StarHub Digital Analytics: Powering business ... - Adobe Inc. · StarHub Digital Analytics:...
Transcript of StarHub Digital Analytics: Powering business ... - Adobe Inc. · StarHub Digital Analytics:...
StarHub Digital Analytics: Powering business strategy with insights
1
Over 2.28 million mobile customers
Over 449,000 TV customers
Over 469,000 broadband customers
Singapore’s first fully-integrated info-communications & entertainment service provider
Note: As at end 1Q2018
Let’s talk about
3
Sharing and acting upon
insights across the
organization
Leveraging digital data to optimize
and grow the business
Laying a strong
analytics foundation in a
large organization
• Implementation• Governance• Validation
• Differences in measuring yardsticks• Multiplicity of projects, limited resources
• Convincing stakeholders through data• Unbiased approach to numbers
Data Analytics Challenges
4
Source: https://www.forbes.com Dated: Apr 13, 2018
The Telco Jungle
Mature Market
Multiple Players
5
Complex Product
Tech Innovation
Complex Data Structure
The Telco Jungle
6
Mobile
TVBroadband
Price Plan
Data Plan
Device Variant
Calling Rates
Data Share Roaming
Messaging
Speed
DataContract Duration
Network coverage
Content Packages
Apps
Bundles
The Digital Data Landscape
7
Data Analytics Challenges
8
Source: https://www.gartner.com Dated: May 16, 2018
THE INSIGHTS: THEY HAPPEN LIKE THIS…
9
So how do we keep sane?
11
Implementing an analytics deployment framework for all digital properties
Data validation to ensure high quality insights
Data governance to optimize on effort and output
Creating an effective tag management system
Striking a balance between demand and supply of insights. Don’t kill the analyst
Organization wide consensus on what to measure, how to measure, when to measure
BUILDING A STRONG ANALYTICS FOUNDATION BE LIKE…
12
13
Implementing a robust analytics deployment framework
14
Analytics Specification:1) Business Requirement Documentation (BRD)2) SDR Documentation Updates3) DTM Implementation Plan4) Data Layer Implementation Plan5) Test Case6) Test Accounts
Analytics Test:1) Staging Report Suite Check2) Staging Data Layer Check3) Legacy Analytics CQ Code Check4) Test Cases Analytics Data Check5) Staging Report Data Captured Comparison
Development Specification:1) FSD2) Screen Design3) Task Flow4) Test Case5) Test Accounts
IT Ticket
SIT & UAT Deployment
UAT
MRT / BRTDeployment
Launch!
Analytics Verification:1) Live Report Suite Check2) Live Data Layer Check3) Live Report Data Captured
ComparisonProjectStart
Campaign Tagging Best Practices
15
Clean Analytics Data
Detailed Saint Classifications
Validated Campaign
Fields
• Campaign creation• Tag creation, editing, deletion• Export campaign logs• Regular upload onto Adobe Analytics
The Tagging Portal
< > 16
Comprehensive data dimensions
Simple interface, hassle free tagging
Implementing an effective tag management system
17
DTM
• DTM Rules Inventory
• Leverage data layer
• Descriptive rule names
• Classify rules with meta-data
• Expunge obsolete rules
• 30 day expiry for new rules
• Appoint a data quality champion
Ensure that the current analytics is error free
18
Ensure that the current analytics is error free
19
Analytics Implementation
Test
Environment
DTM Code Placement
Data Layer Code
Image Requests and DTM
Rules
Solution Design
Reference(SDR)
AuditReal-time Data on
Dashboard
Supporting various stakeholders on a regular basis
Standardization Simplification
Dashboarding Periodic Reviews
20
• Scope• Template• Turn around time
• Weekly/Monthly WIPs
• Feedback• Impact
Measurement
• Key Performance Indicators
• Key Reports
• BAU• Campaigns• Ad Hoc
Powerful insights that shape business strategy
21
22% Click Throughs
60% Click Throughs
Creative A
Powerful insights that shape business strategy
22
206%
289%
0%
50%
100%
150%
200%
250%
300%
350%
Creative C Creative B
CTR Improvement
Creative B
Creative C
Powerful insights that shape business strategy
23
Retail Sales Digital
Sales
Business ChallengeOnline Visit
Store Visit
Sale
Approach: Paradigm Shift
22-34% of eStore visitors are likely to purchase
Most Store purchases are likely to happen within 7 days of eStore visit
13-22% of buyers have considered an eStore purchase in the same month
In summary
If you must remember only 3 things
Data has to be clean and representative, before it can be analyzed
In a world of information overload, it helps to be simple and streamlined
If you cannot action the insights, don’t bother pulling them
24
Thank You
< > 25