5 Proven Strategies For a Successful Analytics Product Launch

GoodData Confidential. 2013 GoodData Corporation. All rights
reserved.
June 10, 2014
5 Proven Strategies
to successfully
launch an analytics
product

reserved.
Kevin Smith, NextWave Performance
Speakers
Cory Vander Jagt, GoodData

reserved.
Our Discussion
▶Overview
▶Considerations for Success
▶ Monetization Pathway
What we see
Case Studies
▶ Questions and Answers
!
!

GoodData Confidential. 2014 GoodData Corporation. All rights reserved.
GoodData is a business analytics Platform as a Service (PaaS) that
supports the entire lifecycle of data and analytics, from storage
and data governance to data discovery.
!
What Is GoodData?

GoodData Corporate Overview
▶ Serving 40,000+ companies
▶ Nearly 300 employees, including 150 engineers
▶ Founded in 2007
▶ $75.5M in funding
▶ Headquarters in San Francisco
▶ Other offices in Boston, Portland, Prague, Brno
!
!
!

reserved.
Our Customers Think BIG
How do I use
analytics to
transform my
business?
How do I get
critical analytics to
my customers?
What data am I not
capitalizing on
yet?

Embedded Analytics Powered By GoodData

reserved.
40,000+DWHs under management
99.5%
Uptime SLA
85%
Adoption
Terabytes of Data
under management
100+
Powered By
Partners
1,500,000
Data integrations per week
72k
Users at one
partner
Security
Certified
OUR GOODDATA

GoodData Confidential. 2014 GoodData Corporation. All rights reserved. 9
Managing Partner/Co-Founder
NextWave Performance
NOW
VP, Product Management/Service Design
International Asset Systems
Managing Director
EffectiveUI
Director, Solution Design
SAP Labs
VP, Product Management
Retreon
Sr. Director, Engineer Program Management
Qwest (LCI)
.
.
.
BEFORE Sr. Director, Product Strategy & UX
ServiceSource
I’m Kevin Smith

This is NextWave Performance
Based in Denver, CO ∙ Established 2005
Product strategy
Performance strategy
“What should this product
do and for whom?”
“How can I optimize my
services and processes”

I’ve implemented “Powered By” four times
11
“Dispatch Manager”
Ad hoc analytics for container
logistics
“Equipment Repair”
Ad hoc analytics for inventory
repair
ServiceSource
“Renew OnDemand”
Ofﬂine analytics for sales renewals
DemandBase
“Performance Manager”
Analytics for ad campaign
management

My GoodData implementation statistics
number of successful Powered by
GoodData implementations
12
4
90
100
average days it took from project
concept to project implemented
percent of time GoodData was ready
before any other part of the product

% of times
go-to-market issues
have had been more
problematic than
technical issues
13
100
And…

Poll -
Which best describes your company?
1 - Evaluating embedded analytics or a white-label offering
2 - Currently in the development phase
3 - Development complete, pre-launch
4 - One or more products in market
5 - Don’t know / unsure
Type Your Answer In
The Q/A Box

How do you avoid the
major go-to-market
mistakes for a Powered
By product?

You need to plan beyond just the technical details
Determine
vision for the
analytics within
core product
Perform
persona
definition/key
questions
Define initial
db’s/metrics/
reports needed
for personas
Identify data
sources for
analytics
Perform initial
data extracts
Define internal
processes
(provisioning,
support)
Create initial
project
Create ETL
processes
QA all
calculations for
metrics/reports
QA ETL
process
Provide
training to
Sales and
Support teams
Modify contract
language (3rd
party, SLAs,
bench, etc)
Have
customers sign
updated
contracts
Establish on-
going training
system
Sign-off on
metrics/reports
Sign-off on ETL
All contracts
updated
Update
collateral,
logos, ads, etc.
Perform
friendly
customer beta
Gather beta
feedback
Fix issues/
roadmap
needs
Start
Ready to on-
board users
Implement
SSO
Embed BI
system in
iFrame in app
Perform QA
Determine
integration with
product
Determine go-
to-market/offer
package,
pricing
Develop rollout
plan
Pricing
strategy
QA
inadequate
Marketing
plan
Training plan
Customer
beta
Change
management
Product
Definition
1
User
Definition
2
Selling plan
3
Legal details
5
Support
processes
4

