#MCN2014 - What Are Your Visitors Really Telling You? Data Analytics and What to Do with This...

Preview:

Citation preview

•••

●●●

●●●

●●●●

●● …●●

●●●

What is the context?

Dont forget human intuition.

●●●

ANALYSIS: ISSUES TO CONSIDER

● How many data points is statistically significant?

● What time period is sufficient for analysis then action?

● All hypotheses are dangerous● How should we test our theses?● How to balance #s with politics?

ANALYZE: Content● # of Visitors / tour / language● # of Visitors / stop / language● Visitors / tour (floor / tour type)● Visitors / language● Most listened vs. least stops● # of canceled Stops / tour / language● Detailed activity / tour (canceled vs. completion)●

IN-APP A/B TESTING

● Comparing (2) tours (Temp/Perm) at the same site:○ # Visitors / tour / language○ # Visitors / stop / language○ Most vs. least listened stops

What content conclusions can be made when the most vs. least listened to stops vary significantly by language?

● Time on-the-ground qualitative research with data analytics analysis

● Draw conclusions from comparisons of qual research + analysis ● Propose changes to test hypotheses (duration, content,

speaker/tone, placement, UI, design, relationship to other content, etc.)

● An iterative approach: A/B test on a select # of devices ● Collect, analyze, share again!

•••••••

••