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Marketing Cloud How to Derive Insight from your Social Media Data
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Page 1: How to Derive Insight from Your Social Media Data

Marketing Cloud How to Derive Insight from your Social Media Data

Page 2: How to Derive Insight from Your Social Media Data

Kraft Brand Buzz Challenge!Tweet the correct rank order to #dfinsight J, O, E, L

Tweet the letters in the right order �e.g. JOEL #dfinsight

Page 3: How to Derive Insight from Your Social Media Data

Tom Webster

VP, Strategy Edison Research

@webby2001

Jolanta Oliver

Assoc Dir Consumer Relations, Kraft Foods

@jolantaoliver

Neil Crist

Founder, Venuelabs @neilcrist

How to Derive Insight from your Social Media Data

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Does anyone tweet about brands besides people who work in marketing, advertising, PR or Social Media?

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Big Data is seductive.

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Pre-Iowa

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How many of you tweeted about the ads?

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What is the number one beer in America?

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1. Who are you “sampling?”

2. Who aren’t you sampling?

3. Where are your customers?

Three Questions:

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Jolanta Oliver Kraft Foods

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Who uses data @Kraft?

Consumer Relations Insights Marketing / Agency Analytics

Listening / Monitoring

Customer Satisfaction

Issue Management

Workflow Routing

Product Development

Survey Research

Customer Deep Dives

Customer Journey / Map

Competitor Intelligence

Platform Management

Planning & Targeting

Engagement

Consumer Profiling

Campaign Management

Predictive Analytics

Measure Target Response

Brand engagement

Link to Offline Sales

360° Consumer Database

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Key Metrics

Volumetric

Posts – ‘Buzz’ Share of Voice Likes / Fans Reach Demographics Geo-location

Consumer Behaviour

CATEGORY BEHAVIORS Usage Frequency Form / Flavors Brands Occasions

LIFE BEHAVIORS Hobbies & Interests Employment Entertainment

Consumer Attitudes

Sentiment / Passion Engagement Influence Intent to buy Attitudinal Segmentations

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How we Calibrate

Call Center

Qualitative Research

Quantitative Research

Social Data

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Campaign Analysis: Reaching the Target

834% change for U35s

Before During

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35

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Neil Crist VenueLabs

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Consumer content with geo-location

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Consumer content with geo-location • Mobile consumers leaving 4.1 billion activities & messages

monthly. • XX% are at a place of business • ~5% have photos • ~20% have distinct sentiment/mood (+/-)

• Geo tagged content will surpass non-geo consumer content in the next 24 months.

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Cross Signal Calibration is Critical •  Consumer channels >50 per location

•  Difficult to anticipate which channels are most active

•  True understanding comes through holistic listening across channels

•  Profiles are created by consumers

•  Traditional social media tools do not surface this content

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Location-based is Powerful “Last Mile” of Context

“What are my customers saying at the point of purchase?“

“When our reputation is in trouble, how can I identify the source issue?”

“What new channels are my customers engaging with by brand on?”

“Which of my locations produce the best customer experience?“

“Where can I best invest marketing dollars and reach the right audiences?”

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•  Franchise Brand, 250 Locations

•  Execute National Campaigns with local execution by franchisees

•  Local measurement insures marketing compliance and provide understanding local ROI

•  Found 1 metro area with 4x the return on campaign

•  Analyzed and found they did not follow campaign program, but produced a better experience.

“With local listening and measurement, we found one franchise owner that was seeing 4x return on campaigns.”

- Steve S., Director of Marketing

Case Study: Local Marketing ROI

250 Location QSR Identifies New Marketing Opportunities

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•  Over 900 locations

•  Found repeated patterns of improper cleaning of pumps

•  Discovered patterns of blocking customer purchases

•  Identified facility cleanliness and safety issues

•  Identified staff and managers that needed to be let go.

“We found that staff were not being properly trained, and it was costing us significant revenue every day.”

- John J., Regional Manager, West Stores

Case Study: Staffing, Customer Experience, Revenue

National Convenience Store Operator Identifies Staff Training Issues

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•  90 Locations in 7 states, 3 countries

•  Ran Groupon for all locations

•  Sold out, high positive buzz

•  On fulfillment, found local customer sentiment issues following 3-4 weeks

•  Identified trouble stores, customer miscommunications

•  Net impact to sentiment was more negative long term

“There is more to the daily deal than the day of the deal. We followed customer sentiment at our stores for weeks after to discover what customers really thought.”

- Julie T , VP of Marketing and Operations

Case Study: Measuring Daily Deals

Learned the Short-term and Long-term Impacts of Daily Deals

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Tom Webster

Founder, Edison Research @webby2001

Jolanta Oliver

Assoc Dir Consumer Relations, Kraft Foods

@jolantaoliver

Neil Crist

Founder, Venuelabs @neilcrist

Page 46: How to Derive Insight from Your Social Media Data

Kraft Brand Buzz Challenge!Tweet the correct rank order to #dfinsight J, O, E, L

Tweet the letters in the right order �e.g. JOEL #dfinsight

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Marketing Cloud Product Keynote

David Fischer VP, Advertising

Babs Rangaiah VP, Global Media Innovation

Scott Monty Head of Social Media

Turn Insight into Action with the Salesforce Marketing Cloud

Where: Moscone Center South Main Keynote Room

When: Thursday September 20th 1:30 to 2:30 PM

Customer Speakers:

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Win A 2013 Ford Fusion Hybrid! 1. Attend Marketing Cloud Keynote Thursday 1:30 PM for entry form.

2. Redeem in the Campground by 3:30 PM on Thursday.

3. Get an #awesome Marketing Cloud tee-shirt!

4. Winners announced Thursday at 3:45 PM! Need not be present to

win. Image for illustrative purposes only

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Learn more at salesforce.com/marketing-cloud