Your customers are more brutal than you think. An inspiring talk on how to retain customers and market in the age of analytics. Big Data, Predictive Analysis, and Cloud Applications.

1. Your Customers Are More Brutal
Than You Think
A renewed look at acquiring and retaining customers to
enhance their experience.
© 2013 Alpine Data Labs

2. Lighter Touch
Faster Cycle
Many names, but it’s all the same.
PAST: Cold Calling, Well Positioned
Advertising, and Networking.
PRESENT: Search, Lead Nurturing, and
POCs.
FUTURE: Content, Product, Hook,
Engagement
© 2013 Alpine Data Labs

3. Use Case:
Consumer Security Software
Consumer Security Software
•
10 MM New Unique Visitors
per Month.
•
110 MM Active Users but
Declining.
•
< $1 ARPU
•
23% 30 Day Retention
© 2013 Alpine Data Labs

4. Problem Statement
We have these signals in the data gathered from Marketing, Engineering,
Product, and Sales.
How do we link all of this information together to tell a compelling story and
make a recommendation?
This was only part of the
maze…
© 2013 Alpine Data Labs

5. Enter Analytics. A Definition.
Analytics is the application of computer technology, operational
research, and statistics to solve problems in business and industry.
Historically, Analytics was heavily used in banking for portfolio assessment
using social status, geographical location, net value, and many other factors.
Today, Analytics is applied to a vast number of industries and is re-emerging
due to the phenomenal explosion of data from our connected world.
Big Data consists of data sets that grow so large and complex that they
become awkward to work with using on-hand database management tools
McKinsey Global Institute estimates that big data analysis could save the
American health care system $300 billion per year and the European public
sector €250 billion.
© 2013 Alpine Data Labs

6. Solution: Analytics
1. Agency – Customer feedback analytics. “Garbage in, Garbage
Out.”
2. Enterprise Suite – Index, Customize, Overkill, and Expensive.
3. Application for Hadoop – Excel Programming
4. Hadoop + SQL – Data warehousing on the cheap
A. Hive – Relational Database for Unstructured Data
B. Mahout – Open Source Predictive Library for Hadoop.
© 2013 Alpine Data Labs

7. Our Analytics Architecture
© 2013 Alpine Data Labs

8. What We Found
•
We aligned our acquisition flow over multiple
touch points. From clickstream, content delivery
network, application logs to licensing server.
•
Over 60% of customers who clicked on
Download failed to activate as a user.
© 2013 Alpine Data Labs

9. But wait, there was more…
•
Customers who opted in to our product
improvement program were 2X more likely to
retain.
•
Customers who installed a utilities product were
3X more likely to retain.
•
The best time to up-sell a customer is NOT in the
shopping cart but during the installation.
© 2013 Alpine Data Labs

10. Summary and Conclusions
•
Customers will not wait for you… they are going
to try your product and if it doesn’t work they’ll
never look back.
•
B2B or B2C, it won’t make a difference.
© 2013 Alpine Data Labs