Traffic Optimization Partners (TOP)

Kick-Off meeting

??/01/2015

2

Background

Meeting Goals Context Business objectives: Goals and KPIs Business Structure Project structure Project Team Project Management Schedule Next steps

3

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%)

4

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Merchants could withdrawn from our platform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

5

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

6

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

7

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

8

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

9

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)

10

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))

11

12

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

13

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