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CON BIZ DIGITAL PILOTPost campaign AAR17 June 2016
EDB provides this presentation (including oral statements) gratuitously for information only and not for any other purpose. While care has been expended in the preparation of this presentation, EDB hereby disclaims all liability including, but not limited to, inaccuracies, incompleteness or lack of suitability for purpose of any information in the presentation.
2
2
TODAY’S AGENDA
Recap of Campaign objectivesCampaign concept and Approach
Review of Campaign KPIsTopline Campaign Performance
Channel Insights Deep DiveContent insights Deep Dive
Channel top 10 followersSummary (Channel Comparison)
33
RECAP OF CAMAPIGN OBJECTIVES_
Campaign objectives
Digital Channel ViabilityContent Testing
What content speaks to our audience?
Are our TA on LinkedIn and Twitter?
Campaign outcomes
Awareness Building Audience Acquisition
Digital audience acquisition on social media
Building mindshare among target list of Con biz coys
44
CAMPAIGN CONCEPT AND APPROACH_
Campaign design
Hyper-targeting content to TA
Laser-focus content to TA down to geography, designation and company on social media
AmOps + Cluster Con Biz coy target list (HPC + FN = 91 coys)
Tier 1s: CEO, COO, CMO, CFO, CRO, CTO, CIO, President Tier 2s: Directors, VP, GM, Head
HPC Companies FN Companies
Brand Management
R&D
Conbiz Companies TA engaged with horizontal content?
TA engaged with sub-sector specific content?TA engaged in functional content specific to brand management and R&D?
Content is tested on 3 levels
55
CAMPAIGN CONCEPT AND APPROACH_
Content testing to TA over 4 phases
Phase Target Audience Content levels tested FRS article served
1
HPCGeneral Con biz Using Design thinking to win the hearts of consumers
Sub-sector specific (HPC) The men do get it
HPC B&M
General Con biz Using Design thinking to win the hearts of consumers
Sub-sector specific (HPC) The men do get it
Functional specific (B&M) Timing for the tipping point
FN*General Con biz Using Design thinking to win the hearts of consumers
Sub-sector specific (FN) Asia's growing appetite for breakfast snacks
FN R&D*
General Con biz Using Design thinking to win the hearts of consumers
Sub-sector specific (FN) Asia's growing appetite for breakfast snacks
Functional specific (R&D) Asia's bugeoning geriatric nutrition market
*Content served for FN and FN R&D TA for LinkedIn and Twitter platforms were different, as the FN R&D list was not scalable on Twitter.
66
CAMPAIGN CONCEPT AND APPROACH_
Content testing to TA over 4 phases
Phase Target Audience Content levels tested FRS article served
2
HPCGeneral Con biz Can digital services unlock the potential of Asia?
Sub-sector specific (HPC) Beauty and personal care goes high-tech
HPC B&M
General Con biz Can digital services unlock the potential of Asia?
Sub-sector specific (HPC) Beauty and personal care goes high-tech
Functional specific (B&M) Muslim beauty and personal care: A market poised for astronomical growth
FN*General Con biz Can digital services unlock the potential of Asia?
Sub-sector specific (FN) Asia's hunger for mobile food apps
FN R&D*
General Con biz Can digital services unlock the potential of Asia?
Sub-sector specific (FN) Asia's hunger for mobile food apps
Functional specific (R&D) Is this safe to eat?
*Content served for FN and FN R&D TA for LinkedIn and Twitter platforms were different, as the FN R&D list was not scalable on Twitter.
77
CAMPAIGN CONCEPT AND APPROACH_
Content testing to TA over 4 phases
Phase Target Audience Content levels tested FRS article served
3
HPCGeneral Con biz The subscription model: Keep consumers coming back for more
Sub-sector specific (HPC) Halal household care: Small but mighty
HPC B&M
General Con biz The subscription model: Keep consumers coming back for more
Sub-sector specific (HPC) Halal household care: Small but mighty
Functional specific (B&M) The new faces of beauty
FN*General Con biz The subscription model: Keep consumers coming back for more
Sub-sector specific (FN) Keeping an eye on food fraud in Asia
FN R&D*
General Con biz The subscription model: Keep consumers coming back for more
Sub-sector specific (FN) Keeping an eye on food fraud in Asia
Functional specific (R&D) Edible beauty and wellness a big hit in Asia
*Content served for FN and FN R&D TA for LinkedIn and Twitter platforms were different, as the FN R&D list was not scalable on Twitter.
