meaningful metrics - aligning operational metrics with marketing & customer experience

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Copyright © 2016 Earley Information Science 1 Meaningful Metrics: Aligning Operational Metrics with Marketing and Customer Experience Copyright © 2016 Earley Information Science Dino Eliopulos, Managing Director, Earley Information Science Seth Earley , CEO, Earley Information Science John Walker , Principal, SemanticClarity Gerry McGovern, CEO & Founder, Customer Carewords March, 2016

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Page 1: Meaningful Metrics - Aligning Operational Metrics with Marketing & Customer Experience

Copyright © 2016 Earley Information Science1

Meaningful Metrics: Aligning Operational Metrics with Marketing and Customer Experience

Copyright © 2016 Earley Information Science

Dino Eliopulos, Managing Director, Earley Information Science

Seth Earley, CEO, Earley Information Science

John Walker, Principal, SemanticClarity

Gerry McGovern, CEO & Founder, Customer Carewords

March, 2016

Page 2: Meaningful Metrics - Aligning Operational Metrics with Marketing & Customer Experience

Copyright © 2016 Earley Information Science2

Today’s Agenda

• Welcome & Housekeeping• Dino Eliopulos, Managing Director, Earley Information Science

(@deliopulos)

• Session duration & questions

• Session recording & materials

• Take the polls & the survey!

• The Panelist Point of View• Seth Earley, CEO, Earley Information Science (@sethearley)

• John Walker, Principal, SemanticClarity

• Gerry McGovern, CEO & Founder, Customer Carewords (@gerrymcgovern)

• Expert Panel Discussion

• Questions & Answers

• Join the conversation: #earleyroundtable

Page 3: Meaningful Metrics - Aligning Operational Metrics with Marketing & Customer Experience

Copyright © 2016 Earley Information Science3

Dino Eliopulos - Biography

Dino EliopulosManaging DirectorEarley Information

Science

Experienced leader and innovator in industry and high-end professional IT consulting with deep specialization in user experience and highly complex business applications.

Areas of expertise include: strategy, planning, forecasting, budgeting, measurement, sales, talent acquisition / management and retention, career stewardship, program management and service delivery.

Industry experience in • Financial Services• Retail / CPG• Telecommunications• Travel and Entertainment• Healthcare• Pharmaceuticals• Hi-Tech Manufacturing and Energy

Page 4: Meaningful Metrics - Aligning Operational Metrics with Marketing & Customer Experience

Copyright © 2016 Earley Information Science4 Copyright © 2016 Earley Information Science

Meaningful Metrics

Aligning Operational Metrics with Marketing and Customer Experience

Page 5: Meaningful Metrics - Aligning Operational Metrics with Marketing & Customer Experience

Copyright © 2016 Earley Information Science5

Making Sense of Data “Vapor Trails”

• All customer interactions leave traces throughout multiple systems

• We interpret these trails and track data in order to make decisions about what to do differently

– Change a promotion

– Improve performance

– Adjust a user experience

– Modify a product offering

– Etc.

• Metrics provide signals to the organization about what to do and when to do it

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Copyright © 2016 Earley Information Science6

What are the Most Important Metrics?

• Customer Behaviour: buy, buy more/less, recommend, abandon, defection

• Customer Feedback: effort, dissatisfaction , complaints , social media

• Employee Behavior: tenure, knowledge, customer feedback

• Employee Feedback: stories, suggestions, process, tools, systems, policies

• Process performance: cycle time & right first time, system uptime

• Total Cost to Serve: across budgets & domains

• Product Performance: returns , quality, contacts per sale, support calls

Go-to-market and competitive strategies determines areas of focus

Page 7: Meaningful Metrics - Aligning Operational Metrics with Marketing & Customer Experience

Copyright © 2016 Earley Information Science7

Strategy Examples

Strategy Approach Measure MechanismCustomer Intelligence Leadership We will invest in best-in-class

capabilities for sensing, acquiring, analyzing and responding to customer feedback, intelligence and behaviours

Sales and Customer Engagement

• E commerce sales analysis• Customer relationship management • Survey text analytics• Digital Marketing

Ubiquitous & Effortless Access We will invest in channels that enable customer access to expertise, help, services according to need, efficiency and effectiveness

Dissatisfaction • Knowledge bases• Unsupervised Support • Call center support• Community development• Optimized multi channel experience

Next Generation Customer Journey Management

We will invest in customer empowering technologies that reduce effort and provide control.

