conversion optimization case study - lifestyle online

26
Schibsted Lifestyle Online 2015 - 2016 Conversion optimisation

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Page 1: Conversion optimization case study  - lifestyle online

Schibsted Lifestyle Online 2015 - 2016

Conversion optimisation

Page 2: Conversion optimization case study  - lifestyle online

Challenge Q1 2015

Monthly revenue

from affiliates was

not increasing

enough to meet

business goals.

Page 3: Conversion optimization case study  - lifestyle online

Step 1 - Adding skillsQ2 2015

A CRO - specialist and a UX researcher joined the team

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Step 2 - Growth focusQ2 2015

Find the metrics that indicates growth from affiliates

Set a target for each metric!

Bootstrapping implementation of Google Analytics

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Step 3 - Data!Q2 2015

● The right data● To the right person● In the right time

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Step 4 - User research beginsQ2 2015 and ongoing

● Web analysis● Remote user testing● Heatmaps● User feedback

This gave us a long list of hypotheses for improvements to prioritize from

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Step 5 - Vaildate hypothesesQ2 2015 and ongoing

● A/B-testing● Sequential “testing”● Follow the money

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Deep dive: some of the tests and the reseach behind them

3 of many cases

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Test case 1Research 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.

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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.

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Test case 3The 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

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Results at end of Q3

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Increase in affiliate kickback in six months

+132%april

october

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Moving on Q4 2015 - Q1 2016

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Step 6 - Diving deeper in dataQ4 2015

Focus on understanding the differences in behaviour depending on screen size.

Detailed understanding what content and what products creates conversion

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Step 7 -The love of bargainsQ1 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

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Step 8 - Quality trafficQ1 2016 and ongoing

● Added SEO-skills to the team● Knowledge spread to IT and editors● High quality traffic that converts better

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Step 9 - Shoppable content for realQ1 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?

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Results at end of Q1 2016

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Increase in affiliate kickback in one year

April -15

october

March -16

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Year-on-year affiliate kickback

+227%

April -14

April -15

March -16

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Year-on-year affiliate kickback vs. traffic

April -14

April -15

March -16

traffic

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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

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