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CRM is not enough


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Learn more about a world beyond CRM suites and how your company can build the customer data technology stack that matches the reality of today’s multi-channel, digital era.

Published in: Business

CRM is not enough

  1. 1. Wednesday, February 5th
  2. 2. Peter Reinhardt, CEO & Co-founder at Segment
  3. 3. 4 billion global users connected to the internet and growing MORE PEOPLE CONNECTED Currently in the U.S. there are approximately 8 networked devices per person MORE CONNECTED DEVICES 90% of all data has been created in the last two years. MORE DATA GENERATED The digital world is changing Every day more (and different types) of data is coming at us than before
  4. 4. Customer relationships in the past Customer relationships today
  5. 5. How data should flow throughout the org How it actually flows
  6. 6. Who your customers are What actions they’re taking Where those actions are taking place Who What Where Requirements for using data to deliver customer first experiences
  7. 7. The CRM Era Post-CRM Era
  8. 8. Not built to handle the volume and type of data now available to record digital customer interactions, such as activity on your website and mobile apps VOLUME OF DATA Difficult to sync interactions that happen across 3rd party tools such as email, push notifications, support tickets, and payment systems DATA CONSISTENCY Designed to be a “walled garden” — limited connections to other tools outside their ecosystem making it difficult to access data, Even with new integration capabilities, will always prioritize their own solutions. INTEGRATIONS Where CRMs fall short...
  9. 9. $30 billion
  10. 10. CRM suites will never be able to catch up with the explosion and fragmentation of digital channels.
  11. 11. The Birth of an Independent Ecosystem
  12. 12. What does the ideal marketing tech stack look like?
  13. 13. The CRM Suite is no longer the center of the tech stack.
  14. 14. The most important requirement when building your stack is flexibility.
  15. 15. 1. Identify and define what problem you want to solve 2. Choose best-in-class software that is independent and interoperable 3. Connect this flexible stack together and evolve as needed 4. Repeat Principles for building the right stack
  16. 16. Brandon Purcell, Principal Analyst at Forrester
  18. 18. © 2020 FORRESTER. REPRODUCTION PROHIBITED. Why CRM Is Not Enough In The Age Of The Customer Brandon Purcell February 5, 2020
  19. 19. 29© 2020 FORRESTER. REPRODUCTION PROHIBITED. Success in the age of the customer requires deep customer understanding • Behavioral data • Social data • Mobile data • Environmental data • Sensor data • Transaction data • Customer data • Third-party data • Financial data • Sales data • Product data
  23. 23. 33© 2020 FORRESTER. REPRODUCTION PROHIBITED. Customer insights are the gold buried within your data
  24. 24. 34© 2020 FORRESTER. REPRODUCTION PROHIBITED. Key phases of the insights lifecycle Insights Action Data
  25. 25. 35© 2020 FORRESTER. REPRODUCTION PROHIBITED. Customer analytics turns data into insights Customer analytics uses customer data and analytic insight to design customer- focused programs that win, serve and retain customers.
  26. 26. 36© 2020 FORRESTER. REPRODUCTION PROHIBITED. Now let’s explore the menu Chez CustomerAnalytiques
  27. 27. 37© 2020 FORRESTER. REPRODUCTION PROHIBITED. Companies have a wide range of options to choose from
  28. 28. 38© 2020 FORRESTER. REPRODUCTION PROHIBITED. Methods that inform contextual marketing Contextual marketing analytics methods: • Text analytics • Customer location analysis • Customer device usage analysis Text analytics Customer location analysis Customer device usage analysis
  29. 29. © 2015 Forrester Research, Inc. Reproduction Prohibited 39 Case study: customer location analysis › Business objective: Optimize offers, products, or operations based on customer location › Data: Customer location data (either geospatial or in-store) › Analysis: Develop frequency tables to show where customers have been and where they’re likely to go › Action: Deliver targeted marketing based on location, or… Case in Point: Auto finance
  30. 30. 40© 2020 FORRESTER. REPRODUCTION PROHIBITED. Methods that drive acquisition… Acquisition analytics methods: • Behavioral customer segmentation • Customer lifetime value analysis • Customer lookalike targeting Behavioral customer segmentation Customer look-alike targeting Customer lifetime value analysis
  31. 31. © 2015 Forrester Research, Inc. Reproduction Prohibited 41 Case study: Customer Lifetime Value at Royal Bank of Canada Source: › Problem: Royal Bank of Canada wanted to identify subsegments of highly profitable customers to target › Solution: Developed CLV model which identified credit-strapped young medical professionals and developed program to meet their needs › Result: Market share in this subsegment increased from 2% to 18% and revenue per customer is 3.7 times average customer