Total Cost to Serve • Customer self service• Mobile experience optimization • Hyper local services• Dynamic, personalized content

Equipping our People We will build the industry’s highest performing workforce that inspires trust

Internal Engagement • Internal collaboration tools and programs• Knowledge management capabilities • Search Based Applications and Unified

Information access for improved productivity

Page 8: Meaningful Metrics - Aligning Operational Metrics with Marketing & Customer Experience

Copyright © 2016 Earley Information Science8 Copyright © 2016 Earley Information Science

Poll Question #1

What classes of metric are most important to you?

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Copyright © 2016 Earley Information Science9

Customer engagement (behaviors and feedback)

Optimizing support (call center and self service)

Employee engagement (improved internal processes)

None of the above

What classes of metric are most important to you?

a

b

c

d

Page 10: Meaningful Metrics - Aligning Operational Metrics with Marketing & Customer Experience

Copyright © 2016 Earley Information Science10

Seth Earley - Biography

Seth EarleyCEO and Founder

Earley Information Science

Over 20 years experience

Current work

Co-author

Editor

Member

Former Co-Chair

Founder

Former adjunct professor

Guest speaker

AIIM Master Trainer

Course Developer & Master Instructor

Data science and technology, content and knowledge management systems, background in sciences (chemistry)

Enterprise IA and Semantic Search

Information Organization and Access

US Strategic Command briefing on knowledge networks

Northeastern University

Boston Knowledge Management Forum

Long history of industry education and research in

emerging fields

Academy of Motion Picture Arts and Sciences, Science and Technology Council Metadata Project Committee

Editorial Journal of Applied Marketing Analytics

Data Analytics Department IEEE IT Professional Magazine

Practical Knowledge Management from IBM Press

Cognitive computing, knowledge and data management systems, taxonomy, ontology and metadata governance strategies

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Copyright © 2016 Earley Information Science11

Marketing Technology ROI

• Many organizations are driving operationalization of marketing analytics deeper into the organization

• The challenge lies in improving business fluency with analytics

• If specialized knowledge and expertise is required to perform analysis, analytics is not part of the day to day operational process

• In many cases, highly skilled analysts produce reports that are not widely shared and therefore are recreated by others

Big Investments in Marketing Technologies

…but fluency is lacking

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We accurately measure the return on

marketing investment (ROMI) of

campaigns

Marketing pros self assessments are lukewarm…

Less than…

1 in 5 …analytics professionals say their efficiency,

effectiveness or

acquisition…

metrics are

completely effective

Source: Forrester / Burtch Works survey of 170 analytic and measurement professionals

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Source: Q1 2014 Global

Cross-Channel Campaign

Management Forrester

Wave™ Customer Survey

…and analytics is an area of need for campaign managers…“Which of the following are the three most important areas that your

vendor could improve upon?”

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Source: The CMO Survey, cmosurvey.org, August 2013, Top Line Results

Does your company have the right

talent to fully leverage marketing

analytics?

…and analytics often fails senior marketers

14%say “yes” with

confidence

To what degree is your company

leveraging marketing analytics to

answer its most challenging

marketing questions?

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Copyright © 2016 Earley Information Science15

For example, “high bounce rate” can have multiple causes – Content does not meet the needs of the user

– The path to the content was not clear

– The user was in the wrong place

– The user experience led them down the wrong path

– Navigational labeling is misleading

– Search returned the incorrect results

– The user was not clear on what they wanted

Separating Signals

Metrics are signals that tell us to do something. The challenge is determining what the signals are telling us.

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Copyright © 2016 Earley Information Science16

• Different audiences will interpret metrics differently

• Stakeholders require metrics across the application ecosystem

Signals need to be surfaced in context

• Different systems will describe products, content, data and customers using attributes that have to be normalized

• Ownership and clock speed of tools and processes are sources of contention

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Copyright © 2016 Earley Information Science17

Contextualize Analytics through Customer Lifecycle

Profile customers

Evaluate leads

Target prospects

Analyze on site behaviors

Optimize search

Improve user experience

Evaluate promotions

Create cross sell relationships

Personalize offers

Optimize self service

Improve knowledge retrieval

Evaluate product usage

Analyze sentiment

Measure community engagement

Understand loyalty drivers

Stakeholders each have a specific perspective, tools, metrics, priorities

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Copyright © 2016 Earley Information Science18

