In-app messaging. Email sends. Content creation. There are so many things that we do to promote different features of our product. But after awhile, users tend to tune them out especially if they are not relevant. It can be challenging if not impossible to figure out how to re-engage your customers especially when you have a new product that would benefit them. Using usage data from SQL or MixPanel, you can cater your messaging toward the segment of customers who are a great fit for your latest product release or your latest product marketing campaign. In this session we will walk through how to do this through developing a hypothesize, pulling usage data in SQL, and running a campaign based on this data. About Rachel Sprung Rachel Sprung is a Product Marketing Manager at HubSpot specializing in Reporting and Analytics. Rachel loves using SQL, Mixpanel, and all things data to make usage-driven decisions. This transcends through her work developing product positioning, launching product campaigns, and creating content. It's this data-driven approach that earned Rachel the 2014 Excellence in Innovation Award at HubSpot. Previously, she managed internal and external events including HubSpot's annual INBOUND conference. Whether you want to chat data, product, or puppies, you can find her on Twitter @RSprung.

1. HOW TO LEVERAGE USAGE
DATA TO DRIVE
PRODUCT MESSAGING
AND ADOPTION.
Rachel Sprung | Product Marketing Manager

2. I learned how to use Excel
from my dad’s football pool
when I was 10.
@RSprung
RACHEL
SPRUNG

3. 1 Introduction
2 Understanding Your Usage Data
3 Pulling Usage Data Using SQL
4 Running Campaigns
5 Conclusion
AGENDA

6. WHERE DO YOU START?

7. RESEARCH INTO YOUR
USAGE DATA.1

9. How many customers are using
different parts of my product?

10. Are there certain
points in the product
where a customer
stops using the
product?

11. How much money are they
paying me for the product?

12. Did a customer
test my product in
the trial process?

13. How long has the
customer used my
product or service?

14. CREATE A
HYPOTHESIS.2

15. How do you plan for an
upcoming product launch?

16. FIND THE CUSTOMERS
WHO ARE THE PERFECT
PRODUCT FIT.

17. GATEWAY PRODUCTS.
Coffee
Sample
Venti Soy
Lattee

18. GATEWAY PRODUCTS.
Free
Mobile App
Paid
Mobile App

19. GATEWAY PRODUCTS.

20. COMPLIMENTARY APPS.

21. CONTENT INDICATORS.

23. 3PULL YOUR
USAGE DATA.

24. WHAT IS SQL?
SQL = Structured Query Language
• SQL is the vehicle that pulls data out of the
server in a way that we can analyze it.
• SQL has no visualization capacity, but it can
output data

25. COMMON TERMS.
QUERY TABLEDATABASE

26. Who are the people who have
red hair in Massachusetts and
were born in 2003 organized
in alphabetical order?

27. Who are the people who have
red hair in Massachusetts and
were born in 2003 organized
in alphabetical order?

28. • SHOW DATABASES;
• SHOW TABLES in NewEngland;
• Describe people_massachusetts;
UNDERSTAND THE HIERARCHY OF YOUR DATABASE.

29. SELECT statements choose
the fields that you want
displayed in your chart
SELECT.
EXAMPLE QUERY:
SELECT
first_name,
last_name

30. * tells the query that you want
to include all of the columns
of data in your results.
*.
EXAMPLE QUERY:
SELECT
*

31. FROM pinpoints the table that
you want to pull the data from.
Tables:
people_connecticut
people_maine
people_massachusetts
people_newhampshire
people_rhodeisland
people_vermont
FROM.
EXAMPLE QUERY:
SELECT
first_name,
last_name
FROM
people_massachusetts

32. WHERE begins your filter.
Start with any of the fields,
and write what you want to
see.
WHERE.
EXAMPLE QUERY:
SELECT
first_name,
last_name
FROM
people_massachusetts
WHERE
hair_color = “red”

33. AND adds additional criteria.
AND.
EXAMPLE QUERY:
SELECT
first_name,
last_name
FROM
people_massachusetts
WHERE
hair_color = “red”
AND
birth_date BETWEEN ‘2003-01-01’ AND
‘2003-12-31’

34. ORDER BY sorts the fields.
ORDER BY.
EXAMPLE QUERY:
SELECT
first_name,
last_name
FROM
people_massachusetts
WHERE
hair_color = “red”
AND
birth_date BETWEEN ‘2003-01-01’ AND
‘2003-12-31’
ORDER BY
last_name
;

35. GROUP BY aggregates data
that has similarities.
GROUP BY.
EXAMPLE QUERY:
SELECT
first_name,
last_name
FROM
people_massachusetts
WHERE
hair_color = “red”
AND
birth_date BETWEEN ‘2003-01-01’ AND
‘2003-12-31’
GROUP BY
last_name
;

36. TABLE:
ORDER BY VS. GROUP BY.
ORDER BY:
GROUP BY:
ID Name
1 Peter
2 John
3 Greg
4 Peter
ID Name
3 Greg
2 John
1 Peter
4 Peter
# Name
1 Greg
1 John
2 Peter

37. LIMIT is a good way to test
queries by limiting the results
you will get from the query.
LIMIT.
EXAMPLE QUERY:
SELECT
first_name,
last_name
FROM
people_massachusetts
WHERE
hair_color = “red”
AND
birth_date BETWEEN ‘2003-01-01’ AND
‘2003-12-31’
GROUP BY
last_name
LIMIT
100
;

38. YOU DID IT!
http://bit.ly/SQLbootcamp
http://bit.ly/introtosql

39. 4 RUN CAMPAIGNS
BASED ON USAGE DATA.

40. SEND A PERSONALIZED EMAIL.

41. FIND THE CUSTOMER’S POINT-OF-CONTACT.

42. SHOW THE PRODUCT’S VALUE.

43. NOTIFY CUSTOMERS AT THE RIGHT TIME.

44. 5 MAKE ADJUSTMENTS.

46. WERE SOME CUSTOMERS
USING THE PRODUCT INITIALLY
BUT THEN STOPPED?

47. WHAT GROUP OF PEOPLE
ARE USING THE PRODUCT
THE MOST?

48. IN THE MONTHS
FOLLOWING THE
LAUNCH DID
USAGE INCREASE
OR DECREASE?

49. ARE THERE
SEASONAL
FACTORS IN
YOUR
PRODUCT
USAGE?

50. 6 COMBINE DATA.

52. CUSTOMER CLICKED ON A LINK IN YOUR EMAIL.

53. CUSTOMER USES SOCIAL MEDIA APP AND
DOWNLOADS SOCIAL MEDIA CONTENT.

54. CUSTOMERS FROM ONE INDUSTRY USES THE
PRODUCT MORE THAN OTHERS.

55. 7 RINSE AND REPEAT.

57. ANALYTICS RESOURCES TO CHECK OUT.
http://bit.ly/
HSanalyticsresources.

58. QUESTIONS?

59. THANK YOU.