88
CAMPAIGN CONCEPT AND APPROACH_
Content testing to TA over 4 phases
Phase Target Audience Content levels tested FRS article served
4
HPCGeneral Con biz Towards the Next Billion Internet Users: How Singapore is building a bu
siness environment for the internet ageSub-sector specific (HPC) Growing naturally and organically
HPC B&M
General Con biz Towards the Next Billion Internet Users: How Singapore is building a business environment for the internet age
Sub-sector specific (HPC) Growing naturally and organically
Functional specific (B&M) A market ripe for the taking anti-ageing cosmetics for the over 50s in Asia
FN*General Con biz Towards the Next Billion Internet Users: How Singapore is building a bu
siness environment for the internet ageSub-sector specific (FN) Feeding the Next Billion: How the Internet is Addressing Asia's Nutrition
Challenge
FN R&D*
General Con biz Towards the Next Billion Internet Users: How Singapore is building a business environment for the internet age
Sub-sector specific (FN) Feeding the Next Billion: How the Internet is Addressing Asia's Nutrition Challenge
Functional specific (R&D) Eating their way to better looks
*Content served for FN and FN R&D TA for LinkedIn and Twitter platforms were different, as the FN R&D list was not scalable on Twitter.
99
REVIEW OF CAMPAIGN KPIs_
Awareness Building Audience Acquisition
Reach Response RelationshipMeasured during campaign period:1. SBN: # Subscribes2. Twitter/LinkedIn: # Follows
Capturing of Con Biz TA in our database to further nurture w/ content.
Measured through 2 tiers.General Reach metrics:1. SBN: Total Unique page views
on each article 2. Twitter/LinkedIn: Total
impressions made on Con Biz short-form content
Engagement metrics*:1. SBN: Avg time spent on article2. Twitter/ LinkedIn: Engagement
% (e.g. likes, retweets, mentions, shares, comments, click through to article on SBN)
*Engagement metrics because we need monitor if the TA has really consumed the content, so general impressions is not a sufficient indicator
1010
CAMPAIGN PERFORMANCE (FRS)_Topline campaign performance (FRS)
Channel Con biz per phase (avg)
BM (Avg, Always on-
Con biz)
BM (Avg, Media trial*)
KPIs Overall campaign objectives
Analysis and evaluation
FRS Page views 533 1053 1229 Reach Awareness building
Con biz campaign had relatively lower page views vs Always-on (Con biz articles) and Media Trial, due to:1. More budgets (almost 7x more
social spend)2. Better content quality/depth due
to media partnerships w/ Quartz etc. vs content house freelance writers who were not domain experts.
3. FRS eDM highlights also featured 5-7 top stories that was promoted to subscribers (not applied for con biz campaign)
4. Media drivers from media partnership e.g. Quartz also drove traffic to always-on and media trial articles.
Unique Users
418 904 873
Time/session 1.10 0.33 NA Response Audience Acquisition
ConBiz campaign brought in higher quality readers to FRS vs. Always-on (ConBiz articles only), with +233% Time/Session and +99% Pages/Session.
Pgs/session 2.04 1.14 NA
Subscriptions 0.5 1 17 Relationship
*Past Media trial (31 July 2015 to 7 Aug 2015): Conducted on both twitter and linkedIn for the exact same duration of 30 days with similar ad mechanics (single- image dark post), however budgets were higher
1111
CAMPAIGN PERFORMANCE (TWITTER)_Topline campaign performance (Twitter)
Channel Con biz per phase (avg)
BM (Avg, Always on-
Con biz)
BM (Avg, Media trial*)
KPIs Overall campaign objectives
Analysis and evaluation
Twitter Impressions 529,133 565,141.50 1,961,099 Reach Awareness building
Con biz campaign underperformed relative to Always on and media trial due to:1. A narrower media buy budget2. Absence of media drivers from other
media partnership owners’ social media handles (e.g. Quartz twitter handle)
3. More hyper-targeted ad campaign mechanics vs broad –base more topline campaign mechanics
Impressions for Con biz campaign is also significantly more selective and targeted.