Contextualize Analytics through Customer Lifecycle

Profile customers

Evaluate leads

Target prospects

Analyze on site behaviors

Optimize search

Improve user experience

Evaluate promotions

Create cross sell relationships

Personalize offers

Optimize self service

Improve knowledge retrieval

Evaluate product usage

Analyze sentiment

Measure community engagement

Understand loyalty drivers

Customer journey challenges can cause friction due to conflicting drivers

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Source: June 19, 2014, “How Analytics Drives Customer Life-Cycle Management” Forrester report

According to Forrester,

greatest opportunity lies in

latter stages of lifecycle

These are less well

understood by many

marketing organizations

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Copyright © 2016 Earley Information Science20

Good governance leads to greater ROI.– Search metrics

– Behavior metrics

– Utilization metrics

– Content metrics

– Response metrics

Effective Marketing Metrics Requires Governance…

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Copyright © 2016 Earley Information Science21

Marketing Metrics, KPI’s and Integration

Content Marketing

Email

Hubspot

SalesforceTwitterWebinars

Conferences

Executive outreach

LinkedIn

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Copyright © 2016 Earley Information Science22 Copyright © 2016 Earley Information Science

Poll Question #2

What are your biggest metrics challenges?

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Copyright © 2016 Earley Information Science23

Data quality and consistency

Technical integration across systems

Clarity regarding what metrics are most important

None of the above

What are your biggest metrics challenges?

a

b

c

d

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Copyright © 2016 Earley Information Science24

Works with clients and partners to extend their enterprise data architectures to support the challenges of Big Data, and deliver solutions for product recommendations, customer segmentation, and product MDM opportunities.

• 15 years experience driving large-scale content, MDM and BI initiatives

• SCRUM-Certified Senior Engagement Leader

• Solution Domains:

– Omnichannel Retail

– Biotech

– High-Tech

– Publishing

John Walker - Biography

John WalkerPrincipal

SemanticClarity

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Copyright © 2016 Earley Information Science25

• The collection of customer touch point data must be aligned with business goals

• Does data collection support prioritized business metrics?

• Apply governance and data quality checks

• Test the ‘Veracity’ of less trusted data - safely

• Ingest data at full fidelity– >Filter and Persist

• Leverage “Big Data” technologies and techniques to address the ‘Volume’, ‘Variety’, and ‘Velocity’

• Exploring Data Lake and EDW data will provide insights

Big Data / Data Lake Architectures – Collecting the Digital Customer Experience

“Digital initiatives should complement existing customer journeys. Many companies clumsily add digital components to customer journeys that don’t directly benefit the customer or are superfluous to the company’s value proposition. “

What a Great Digital Customer Experience Actually Looks Like , HBR Nov 2015

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Copyright © 2016 Earley Information Science26

Data Lake Architecture – a framework for collecting and processing the digital signal

The Data Lake – the data repository

• Governed and Compliant

• Support for data at “full fidelity”

• Controlled access to less trusted data sources

• Collection aligned to feed metrics

• Storage support for semi and unstructured data

Key framework features

• Process visibility and control

• Alignment with key metrics will focus technical options – simplify

• Support new and extensible schemas

• Processing “Elasticity”

• Data pipeline capability

– Ingest Analysis & Mining

• Support data discovery and visualization

Big Data / Data Lake Architectures – Collecting the Digital Customer Experience

Public or Hybrid Cloud

Data Lake

Enterprise Application

Portfolio

Enterprise Data

Warehouse

Data Exploration

BI and Legacy Reporting

Enterprise Network

Data Center

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Copyright © 2016 Earley Information Science27

Support metric tracking

• Data lineage x Source

• Cleanse / Enhance x Source

• Keep ML meta data

• Active data management

Big Data / Data Lake Architectures – Collecting the Digital Customer Experience

IngestPrepare /

SchematizeProcess / Analyze

Persist

Streaming Source Transform and

AnalyzeCleanse and

Enhance

Batch Source

Machine Learning

Explore and Visualize

Data Store

Data Protection

Authentification / Authorization

Page 28: Meaningful Metrics - Aligning Operational Metrics with Marketing & Customer Experience

Copyright © 2016 Earley Information Science28 Copyright © 2016 Earley Information Science

Poll Question #3

How well is your architecture supporting your metrics?

