Beyond Reach: The Critical Facebook Metrics You Should Measured [webinar deck]
4 key facebook metrics you should be using right now social media week 2013
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Transcript of 4 key facebook metrics you should be using right now social media week 2013
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4 Key Facebook metrics you should be using right now (and a few other :ps…)
#smw4keymetrics @gravitythinking
Gravity Thinking, Emerson Studios, 4-8 Emerson St, London SE1 9DU T 0203 7143000 E [email protected] W gravitythinking.com
FB http://facebook.com/gravitymarketing TW http://twitter.com/gravitythinking
LI http://linkedin.com/company/gravitythinking
Specialist Digital, data and social media
Accountable Data driven and attribution
focused
Independent
5 Years – 25 technologists, strategists & creative thinkers
Partnered Technical, development and
Social
Discipline in digital
Building brand equity through digital and social marketing
About Gravity Thinking
3
Facebook insights goes some of the way….
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….and the export data spreadsheet can take you all the way….
…but what do you look at and what does it mean ?
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1. Organic post reach
Facebook’s Defini/on: Life:me The number of people who saw your Page post in News Feed or :cker, or on your Page’s Wall. (Unique Users) Where to find it: Facebook Insights Post Level, Key Metrics Sheet, Column I Best expressed: as a % = total organic reach / no of posts= average organic reach per post then divide by total number of fans = 12-‐15% Why is it important ? It tells you how well Edgerank rates your posts
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1. Organic post reach
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1. Edgerank
Tip: Use a ruler. Make sure you measure content performance so you know what works best for your audience.
It all starts with your content. Your posts need to have the polish of an ad and be conversa:onal enough to engage people. Not easy.
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Tip: Mix it up. Typically only 12% – 15% of your audience will be shown your content organically, so make sure you design for different audience segments.
Facebook’s EdgeRank decides whether or not your content will be seen in your Fans’ News Feeds.
1. Edgerank
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Fans can take both good and bad ac:ons. That helps EdgeRank decide to show your content to more, or fewer, of your Fans.
Tip: Look for the bad news. Seeing posi:ve stuff is easy, but people hiding or spamming your posts can kill your organic reach.
1. Edgerank
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Tip: Don’t throw good media dollars on poor content. ‘Nuff said.
Aier crea:ng great content, here is your second key lever. Making a “page post ad” shows your content to a lot more of your Fans.
1. Edgerank
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Tip: Ask for the sale. Use crea:ve CTAs that encourage people to share your content.
Now here’s where things gets tricky… When your fans take posi:ve ac:ons, it generates “stories” and EdgeRank decides which of their friends see them.
1. Edgerank
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Tip: Double down. If you see a post is working really well, consider targe:ng non-‐fans with your page post
Their friends see the content in their News Feeds and can also take ac:ons, driving EdgeRank again (or not).
1. Edgerank
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Tip: Put your best foot forward! Test and learn to find the right budget, :ming, and targets for Sponsored Stories.
Here is your third lever. Make a good thing even beoer. Use Sponsored Stories to amplify Fans’ posi:ve engagement and show content to more of their friends.
