We are joined by Mark Dugdale from Monsoon Accessorize to talk about how you can get the most out of your third party technologies, and maximize the ROI on what you are already paying for! Whether it's recommendations, live chat, retargeting, or anything else on or off site, you need to know how much value it is driving for your business.
What is the true ROI on your technology investments?
1. What is the true ROI on your
technology investments?
@qubitgroup
2. Agenda
!
How to make the most out of
your technology investments
– Holly Tabor, Associate Strategist, Qubit
Building a testing strategy for
3rd party technologies
– Mark Dugdale, Head of Online Marketing &
Customer Loyalty, Monsoon Accessorize
!
Q&A
@qubitgroup
3. How to make the most out of
your technology investments
!
!
!
!
Holly Tabor
Associate Strategist, Qubit
@qubitgroup
4. The average ecommerce
business has
30
marketing technologies
on their site
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Qubit, Making the most of your technology investments, 2014
10. What are your goals?
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!
• Conversion rate
!
• Customer engagement
!
• Average order value
!
• Reducing returns
!
• Increasing life time value
!
13. Building your hypothesis
Building your
hypothesis
@qubitgroup
! The basic test:
is having this technology
better than not having it?
14. Ask yourself these kinds of questions
!
• Could this be more effective somewhere else on
the page?
!
• Is this actually increasing conversions, or
Building your
hypothesis
just engagement?
• Which marketing channels drive the highest long
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!
term value?
• Does this tool actually drive revenue?
!
• Does this technology reduce customer returns?
15. What are you measuring?
• Conversion rate
• Customer engagement
!
• Average order value
!
• Reducing returns
• Increasing life time value
!
@qubitgroup
17. Running your test
The 5 checkpoints of testing:
!
1. Use a randomized control group
!
2. Formulate a hypothesis
3. Calculate the necessary sample size
4. Wait for the test to reach significance
5. Validate your tests
18. Compare your results against your vendors’ claims
Compare your results
to your vendor’s claims
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19. Test technologies against each other
!
You might even find that technologies work best in
conjunction with each other, rather than on their own
Example
!
!
!
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20. Check your results by testing again
Repeat tests,
run them regularly
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22. You can begin personalizing your tech deployment
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23. Do you think you can deploy your tags more effectively?
Can you deploy your tags more effectively?
!
Should you deploy live chat just to new visitors?
!
Should you have a minimum rating threshold to
show ratings and reviews?
!
Is it best to only retarget specific products?
@qubitgroup
24. How to make the most out of
your technology investments
!
!
!
!
Holly Tabor
Associate Strategist, Qubit
@qubitgroup
29. • Remove
‘Gut
feel’
from
decision
making
and
replace
with
hard
data
• Truly
understand
new
technology
effectiveness
against
our
KPIs
• Effectively
measure
ROI
• Supplier
leverage
33. Onsite:
Search
test
Hypothesis
New
improved
search
functionality
will
increase
website
conversions
!
Segmentation
50/50
split
test
All
users
visits
(>2)
KPIs
Conversion
uplift
versus
control
Incremental
Revenue
ROI
(Profit
less
tech
cost)
34. Onsite:
Interactive
shopping
experience
Hypothesis
Customers
engaging
with
content
will
convert
better,
&
spend
more.
!
!
Segmentation
Purchasers
Non
Purchasers
visits
(>2)
KPIs
Conversion
ATV
Conversion
of
items
featured
in
Editorial
Dwell
time/Interaction
with
content
35. Offsite:
Effectiveness
of
brand
PPC
Hypothesis
Brand
PPC
will
drive
increased
site
visits,
convertors
&
revenue
compared
to
Monsoon
challenged
on
incremental
revenue
driven
by
brand
and
brand
generic
PPC
Proposed
control/expose
test
to
measure
incremental
revenue
driven
by
brand
&
Triggers
&
Segmentation
!
Purchaser
=
No,
Session
number
>2
!
Goals
!
Conversion
Conversion
of
items
featured
in
Swoon
Interaction
with
content
brand
PPC
Cities
paired
based
on
visitors,
converters
&
revenue
split
between
control
&
variant
During
test
period
visitors
in
variant
exposed
to
brand
PPC,
visitors
in
control
were
not
Pre
&
post
test
periods
used
as
control
of
performance
in
cities
Incremental
revenue
driven
by
PPC
in
variant
cities
compared
pre
&
post