E/R 0.92% 10.72% 1.13% Response Audience Acquisition
Con biz campaign underperformed for Acquisition metrics compared to benchmarks because:1. Always-on had a broader TA vs
hyper-targeted finite list for Con biz Campaign
2. Ad-formats for Always-on was multi-image + page posts vs Con biz’s single image + dark posts
3. Content angles for media trial was focused on function i.e. operations and HR, suggesting that Con biz’s campaign approach (i.e audience type – HPC, HPC B&M) might be less effective in garnering twitter engagement
Follows 7 27 456 Relationship
1212
CAMPAIGN PERFORMANCE (LINKEDIN)_Topline campaign performance (Twitter)
Channel Con biz per phase (avg)
BM (Avg, Always on-
Con biz)
BM (Avg, Media trial*)
KPIs Overall campaign objectives
Analysis and evaluation
LinkedIn Impressions 134,353 58,491 657,687 Reach Awareness building
• Again this is subject to media buy budgets and presence of other media drivers from existing media partnerships.
• However, the fact that Con biz campaign (with a more hyper-targeted and finite TA) performed better than Always-on (broad base), suggests that Con biz TA is substantial on LinkedIn
CTR 0.57% 0.42% 0.47% Response Audience Acquisition
Con biz campaign performed significantly better than both benchmarks suggesting:1. Content angle based on
audience type (for Con biz campaign) instead of function (Media trial campaign) may be more effective in garnering Click-throughs for LinkedIn (opp of Twitter)
Follows 61 13 174 Relationship
*Past Media trial (31 July 2015 to 7 Aug 2015): Conducted on both twitter and linkedIn for the exact same duration of 30 days with similar ad mechanics (single- image dark post), however budgets were higher
1313
CHANNEL INSIGHTS DEEP DIVE_Twitter channel insights (E/R and A/R) across 4 phases – audience type
Phase 1 Phase 2 Phase 3 Phase 40
0.5
1
1.5
2
2.5
3
-0.00499999999999999
6.07153216591883E-18
0.00500000000000001
0.01
0.015
0.02
0.025
Enga
gem
ent R
ate
(%)
Acq
uisi
tion
rate
(%)
FN+ FN R&D (E/R)
HPC B&M (A/R)
HPC B&M (E/R)
HPC (E/R)
HPC (A/R)
Media Trial E/R: 1.13%
Media Trial A/R: 0.02%
Always on (Con Biz) A/R: 0.00045%FN+ FN R&D (A/R)
1414
CHANNEL INSIGHTS DEEP DIVE_Twitter channel insights (E/R) across 4 phases – audience type
Topline Twitter channel analysisEngagement rates1. FN + FN R&D audience were the most engaged audience consistently over 4 phases and outperformed
Media trial E/R of 1.13%, suggesting Twitter may be the right platform to reach out to this TA2. HPC B&M audience were the second most engaged audience, outperforming Media trial E/R
benchmarks except for final phase when media budgets were significantly reduced which caused the drop in E/R
3. HPC audience was the least engaged consistently underperforming in comparison to Media Trial benchmark.
All Con biz audience E/R underperformed compared to Always on (Con biz) E/R Benchmark of 10.72% because of the different ad format (multi-image + page post) and broader TA vs Con biz campaign ad format (dark posts) and more limited and hyper-targeted TA list
*Phase 4 data overall faced a significant dip due to reduced media spend for the final phase. Also HPC budgets were completely reallocated to HPC B&M and FN+ FN R&D audiences as it was the slowest “burning” in terms of social spend consumption **FN R&D audience on its own was insufficient to scale on Twitter – suggesting Twitter may not be the right channel to reach deep dive functional target audiences.
1515
CHANNEL INSIGHTS DEEP DIVE_Twitter channel insights (A/R) across 4 phases – audience type
Topline Twitter channel analysisAcquisition rates1. FN and FN R&D audience had the highest acquisition rates. HPC B&M audience followed closely
behind in terms of acquisition.2. HPC audience had the lowest acquisition rates over 4 phases underperforming consistently compared
to Always on (Con biz) A/R Benchmark.