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Copyright © 2016 Earley Information Science29

Very well, architecture is well built and tuned

Getting by with what we have, could be better

Struggling to manage our data, not serving the need

What data architecture?!

How well is your architecture supporting your metrics?

a

b

c

d

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Copyright © 2016 Earley Information Science30

• Gerry helps large organizations become more customer centric on the Web. His commercial clients include Microsoft, Cisco, NetApp, VMware, and IBM. He has also consulted with the US, UK, Dutch, Canadian, Norwegian and Irish governments.

• He is the founder and CEO of Customer Carewords, a company that has developed a set of tools and methods to help large organizations identify and optimize their customers’ top online tasks.

• He has written five books on how the Web has facilitated the rise of customer power. The Irish Times described Gerry as one of five visionaries who have had a major impact on the development of the Web. In 2015, he was shortlisted for a Webby for his writings.

Gerry McGovern - Biography

Gerry McGovernCEO & Founder

Customer Carewords

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Copyright © 2016 Earley Information Science31

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Copyright © 2016 Earley Information Science32

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Copyright © 2016 Earley Information Science33

GOT THE HOUSING BLUES?

StartSaving!

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Copyright © 2016 Earley Information Science34

✓Traffic to product

pages increased by

520%

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Copyright © 2016 Earley Information Science35

Cisco’s Digital Presence

355Mvisits to Cisco.com

11.5Msocial reach

3.9Mpaid search click-

throughs

112Morganic search

referrals

40% 34%

71%

4%

10.7Mmobile web visits

1.4Msocial referrers to Cisco.com

3Msocial media mentions

5.7Mcustomer app

downloads

2.5Mvideo views on

Cisco.com

Social Media MobileWeb Video

7.5Mvideo views on Cisco

YouTube

47%

[Date Range: Q1FY14 – Q4FY14]

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Copyright © 2016 Earley Information Science36 36

Create a new guest account to access the Cisco.com website and log in with this new account.

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Copyright © 2016 Earley Information Science37

Jun 2015Dec 2014

22 mandatory and

optional fields

11 mandatory

fields

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Copyright © 2016 Earley Information Science38 Copyright © 2016 Earley Information Science

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Copyright © 2016 Earley Information Science39 Copyright © 2016 Earley Information Science

Panel Discussion

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Copyright © 2016 Earley Information Science40

Roundtable Discussion

Seth EarleyCEO

Earley Information Science

@sethearleywww.linkedin.com/i

n/sethearley

John WalkerPrincipal

SemanticClarity

www.linkedin.com/in/john-walker-

32b40117

Gerry McGovernCEO & Founder

Customer Carewords

@gerrymcgovernhttps://ie.linkedin.com/i

n/gerry-mcgovern-07876469

Dino EliopulosManaging DirectorEarley Information

Science

@deliopuloswww.linkedin.com/in/

deliopulo

Moderator

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Copyright © 2016 Earley Information Science41

Beckon White Papers & Reports

• http://pages.beckon.com/rs/beckoninc/images/The-Art-of-the-Marketing-Scorecard-Beckon-White-Paper.pdf

• http://pages.beckon.com/rs/beckoninc/images/Marketing-Funnel-Metrics-Beckon-White-Paper.pdf

• http://pages.beckon.com/rs/976-IET-418/images/Marketing-Measurement-Metamorphoses-James-Nail-Forrester-Report.pdf

• http://pages.beckon.com/rs/beckoninc/images/Forrester_Adopt_A_Staged_Approach_For_Marketing_Mix.pdf

EIS Blog

• http://www.earley.com/blog/enhancing-your-digital-customer-experience-analytics-and-insights

References

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Copyright © 2016 Earley Information Science42

Next ERT Topics

OK so Enterprise Search is "Janky" - Now what?

Predictive Analytics, AI and the Promise of Personalization

April 20th @ 1:00PM ET May 25th @ 1:00PM ET

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Copyright © 2016 Earley Information Science43

Earley Information Science helps organizations establish a strong information architecture

and content management foundation

Realize your digital transformation

vision with EIS.

Earley Information Science (EIS)Information Architects for the Digital Age

Founded – 1994 Headquarters – Boston, MA

www.earley.com

For more info contact:

[email protected]@earley.com