How to explain data in a way people ACTUALLY understand with Dr Grace Kite, Econometrician
Episode 95, Sep 09, 2022, 04:05 AM
We picked a card, any card, and drew the econometrics Ace and Founder of magic numbers, Dr. Grace Kite.
Grace has over 20 years of number crunching experience across all the main advertising buying categories and is dead set on helping marketers make the most of their data.
Tune in as we pull a ton of topics out of a hat, including her first job at a bingo hall, her fascination with real people, why data people need people skills, explaining analytics to clients like they’re a mate in the pub, whether ROI is higher when advertisers commit more budget, strategies for marketing effectiveness in a recession, and loads more.
Open sesame your ears and let the smarts pour in.
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Follow Grace on Twitter and LinkedIn
Check out magic numbers
And follow them on Twitter and LinkedIn too
Read all Grace’s Marketing Week articles
This episode talks about these two in particular:
When it comes to marketing payback, words matter just as much as numbers
Advertisers need to get over their fear of commitment
Timestamps
(01:48) - Quick fire questions
(03:23) - First ever job at a bingo hall
(06:26) - Similarities between her insurance and marketing jobs
(09:26) - magic numbers and what they do
(14:38) - Why words matter as much as numbers in data analysis
(18:18) - Findings around annual marketing budget versus ROI
(28:41) - Listener questions (including one from Dave Wakeman)
(35:20) - 4 Pertinent Posers
Check out magic numbers
And follow them on Twitter and LinkedIn too
Read all Grace’s Marketing Week articles
This episode talks about these two in particular:
When it comes to marketing payback, words matter just as much as numbers
Advertisers need to get over their fear of commitment
Timestamps
(01:48) - Quick fire questions
(03:23) - First ever job at a bingo hall
(06:26) - Similarities between her insurance and marketing jobs
(09:26) - magic numbers and what they do
(14:38) - Why words matter as much as numbers in data analysis
(18:18) - Findings around annual marketing budget versus ROI
(28:41) - Listener questions (including one from Dave Wakeman)
(35:20) - 4 Pertinent Posers