All Con Biz TAs’ A/R underperformed in comparison to Media trial A/R of 0.02% (similar campaign setup, much bigger budgets and different content angles tested) suggesting that perhaps “functional” (i.e. operations, human resource) content angles will work better than content angles based on “audience type” (i.e. HPC, FN, HPC B&M etc) in digital acquisition of TA.
However, FN and FN R&D and HPC B&M audiences A/R still performed better than Always on (Con Biz) A/R benchmark of 0.00045% over phase 1-2 (with different campaign setup but similar budgets), suggesting that a more hyper-targeted campaign setup was more effective in acquiring our TA than broad base targeting in Always on (Con biz).
*Phase 4 data overall faced a significant dip due to reduced media spend for the final phase. Also HPC budgets were completely reallocated to HPC B&M and FN+ FN R&D audiences as it was the slowest “burning” in terms of social spend consumption **FN R&D audience on its own was insufficient to scale on Twitter – suggesting Twitter may not be the right channel to reach deep dive functional target audiences.
1616
CHANNEL INSIGHTS DEEP DIVE_LinkedIn channel insights (CTR and A/R) across 4 phases – audience type
Phase 1 Phase 2 Phase 3 Phase 40
0.2
0.4
0.6
0.8
1
1.2
0
0.1
0.2
0.3
0.4
0.5
0.6
Clic
k th
roug
h ra
te (%
)
Acq
uisi
tion
rate
(%)
Media Trial CTR: 0.47%
Media Trial A/R: 0.057%
Always on (Con Biz) CTR: 0.42%
Always on (Con Biz) A/R: 0.053%
FN (CTR)
FN (A/R)
HPC B&M (CTR)
HPC B&M (A/R)
FN R&D (CTR)
FN R&D (A/R)
HPC (A/R)
HPC (CTR)
1717
CHANNEL INSIGHTS DEEP DIVE_LinkedIn channel insights (CTR) across 4 phases – audience type
Topline LinkedIn channel analysisEngagement rates (CTR)1. HPC B&M audience on the overall was the most engaged audience on LinkedIn, with phase 1 and 2
performing consistently or close to Media trial CTR benchmark of 0.47% and Always on (Con biz) CTR benchmark of 0.42%. suggesting LinkedIn may be the right platform to reach out to this TA
2. FN audience followed closely behind in engagement rates, followed by FN R&D and HPC audiences with an almost similar E/R average over the 4 phases.
Overall all TA’s average CTR over 4 phases outperformed Always on (Con biz) benchmark of 0.42%, while only HPC B&M TA CTR outperformed Media Trial CTR benchmark of 0.47%. This suggests that a hyper-targeted approach for LinkedIn (con biz campaign) is more effective in garnering engagement as compared to a broad-base approach (Always On) from the Con biz TA.
*Phase 4 data overall faced a significant dip due to reduced media spend for the final phase.
1818
CHANNEL INSIGHTS DEEP DIVE_LinkedIn channel insights (A/R) across 4 phases – audience type
Topline LinkedIn channel analysisAcquisition rates1. FN TA had the highest acquisition rates over LinkedIn 2. HPC TA came in 2nd in terms of acquisition rates, followed by HPC B&M and finally FN R&D TA
All TA of Con biz campaign significantly outperformed Always on (Con biz) A/R Benchmark of 0.053% and Media Trial A/R Benchmark of 0.0057%, suggesting that LinkedIn might be a better channel to acquire Con biz TA than Twitter.
