The 10 Most Influential CMO's Leading the Way of Success, 2024 (Final file) (...
Email measurement is evolving...are you?
1. Data protection 2013
Email measurement is
evolving…are you?
Friday 8 February
Thursday 27 February 2014, TMW
#dmaiab
#dmadata
Supported by
Sponsored by
2. Agenda
9.00am
Registration and breakfast
9.30am
Welcome from the Chair
Guy Hanson, Director of Consulting, Return Path
9.40am
Marketing – Bringing out your inner geek
Matt Crole-Rees, Head of ECRM, Confused.com
10.10am
Interactive session
10.25am
What do I do with all of this data: beyond the noise of clicks and opens
Skip Fidura, Client Services Director, dotMailer
10.55am
Interactive session
11.10am
Summary
Guy Hanson, Director of Consulting, Return Path
11.25am
Close
Sponsored by
7. . . . But Now There’s a Lot More to Measure!
“Not everything
that can be
counted counts,
and not everything
that counts can be
counted”
Albert Einstein
9. Campaign Metrics
• Total:Unique ratio
• Unsubscribe:Complaint ratio
• Sign-up:Churn ratio
• Positive vs Negative clicks
• View web version
• Disaffection index
DMA National Email Benchmarking Report: October 2013 Edition
16. ROI Metrics
•
•
•
•
•
•
•
•
•
Attributable transactions
Responsiveness generated online
Value per individual email address
Value of email program
Customer acquisition cost
Marketing spend as % of CAC
Customer LTV as % of CAC
Payback on CAC
% customers who are marketing attributable
24. We face some big challenges
Low engagement sector
Insurance is a once a year purchase
PPC is getting more expensive and Google
dominates
TV, radio and other ATL media don’t come cheap!
Mobile is growing
People are lazy!
26. Measurement - The Holy Grail
All your channel tags in one area
All campaigns run through one platform
Track your customers everywhere they go
Know every action they take
Real time data and reporting across all products
Attribution model in place
MI in one place
27. Measurement - The Holy Grail
All your channel tags in one area
All campaigns run through one platform
Track your customers everywhere they go
Know every action they take
Real time data and reporting across all products
Attribution model in place
MI in one place
28. Where we’re at
Email marketing experts to run campaigns in house
Insight/BI function
Content/editorial team
Integration with customer support
A good ESP – Ebay Enterprise Solutions
Design resource
IT resource
Endless differing ways at measuring performance
29. What does it mean for us
Welcome new customers
Transactional emails
Renewal emails
Solus email campaigns
Fortnightly newsletters
Get the customer engaged in conversations
Reinforce our brand
35. How Reactive Are You?
Being first to market with new news is
key
ROI can more than DOUBLE
1. How quickly can you get a new
campaign out?
2. Is your ESP full service – chances are
you aren’t reactive enough
3. Do you have the right expertise
internally?
37. Subject lines – Your shop window
How long do you spend designing and building an
email?
How long do you spend on subject lines?
38. Lessons to live by
Geeks are cool
Content is king
Personalise what you can
Mobile has arrived and evolving
Make time for subject lines
Track what you can – you may learn more than you
think
41. What do I do with all of this data:
beyond the noise of clicks and
opens
Skip Fidura, Client Services Director, dotMailer
#dmaiab
Sponsored by
42. What do I Ido with all this data? ?
this data
What do do with
It’s NOT “Big Data” – it’s Smart Data
It’s NOT “Big Data” – it’s Smart Data
Skip Fidura
dotMailer, Client Services Director
43. It’s Retail But Not As You Know It
• Stock and product mix changes weekly
• Cost of stock changes after it is “on the shelves” and
can even change after the product has been sold
• Products cross traditional demographic buckets
adding to selection and segmentation complexity
… but like retail ODEON generates literally tons of data.
