customer engagement in an omni-channel world
DESCRIPTION
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.TRANSCRIPT
Webinar, March 27, 2014
Customer Engagement in an Omni-Channel World
Introductions
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Our presenters have years of experience in different industries and countries
Rosie Poultney Alyson Kelly KayeProfessor, Bentley UniversityVice President of Analytics,
89 Degrees
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
The shift in theoretical strategy and understanding
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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
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%
Your digital data, and what it enables
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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 visitKatie 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 welcomeThat 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 experienceShe 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 skinand 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 afterAt 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 communicationOngoing, 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
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.
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
Maximize each interaction
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Traditional Customer Database
• Value and behavioral segments
• Price sensitivity and promotional behavior
• Demographics
• Preferences
EM/M CampaignsPersonalized,
encourage web visits
Web visitDynamic 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’.
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
What marketers should be asking
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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.comfor more information.