*Phase 4 data overall faced a significant dip due to reduced media spend for the final phase. Also HPC budgets were completely reallocated to HPC B&M and FN+ FN R&D audiences as it was the slowest “burning” in terms of social spend consumption
1919
CHANNEL INSIGHTS DEEP DIVE_Twitter channel insights (with TA size) – Average of 4 phases
0.600 0.700 0.800 0.900 1.000 1.100 1.2000.00000
0.00050
0.00100
0.00150
0.00200
0.00250
0.00300
0.00350
0.00400
Twitter channel insights (E/R, A/R and TA size – avg)
A/R
Engagement Rate (%)
Acq
uisi
tion
rate
(%)
HPC
HPC B&MFN + FN R&D
Media Trial E/R: 1.13%
Media Trial A/R: 0.02%
Always on (Con Biz) A/R: 0.00045%
Always on (Con Biz) E/R: 10.72%
• Acquisition for HPC B&M audience was most effective, while FN + FN R&D audience were the most engaged • Despite HPC audience being the most sizeable, acquisition and engagement rates paled in comparison to the other two TA list. • All TA A/R outperformed Always on (Con biz) A/R, suggesting a hyper-targeted approach might be more effective for acquisition.• All TA E/R underperformed compared to Always on (Con biz) E/R because of the different ad format (multi-image + page post) and
broader TA vs Con biz campaign ad format (dark posts) and more hyper-targeted TA list. • TA E/R and A/R also underperformed in comparison to media trial, suggesting that content angles focused on function (i.e. operations
and HR) might be more effective than content angles based on audience type (i.e. HPC, HPC B&M)
2020
0.350 0.370 0.390 0.410 0.430 0.450 0.470 0.490 0.510 0.5300.050
0.070
0.090
0.110
0.130
0.150
0.170
0.190LinkedIn channel insights (CTR, A/R and TA size – avg)
A/R
Click through rate (%)
Acq
uisi
tion
rate
(%)
CHANNEL INSIGHTS DEEP DIVE_LinkedIn channel insights (with TA size) – Average of 4 phases
HPC
HPC B&M
FN
FN R&DMedia Trial CTR: 0.47%
Always on (Con Biz) CTR: 0.42%
Media Trial A/R: 0.057%
Always on (Con Biz) A/R: 0.053%
• FN TA was the most sizeable on LinkedIn with the highest acquisition rates. On the other hand, HPC B&M TA although limited in size, was the most engaged TA on LinkedIn outperforming both media trial and always on (con biz) CTR benchmarks.
• From the results, FN R&D may not be the right TA to reach on LinkedIn with low A/R and CTR• All TA’s A/R significantly outperformed Media Trial and Always on (Con biz) A/R benchmarks, suggesting that a hyper-targeted approach
(dark post) and targeting content by audience type might be more effective in garnering acquisition on LinkedIn• Overall all TA were engaged on LinkedIn performing within the benchmark ranges of Media Trial and Always on (Con Biz) CTR,
suggesting that the approach for the Con biz campaign was successful, given that Media trial also had biggest media spend bugets (5x more than Con biz campaign pilot)
2121
CONTENT INSIGHTS DEEP DIVE_Twitter HPC TA content insights (E/R) across 4 phases
All Con Biz HPC0.000.200.400.600.801.001.201.401.601.802.00
1.05 1.05
0.57
1.88
0.92 0.95
0.00 0.00
0.64
0.97
HPC Target Audience (E/R)Phase 1 Phase 2 Phase 3 Phase 4
Content angles tested
Enga
gem
ent R
ate
(%)
• Overall HPC TA consistently underperformed for both “All Con biz” and “HPC” content angles, in comparison to both Media Trial and Always on (Con biz) E/R benchmarks. HPC content worked better than General all Con biz content (0.97% E/R avg). Due to consistently low E/R performance, phase 4 budgets were reallocated to better performing HPC B&M and FN + FN R&D list.
• Analysis:1. We are not pushing out the right content to HPC TA2. Targeting HPC TA with content based on “function” (media trial - i.e. human resource, operation etc) might be more effective vs
“audience type” • Limitations: Always on (Con biz) and media trial had bigger budgets for content development partnership with content experts e.g.
Quartz, while Con biz campaign was limited by freelance writers who may not be able to develop in-depth or relevant content to our TA.
Media Trial E/R: 1.13%
Always on (Con Biz) E/R: 10.72%
2222
CONTENT INSIGHTS DEEP DIVE_Twitter HPC B&M TA content insights (E/R) across 4 phases
All Con Biz HPC HPC B&M0.00
0.20
0.40
0.60
0.80
1.00
1.20
0.78 0.73
0.590.48
1.05
0.660.67
0.840.90
0.69
0.00
0.90
0.65 0.660.76
HPC B&M Target Audience (E/R)Phase 1 Phase 2 Phase 3 Phase 4
Content angles tested
Enga
gem
ent R
ate
(%)
• Overall HPC B&M TA consistently outperformed media trial E/R benchmarks for all content angles tested and responded best to HPC B&M content.