1. Edgerank
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1. Edgerank
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• Measure content performance • Design content for different audience segments • Watch all user ac:ons, including the nega:ve ones • Spend media dollars wisely • U:lize CTAs • Target non-‐fans with strong content • Only amplify your best content
…….so to make Edgerank work for you remember
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Facebook Dashboarding -‐ how it works
Accepts Permissions
Social Performance Dashboard Deep Data Your Content Your Audience Your Performance
Scoring algorithms deliver real-time
measurement
✓
Audience Segments
Export: Direct
Marketing & CRM
PageScore
PostScore
PeopleScore
Engagement
100m Data Points per 100k Users
• Real-‐:me Dashboard • Jane is in the highly engaged Passionate Urbanite
segment; allowed email match-‐back Monthly Subscription API
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PageScore
447 DASHBOARD FEBRUARY 2013
PUBLISHING ACTIVITY AUDIENCE GROWTH
AVERAGE REACH CONTENT AMPLIFICATION (VIRAL FRIENDS OF FANS)
AVERAGE ORGANIC POST REACH AVERAGE POST RESPONSE
Offers
0 Ques:ons
0 Text Posts
0 Link Posts
0 Events
0 Photo Posts
25 Video Posts
1 Total Posts
26
370K
1,587K
3,309K 4,315K
2,122K 1,986K 14K
22K
236K
139K
298K 37K
27K
30K
53K
106K
74K 48K
0K 500K 1000K 1500K 2000K 2500K 3000K 3500K 4000K 4500K 5000K
Sep Oct Nov Dec Jan Feb
Organic Viral Paid
FAN ENGAGEMENT
5%
10%
35%
25% 27% 27%
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
Sep Oct Nov Dec Jan Feb
704K 752K 795K 863K
946K 995K
0K
250K
500K
750K
1000K
Sep Oct Nov Dec Jan Feb
5.2%
4.29% 4.58%
7.50%
13.44%
8.26%
7.46%
0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
14.00%
16.00%
Sep Oct Nov Dec Jan Feb
1.06% 1.15%
2.39%
3.20% 3.11%
1.21%
0.00%
0.50%
1.00%
1.50%
2.00%
2.50%
3.00%
3.50%
Sep Oct Nov Dec Jan Feb
14.83
9.73
42.54
30.51
40.05
7.56
0
5
10
15
20
25
30
35
40
45
Sep Oct Nov Dec Jan Feb
AUDIENCE BEHAVIORAL SEGMENTS
35.48%
0.14%
43.89%
16.67%
3.82%
0% 20% 40% 60% 80% 100%
Storytellers
Advocates
Consumers
Likers
Cynics
POST SUMMARY FEBRUARY 2013
AVERAGE ORGANIC POST REACH AVERAGE POST RESPONSE AVERAGE POST DECAY (HOURS)
AVERAGE STORYTELLER ACQUISITION AVERAGE NEGATIVE RESPONSE AVERAGE POSTSCORE
18.59%
8.79%
6.30% 7.26%
3.45% 3.56%
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
Sep Oct Nov Dec Jan Feb
2.39 2.42 2.64 2.70
2.92 2.58
0
1
2
3
4
Sep Oct Nov Dec Jan Feb
252 138
795
461
648 638
-‐
100
200
300
400
500
600
700
800
900
Sep Oct Nov Dec Jan Feb
9
17
11
13
8
10
0
2
4
6
8
10
12
14
16
18
Sep Oct Nov Dec Jan Feb
PUBLISHING ACTIVITY BY POST CONTENT PUBLISHING ACTIVITY BY MEDIA TYPE
Budge:ng
1 Card Edu.
3 Entertain.
5 Gen Lifestyle
7 Shopping
2 Tab Promo
7 Tips
1 Total Posts
26
Promo
9 BPV Either/Or
4 Quote
1 Royalty Free
0 BPV Fill-‐in
4 Brand Poster
Photo
6 Brand Poster
Illus.
1 Total Posts
25 By Promo vs Non-‐Promo By Audience Segment
10
16 15
5
6
Travel
Outdoor
Food
Non-‐Promo
Promo
4.29% 4.58%
7.50%
13.44%
8.26% 7.46%
0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
14.00%
16.00%
Sep Oct Nov Dec Jan Feb
1.06% 1.15%
2.39%
3.20% 3.11%
1.21%
0.00%
0.50%
1.00%
1.50%
2.00%
2.50%
3.00%
3.50%
Sep Oct Nov Dec Jan Feb
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2. Post response
Facebook’s Defini/on: Life:me The number of people who clicked anywhere in your posts. (Unique Users) Where to find it: Facebook Insights Post Level, Key Metrics Sheet, Column P Best expressed as a % of people that ‘interacted with a post” = ‘Lifetime Engaged User” / “Lifetime Post Total Reach” Why important ? Shows how well people react to your content and if you use paid content posts that drive engagement are worth weight in gold
