Using customer data to identify the best ways to engage is a well-established practice. Organizations routinely build propensity models using customer transaction data, demographics and contextual data. Findings from previous campaigns are then layered into the planning process. A more recent development is to mine digital interactions - open, click, search, login, social media connections - to create engagement metrics at a member level. No longer is a click simply part of a campaign KPI, it's part of a consumer's brand experience and informs subsequent communications and offers. This is part of Big Data that companies can't afford to miss out on.
89 Degrees is increasingly working with its clients to create engagement segments that, combined with traditional segmentations and scores, maximize the relevancy of offers and communications both scheduled and triggered in real time. In this session, Rosie Poultney, VP Analytics at 89 Degrees, will describe how digital data can be integrated.
The recent developments are also being addressed in academia. At Bentley, Professor Alyson Kelly Kaye teaches students in Advertising, Consumer Centric Marketing, Marketing Research and Promotional Strategies the importance of relevancy and the questions we should be asking internal teams and agency partners.
2. Introductions
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Our presenters have years of experience in different industries and countries
Rosie Poultney Alyson Kelly Kaye
Professor, Bentley UniversityVice President of Analytics,
89 Degrees
3. Overview
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Omni-channel marketing moves us from ‟push‟ to „dialogue‟.
Today we will discuss:
• The shift in theoretical strategy and understanding
• Your digital data, and what it enables
• What marketers should be asking
5. Customers want relevance
Best practice in customer marketing agrees with our experience
• Capturing the customer interactions with a brand, product or service,
allows us to distill the drivers of preference and, ultimately, purchase
Interactions are much more than just purchases
• Only way to start a 2-way dialogue is to allow customers to share
what is on their mind
49% of corporate decision makers are not using data to effectively
personalize marketing communications
• Customers want to be showered with attention, recognition,
friendship and service
39% do not update customer data or have ability to understand real-time
Source: Marketing ROI in the Era of Big Data: The 2012 Brite/Nyama Marketing in Transition
Study: 253 corporate decisions makers, director-level and above
6. They expect you to use their data
• Integrate information from different data sources to drive
the business through deeper consumer insight
• Understanding consumer life cycle within organization
helps to establish different contact points and develop
methods to engage at these stages in the relationship.
of decision makers lack sharing data
across organization creating obstacle
to measuring ROI of marketing51%
8. Katie‟s Journey in an Omni-channel world
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“Three hours of mall time” Katie says as she pulls into a parking spot. Checking in on Facebook she sees a sponsored
post from Glow* offering a free make-over. “Perfect timing! I‟ll look great when I meet my friends for lunch.”
Booking the visit
Katie downloads the store‟s app, logs
in with Facebook Connect, books a
convenient time slot, and heads
out to shop
o Katie receives a rich text message
15 minutes before her appointment,
showing the store location.
Registration and welcome
That evening, Katie completes the
registration. She connects using
Facebook and finds everything pre-
loaded. She completes her preferences
and signs up for emails
o She receives an email welcoming her to
the program and giving her a free gift –
20% off her foundation, plus free
shipping.
o Katie orders and picks two free sample
sizes from a list customized to her skin
type. “I could get used to this!”
The in-store experience
She walks into the store promptly and
finds the associate waiting. Katie is
pleased. She doesn‟t want to be late
for her friends.
o Katie loves the make-over. The new
liquid foundation feels great on her skin
and the eye colors work well with the
new top she bought
o She asks the associate to write down
all the products used. “I can do better
than that!”, Handing Katie the store’s
loyalty card, she scans the products.
“Complete the registration online – the
details will be there.”
Directly after
At lunch, her friends notice . “You look
fantastic!” they exclaim. Katie raves about
her experience. One is already a member
o “Take a look at their online service, I never
run out of product these days, and I get a
discount!”, she says
o Katie tweets a picture from lunch –
“Looking good with my Besties! Thanks
@Glow for make-over #LongTimeFriends
#PrettyEyes
Ongoing communication
Ongoing, Katie receives regular
communication.
o The monthly email newsletter has
relevant product, videos and new
beauty trends. She shares some
via Pinterest
o Today she received an invitation for
an event at the mall. She’s already
accepted it!