• Analysis:1. We are pushing out relevant content that the HPC B&M TA are generally interested in2. Targeting HPC B&M TA with content based on “audience type” is more effective than by “function” (i.e. human resource etc)3. Specific domain expertise content (Branding and marketing) vs General or sub-sector industry content (home and personal
care goods industry) is more relevant• Limitations: Always on (Con biz) have bigger budgets for content development and media partnership with content experts i.e. quartz,
while Con biz campaign pilot was limited by our FRS freelance writers who may not be able to develop in-depth or relevant enough content to our TA. Con biz campaign also had a more finite target audience list compared to broad base targeting in always on.
Media Trial E/R: 1.13%
Always on (Con Biz) E/R: 10.72%
2323
CONTENT INSIGHTS DEEP DIVE_Twitter FN and FN R&D TA content insights (E/R) across 4 phases
All Con Biz FN FN R&D0.000.200.400.600.801.001.201.401.601.80
0.98
1.58
0.690.63
0.93
1.25
0.73
1.10
0.890.91
0.660.550.81
1.070.85
FN and FN R&D Target Audience (E/R)Phase 1 Phase 2 Phase 3 Phase 4
Content angles tested
Enga
gem
ent R
ate
(%)
Media Trial E/R: 1.13%
Always on (Con Biz) E/R: 10.72%
• Overall FN + FN R&D TA consistently outperformed media trial E/R benchmarks for all content angles tested and responded best to FN content (Avg E/R: 1.07%). FN+FN R&D TA had the highest E/R avg compared to the other two TA.
• Analysis:1. We are pushing out relevant content that the the FN + FN R&D TA are interested in2. Targeting FN + FN R&D TA with content based on “audience type” is more effective than by “function” (i.e. human resource
etc.) 3. Sub-sector industry content (Food and nutrition) vs domain expertise content (R&D) is more relevant
• Limitations: Always on (Con biz) had bigger budgets for content development and partnership with content experts i.e. quartz, while Con biz campaign pilot was limited by freelance writers who may not be able to deliver in-depth or relevant enough content to our TA. FN R&D audience itself was also not scalable and therefore needed to be combined w/ FN for hyper-targeting efforts.
2424
CONTENT INSIGHTS DEEP DIVE_LinkedIn HPC TA content insights (CTR) across 4 phases
All Con Biz HPC0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.31
0.49
0.27
0.58
0.24
0.350.30
0.00
0.280.35
HPC Target Audience (CTR)Phase 1 Phase 2 Phase 3 Phase 4
Content angles tested
Clic
k Th
roug
h R
ate(
%)
• Overall HPC TA responded best to HPC content (Avg CTR:: 0.35%), with only phase 1-2 outperforming media trial and Always on (con biz) benchmarks. All Con biz content consistently underperformed compared to benchmarks.
• Analysis:1. We might not be pushing out content relevant to the HPC audience2. Sub-sector industry content (Home and personal care goods) is more relevant vs general con biz industry content 3. Targeting by “function” (i.e. human resource etc.) is more effective than content based on “audience type”
• Limitations: Always on (Con biz) had bigger budgets for content development and partnership with content experts i.e. quartz, while Con biz campaign was limited by freelance writers who may not be able to deliver in-depth or relevant enough content to our TA.
Media Trial CTR: 0.47%Always on (Con Biz) CTR: 0.42%
2525
CONTENT INSIGHTS DEEP DIVE_LinkedIn HPC B&M TA content insights (CTR) across 4 phases
All Con Biz HPC HPC B&M0.000.100.200.300.400.500.600.700.800.901.00
0.40
0.510.44
0.00
0.750.86
0.00
0.47
0.17
0.42
0.00
0.360.20 0.44 0.46
HPC B&M Target Audience (CTR)Phase 1 Phase 2 Phase 3 Phase 4
Content angles tested
Clic
k Th
roug
h R
ate(
%)
• HPC B&M CTR was comparable to benchmarks and preferred HPC B&M content best (Avg CTR: 0.46%). HPC B&M TA was also the most engaged TA out of all the TA list
• Analysis:1. We are pushing out relevant content that HPC B&M TA is interested in and LinkedIn may be the right channel to reach this TA2. HPC B&M audience is agnostic to both content based on “audience type” and by “function” (i.e. human resource etc.) 3. Domain expertise content (Branding and marketing) is more relevant vs General con biz industry content
• Limitations: Always on (Con biz) had bigger budgets for content development and partnership with content experts i.e. quartz, while Con biz campaign was limited by freelance writers who may not be able to deliver in-depth or relevant enough content to our TA.