Posted Lifetime Post Total Reach
Lifetime The number of people who saw your Page post. (Unique Users)
9/20/13 5:56 AM 5538
Lifetime Engaged usersLifetime The number of people who clicked anywhere in your posts. (Unique Users)
278
20
2. Important elements of post response
Timing
Targe:ng
2. Important elements of post response
Copy
2. Important elements of post response
Assets
POSTSCORE ANALYSIS FEBRUARY 2013
0.00
0.00
3.10
2.30
1.80
2.75
2.90
0 1 1 2 2 3 3 4 4
Offers
Events
Ques:ons
Videos
Link
Text
Photo
BY TYPE BY CONTENT BY MEDIATYPE
BY AUDIENCE SEGMENT BY PROMO VS NON-PROMO BY TIME AND DAY
3.10
3.60
2.80
2.40
3.15
2.90
3.20
0 1 1 2 2 3 3 4 4
Ques:on
Fan Thanks
Curated
Promo
This or That
Fill In
Seasonal
3.35
2.75
3.10
0 1 1 2 2 3 3 4 4
Outdoor
Travel
Food
2.40
3.35
0 1 1 2 2 3 3 4 4
Promo
Non-‐Promo
2.58
2.60
2.44
2.67
2.33
2.66
2.75
0.00
0.00
3.26
3.33
2.38
2.67
0.00
0.00
0 1 1 2 2 3 3 4 4
Sunday Saturday
Friday Thursday
Wednesday Tuesday Monday
10PM -‐ 12PM 6PM -‐ 10PM 2PM -‐ 6PM 12PM -‐ 2PM 9AM -‐ 12PM 7AM -‐ 9AM 5AM -‐ 7AM 12AM -‐ 5AM
3.75
2.80
2.90
3.15
2.90
3.30
2.90
0 1 1 2 2 3 3 4 4
Snipgraphic
Img Frame
Watermark
This or That
Fill In
4 Up
Quote
POST PERFORMANCE – POSTS 1 - 3 of 28 FEBRUARY 2013
POSTSCORE 4
TYPE Photo
MEDIA TYPE Promotional
CONTENT TYPE Tab Promo
PROMOTIONAL Yes
RESPONSE RATE 4.7%
SHARES 3,069
COMMENTS 318
LIKES 19,634
NEGATIVE % .14%
POSTSCORE 3.33
TYPE Photo
MEDIA TYPE Promotional
CONTENT TYPE Card Education
PROMOTIONAL Yes
RESPONSE RATE 4.4%
SHARES 246
COMMENTS 58
LIKES 6,946
NEGATIVE % .37%
POSTSCORE 3.33
TYPE Photo
MEDIA TYPE Best Practice; Fill-in-the-blank
CONTENT TYPE Entertainment
PROMOTIONAL No
RESPONSE RATE 5.3%
SHARES 116
COMMENTS 255
LIKES 1,938
NEGATIVE % .74%
a AudienceArc February 24 a AudienceArc
Kick off your shoes off and start enjoying the great weather!
February 3
I like my steak with a side of _________!
a AudienceArc
Make sure you set your payday priorities!
February 15
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3. Stories
Facebook’s Defini/on: A ‘story’ is an ac:on that can be seen by a user’s friends. For posts, stories are generated by ‘Likes’, comments and shares. Where to find it: ‘Life:me Post Stories by ac:on” Tab Best expressed: Count ‘Likes’, comments and shares on a post on your :meline – not all are equal – create a weighted engagement score Why important ? Balance lightweight engagement, brand relationship and advocacy
3. Stories -‐ products
3. Stories – heritage / AiR
3. Stories -‐ dis:llery
3. Stories – Highland Games
80% 79% 87%
80% 76% 73%
17% 18% 11%
17% 20% 21%
3% 3% 2% 3% 4% 6%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Sep Oct Nov Dec Jan Feb
STORYTELLER SUMMARY FEBRUARY 2013
AVERAGE ENGAGEMENT FREQUENCY (STORIES) AVERAGE PEOPLESCORE
AUDIENCE ENGAGEMENT FREQUENCY (NUMBER OF ENGAGEMENTS)
STORYTELLER VALUE SEGMENTS STORYTELLER GROWTH
High Value
1% Medium Value
37% Low Value
61% Storyteller Value Segments
31%
69%
Gender Breakdown Top 5 Countries
1 United States – 91% 2 La:n America – 6% 3 United Kingdom – 1% 4 Spain – 1% 5 France – .1%
2.20 1.94 2.00
1.85 1.74 1.70
0
1
2
3
Sep Oct Nov Dec Jan Feb
Female
Male
5 or more :mes 2 to 4 :mes Once
RE-‐ENGAGED STORYTELLERS
1.11 1.10 1.12 1.19 1.32 1.27
0
1
2
Sep Oct Nov Dec Jan Feb
815 775 1,552
6,293 6,598
12,220
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
