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Using Engagement Data To Drive Mul4channel Relevancy
#mul%channel Webinar Sponsored by
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About Retail TouchPoints ü Launched in 2007
ü More than 25,000 subscribers
ü Provide executives with relevant, insightful
content
ü Free Resources such as White Papers, E-book,
Webinars, Research and Podcasts
www.RetailTouchPoints.com
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BrightTALK
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Today’s Panelists
Alicia Fiorletta Associate Editor Retail TouchPoints
MODERATOR
Ken Blake Senior Vice President, Analytic Consulting Group Harte-Hanks, Inc.
USING ENGAGEMENT TO DRIVE MULTI-CHANNEL RELEVANCY KEN BLAKE, SENIOR VICE PRESIDENT HARTE-HANKS ANALYTIC CONSULTING GROUP
BIG DATA BRIDGES THE GAP BETWEEN GUT MARKETING AND TARGETED CUSTOMER ENGAGEMENT PROGRAMS THAT GENERATE MEASURABLE ROI
7
8
CHANGING LANDSCAPE
Consumers seek a quality/price value equation – makes meeting individual needs challenging…
…There’s a multitude of communication channels to choose from
How consumers interact with these platforms is dynamic — and trends are constantly shifting…
9
Automated Pre-Processing of Standardized Files (ETL)
Custom Data Management Processing (see next slide for details)
Post CDM & Transaction Processing in the ODS (Operational Data Store)
Daily Processing for Fulfillment and Thank You Emails for Hand-raisers
Weekly Trigger Files: § Welcome DM § Welcome Email § Thank you Email
Quarterly Cross-country Extract
Weekly High Mileage Extract
Ad-hoc MPN Email Notification
Weekly Sirius File
Analytic Users
User Authentication
THE NEW NORMAL
Email Response Data Web Events Call Center Survey Sales Data
Vendor Firewall
PGP
HH Firewall
Email Blasts
Reporting
Direct Mail Campaigns
Ad-Hoc Extracts FTP Service Data CRM a methodology and discipline to manage interactions through the application of technology that
organizes and automates marketing processes
— offers a truly effective means to navigate these new dynamics and execute against the fearless pursuit of the consumer
10
AN APPROACH LEVERAGING NEW TECHNOLOGIES
Making it easier for customers to share opinions…
CRM Methodologies
Consumer Enthusiasm &
Brand Love
…applying what is learned to engage directly and meet individual needs
Customer Relationship
Marketing
11
SIGN OF CHANGE - 1990S
FROM DANCING…
12
SIGN OF CHANGE – 2010+
… TO CAPTURING AND SHARING
13
WHY BIG DATA
It’s about the 4 V’s…
VOLUME VELOCITY VARIETY
…AND ABOUT DOING IT AT SCALE
VERACITY
14
BIG DATA FOR MARKETERS
DATA ONBOARDING Ease and efficiency of integra%ng raw data and turning it into insight. Transforming raw data into %mely insight is the core of a good BI strategy.
AGILE ANALYTICS Faster Insight, Be;er Decisions through high speed analy%cs via high quality data and solid data management techniques.
ANALYZING DATA AT SPEED AND SCALE Be;er business performance by analyzing large volumes of accurate data in a shorter amount of %me.
SELF SERVICE EXPLORATION PuOng data explora%on tools & drill-‐down capabili%es directly in the hands of end users allows for quickly answering ques%ons and removes the burden from IT.
15
Content Consumption Browsing Behavior
Product Spend
Reviews Sales Transactions
Abandoned Carts
Social
ENGAGEMENT IS THE KEY
16
OBSERVING A TREND
Top RFM Segments
Recent Buyers
Top Model Scores
Most Recently Engaged
Our best purchasing segments had the best engagement rates
Engaged customers spend 2-4x more than unengaged
17
SINCE ENGAGEMENT IS TIED TO SALES
Then we will: • Expand our universe of potential buyers • Develop contact strategies to create and then increase engagement (in addition to
sales) • Track and migrate customers across more interactions
If we can…
Make the unengaged consumer engaged
Make the less engaged more
engaged
Generate more engagement
points to supplement
purchase
Keep selling but also focus on
engaging
18
ENGAGEMENT MODEL CONCEPT
JAN 2011 DEC 2011
JAN 2008 DEC 2011
A response model works well when purchases are frequent…
…but many brands are purchased infrequently due to the nature of their products
For a High Frequency brand, this is an Attriter For other brands, this could be a Best Customer Difficult to tell an Attriter from a Best Customer
19
ENGAGEMENT CAN BE HIGHLY PREDICTABLE
The top decile exhibits a level of engagement 2.5 times higher than the average The lift ratio from the top to bottom decile is 15 times
Average = 1.08%
.00
.50 1.00 1.50 2.00 2.50 3.00
1 2 3 4 5 6 7 8 9 10
Leve
l of E
ngag
emen
t
Decile
20
DATA ACQUISITION STRATEGY
• Start small and do it well – if you aren’t effectively using the basic data you have, adding more is rarely the answer