Media Trial CTR: 0.47%
Always on (Con Biz)
CTR: 0.42%
2626
CONTENT INSIGHTS DEEP DIVE_LinkedIn FN TA content insights (CTR) across 4 phases
All Con Biz FN-0.20
0.00
0.20
0.40
0.60
0.80
1.00
1.20
0.25
1.15
0.00
0.42
0.00
0.320.17
0.000.11
0.47
FN Target Audience (CTR)Phase 1 Phase 2 Phase 3 Phase 4
Content angles tested
Clic
k Th
roug
h R
ate(
%)
Media Trial CTR: 0.47%
Always on (Con Biz)
CTR: 0.42%
• FN TA preferred FN content with an avg CTR that is comparable to media trial and outperformed Always on (Con biz) Benchmarks. Despite pumping budgets in for “All con biz” content angle, media budgets did not burn (i.e. no engagement w/ content though there was impressions)
• Analysis:1. FN TA are not interested in General con biz industry content but prefers sub-sector industry content (Food and nutrition)2. FN TA are agnostic between content based on “audience type” vs content based on “function” (i.e. human resource etc.)
• Limitations: Always on (Con biz) had bigger budgets for content development and partnership with content experts i.e. quartz, while Con biz campaign pilot was limited by freelance writers who may not be able to deliver in-depth or relevant enough content to our TA.
2727
CONTENT INSIGHTS DEEP DIVE_LinkedIn FN R&D TA content insights (CTR) across 4 phases
All Con Biz FN FN R&D0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.28
0.64
0.43
0.24
0.50
0.23
0.06
0.280.32
0.38 0.410.45
0.24
0.46
0.36
FN R&D Target Audience (CTR)Phase 1 Phase 2 Phase 3 Phase 4
Content angles tested
Clic
k Th
roug
h R
ate(
%)
Media Trial CTR: 0.47%
Always on (Con Biz)
CTR: 0.42%
• FN R&D TA prefers FN content most, while FN R&D and All con biz content angles underperformed in comparison to benchmarks. Despite FN R&D TA being the least sizeable on LinkedIn, CTR performance for FN content (0.46%) was still better than Always on (Con biz) benchmarks (CTR: 0.42%) and comparable to media trial CTR 0.47%
• Analysis:1. FN R&D audience is agnostic to content based on “audience type” vs by “function” (i.e. human resource etc.) 2. Sub-sector industry content (Food and nutrition) is more relevant to FN R&D audience vs domain expertise content (R&D) or
general con biz content • Limitations: Always on (Con biz) had bigger budgets for content development and partnership with content experts i.e. quartz, while
Con biz campaign was limited by freelance writers who may not be able to deliver in-depth or relevant enough content to our TA.
2828
CONTENT INSIGHTS DEEP DIVE_LinkedIn FN R&D TA content insights (CTR) across 4 phases
All Con Biz FN FN R&D0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.28
0.64
0.43
0.24
0.50
0.23
0.06
0.280.32
0.38 0.410.45
0.24
0.46
0.36
FN R&D Target Audience (CTR)Phase 1 Phase 2 Phase 3 Phase 4
Content angles tested
Clic
k Th
roug
h R
ate(
%)
Media Trial CTR: 0.47%
Always on (Con Biz)
CTR: 0.42%
• FN R&D TA prefers FN content most, while FN R&D and All con biz content angles underperformed in comparison to benchmarks. Despite FN R&D TA being the least sizeable on LinkedIn, CTR performance for FN content (0.46%) was still better than Always on (Con biz) benchmarks (CTR: 0.42%) and comparable to media trial CTR 0.47%
• Analysis:1. FN R&D audience is agnostic to content based on “audience type” vs by “function” (i.e. human resource etc.) 2. Sub-sector industry content (Food and nutrition) is more relevant to FN R&D audience vs domain expertise content (R&D) or
general con biz content • Limitations: Always on (Con biz) had bigger budgets for content development and partnership with content experts i.e. quartz, while
Con biz campaign was limited by freelance writers who may not be able to deliver in-depth or relevant enough content to our TA.