Sep Oct Nov Dec Jan Feb
1.50%
2.04%
4.95%
6.35% 7.94%
9.19%
0%
2%
4%
6%
8%
10%
Sep Oct Nov Dec Jan Feb
TOP STORYTELLERS FEBRUARY 2013
PROFILE PIC
NAME TYPE ENGAGEMENT FREQUENCY FIRST SEEN
LAST SEEN
INFO LEVEL
MATCH BACK
PEOPLE SCORE
Jane Smith Storyteller High High 7/27/12 2/26/13 Basic ý 4.00
Jane Smith Storyteller Medium High 7/30/12 2/26/13 Extend þ 4.00
Jane Smith Storyteller High Medium 8/13/12 2/26/13 Basic ý 4.00
John Smith User Medium Medium 10/7/12 2/27/13 Basic ý 4.00
Jane Smith User Medium Low 11/13/12 2/26/13 Extend þ 3.50
John Smith Storyteller Low Low 11/17/12 2/26/13 Extend þ 3.40
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4. Nega:ve responses
Facebook’s Defini/on: Life:me The number of people who have given nega:ve feedback to your post, by type. (Unique Users) Where to find it: ‘Life:me Nega:ve Feedback” Tab Best expressed: Add total nega:ve ac:ons and divide by the number of unique users reached by the post (on ‘Key Metrics Tab” the “Life:me Post Total Reach” Why important ? If puvng paid spend need to track in real :me – benchmark average nega:ve feedback – due to content or off ad targe:ng (eg non fans)
Food for thought……
34
CUSTOMER
DEMOGRAPHICS Name: Jane Smith Age: 32 Birthday: Nov 13, 1980 Gender: Female Family: Married Education: MBA College: Dartmouth Major: Economics Home: San Francisco, CA Hometown: Bloomfield Hills, MI Country: USA Employer: Oracle Position: Sales Director Language: English, French
INTEREST GRAPH BRANDS Mercedes Benz, BMW, Tesla, NorthFace
CELEBRITIES Anderson Cooper, Maria Bartiromo, Lindsay Vonn
SOCIAL GRAPH FRIEND: Nancy Age: 36 Gender: Female Likes: Tesla, Prada Check-Ins: Giant Stadium
BROTHER: Aaron Age: 34 Gender: Male Likes: BMW, Ferrari Check-Ins: Heavenly Mountain
Resort
ACTIVITY GRAPH CHECK-INS � Giant Stadium � Disney World � Heavenly Mountain
Resort � AMC Metreon 16
RSVPs � Giants Game � Heavenly Weekend � Family Movie Night � Dartmouth Reunion
AUDIENCE PROFILE SEGMENT: High income, urban mom’s, car enthusiast
BIRTHDAY: Turned 32 in November2012
PROMOTION: Her job title just
changed in January 2013
NEW BABY: Had her twin boys
in February 2012
LIFE EVENTS
Social – detailed user data
Run Anova
Run Correlation
Run K-Means Clustering
Run Frequency Distribution
Run Clusters
Develop Segment ID
Develop Annotated List
Produce Audience Segments
Grants User Permissions
Pull Profile Data
Run X times
35
Luxury Auto Brand Page ‘Likes’
BMW
Mercedes Benz
Infiniti Lexus Range Rover
Activities
Outdoor Sports
(Summer)
Winter Sports
Auto Racing
Bike Riding
Nascar
Demographics
65% Male v. 35% Female
Top 5 Cities:
• Chicago • Boston • Daytona Beach • Miami • Newport Beach
11% 36%
27% 14%
12%
65+ 45 - 64 25 - 44
18 - 24 Under 18
Other ‘Likes’
15% The Harry Potter Book Series 30% The Rolling Stones 40% Motorcycles 25% Roller Coasters
Relationships
• 27% ‘Like’ 3 or more luxury car brands and 34% ‘Like’ 2 or more • Fans in urban areas are 4x more likely to ‘Like’ multiple luxury car brands • Rolex and Nieman Marcus are the top retail brands liked by fans of luxury car brands • Of Winter sports, skiing is the most commonly named activity
Profiles
Number of Profiles: 157,320
36% shared on Facebook, Twitter, etc. 9% shared multiple times 78% were not existing fans and of those, 90% (110,439) liked the Page
Developing audience segments
36
• Facebook insights only go so far
• Delve deeper for more insight
• Consider us of ‘Big Data’ tools to aid analysis
• Think about how much further you could go……
Summary
37
QUESTIONS?