44. Leveraging Customer Behaviour
• >2 Million members of the loyalty program – Odeon
Premiere Club
– Launched 5 years ago
– Booking data – Online and box office
– Retail Data
• >2M CRM customers – Online booking data only
• Other Customer Data
–
–
–
–
14 Million ‘unique’ ticket buyers with booking data
Social media interactions
Guest Service contacts
Web browsing activity
45. Big Data
• Not new – companies have always had loads
• Technology now makes it seem feasible but
companies face two big risks:
– Organising the data into something usable
– Reluctance to act before finding the perfect
solution
46. Big Data – Two Approaches
1. Take a lot of data and do loads of analysis
on it
• Really big job which can stall because of risks
above
• Long delay between investment and payback
2. Define what you want to achieve
• Breaks the task down into bite size chunks
• A series of quick iterative wins
47. Find The Audience For The Film
Genre
Cinema
Actors
Director
Writer
Producer
Crew
Format
Certificate
Customer
Preferences
Information
about the
Films
Purchase
and Click
Behaviour
Ticket type
Seating
Quantity
Date
Time
Screen
Performance
Channel
Promotions
Member type
Engagement
Food
Drink
50. The Business Case of Segmentation
Incremental Revenue
Fill Your
Boots
Cost of Segmentation
51. How ODEON Are Working
• What are the goals for the business
– Get more visitors more often
– Sell more retail
• Work backwards to determine what the email
has to deliver
52. The ODEON Approach
• RFV flags for each record
• Segmentation based around high level behaviour
–
–
–
–
New
Inactive
Unusable
Active
• Models to help improve targeting based on film
54. Exploring Relevance
• Blockbuster film, but not a
traditional ‘ODEON film’
• ‘Set reminder’ campaign 3 months
from opening
• Father’s Day campaign
– Segmented base by cinema preference and
bookings
– Drive advance book
– Segmented into IMAX, ISENSE, Gallery, The
Lounge, Croma and default 3D content
• Over 20K incremental bookings
• Market leader for the film
55. Growing The Audience
• Good film performance on opening
but wanted to improve
• Targeted genre specific IMAX
audience
– Targeted BFI audience, and London
and home counties with BFI message
– Used first weekend booking data in
correlation model to target new
members
– Overlay with IMAX up sell message for
members who had never seen the
format before
• ODEON jumped to no1 in second
week
56. We Do More Than Films
• Live screenings of London theatre
and other cultural events
• 2013 Stephen Fry played Malvolio
in The Globe’s Twelfth Night
• Email sent to OPC members to drive
advance book:
– an interest in cultural events
– previously attended a cultural event
– film correlations
• High response led to 18 new
cinemas being added
• Further email push drove bookings
and share
57. Why dotMailer?
• Consolidated Data Base
– Email and purchase data merged into a single platform
– Dramatically reduced campaign set-up and data selection turn around
times – Data selections that used to take four days can be completed
in 6 minutes
– Opportunity to focus on using their data productively
• Automation functionality around segmentation,
content tailoring and campaign sending
• Usability – The team that found it complicated to
brief are now able to do it themselves – Test, Trial
and Think About It
58. What’s Next?
• Overcoming reliance on blockbuster films
– Build entire programs around the release calendar
– Group releases together into a slate of films and promote
the whole slate throughout the year
• Looking at the people that are falling outside of the
segments – email is all inclusive
– Who are they
– Why are they not receiving email
– What should we say to them
59. What’s Next?
• Marketing Automation
– A lot of what we want to say does not change from
campaign to campaign
– The more we can automate the more we can focus on
strategy rather than execution
– Customers’ “pulling” content based on their behaviour on
web, social, purchases, etc. supplemented by push
content
60. What’s Next?
• Using the “Big Data” to drive the business not just
marketing campaigns
– Traditionally marketing or sales come up with propositions
– This gut instinct is still important but should be combined
with data
• More offering around occasions like date night
• Deciding which films to program and use the data as leverage over
the distributors
