The document discusses using data and analytics to drive business outcomes. It presents the W-model for data-driven learning which involves listening, interpreting, predicting, responding and monitoring data in cycles. It provides examples of different types of qualitative and quantitative data and metrics that can be gathered, such as conversion rates, social media metrics, search engine metrics and customer satisfaction scores. It advocates defining behaviors that drive soft key performance indicators, bundling predictors into impact factors, and using these to track company success over time. An overall "customer happiness impact factor" or CHIF is proposed as a way to measure how choices and projects impact customer satisfaction.

1. how to make UX count
become a super hero
Amsterdam

2. 2
The Brand

3. 3
Factsheet of a love brand

4. 4
Factsheet organisation

5. what is the main goal of your company?

6. 42

7. 4243

8. 8
user realtor
The user and realtor

9. 42

10. so.. what’s the problem?

11. ..and you can’t drive outcomes!
data is an outcome!

12. The W-model of data driven learning
Listen
Interpret
PredictRespond
Monitor
Listen
Interpret
PredictRespond
Monitor

13. Listen
What
Interpret
Why
Predict
When
Respond
Wow
Monitor
Well
The W-model of data driven learning

14. Listen
What
Interpret
Why
Predict
When
Respond
Wow
Monitor
Well
The W-model of data driven learning

15. Listen
What
Interpret
Why
Predict
When
Respond
Wow
Monitor
Well
The W-model of data driven learning
Analytics
Qualitative
Quantitative

16. Listen
What
Interpret
Why
Predict
When
Respond
Wow
Monitor
Well
The W-model of data driven learning
Gap!

17. so.. what does this mean for our business?

18. ..and you can’t drive outcomes!
revenue is an outcome!

19. 41 shades of blue?
change image?
different houses?
larger?
icons?
different animation?
colorscheme?

20. Soft KPI’s:
Customer loyalty
Satisfaction
Usability
Brand perception

21. insights you are probably gathering

22. Conversion
Product page conversion
Funnel analysis
Basket abandonment
Bounce rates
Leads
Subscribers to newsletters
Unique visitors
Returning visitors
Page views per visit
Visit to order ratio
Load time
Registrations
Session length
Time on page
Referring pages/links
The classics

23. Recognition Rate
Reported expectations and performance
Facial reaction
Number of back presses
Gap satisfaction
Work-flow matches mental model or not
User Tests

24. SEM keyword value
SEO positioning
Changes in SERP results/rankings
Top entry pages
Number of keywords triggering results for your site
Number of clicks to your site from keywords
Google trends
Inbound links (back link discovery)
Percentage share of each engine
Branded vs non-branded searches
Affiliate links
Affiliate fees
SEO stuff

25. Call/customer contact centre
Average call length
Support vs sales calls
Inbound vs outbound calls
Web generated calls (unique number on website)
Web fulfilled information calls
Support

26. Social media
Facebook referrals
Incoming Twitter links
Facebook sends/shares/mentions
Facebook likes
Facebook fans
Facebook fan rates
Tweets
Retweets
@s on Twitter
Twitter followers
Twitter follow rate
Social media

27. Comscore
Hitwise
Alexa
Compete
3rd party

28. Net Promoter Score
ASQ PDF: After Scenario Questionnaire (3 Questions)
NASA-TLX : NASA’s task load index is a measure of mental effort (5 Questions)
SMEQPDF: Subjective Mental Effort Questionnaire
UMEPDF : Usability Magnitude Estimation
SEQ PDF: Single Ease Question
SUS: System Usability Scale or sometimes the Single usability score
Scales

29. how can you put these to action?

30. who will win?
Do you want to seduce or feed your customer?
3636
Define which behaviors drive your soft KPI’s
and track these in a dashboard
Bundle the predictors to an impact factor
for each KPI, so you can see growth and
success in each goal
Bundle the KPI’s into a general measure
of company success

31. Conversion rate (on a journey level)
Average conversion worth
Uplift of pageviews
Drop of drop-off
Drop of helpdesk calls
Growth in usage
Accounts
Costumer lifetime value
Spend per visit
Spend of budget
Net promotor score
Brand perception
Traffic related to certain touch points
Revisit rate
Adoption rate of new features
Social media outings
Acquisition costs
Journey impact factor
# converting visitors or % uplift
EUR or leads
# of % uplift
# of % drop
# of % drop
# users, # times, % growth
#
# or % or EUR
average spend of % uplift
Leads, EUR
Exit survey
#usage directly after release
Hashtags, webcare
Effort to find/bind customers
Example

33. Spend per visit increase
Match with mental model
NPS score
Standardize to a scale of 1 to 5
Benchmark and define targets
…they don’t add up!

34. customer happiness impact factor

35. customer happiness impact factor

36. “This project will impact the CHIF with…”
“We did not make the right choices last quarter, as the CHIF went down”
"This will be better for the customer, it will increase the CHIF by … because it will have an effect on [factors]"

38. now you're a super hero!
questions? barbara@funda.nl