Gravity Thinking, Emerson Studios, 4-8 Emerson St, London SE1 9DU T 0203 7143000 E [email protected] W gravitythinking.com
FB http://facebook.com/gravitymarketing TW http://twitter.com/gravitythinking
LI http://linkedin.com/company/gravitythinking
Facebook fan segmenta:on Sample Report
1. Analyse Facebook user profile data (with appropriate access permissions) to develop an understanding of the brand’s Fan base and surface sta:s:cally significant Fan segments
2. Analyse segments to determine interac:on, by segment, with brand content
3. Provide user-‐level CRM-‐match with associated segmenta:on data appends
39
Objec:ve
40
Process Step Explanation
Frequency Distribution Determines total count and percentage from all Fan ‘Likes’ categories as well as individual ‘Likes’
K-Means Clustering Creates clusters of ‘Likes’ and ‘Likes’ categories using data from the frequency distribution
Anova Measures the effect size between clusters to see if they are statistically different
Correlation Determines the degree of correlation between clusters
Repeat & Refine Run the previous steps 2+ times to determine segments
Clusters Manually examine the segments and determine if further segmenting is required
Human Segment ID From the initial set of segments, determine which are significant and common characteristics
Fan Segments Description and summary statistics of the final segments
Run Anova
Run Correlation Run
K-Means Clustering Run
Frequency Distribution
Run Clusters
Develop Human Segment ID
Produce Fan Segments
Implement FB Survey
Pull Fan Data
Rerun 2+ times
Fan segment process map
41
Findings
42
• 4,185 respondents • 3,420,960 total ‘Likes’ • 817 average ‘Likes’ per respondent • 139,934 unique Pages over 210 content categories
• 1,215 unique Pages were Liked by at least 10% of the survey universe
• Target was the top Page with 61% of respondents being Fans of the Page
Overview
• The universal client Fan shows three common elements: • Budget-‐Focused – Fans ‘Like’ a wide variety of Pages in retail categories to look for
deals & coupons • Home-‐Centric – Prominent categories of Pages reflects their home-‐centered lives • Health/Beauty-‐Conscious – 9 out of the top 20 Pages center around health/beauty
• The graph below shows universal Fans and their Page ‘Likes’ from the top 10 percen:le of Pages (1,215 Pages). In total, there are 192,128 Fan ‘Likes’ within these pages
43
17.39% 15.62%
13.62%
8.95% 7.58% 6.96% 6.81%
4.25% 4.14% 3.73% 3.33% 2.95% 1.91% 1.80% 0.98%
0.00% 2.00% 4.00% 6.00% 8.00%
10.00% 12.00% 14.00% 16.00% 18.00% 20.00%
*Other category includes a wide range of additional Pages ranging from Fed Ex to JetBlue
Universal Client fan overview
Top 20 Pages, broken down by percentages:
44
61%
54% 53% 52% 51% 51% 50% 50% 49% 49% 49% 49% 49% 48% 48% 48% 47% 47% 47% 46%
0%
10%
20%
30%
40%
50%
60%
70%
Universal Client fan overview (ctd)
45
1st Popular 2nd Popular 3rd Popular 4th Popular 5th Popular
Music Universal Music Group Country Music The GRAMMYs 80’s Music Yamaha Ent. Group
Television FX Has The Movies The Ellen DeGeneres Show SpongeBob SquarePants Official Peppa Pig – US WNCN
Books Books R Us Slap Dash Mom James Patterson Kelly Stilwell Aunt Maggie Rocks
Internet Good Housekeeping All You Magazine Womensforum.com TotalBeauty.com ShefFinds.com
Movies Redbox Yahoo! Movies Oz The Great and Powerful Blockbuster AMC Theaters
Universal Fan ‘Like’ Count ‘Likes’ per Fan
Music 1,342 1.6
Television 14,244 17
Books 4,678 8.4
Internet 4,216 5.0
Movies 11,434 13.7
Metrics by media Pages:
Top five media Pages:
Universal Client media pages
46
Sample Segment analysis The analysis produced segments that are both sta:s:cally significant within the universal popula:on and sta:s:cally different from other
segments. Following is a sample segment:
Segment Bio and Behavior
The Passionate Urbanite is driven by their interests and values. While showcasing a traditional religious outlook, their Page ‘Likes’ revolve around media consumption and cars. Of all three segments, they care the
most about entertainment, particularly African-American-centric music, television, and movies.