!
The Five
Proven Strategies
for a Successful
Analytics
Product Launch

Know how BI will fit in
with the existing product1

What is the product?
Key Product Decisions We
Really Should Have
Considered Before Starting
Implementation
Who gets
to use it?
What’s the tiering/
pricing structure?
Is GoodData
white-labeled
or black-
labeled?
How is it sold (same
contract, separate
paper, etc.)
How are custom
requests
handled?
How are
legacy
customers
brought on-
board?
What is the business
problem being solved
though the addition of
analytics?
1

What is the product?
Product
Workshop
Key Product Decisions We
Really Should Have
Considered Before Starting
Implementation
Who gets
to use it?
What’s the tiering/
pricing structure?
Is GoodData
white-labeled
or black-
labeled?
How is it sold (same
contract, separate
paper, etc.)
How are custom
requests
handled?
How are
legacy
customers
brought on-
board?
What is the business
problem being solved
though the addition of
analytics?
1

• Decide what you want to be when
you grow up
• Select your personas
• Develop your pricing/tiering
model
• Determine responsibilities
• Identify boundaries
The Workshop1

Decide what you want to be
Framework from Reaching Escape Velocity, Geoffrey Moore, 2012
Differentiate
Neutralize
Optimize
Core Value Key Metric Main Challenge
Separation Unmatchable How far?
Comparability Good enough How fast?
Productivity Best in class How deep?
1

Because it determines your tactics
Framework from Reaching Escape Velocity, Geoffrey Moore, 2012
Differentiate
Neutralize
Optimize
If you choose Instead of You get
Parity with the
competition
vs
Unmatchable
functionality
→
Squandered
resources as
competitors quickly
catch up
Best-in-class vs
Good
enough
→
Wasted
budget
Good
enough
vs Best in class →
Higher operating
costs than the
competition
In this mode
1

What do you mean by BI?1
You keep using
that word. I do
not think it
means what
you think it
means.

Category Types of Analytics Questions Answered
Prescriptive
• Optimization
• Randomized testing
• What’s the best that can happen?
• What happens if we try this?
Predictive
• Predictive modeling/forecasting
• Statistical modeling
• What will happen next?
• What is making this happen?
Diagnostic
• Data exploration
• Intuitive visuals
• Why did this happen?
• What insights can I gain?
Descriptive
• Alerts
• Query/drill-down
• Ad hoc reports/scorecards
• Standard reports
• What actions are needed?
• What is the problem?
• How many, often, where?
• What happened?
SOURCE:
Disambiguating Analytics, July 2, 2013, Sanjeev Kumar,
International Institute for Analytics
SOURCE:
Magic Quadrant for Business Intelligence and Analytics Platforms, February 5,
2013, Analyst(s): Kurt Schlegel, Rita L. Sallam, Daniel Yuen, Joao Tapadinhas
Capability
25
What do you mean by BI?1

Stuff We Won’t Do
Stuff We Won’t Do
StuffWeWon’tDo
StuffWeWon’tDo
Set your product boundaries1
The Product
Stuff We’ll Do as
Part of the Core
Product
Stuff We’ll Do for
an Extra Fee

Sample pricing & tiering plan
Standard
• Included for all
customers
• Uses standard project/
template
• No customization
• Users cannot modify
dashboards
• No internal or external
benchmarking
• 1 year historical data
Plus Pro
• Upgrade from
Standard
• Uses standard project/
template
• Customization for an
additional fee
• Users cannot modify
dashboards
• Internal benchmarking
included — no external
benchmarking
• 2 years historical data
• Upgrade from
Standard/Plus
• Uses standard project
and is customized per
customer needs
• Users can modify
dashboards
• Includes external
benchmarking
• 3 years historical data
+25% +50%
1
+5%