*Glow = fictional beauty and make-up store, for illustrative purposes
9. Website Stats
For example Google
Analytics. Summarized
information
• Visitors by source (paid or
natural search, direct,
referred, campaign codes)
• Time on site
Email Responses
From your email
platform. For every
email address and
campaign combination
• Received
• Opened
• Clicked
• Bounced
• Unsubscribed
Website Tracking
Either extracted directly
from your web site, or
provided by service
such as Omniture
• Cookie IDs
• Granular detail on
pages seen
• Campaign codes
• Sources
Digital data includes many parts
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Move beyond summary statistics to understand customers
at an individual level.
10. 9/209/189/129/89/1 9/28
Linking online and offline behavior
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• In this example
Unknown customer browses 32 pages on website. A cookie is installed on
their machine
8 days later they receive an unrelated loyalty email and click through to the
website. Their customer identifier from the email is now linked to the cookie
previously installed.
On-site behavior is now linked to purchases both on-site and in retail stores
• This is big data …. but don’t be put off
It‟s possible to subset fields to make it more manageable
11. Maximize each interaction
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Traditional Customer
Database
• Value and behavioral
segments
• Price sensitivity and
promotional behavior
• Demographics
• Preferences
EM/M Campaigns
Personalized,
encourage web visits
Web visit
Dynamic Content
influenced by historic
behavior and real-time
onsite activity Combine with offline behavior to enhance
customer understanding, flag indicators of
longer term purchases.
Create engagement scores and
individual response patterns across
time, product content, offer.
Remember, Omni-channel marketing moves us from ‟push‟ to „dialogue‟.
12. Immediate benefits
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• Expand product recommendations to be more than session-specific
Particularly important for products that need research
• Identify patterns which convert to purchase
We have seen hot spots where customers are 20 to 30 times more likely
to purchase, and usually offline, than the average visitor
Trigger programs
• Create engagement segmentations and scores to inform
communication and offers
14. The important questions
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• Can you distinguish between customer segments and use relevant messages
across multiple channels?
• How often do you use customer data to make marketing decisions? Are you
able to review the results of your marketing activity across campaigns?
• Do you collect and link data from multiple consumer touch points? Do you
include online and mobile?
• Does your ESP only provide summary campaign stats, or do you also get
responses at the email level?
• Are emails appropriately tagged? Can you recognize a customer when they
click through from an email? Can your IT infrastructure handle terabytes of web
tracking data?
• Do your emails display well on mobile?
Check out 89Degrees.com
for more information.
Hinweis der Redaktion
Aly
Aly – students understand that, and their generation expect relevancy.
Rosie – Data sources, what she is being bombarded
about the touch points that we can expect on the journey. They data behind and how it fits and facilitate in real time what we want to do with that data.
revamping slide
Data Sources – this is what we take back from what Robert’s choice girls name
Consistent clicking on certain business areas (both within an email and on the site)
Downloading of certain educational/preparation information (buying guides, warranty information)
Clicking “inquiries” on the site relative to services such as delivery
Complements is a program driven off purchase data for cross sell purposes. This is much more.
This is the part they might own, but they probably have not the skills in house to mine it properly. They probably have a recommender, but they are missing out on the bigger picture. This is exciting information and not scary once a strategy is created. The strategy needs to be consistently redefined, but the bigger picture is available.
Tracked customers don’t need to create an account to be recognized
You can tailor their experience based on historic behavior
Relevant versions of offers can be pre-loaded
One the client owns already and most understand what are doing currently.
Understand there is a lot of data and can view each independently as email is an example.
Too often email is batch-and-blast.
One-way communication, driving customers online or in-store to purchase.
Emails come from different parts of an organization
Often measured only in terms of open and click rates, usually for a single email
Rich source of information for understanding customer behavior
What marketers should ask, how to prepare your organization and ask the right questions.