60 tips in 60 minutes: Social, Search & Conversion - Sam Crocker
Using Data to Value & Optimise the Affiliate Channel
1. Using Data to Value & Optimise the Affiliate Channel
#A4US3
Matthew Turner 30th August 2012
2. Introductions
Helen Southgate
Helen Southgate
Online Marketing Controller
Online Marketing Controller
Strategy & Planning
Strategy & Planning
BSkyB
BSkyB
@HelenMarie21
@HelenMarie21
#A4US3 Matt Swan
Matt Swan
Client Strategist
Client Strategist
Affiliate Window
Affiliate Window
@awin_strategy
@awin_strategy
3. W is Big Data?
hat
2012’s Buzz Word
2010 - Mobile 2011 - Attribution 2012 – Big Data
“Aggregating and sorting
“Aggregating and sorting
enormous amounts of
enorm ous amounts of
data into actionable
data into actionable
statistics and insight”
statistics and insight”
#A4US3 3 3
4. The Challenges of Big Data
There is a reason why it’s called BIG
#A4US3 4 4
6. Affiliate Window Platform
How Affiliate Window support data sharing
Client visibility Awin visibility Client visibility Client visibility Client visibility
Wider Awin project to conduct ongoing analysis of
affiliate programme quality: will rely on data
sharing
#A4US3 6
7. Attribution
Looking beyond last click
On average there are 4 interactions per order
76% of journey’s involve multiple channels
Affiliates have the largest share of “pure channel”
orders
#A4US3 7
10. Quality
Affiliates drive LTV as contribution increasing over length of time
Contribution
#A4US3
10
11. Quality
Affiliate contribution is strongest over time vs. Online & other RTM’s
Other RTMs
Contribution at
Activation
Contribution
Affiliate Contribution at
Activation
Online Contribution at
Activation
#A4US3
11
12. Quality
Affiliate contribution is strongest over time vs. Online & other RTM’s
Other RTMs
Contribution at
Activation
Affiliate Contribution at
6 Months
Contribution
Other R TMs
Contribution at 6
Months
Affiliate Contribution at
Activation
Online Contribution at 6
Months
Online Contribution at
Activation
#A4US3
12
16. Mobile
Using data to adapt quickly to changing consumer behaviour
Currently mobile = 20% of traffic, we think
it will be 50% by 2016
Mobile optimised site
more than doubled CR
from Smart Phones
#A4US3 16
19. The Future of Big Data
True Multi-Channel Marketing = Being Sales Agnostic
Over 80% of
consumers do their
research online
Not all of those
buy online
Data is Key
Understand consumer touch
points
Ensure all channels are
recognised / awarded
Ensure a consistent customer
journey
#A4US3 19
MATT – key things to note are that affiliates drive an additional 25% of orders beyond last click, however, when you look further they gain more from other channels (32%) than they lose (25%). The biggest cross over appears to be between affiliates – 33%
MATT – Pure Channel = that affiliate only, i.e. only the cashback site was involved. Cashback has highest pure incremental but gains more than it loses. Voucher has the biggest loss to other channels, All others lose more than they gain. NB: this didn’t look at all affiliates, just a few examples in each area (2)
Contribution a KPI for determining customer value Varies by promotional type Affiliate channel compares favourably to other routes to market
This slide shows contribution at activation – key thing is that affiliates is above online average, but below other RTMs. Can explain that harder to cross and upsell in online than offline channels such as the telephone / face-to-face
This slide adds in contribution after 6 months – key to show affiliates increases significantly, so LTV is high. Other RTMs comes down, common as face-to-face can lead to “oversell” in some cases.
Churn another indicator of value Again, varies by promotional type Affiliate channel showing lower churn rates than all RTMs