3.E: Data driven decision making(Exercises)
- Page ID
- 36853
\( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \) \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)\(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\) \(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\)\(\newcommand{\AA}{\unicode[.8,0]{x212B}}\)
Case study questions
- What role did data play in the planning and execution of the Royal Canin campaign?
- Why was it so important for Royal Canin to continuously monitor the campaign results and update their CRM database?
- What beneficial effects did the data generated by the Royal Canin campaign have on the running of the business overall?
Chapter questions
- Why should a business try to be data-driven?
- What should be done with data once it has been collected?
- What are some of the most important sources of data?
- What are some up-and-coming data collection tools/sources that you foresee being useful in the near future?
Further reading
Personalisation is important for great customer experiences, but read about how this might be a problem for small businesses here: adage.com/article/digitalnext/personalization-a-problem-brands/305554
Check out the Kissmetrics blog for articles about analytics and testing: blog.kissmetrics.com
The Analytics Vidhya blog has some more complex data information: www.analyticsvidhya.com/blog
Take a look at the Freakonomics blog: freakonomics.com