The Marketing Analytics Stack - How to Use Customer Data for Traction and Growth

THE
MARKETING ANALYTICS
#STACK
www.popcornmetrics.com info@popcornmetrics.com @popcornmetrics

“customer data,
without depending on developers”

Paul Boyce, CEO
3rd Startup
20 yrs Tech & Sales
4years @JP Morgan
Hacker, Coder, Marketer
Luis Correia, COO
Chartered Engineer
Customer Success
Hacker

#marketing #analytics @popcornmetrics
great session on #marketing #analytics by
@popcornmetrics at @seedcamp
+feedback

GROWTH
(TRACTION)

TRACTION
DATA

TRACTION
DATA TOOLS

TRACTION
DATA TOOLS
PROCESS

Data.
without data, you’re guessing.

KISS.
(it can get complicated)

What data should you track?

track everything,
decide from 1 (or 2)

How do we model growth?

Pirate Metrics

What’s my TRUE North?
pirate + omtm

What’s my TRUE North?
pick 1

TRUE North
can
CHANGE

What makes a good metric?

A “Good” Metric is:
Comparative: “vs last week”
Ratio/Rate: “%, per hr/day”
Understandable: “team”
Actionable: “not vanity”

What’s more useful?
20 miles - distance
20 mph - speed
20 mph/s - acceleration

a good metric
changes
your
behaviour

Exercise:
1. Write your top 3-5 metrics (watch daily)
2. How many are good?
3. Can you eliminate any?
4. What could you add?
5. Could you drive from just one?

Benchmarks.
(how well are you doing?)

SaaS:
Start Trial: 5-10%
Subscribe: 15-25%
Churn: 2% <5%
-------------------------------------------------------------------------------------
Upsell 20% (annual $)
TRIALS: 20% serious | 20% casual | 60% curious

user content:
pinterest: 14 mins, tumblr: 21 mins, facebook:60 mins
Time on Site: 17mins / day
-------------------------------------------------------------------------------------
5-15% generate content
80% content < 2% of users

e-commerce:
amazon: 9.6%, ebay: 11.5%
-------------------------------------------------------------------------------------
startups: 1-3%
2% -> 10% : loyal | skus | repeat
4.5% mobile searches >> purchase

tools.

should you build in house?

Session
Analytics
e.g.
Google
Analytics
User Lifecycle Messaging
e.g. Customer.io, Intercom.io
Feedback,
Surveys
e.g. Web Engage,
Qualaroo, Hotjar
User Analytics (Funnels, Cohorts)
e.g. Mixpanel, KISSmetrics, Woopra
Chat
e.g. Olark,
Intercom,
Zopim
A/B Test
e.g. VWO,
Optimizely
Channel Pixel
e.g. facebook,
twitter, adroll,
perfect audience

1. Channel:
google analytics
2. Conversion Funnel:
mixpanel, kissmetrics, woopra
3. Lifecycle Emails:
customer.io, intercom.io

Channel Report + Events
Set up an Event for an event called add to cart
ga('send', 'event', 'ecommerce','Add to Cart');

Channel Report + Events

channel: anonymous/pages
user centric
gated funnels
visual
user walkthru
A/B test (messaging tools)

Deep Conversions: Playmode

Funnels: uber & micro

COHORTS 101:
"The cohort report is the single best tool for
analyzing how customer behavior shifts over
time." (Hiten Shah, KISSmetrics)

COHORTS:

“a group of people who share a common
characteristic over a certain period of time.”
e.g. customers who signed up on 1st March
have the same signup date.”

Lifecycle
Emails
timed | triggered

goal: get user to the NEXT step
educate + motivate

1. Warm welcome: initial value
2. How to: next step(s)
3. Halfway: reminder
4. Conversion: close/offer
5. Canceled: ask why?

Test, Test, Test:
● subject
● time of day
● frequency
● CTAs

we send a lot of emails.

tools need data:
so, how to get customer data?

Event Driven: Tools need DATA

engineers do this: marketers do this:

Process.
turning guesses into facts

1. MODEL: pirate metrics AARRR
2. BASELINE: install metrics
3. FOCUS: what’s your stage? where’s north?
5. BRAINSTORM: instincts/guesses?
6. BACKLOG & PRIORITISE: fast, easy, roi
7. EXPERIMENT: hypothesis + result
7. MEASURE: facts
8. ITERATE: diminishing returns, downstream

Process.
discipline + focus

RESOURCES:

Blogs I Follow:
Lincoln Murphy (16ventures.com)
GrooveHQ (groovehq.com/blog)
Baremetrics (baremetrics.com/blog)
David Balfour (coelevate.com)

3 months FREE
for Seedcamp Family
signup: http://PopcornMetrics.com

7 Essentials of Marketing Analytics
http://blog.PopcornMetrics.com

QUESTIONS:

thank you.

The Marketing Analytics Stack - How to Use Customer Data for Traction and Growth

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