The Science of Software Developing Data-Driven Product Roadmaps (ProductCamp Boston 2016)

The Science of Software

Developing Data-Driven Product Roadmaps

ProductCamp Boston - 09 April 2016

Keith FenechVP Software Analyticswww.trackerbird.com

http://www.trackerbird.com/

Housekeeping

Connect to the "Cambridge" wireless network Open an Internet browser You'll be redirected to a logon page

When prompted, use the code: pc0409

Follow us @PCampBoston

Official Hashtag – include in tweets: #PCampBoston

Session Evaluationswww.lanyrd.com/2016/productcamp-boston-sessions/schedule/

OR download Lanyrd App

http://www.lanyrd.com/2016/productcamp-boston-sessions/schedule/

4

About me

• M.Sc. Computer Science• Specialized in High Performance computing• 15 years experience in Software Development and

Product Management• Co-founder/Manager of LinkedIn Group

Networking Product Management (81K+ members)

• Co-founder of Trackerbird Software Analyticswww.trackerbird.com #PCampBoston #SoftwareAnalytics

http://www.trackerbird.com/

5

Product Managers need data

• Strategic PM decisions impact the whole organization

• Build Roadmaps• Prioritize Features• Measure ROI– product development– product marketing

www.trackerbird.com #PCampBoston #SoftwareAnalytics

Where do we get data?

• Mix & Match statistics from various sources– Download logs– Call-home logs– Sales or channel feedback– Surveys with customers– Feedback from lost leads– CRM

Painful + Time Consuming + Inconclusive !


7

What are companies doing?

• Marketing people rely on web analytics solutions– Google Analytics, Adobe Analytics, Hubspot, etc.

• Product managers tend to keep their own metrics or beg engineering to build in-app data collection

• Packaged (downloadable) products tend to become a black box after download


Do you know?

• What happens AFTER download?

• How do users evaluate your software?

• Which features are used?• Where should you focus

your R&D ?• In-app metrics is key

Visit WebsiteDownload

InstallEvaluateBuyAdoption

RetentionExpansion


BUSINESSMARKET PROGRAMSPLANNING SUPPORTREADINESS

STRA

TEGY

EXECUTIO

N

FOCUS

Pricing

Buy, Build or Partner

BusinessPlan

Product Profitability

Win/Loss Analysis

Distinctive Competencies

Market Problems

MarketingPlan

Customer Acquisition

Customer RetentionProgram

Effectiveness

BuyingProcess

Buyer Personas

UserPersonas

Positioning

Product Portfolio

Market Definition

Distribution Strategy

InnovationCompetitive Landscape

AssetAssessment

Lead Generation

Thought Leadership

Referrals & References

LaunchPlan

UseScenarios

Requirements

StakeholderCommunicatio

ns

Product Roadmap

Presentations

& Demos

EventSupport

“Special”Calls

ChannelSupport

Channel Training

SalesProcess

Collateral

SalesTools

©1993-2016 Pragmatic Marketing Framework™

How In-app data collection ties into the Pragmatic Marketing Framework

BUSINESSMARKET PROGRAMSPLANNING SUPPORTREADINESS

STRA

TEGY

EXECUTIO

N

FOCUS

How In-app data collection ties into the Pragmatic Marketing Framework

Pricing

Buy, Build or Partner

BusinessPlan

Product Profitability

Win/Loss Analysis

Distinctive Competencies

Market Problems

MarketingPlan

Customer Acquisition

Customer RetentionProgram

Effectiveness

BuyingProcess

Buyer Personas

UserPersonas

Positioning

Product Portfolio

Market Definition

Distribution Strategy

InnovationCompetitive Landscape

AssetAssessment

Lead Generation

Thought Leadership

Referrals & References

LaunchPlan

UseScenarios

Requirements

StakeholderCommunicatio

ns

Product Roadmap

Presentations

& Demos

EventSupport

“Special”Calls

ChannelSupport

Channel Training

SalesProcess

Collateral

SalesTools

©1993-2016 Pragmatic Marketing Framework™

11

• Across all company sizes• Across all industries (B2B & B2C)• 50-75% of companies tried collecting some

form of in-app data from their product• Most of them are still unhappy with how data

is presented to them

Lack of Actionable data for PM


12

• Primary aim is to get actionable metrics

• Vanity metrics have no business value– Wow, cool chart, now what?!

• Beware of Noise– Don’t bury yourself in data you cannot consume

Choosing the right metrics


13

• Download counts• Installation counts• Runtime session count and evaluation duration• Feature usage and user engagement• Churn/Dropoffs/Uninstalls (trial activity)• Customer vs Churn Profiles/Trends

Actionable Metrics (examples)



15

• Churn showed users dropping within 1 day.

• Discovered this dropoff due to wizard…

Case Study – Churn leads to Redesign


16

• Go beyond data collection• Convert raw metrics into actionable Business Intelligence reports• Visualization is crucial to help digest data

• Every team member has different requirements– Tool must provide easy access to data– Interactive & customizable– Ability to drill-down & segment data to answer specific questions in real-time

• Ability to adapt & scale with your business needs– Tool must scale with you as you grow– Over time you will require more advanced reporting requirements, so ensure tool

can be used to answer more advanced questions

Choosing the right tool


17

• Focus on your core competencies– Would you build your own web analytics solution?– Cost of development, infrastructure, maintenance,

time to deploy

• Automated in-app collection is more scalable & accurate than manual methods (such as customer surveys & lost leads surveys)

In-app data collection – build vs buy?


18

• Actionable Data• Visualization• Interactive Reporting• Scalable tool

Keys to a data driven product roadmap


[email protected] @trackerbirdnews @vilabs

blog.trackerbird.com

Try Trackerbird Software Analytics for FREEwww.trackerbird.com/register

?

Thank you


mailto:[email protected]

http://blog.trackerbird.com/

http://www.trackerbird.com/register