Go minimal first and evolve1
FULL PREDICTIVE for
version 1.0!
● De-risks decisions
● Establishes a roadmap for future
development
● Allows for emergence

Know who the users are2

Who is the user?
Potential BI Users
Your sales team
Your ﬁnance
team
Your support
team
End Users
Executive
management
Mid-level
management
Front-line users
Reporting
analysts
Buyers
Executive
sponsor
Implementation
owner
Your operations
team
2
3
1
2

Start with a persona
Role or Job Title: VP Customer Advocacy Key Characteristics
“We need to know if customers are unhappy
with our service, what aspects of our service,
and what we can do to improve performance.”
• Looked to for answers

• Is a trusted advisor to the Sales team

• Focused on root cause analysis

• Uses NPS to track performance
Frustrations and Pain Points
• I feel like I’m operating blindly until the quarterly reviews occur

• I have to rely on others to build reports to tell me what’s going on

• I focus on individual customers & issues that seem to be “hot” that day — I don’t know if these are the right things

• I worry that I’m not making any long-term improvements, just day-to-day tactical fixes

• It takes us way too long to identify trends and patterns in customer usage. By the time we see them, it’s too late..
Questions Other applications Feature requests
• Is customer health trending up or down
and why?

• Are there global issues that I can correct
to improve retention?

• If I fix the issues, how much uplift do I
get?

• How do we compare to everyone else
for retention and customer satisfaction?
• SurveyMonkey

• MS Excel

• NPS tools (Verint,Vovici)

• Tableau
• Allow customers with high value and potential
issues to be made easily identifiable

• Show trends over time globally, for segments,
products, and specific customers.

• Show how I perform relative to peers

• Allow me to track corrective actions made
and the resultant performance shifts.
Jon
2

Use persona questions to determine
dashboard and chart priorities
AnalyticGroupNeedPersona
CMO
Marketing
Manager
Sales
VP
See long-term
trends
Understand how
budget is spent
ID underserved
opportunities
View team
performance
Increase customer
interest
Neutralize
competition
CMO Dashboard
Chart 1
Chart 2
Chart 3
Chart 4
Chart 5
Chart 1
Chart 3
Chart 4
Chart 6
Chart 7
Chart 1
Chart 7
…
Marketing
Dashboard
CMO Dashboard
Marketing
Dashboard
2

Define the Sales rollout
strategy3

How to mess up the sales rollout
1 Failure to provide a schedule
2
Poor communication of
capabilities
3 Failure to provide training
4 Lack of boundary details
5 Allowing early demos
now, with 100%
more analytics!
3

Making Sales successful
• Conduct multiple training sessions
(awareness, functionality, processes)
• Keep a running “master metrics list” that
all internal users can access
• Prepare “plain-English” deﬁnitions for
each report, metric, dimension, ﬁlter
• Incorporate GoodData training into the
core app’s training processes
3

Put support processes in
place4

Support processes are key to success
SaaSServices/Data
Management
Provisioning
Training
Support
Marketing
Finance
ChangeManagement
Core Product
BI FunctionalityCompanies
focus on
this…
…and
forget
about this
(until it’s too late)
4

Getting the processes right4
Workshop
brainstorm
Build mind
map of
tasks
Create
project
plan
Make
people
accountable
Conduct
status
reviews
Do a walk-
through
(role-play)
Plan for
issues
(FMEA/RACI)
EVERYTHING
ready?
Launch!
FIX!
yes
no