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Name Company Position URL
Jose Quesada Data Science Retreat Dir. https://twitter.com/Quesada
Ian Bell Digital Trends CEO https://twitter.com/IanBell330
Mark Westron Fujitsu Chief Architect http://twitter.com/westron2005
Martin Faller IFRC Head of Ops, APAC http://twitter.com/martin_faller
Dan Radley KPMG Dir., ASPAC Sales & http://twitter.com/danradley
Dave Peck PayPalGlobal Head, Social Media & Influencer
Marketinghttp://twitter.com/davepeck
Jay Samit SeaChange International CEO http://twitter.com/jaysamit
Bill Carmody Trepoint CEO http://twitter.com/BillCarmody
Simon Mainwaring We First Inc. CEO http://twitter.com/simonmainwaring
Larry Kim Wordstream CTO http://twitter.com/larrykim
TOP 10 AUDIENCE FOLLOWS (TWITTER)_
3030
Name Company Position URL
Karl Kusreau Comcast Regional Manager, Sales Strategy
https://www.linkedin.com/in/karl-kusreau-iv-34384654
Bill Giermann Energizer National Manager, Sales https://www.linkedin.com/in/billgiermann
Sara Thompson Gap GM, Athleta https://www.linkedin.com/in/sara-thompson-4548a544
Linda Wang L’Oreal Area Manager, Greater China
https://www.linkedin.com/in/linda-wang-93585537
Victoria Campbell L’Oreal GM, Designer Fragrances
https://www.linkedin.com/in/victoria-campbell-06b01b64
Sebastiano Collino Nestle Head, Metabolomics https://www.linkedin.com/in/sebastiano-collino-81b01a70
Audrey Yoo Nike Senior Dir., Emerging Markets
https://www.linkedin.com/in/audrey-yoo-74339142
D. Scott Miller P&G Dir., Corporate Design https://www.linkedin.com/in/dmiller9
Karen Clark P&G VP, Global Business Services
https://www.linkedin.com/in/karen-clark-430a523b
Chang Andy Shiseido GM, Sales (Taiwan) https://www.linkedin.com/in/chang-andy-505838b0/en
TOP 10 AUDIENCE FOLLOWS (LINKEDIN)_
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SUMMARY (CHANNEL COMPARISON)_Twitter LinkedIn
Digital audience Acquisition (measured by response and relationship metric)
Most engaged TA (response) FN+ FN R&D (below both E/R benchmarks) HPC B&M (above both CTR benchmarks)
Least engaged TA (response) HPC (below both E/R benchmarks) HPC (below Media trial, comparable to Always on CTR benchmarks)
Which Channel is more effective in engaging the Con Biz TA?
All TA performed below E/R benchmark #, suggesting that Twitter might not be the best
platform to engage con biz TA
All TA either performed better or comparable to Always on CTR benchmarks, suggesting that
LinkedIn might be a better platform to engage our TA
TA with highest acquisition rates (R/S) HPC B&M (above always on below media trial A/R benchmarks)
FN (above both A/R benchmarks)
TA with lowest acquisition rates (R/S) FN + FN R&D (above always on below media trial A/R benchmarks)
FN R&D (above both A/R benchmarks)
Which Channel is more effective in acquiring the Con Biz TA?
All TA performed better than Always on A/R benchmarks but underperformed in comparison to
Media Trial A/R
All TA performed better than A/R benchmarks, suggesting that LinkedIn might be a better
platform to acquire our TA
Content preference of each target audience list
HPC audience HPC content (below both E/R benchmarks) HPC content (below both CTR benchmarks)
HPC B&M audience HPC B&M content (above media trial, below always on E/R benchmarks)
HPC B&M content (above always on, close to media trial CTR benchmarks)
FN audienceFN content (above media trial, below always on
E/R benchmarks)
FN content (above always on, similar to media trial CTR benchmarks)
FN R&D audience FN content (above always on, close to media trial CTR benchmarks)
Content preferences across both channels Clear consistency in content preference for both channels in each TA.
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Thank You