  32. 32. 42© 2020 FORRESTER. REPRODUCTION PROHIBITED. Methods that increase retention and loyalty… Retention and loyalty analytics methods: • Customer propensity analysis • Churn and attrition analysis • Social network analysis
  33. 33. 43© 2020 FORRESTER. REPRODUCTION PROHIBITED. Methods that drive personalization… Personalization analytics methods: • Next best action • Recommendation analysis • Cross-sell and upsell analysis
  34. 34. © 2015 Forrester Research, Inc. Reproduction Prohibited 44 Recommendation analysis can inform the digital and physical shopping experience › Business objective: Sell more by uncovering correlations between products › Data: Transaction data, SKU-level data › Analysis: Quantify co-occurrence of product purchases › Action: Recommendation engines or product placement Case in Point: Hurricanes
  35. 35. © 2015 Forrester Research, Inc. Reproduction Prohibited 45 A match made in heaven… +
  36. 36. 46© 2020 FORRESTER. REPRODUCTION PROHIBITED. Methods that improve the customer experience… Customer experience analytics methods: • Customer satisfaction analysis • Customer engagement analysis • Customer journey analysis
  37. 37. 47© 2020 FORRESTER. REPRODUCTION PROHIBITED. But they should not exist in isolation Source: February 2014 “TechRadar™: Customer Analytics Methods, Q1 2014”
  38. 38. 48© 2020 FORRESTER. REPRODUCTION PROHIBITED. It’s time for a new “Next Best” paradigm… The Next Best Experience (Friends call it NBX for short)
  39. 39. 49© 2020 FORRESTER. REPRODUCTION PROHIBITED. The Next Best Experience focuses on customer lifetime value optimization
  40. 40. 50© 2020 FORRESTER. REPRODUCTION PROHIBITED. Delivering the Next Best Experience requires robust, real-time customer data… Source: Vendor Landscape, Personalization Solution Providers, Q3 2017
  41. 41. 51© 2020 FORRESTER. REPRODUCTION PROHIBITED. All of this requires robust customer data… Can your CRM provide all this data? Source: Vendor Landscape, Personalization Solution Providers, Q3 2017
  42. 42. 52© 2020 Forrester. Reproduction Prohibited. Firms struggle most with data, process, and people Base: 246 North American analytics and measurement professionals Source: Forrester/Burtch Works Q3 2019 Global State of Customer Analytics Survey 19% 26% 27% 29% 31% 41% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% Standardizing metrics across the organization Hiring and retaining talent to manage measurement and analytics Getting buy-in from business stakeholders on the value of measurement and analytics Transforming insights into relevant business actions Accessing data from a variety of sources Ensuring data quality from a variety of sources Please rank the top three challenges for your organization when making use of measurement and analytics.
  43. 43. 53© 2020 Forrester. Reproduction Prohibited. Start with a minimum viable data approach to prove value then incorporate more data Source: the “How To Calculate Customer Lifetime Value For Your Business [157640]” Forrester report. Example: a minimum viable data approach to customer lifetime value analysis
  44. 44. 54© 2020 Forrester. Reproduction Prohibited. Analytics team composition – common roles Strategist and business lead Manages the team to optimize a specific business outcome Project manager Plan, scope, staff, and oversee delivery of insights projects Technology leader Responsible for insights testing, implementation, and architecture Domain experts Recognizes insights worth the investment – sits in BUs but participate in pilot teams Developers Test and implement insights in software and business rules Data scientists Build models and exercises them to reveal potential insights Data engineers Gathers, assesses, integrates, prepares, and manages data Primary researchers Conducts qualitative and quantitative research to provide deeper insight into customers’ needs, wants and motivations Facilitator Facilitates customer and internal work sessions (co-creation, journey mapping, ecosystem mapping, etc.) to turn insights into action
  45. 45. 55© 2020 Forrester. Reproduction Prohibited. Build a customer insights center of excellence
  46. 46. 56© 2020 Forrester. Reproduction Prohibited. - commitment - adoption - applications - analytics skills - org structure - partnerships - sources - management - preparation - workflow - prioritization - execution - sharing - production - consumption - activation Assess your capability across six key dimensions and create your roadmap to analytical maturity Strategy Structure Data Process TechnologyAnalytics - methodology - metrics - business KPIs - ROI
  47. 47. 57© 2020 Forrester. Reproduction Prohibited. The enterprise martech stack is evolving to succeed in the Age of the Customer
  48. 48. FORRESTER.COM Thank you © 2020 FORRESTER. REPRODUCTION PROHIBITED. Brandon Purcell +1 510.926.2694
  49. 49. @Peter Reinhardt @Brandon Purcell Fireside Chat
  50. 50. Q&A
  51. 51. Thank you to our sponsors