Planning for problems4ProcessStep
Component(s)
Effected
FailureMode
PotentialEffects
SeverityofFailure
(1=low,10=high)
ProbabilityofFailure
Occurrence
(1=low,10=high)
DetectionControl(s)
Description
Effective-nessof
DetectionControls
(1=high,10=low)
RiskPriorityNumber
(RPN)
Action
RecommendedUpon
Failure
Responsibility
#5:
Submit
order to
Order
Entry
group
Order
Order
not
delivered
within 24
hrs of
signature
Order
not
entered
into OE
system
on time
5 8 None 10 400
Contact
Sales Rep
to get
contract
delivered
OE
manager
Failure Modes chart RACI Matrix
• “When a problem occurs, how are we going
to respond?”
• “What kinds of problems might we expect?”
• “Who is responsible for each process step?”
• “Who is accountable for each process step?”
• “Who is consulted for a given process step?”
• “Who is involved at each process step?”

Anticipate legal and
contract scenarios5

Avoiding pain from lawyers5
I hear you want to want
implement a new product
that requires me to re-visit
all of our contractual
obligations to customers.
By next week.
“
”

Avoiding pain from lawyers
• Get the legal team in the loop early, update
them often
• Ensure that the product’s SLA = analytics’ SLA
• Update contracts to reﬂect 3rd party data
processing
• Consider having customers sign new  
contracts or amendments
• Think through benchmarking 
implications
5

reserved.
Conduct product definition workshop and
define how GoodData will fit in
Create personas and map to workflows
Define sales roll-out strategy
Brainstorm impacted processes, build a
plan, review progress regularly
Anticipate legal and contract scenarios
Recap: Strategies for a Successful Launch
4
1
2
3
5

reserved.
▶ End-to-end program designed from a partnership POV
▶ 100+ implementations = best practices
▶ 50+ unique business models in place
▶ NextWave is available for deeper consulting
Powered By GoodData is a Program
LAUNCH
Product
Definition
Product Mgmt
Engineering
Marketing/
Product Marketing
Support
Sales
Ongoing Marketing &
Product Enhancements
PROGRAM
EXAMPLE
KEY
GROUP
Product
Rollout
Enablement
Cross-Functional
Teams

reserved.
Case Studies
Business Model
!
Pricing Strategy
!
Number of Products
!
Uplift
!
Result
!
Subscription based License + Maintenance
A la carteIncluded in price
2
20% - 30%
11 verticals
20% - 80%
#1 reason people upgrade Fastest growing unit
* managed service * self-service

reserved.
‣  Anonymous
benchmarking against
industry peers
‣  Include CRM, ERP,
and other data
sources
‣  Out of the box
reporting
‣  Simple dashboards
‣  Basic filtering
1 2 3 4
reporting
‣  Custom reporting &
dashboards
‣  Ad hoc reporting
‣  Filtering
‣  Refresh interval
‣  Notifications
‣  Anonymous
benchmarking
against industry
peers
and other data
sources
Basic Analytics
Premium Analytics
Benchmarking
Additional Data
Sources
Powered By GoodData Pathway

reserved.
‣  Anonymous
benchmarking against
industry peers
and other data
sources
reporting
1 2 3 4
reporting
‣  Custom reporting &
dashboards
‣  Ad hoc reporting
‣  Filtering
‣  Refresh interval
‣  Notifications
‣  Anonymous
benchmarking
against industry
peers
and other data
sources
Basic Analytics
Premium Analytics
Benchmarking
Additional Data
Sources
“The #1 reason our customers upgrade.”
“Upsell at the click of a button.”
“Building a $10M+ business practice.”
LEADING MEDIA
AGENCY
“Instant
dashboards.”
Pathway in Practice

reserved.
Questions?

reserved.
Thanks!
kevinmichaelsmith 
cvanderjagt
www.gooddata.com 
www.nextwaveperformance.com
team@gooddata.com
ksmith@nextwaveperformance.com

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5 Proven Strategies For a Successful Analytics Product Launch