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Analytics as a Service
21.5.2022
Petri ‘Pete’ Mertanen
• Speaker, author, analytics coach & consultant
• BBA, Specialist Qualification in Management
• (Digital) Analytics experience since 2005
• Lecturer at Aalto University and Laurea University
of Applied Sciences
• Presentations at SlideShare
• Certifications for Analytics and Data Science:
• Elements of AI
• Cookie Consent Expert
• Statistical thinking for Data Science & Analytics
• Google Analytics Individual Qualification,
Google Tag Manager Fundamentals,
Introduction to Data Studio
Issues in (our) analytics business
• We have done a lot of implementation projects (and audits)
• GTM, UA/GA4, Data Studio etc. → we have lots of data
• Data itself doesn’t have any value
• In project business, the income (and HR) is hard to predict
• There may be some additional tasks or sub projects
• It may be hard to budget for clients as well
• Customers may not have analyst(s) in-house
• Procurement may be hard, even with cheaper tools e.g. Hotjar
• Marketing actions are not necessarily really data driven
What we want?
• Concentrate on relevant metrics / KPIs for business
• Create value for customers
• Improve customers’ business
• Have more predictable income
• Have more stable and profitable business
• Make it easy for customers
• And we want to grow, together with clients
What we want?
• Transform analytics services as a SaaS business
• Create something concrete for customers
• Easy to understand packaging (small/medium/large or silver/gold/platinum)
• The AaaS can include work and tools / licences
• Easy to scale up (or down)
• Easy to budget
Analytics as a Service
• Regular tag audits (with ObservePoint, Detail etc.)
• Regular setup / implementation audits (with Verified Data, Diib etc.)
• Regular data validation → data quality
• GA4 insights, UA notifications, Hotjar heatmaps, recordings and user
feedback, Google Ads recommendations as an input
• Analyst will filter inputs and do the deep dive / analysis
• Clear data driven recommendations or testing hypothesis for clients
• Customers will decide what to do next
• Different kind of actions listed (annotations in UA)
Conversion optimization process
ANALYZE
Analyze and evaluate
test results.
EXECUTE
Test and run the test..
PLAN
Plan a hypothesis and test.
DATA
Start with conversion
analysis
On-going conversion
optimization
REPEAT
Start here:
P.S.
• We have few Analytics as a Service customers in Finland
• We are planning to apply funding from Business Finland
• With the funding we would finalize productization
• We are looking for an international client for a pilot
Questions & Answers
www.mertanen.info
Mertanen Analytics Oy
petri@mertanen.info
Puh. 0400 792 616
Petri Mertanen
https://www.linkedin.com/in/petrimertanen/
https://twitter.com/mertanen

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MeasureCamp Amsterdam 2022

  • 1. Analytics as a Service 21.5.2022
  • 2. Petri ‘Pete’ Mertanen • Speaker, author, analytics coach & consultant • BBA, Specialist Qualification in Management • (Digital) Analytics experience since 2005 • Lecturer at Aalto University and Laurea University of Applied Sciences • Presentations at SlideShare • Certifications for Analytics and Data Science: • Elements of AI • Cookie Consent Expert • Statistical thinking for Data Science & Analytics • Google Analytics Individual Qualification, Google Tag Manager Fundamentals, Introduction to Data Studio
  • 3. Issues in (our) analytics business • We have done a lot of implementation projects (and audits) • GTM, UA/GA4, Data Studio etc. → we have lots of data • Data itself doesn’t have any value • In project business, the income (and HR) is hard to predict • There may be some additional tasks or sub projects • It may be hard to budget for clients as well • Customers may not have analyst(s) in-house • Procurement may be hard, even with cheaper tools e.g. Hotjar • Marketing actions are not necessarily really data driven
  • 4. What we want? • Concentrate on relevant metrics / KPIs for business • Create value for customers • Improve customers’ business • Have more predictable income • Have more stable and profitable business • Make it easy for customers • And we want to grow, together with clients
  • 5. What we want? • Transform analytics services as a SaaS business • Create something concrete for customers • Easy to understand packaging (small/medium/large or silver/gold/platinum) • The AaaS can include work and tools / licences • Easy to scale up (or down) • Easy to budget
  • 6. Analytics as a Service • Regular tag audits (with ObservePoint, Detail etc.) • Regular setup / implementation audits (with Verified Data, Diib etc.) • Regular data validation → data quality • GA4 insights, UA notifications, Hotjar heatmaps, recordings and user feedback, Google Ads recommendations as an input • Analyst will filter inputs and do the deep dive / analysis • Clear data driven recommendations or testing hypothesis for clients • Customers will decide what to do next • Different kind of actions listed (annotations in UA)
  • 7. Conversion optimization process ANALYZE Analyze and evaluate test results. EXECUTE Test and run the test.. PLAN Plan a hypothesis and test. DATA Start with conversion analysis On-going conversion optimization REPEAT Start here:
  • 8. P.S. • We have few Analytics as a Service customers in Finland • We are planning to apply funding from Business Finland • With the funding we would finalize productization • We are looking for an international client for a pilot
  • 10. www.mertanen.info Mertanen Analytics Oy petri@mertanen.info Puh. 0400 792 616 Petri Mertanen https://www.linkedin.com/in/petrimertanen/ https://twitter.com/mertanen