I was part of a team with a mission to optimize for product market fit. The idea was shoppable content. Fashion editors were producing content and had the ability to pull products directly into the content from affiliate programs iike Zalando och Asos. I had a blast doing this project.

1. Schibsted Lifestyle Online
2015 - 2016
Conversion
optimisation

2. Challenge
Q1 2015
Monthly revenue
from affiliates was
not increasing
enough to meet
business goals.

3. Step 1 - Adding skills
Q2 2015
A CRO - specialist and a
UX researcher joined the team

4. Step 2 - Growth focus
Q2 2015
Find the metrics that indicates
growth from affiliates
Set a target for each metric!
Bootstrapping implementation
of Google Analytics

5. Step 3 - Data!
Q2 2015
● The right data
● To the right person
● In the right time

6. Step 4 - User research begins
Q2 2015 and ongoing
● Web analysis
● Remote user testing
● Heatmaps
● User feedback
This gave us a long list of hypotheses
for improvements to prioritize from

7. Step 5 - Vaildate hypotheses
Q2 2015 and ongoing
● A/B-testing
● Sequential “testing”
● Follow the money

8. Deep dive: some of the tests
and the reseach behind them
3 of many cases

9. Test case 1
Research finding: 40% of recorded clicks are placed on the
image even though not clickable. Only 4% of clicks on what we
want: the button “To shop”
research method: CRO review and heat map
Tool: Hotjar
›› Changed - Clicks on the product lead directly to
the partner shop.
›› Effect - Lift from 13% to 20% in users who enter
affiliate from product pages.

11. Remove price from preview in product list
Test case 2
Research finding: Users hover the product list
see the price and make a fast decision to not
click based on price.
research method: Remote user tests
Tool: Tweaky.se
›› A/B-test: Show price versus not
showing price on mouse-over
›› Effect - Lift by 10% in users who
enter affiliate from product list.

12. Test case 3
The header
Research finding: Users who enter in one content
type don’t switch to a different type, even if the
consume a lot of content during the session.
Only some of the content types can promote
products. We want them to find those content types.
research method: web analysis
Tool: Google Analytics
›› Changed - We have tested so many
things in the menu. Making it sticky,
swiching orders, taking away drop downs
and enlarged the search field.
›› Effect - No detectable effect

13. Results at end of Q3

14. Increase in affiliate kickback in six months
+132%
april
october

15. Moving on
Q4 2015 - Q1 2016

16. Step 6 - Diving deeper in data
Q4 2015
Focus on understanding the
differences in behaviour
depending on screen size.
Detailed understanding what content
and what products creates conversion

17. Step 7 -The love of bargains
Q1 2016 and ongoing
Our main persuasive trigger is offering
discounts at our affiliate partner sites.
● 5 collabo-campaigns with partners
● Increases total conversions
● Increases Average order value

18. Step 8 - Quality traffic
Q1 2016 and ongoing
● Added SEO-skills to the team
● Knowledge spread to IT and editors
● High quality traffic that converts better

19. Step 9 - Shoppable content for real
Q1 2016 and ongoing
We are currently focusing on how to really offer seamless shoppable content.
How do we integrate the right products in content and by minimum workload?

20. Results at end of Q1 2016

21. Increase in affiliate kickback in one year
April
-15
october
March
-16

22. Year-on-year affiliate kickback
+227%
April
-14
April
-15
March
-16

23. Year-on-year affiliate kickback vs. traffic
April
-14
April
-15
March
-16
traffic

25. This made it possible
● High level mandate
● Culture of “lets try it”
● Throw out assumptions
● It is not a one man show
● Product owner on business side
● Everyones interest in being data informed
● No silo thinking between business and product teams