are not current members, but who have already engaged with one of these top five products. This resulted in a list of 276 prospects for future membership conversion. $32K ANNUAL REVENUE GROWTH=
  • 11. RECOMMENDATIONS 10 Target Best Prospects - Target your current "A-List" customers who have already engaged with one of your top five products. Based on current data, these prospects are most likely to explore membership and provide the best return on marketing investment. Referral Program - Create an incentivized referral program to help engage current members in finding new subscribers. Your network is largely organic in nature, so this strategy would fit well with the current culture and is most likely to be an effective use of resources. Re-visit September 2016 initiative - Whatever you did in September 2016 was incredibly effective at attracting prospective subscribers. If at all possible, repeat this strategy, or explore the list of members who first contacted you during this season to find out why they engaged. Lead with key products - We have determined the five most effective products/resources for converting "A-listers" to members. Platform these products front-and-center to your current database. Standardize Data Hygiene - Data which could help improve your marketing effectiveness (annual revenue, parent org, staff size, etc.) is either missing or lacks standardization in the member database. Re-assessing the info captured at subscription, and potentially gathering information for existing members through your coaches could result in more precise data for the future. Based on this information, our recommendations for growing the member base are:
  • 12. TUNING PROSPECTING ALGORITHM The algorithm we created using current user data will continue to grow and change. Tuning this algorithm over time will ensure your list of prospective members is current and effective. AREAS FOR FURTHER STUDY 11 THANK YOU Growing your business is hard work. Understanding your data can make it easier. We have enjoyed partnering with you in this process, and look forward to helping you thrive in the days ahead. *Alan E. Webber, "B2B Customer Experience Priorities In An Economic Downturn," Forrester Research, February 19, 2008 COMBINING SALES DATA Merging this information with sales/purchase data would help determine the effectiveness of subscriptions as a revenue stream vs. purchased products and other sources. This could help provide more robust recommendations for revenue growth. CHURN PREDICTION Preventing membership churn is 5-6 times less costly than prospecting a new subscriber.* Obtaining data on members who have canceled their subscription would allow us to create a churn prediction model. This would enable you to identify those members most likely to cancel their subscription and engage proactively to help prevent cancellation, significantly decreasing your overhead cost per paying subscriber.