47
Segment Demographics
• Gender: Female/Male
• Age: 45 – 64
• Ethnicity: Caucasian & African American
• HHI: $0K - $25K & $40K - $70K
• Rent/Own: Rent & Own
• Segment Value: High
• Segment Content Engagement: Medium-High
Primary ‘Like’
Associated ‘Likes’
Fan segment: Passionate urbanite
The graph below shows the percentage of Fans that ‘Like’ AT&T U-‐Verse and an addi:onal Page
48
13% 13% 13% 13%
11% 11% 11% 11%
9% 9% 9% 9% 9% 9% 9% 9% 9% 9% 9% 9%
0%
2%
4%
6%
8%
10%
12%
14%
*These ‘Likes’ do not repeat with the other Fan segments
Passionate Urbanite – top ‘Like’ pages
49
‘Likes’ Per Fan 1st Popular 2nd Popular 3rd Popular 4th Popular 5th Popular
Music 2.5 Yamaha Entertainment Group No Ego Records Universal Music Group The GRAMMYs EMG Pickups
Television 29.9 FX Has The Movies The Ellen DeGeneres Show Hallmark Channel USA Entertainment Tonight Dog and Beth: On the
Hunt
Books 11.1 James Patterson Suzanne Woods Fisher Ryan Winfield Susan May Warren Fiction Siri Mitchell
Internet 24.5 iHeartRadio Good Housekeeping AOL Kudosz Womensforum.com
Movies 26.4 Redbox Oz The Great and Powerful AMC Theatres Cinemark Wreck-It Ralph
Total Page ‘Likes: 28,964 Average number of ‘Likes’ per segment responded: 526.8
Media Total ‘Likes’ by media Music 140
Television 1,642
Books 613
Internet 1,347
Movies 1,450
Top ‘Likes’ by media
Passionate Urbanite overview
The Savvy Mom supports her family by locating the best possible deals/coupons and in some cases, generates extra income through an independent consultancy or personal business venture (e.g., Etsy). She likes products that frequently offer coupons and that are easy to stockpile. She’s resourceful and is
seen as practical.
Segment Bio and Behavior
50
Segment Demographics
• Gender: Female
• Age: 25 – 44
• Ethnicity: Caucasian
• HHI: $35K - $40K & $50K - $70K
• Rent/Own: Rent & Own
• Segment Value: High
• Segment Content Engagement: Medium-High
Primary ‘Like’
Associated ‘Likes’
Fan segment – Savvy Mom
The graph below shows the percentage of Fans that ‘Like’ Oberto Beef Jerky and an addi:onal Page
51
*These ‘Likes’ do not repeat with the other Fan segments
15%
13%
12% 12% 12% 12% 12% 12% 12% 12% 12%
10% 10% 10% 10% 10% 10% 10% 10% 10%
0%
2%
4%
6%
8%
10%
12%
14%
16%
Fan segment – Savvy Mom page top likes
52
‘Likes’ Per Fan 1st Popular 2nd Popular 3rd Popular 4th Popular 5th Popular
Music 1.2 Yamaha Entertainment Group 80’s Music Universal Music Group Rock Music The Fillmore Detroit
Television 19.3 FX Has The Movies The Ellen DeGeneres Show
SpongeBob SquarePants Official Peppa Pig – US WNCN
Books 16.5 Kelly Stilwell Books R Us Slap Dash Mom Aunt Maggie Rocks Gladys Parker and Christina Lanphere
Internet 27.2 Good Housekeeping All You magazine Womensforum.com TotalBeauty.com Thri"y Momma Ramblings
Movies 15.4 Redbox Hop Blockbuster Walmart Moviecenter Oz The Great and Powerful
Total Page ‘Likes: 31,854 Average number of ‘Likes’ per segment responded: 612.6
Media Total ‘Likes’ by media Music 64
Television 1,003
Books 616
Internet 1,414
Movies 801 Top ‘Likes’ by media
Savvy Mom overview
53
Savvy Mom ‘Likes’ Per Fan
Boardwalk Bettie ‘Likes’ Per Fan
Passionate Urbanite ‘Likes’ Per Fan
Universal ‘Likes’ Per Fan
