The Move to Predictive Social Behavior
46
1 March 31, 2014 The Move to Predictive Social Behavior #SMWF
-
Upload
viralheat -
Category
Social Media
-
view
166 -
download
0
description
Social media is becoming the new way to reach out to potential customers. With the advent of predictive social analytics, it becomes simple to target customers interested in making a purchase.
Transcript of The Move to Predictive Social Behavior
1
March 31, 2014
The Move to Predictive Social Behavior#SMWF
Small BusinessSmall BusinessThe view from The view from main street.main street.
3
About Viralheat
Patented, real-time data, sentiment and analytics
1B+…mentions per day
explosive
Growth
Comprehensive social media management
Social and Enterprise
integrations
4
• Market Overview
• Customer Challenges
• Case Studies – Predictive Social Behavior
• T-Mobile/HBS Case Study
• Appia Case Study
Agenda
The Move to Predictive Social Behavior
5
In the beginning
6
It was easier to target customers
First online display banner ads delivered October 19941.
First ad on Facebook ran from Y2M in 20042.
7
The Customer Funnel
2008 Today
8
The Customer Funnel
* Forrester
9
Marketing Channels
10
Customer Challenges
• Identifying
• Targeting
•Measuring
11
Social Management for Marketing Managers
Enterprise Data Integration for
Marketing Executive
SalesforceSalesforceSugarCRMSugarCRM
MARKETO MARKETO
ZendeskZendesk Google ,AnalyticsGoogle ,Analytics
API - Data ManagementAPI - Data Management
PublishPublish EngageEngage
AmplifyAmplifyAnalyzeAnalyze
MonitorMonitor
Viralheat Product Architecture
Page 12 © 2014 Marketo, Inc. #mktgnation14
Social Signals
Processor
Processor
Social Signals
API
Synching and Matching
CustomerContact
Database
Social Actions Contact
Details
API
Social Signal provide a more complete view of existing leads and
customer preferences
Jeff: Do we need a how to get there transition?
So, So, howhow do we do we get there?get there?
1.1.Case StudyCase Study. – . – IdentifyingIdentifying
You don’t always needYou don’t always needto burn time on to burn time on new new ideas.ideas.
2.2.Case StudyCase Study. - . - TargetingTargeting
Targeting can be challenging...
The Life Changing Event
Tracked Keywords and Hashtags:
#imengaged #justengaged #wereengaged #engaged #isaidyes
#shesaidyes "I'm engaged”
What’s our Wedding Pool?
What’s This?
Engagement Trends
The Ashton Kutcher Effect
Increased Lead Generation.
Lead Drilldown
Engagement Influencers
The Perfect Couple #Engaged!
Wedding Promoters
The waitress asked if I was done with that, and I said yes, but I’m married to it!
Wedding Crashers
Maybe not a engagement lead but……
New Lead Opportunities
New Lead Opportunities
New Lead Opportunities
3.3.Case StudyCase Study. – . –
MeasuringMeasuring
38
Case Study – T Mobile
Launch New VoIP ProductInternet based business phone system
First small business-focused VoIP product for T-Mobile
zzT-Mobile Hosted Business Solutions
• Crowded category
• First business-focused VoIP product
• Needed to identify relevant audience
• Target key influencers & adopters
The Challenge
T-Mobile turned to social media to:
•T-Mobile brand sentiment
•Learn where engagement highest
•Determine language/terms used
•Identify SMEs
Social Discovery
SolutionReal-time research – #VoIP, #newoffice
Target key influencers re: T-Mobile@work
Identify & cultivate leads
Determine most effective channels
Monitor the Conversation
500 pilot customersHigh percentage were Influencers
Identified best terminologyInsights implemented into campaign
Results
T-Mobile turned to Viralheat due to:
•End-to-End Social Media Monitoring and Management
•Real-time, actionable insights and analysis
•Integration with existing Enterprise applications
•Intuitive, easy-to-use application and interface
Viralheat Advantages
![Predictive Modeling of Human Behavior: Supervised Learning from Telecom Metadata [Doctoral Thesis Presentation]](https://static.fdocuments.us/doc/165x107/5a65e1fc7f8b9ad05e8b49d5/predictive-modeling-of-human-behavior-supervised-learning-from-telecom-metadata.jpg)
