Customers come and customers go. What if you could know before they go? Account Based Marketing (ABM) isn't enough. ABM needs to be paired with a data-sharing architecture and predictive analytics to prevent customers from churning (leaving).
1. Scoring Customer
Churn Risk
A Customer Use Case
An overview
Israel Kloss
Findable Consulting
@risraelkloss
Israel@findable.me
2. *A.k.a. “The Godfather of Web Analytics”
Jim Sterne* is
concerned!
He has a client
with a big
challenge.
3. Jim’s Task:
Help Build a Strategy Measuring:
●Customer acquisition
●Customer lifecycle
● Customer churn prevention
4. DATA SILOS!
● Marketing Data Problems
● Engineering Data Problems
● Finance Data Problems
Jim digs in and his alarm
bells start going off…
department by
department:
5. Jim's client has:
Let’s Dive in!
Customer Churn Prevention
1. A technical problem
2. A data sharing problem
7. Customers are telling you
their intentions.
Let’s look at some.
Customer Churn Prevention
8. We collected a set
of data on
CUSTOMERS
WHO LEFT
the Company.
Step 1: Data Clarity, Collection & Cleaning
9. Step 2:
Using that data set of churning customer behaviors,
we CALCULATE A PROBABILITY MODEL
to monitor customer’s behaviors.
Calculation
(client references hidden)
10. But R is a bit beyond the
scope of this webinar.
Here’s a
peek at how
the “Flight
Risk” Scores
(Churn Risk)
can be
generated
12. Data Sharing is Data Caring!
Using internal customer data and
APIs, we connected multiple systems across
departments.
Ahhh… DASHBOARDING Happiness!
Step 3: Data Sharing
Go Cross-Departmental
I Data
Stitching
13.
14. Data Sharing
Continued
After a customer
completes some
behavior related to
churn, APIs are set to
trigger unique alerts
to each appropriate
department.
15. We started
DASHBOARDING CHURN INDICATORS across
multiple departments. Starting with the CUSTOMER SERVICE TICKETING
SYSTEM
(client name hidden)
Churn Risk Dashboard
Step 4: Dashboarding!
24. Feel free to contact me with
any questions:
israel@findable.me
http://bit.ly/DAA_webinar
You can download
this deck at
Editor's Notes
Marketing is buying a Marketing Automation tool. But they bought the Marketing Automation tool with the API that nobody knows how to harness. That’s a Marketing data problem.
Engineering is all excited about their latest software upgrade. But Customer Service can’t see the customer’s login records, and they don’t know what the customer experience or history has been when they get a complaint. That’s an Engineering data problem.
Finance just bought a new billing & renewals system but didn’t tell anybody what they were buying. And nobody verified that it will work with the Marketing Automation API or with the Customer Service Ticketing System API or Engineering’s customer system (unpaid customers need payment reminders). That’s a Finance data problem.
I'm going to dive a bit into the technical issue and offer a customer churn solution and then take a data stitching approach to tackle the data sharing problem
Because we connected the Marketing Automation system to the CRM, we are now ready to do full analysis of the customer acquisition. And with a customer data warehouse also connected to the CRM, there there is also the opportunity to marry the customer churn data with the customer acquisition data -- giving a view into the full customer lifecycle.