Music 1.2 1 2.5 1.6
Television 19.3 14.5 29.9 17
Books 16.5 5.3 11.1 8.4
Media 27.2 15.1 24.5 5.0
Movies 15.4 10.5 26.4 13.7
Across segments, the Fans in the Passionate Urbanite group have the most media ‘Likes’ in 3/5 categories, while Savvy Moms have the highest amount of ‘Likes’ per Fan
Total Brand ‘Likes’ Avg. ‘Likes’ per Respondent Savvy Mom 31,854 612.6
Boardwalk Bettie 29,269 340.3
Passionate Urbanite 28,964 526.8
Universal 684,192 817
Sample segment comparison
54
Sample CRM Export (Facebook)
Fan Name
Reach (Friends/
Followers) Email Address Profile Link Fan Segment Engagement
Level Influence First Seen
Last Seen
Client CRM Segment
Marcus Nieman 693 [email protected] https://www.facebook.com/ xxxx Savvy Mom Med High 9/12/12 4/30/13 2a
Jill Lang 703 [email protected] https://www.facebook.com/xxxx Savvy Mom Med High 7/10/11 5/30/13 3c
Tyler Morrison 731 [email protected] https://www.facebook.com/xxxx Passionate
Urbanite Med Med 5/6/11 4/17/13 2a
Amanda Feldt 511 [email protected] https://www.facebook.com/xxxx Boardwalk
Bettie Low High 3/2/13 5/30/13 4e
Robert Florent 575 [email protected] https://www.facebook.com/xxxx Passionate
Urbanite Med Med 12/28/13 5/22/13 4e
Zoey Fields 490 [email protected] https://www.facebook.com/xxxx Boardwalk
Bettie Low Low 1/24/12 5/27/13 2a
Mark Downey 274 [email protected] https://www.facebook.com/xxxx Passionate
Urbanite High Med 7/20/11 5/08/13 3c
Eric Liebert 607 [email protected] https://www.facebook.com/xxxx Boardwalk
Bettie Low Med 6/16/10 5/09/13 2a
Katherine Smith 598 [email protected] https://www.facebook.com/xxxx Savvy Mom High High 9/13/13 5/09/13 4e
Kevin Nguyen 276 [email protected] https://www.facebook.com/xxxx Passionate
Urbanite Low Low 2/7/12 5/30/13 2a
Sample export data to Client CRM
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Measuring campaign effec:veness
Social measurements :e to the brand’s overall success metrics. Social KPIs are defined at the brand level, with social measurement mapping back to key success metrics. AudienceArc, in conjunc:on with tradi:onal research tools, measures audience, content and campaign value, showing you what drives brand metrics.
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Social KPI’s Framework
M E T R I CS
B RA N D S O C I A L K P I s
40% Lii Over Control
Purchase Intent Brand Awareness Online Retail Sales Advocacy/Referral
Quarterly Social Fan/Follower Survey 1. Fan/Follower Survey 2. Social Competitive SOV Referral Traffic from Social Social Shares, Retweets, etc.
30% Increase Year 1
15% Of Referral Traffic
300k Shares
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Audience Segments & Engagement
BrandFacebook
Page
100k to 10m+ fans Audience ProfilingCohorts and propensity modeling by
demographics, psychographics, likes, activities, etc.
Data StoreApproximately 10 million data points
per 10,000 authorized fans
Facebook Profiles AudienceArc
BIEngine
Pulls allavailable data
Algorithms:Clustering, Propensity& Statistical Analysis
BrandSurveyResults
BRAND SURVEY
�/�+!��&ƞCampaign RecallPurchase Intent
Facebook brand research
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Glossary
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