traffic optimization partners (top) kick-off meeting ??/01/2015
TRANSCRIPT
Traffic Optimization Partners (TOP)
Kick-Off meeting
??/01/2015
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Background
Meeting Goals Context Business objectives: Goals and KPIs Business Structure Project structure Project Team Project Management Schedule Next steps
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Context (1/2)
Through different channels (API, shopping box and channel), our partners generate up to 40% of merchants traffic
55 Partners
Merchants
LG Sites
40% 60%
15 APIs(70%)
40 Partner sites(30%)
Shopping box
(20%)
Shopping channel
(80%)
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Context (2/2)
Partners traffic is taking a larger part in Leguide.com traffic and revenue mix.
But the merchants are complaining receiving a bad quality traffic originated from our partners :
Merchants could withdrawn from our platform
Evolutions have been implanted over the years to improve the quality : A larger panel of shopping boxes (product rotation, retargeting, etc.) Offer and merchant shuffling in result pages Partner capping
We are suffering from a lack of visibility on our traffic quality.Currently we monitor the partner traffic only from a “click-outs” approach:
80% originated from a Shopping channel page 20% from a shopping box: retargeting or product boxes
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Business objectives: Goals and KPIs
The Business objective is to secure and increase LG revenue from the partners websites
Goals• Increase partners traffic to reduce Google dependency• Increase merchant satisfaction by optimizing partners traffic quality • Maintain/increase partner satisfaction
Key Performance Indicators• Partners traffic (# clicks)• Merchant cost of sales• Merchant loyalty/terminations
Identified problems• LG’s dependency on SEO traffic (Google)• Possible loss of merchants due to the low quality traffic• Possible loss of partners for higher revenue sources
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Business Structure (1/2)
The first step taken towards this goal was using user behavior analysis through the retargeting process
Billing Clicks Offers Shops
Display Strategy
Partners LG sites Merchants
Clicks Valo
User behavior
Key words
Retargeting
Processing
Capping
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Business Structure (2/2)
The targeted business structure will massively use BI and predictive algorithm to ensure more and better qualified traffic to our clients
Billing Clicks Offers Shops
Display Strategy
Partners LG sites Merchants
Clicks Valo
User behavior
Key words
Retargeting
Processing
Capping
External data
Predictive algorithm
Business Intelligence
KPIs
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Project structure (1/2)
Due to the amount of work to do, the stream is divided into interdependent sub-projects
Data collection• Merchant tagging• External data collection
Business Intelligence
Predictive performance/risk
algorithm
New Billing
Sales evolutions
Business/strategic decisions
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Project structure (2/2)
The Business Intelligence will lead to possible new strategic decisions that must be anticipated in order to amend the new billing project
Brainstorming on possible changes: Developing new offers:
“High visibility”: more traffic but lower quality New grid system to allow multiple grid options:
A lower price for some categories A higher price for others
Developing a real time valorization
To be discussed during workshop(s)
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Project Team
The Business Development team is leading the stream that impacts the whole partners revenue stream
Role Actor
Business Owner Christophe GaresYves Guerreiro
Project Manager Tom BienvenotRenaud Moulas
Sponsors Executive Committee
Stakeholders Cyril BouskilaNadège Chagne Franck Jaminet
Technical team Christophe De KervillerThomas LehouxBruno Cadu
Project Management
Our traditional methodology will be used to conduct the project
Governance
Stand up : daily
Sprint planning : each 2 weeks
30’ Weekly stream leaders sync (PMO + Business owner + MB)
Steerco meeting (Sponsors + Busniess owner + PMO + MB)
Tools
Dedicated Wiki
Dedicated workspace on Jira (to be defined))
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Schedule
The predictive algorithm is the last step after completing the data collection, the BI tools and the New Billing project
Q1 Q2 Q3
Data collection V1 :• Merchants tagging• External data: TradeDoubler
Business Intelligence V1
New Billing
Sub-subject 2 ?
Predictive performance algorithm
New offers, new deals with partners
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Next steps
All bricks are being investigated and defined simultaneously in order to pin out the dependencies
Data collection: Internal data : Work in progress External data: Work in progress
Business Intelligence: Purchase negotiation for Pentaho software Data collection/normalization Tool implementation
Predictive algorithm: Guidance workshop to be scheduled (January)
Sales evolutions Guidance workshop to be scheduled (January)
Billing: Brainstorming on possible dependencies