Registration Data
Data Today
Promotion History
Segments, Geography, Tenure, Opt-in
Desired Data Promotion History
# of contacts # click/opens # registrations
Purchase History RFM, 1st purchase , tenure, source of
purchase, migration paths, time between purchase , purchase based segmentation
schemes and predictive models
Web Browsing Behavior Last session, categories/products browsed,
number of sessions in past month
Models Custom
built
3rd Party Data
Engagement Registrations, preference center
completion and updates, customer care, social
engagement
Mosaic Clusters
Control Groups Camp and
Frozen
Social Data
Segmentation RFM, Lifestage, Engagement, Cross-shop
Research/NPS/ Reviews
Longitudinal Studies, share of wallet, did you eat, NPS
21
THE RIGHT MESSAGE AT THE RIGHT TIME
Using enhanced CRM principles, marketers will better…
Develop and execute plans to
interact with consumers in a way that delivers what they need, when they need it and how they want it
Apply the right staff
resources, business process,
technology and data content
Understand and predict current and potential
customer needs & behavior
patterns across all channels
Transform data and
analysis into business
intelligence
Leverage the channel mix to
most effectively interact with
consumers at points of
exploration, consideration &
decision
PUTTING ENGAGEMENT DATA INTO ACTION
Real World Applications of Big Data
23
APPLICATION 1: LEVERAGING A HOLISTIC VIEW OF CUSTOMER BEHAVIOR
Customer Product Engagement Score (PES)
Category Purchasing
Sum of Total Net Spend in Product
Category
Total Number of
Product Items
Purchased
Total Number of Transaction
s that Contain Product
Category Web
Browsing
Total Number of Days that a
Product was
Browsed
Total Number of Times that a Product
was Browsed
Category Online
Abandon Cart
Total Number of
Times a Cart is
Abandoned that
Contained Product
Total Number of Products
Items Abandoned
Category Post
Reviews
Total Number of
Positive Products Reviews
50% of the Total
Number with
Negative Reviews
SEEING A CUSTOMER’S FULL SHOPPING EXPERIENCE CAN OFTEN BE MORE VALUABLE THAN SEEING ITS OUTCOME
24
APPLICATION 2: OPTIMIZING THE PURCHASE DECISION CONTINUUM
A CUSTOMER’S LOCATION ON THE DECISION CONTINUUM IS CRITICAL FOR DETERMINING THE APPROPRIATE MESSAGING STRATEGY
Learning Evaluating Deciding Buying
Strategy: Provide information, keep
warm, monitor
Strategy: Establish comparative
benefits
Strategy: Provide stimulus to act
Strategy: Reinforce decision,
facilitate the transaction
25
APPLICATION 2: OPTIMIZING THE PURCHASE DECISION CONTINUUM
BIG DATA CAN BE CAPTURED AND MODELED TO SEAMLESSLY & CONTINUOUSLY PLOT CUSTOMERS ALONG THE CONTINUUM
Learning Evaluating Deciding Buying
Engagement Activity
Transaction Activity
Content Consumption
Social Activity
26
APPLICATION 3: DRIVING RELEVANCY AND MAPPING THE BEST ENGAGEMENT PATH
AT EACH SUBSEQUENT STAGE OF THE CONTINUUM THE PICTURE OF THE CUSTOMER BECOMES MORE CLEAR AND, THEORETICALLY, OUR ABILITY TO SPEAK TO THEM RELEVANTLY SHOULD IMPROVE...
Learning Evaluating Deciding Buying
27
APPLICATION 3: DRIVING RELEVANCY AND MAPPING THE BEST ENGAGEMENT PATH
…HOWEVER, IT IS CRUCIAL TO UNDERSTAND HOW THE CONVERTED CUSTOMER IS MOVED ALONG THE CONTINUUM – AND HOW THIS MOVEMENT CAN BE FOSTERED WITH A POSITIVE BRAND BIAS
Learning Evaluating Deciding Buying
How does their engagement differ? What can we impact?
Customer purchases a competitive brand
Customer purchases the brand
28
APPLICATION 4: DRIVING LOYALTY AND ADVOCACY
THE CONCEPT OF “BEST” ENGAGEMENT PATH CAN ALSO BE USED TO FOSTER POSITIVE MOVEMENT ALONG A PATH TO LOYALTY OR ADVOCACY
First Time
Customer Repeat
Customer Loyal
Customer Advocate
Customer becomes a brand advocate
Customer’s progression stops short of loyalty
How does their engagement differ? What can we impact?
29
Dedicated and skilled employees
ROADMAP TO SUCCESS An organizational culture that values fact-based research and decision-making
Successful data management strategies include the following crucial elements
Ultimately striving for faster and more agile analytics
Starting with the data you have and grow it over time
Technology tools to ensure large volumes of data are accurate, consistent and easily accessible
An organizational willingness to test and learn
Management support and adequate support
30
THANK YOU
Ken Blake
Senior Vice President, Analytic Consulting Group
Harte-Hanks, Inc.
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Q&A // Submit Your Ques%ons
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Thank You For Joining Us!
Download the slides from this presenta4on:
http://rtou.ch/multichannel-web