I'm pretty lost at how to approach this, and particularly with regards to the terminology; so please feel free to point to resources, fix my question name, etc. Thanks.
I used R back in college, I've got Orange installed. I've heard of MiniTab. I've got Excel installed. I've got access to SQL Server 2008 w/ Analysis Services. That's the breath of my toolkit. [I'm a developer, but that's all I know of for statistical analysis.]
I'm marketing a product, and I've got a few datasets.
- Campaign they clicked on, and the date.
- Campaign they converted on, and the date.
- The amount of biz they did with us in Q1 2010
- The amount of biz they did with us in Q2 2010
- The amount of biz they did with us in Q3 2010 ... etc.
- Day of the week
- Time of Day
- Specific pitch
- Number of purchases per customer
- Value of purchases per customer
I could easily go hogwild, guessing at patterns and testing them to see if there's any accuracy; but it's not a best use of time. What I'd like to know are a few things...
- A ranking of the various pitches in their effectiveness, and an indication of how much the pitch affects the result.
- Same for the day of the week and time.
- And, trickier -- How much of a correlation does their previous business have to do with who converts now? Is it the previous big spenders that convert? Are they the ones buying the most product?
- And finally, of all the attributes above, how do they rank in their importance to conversions?
I assume these would all come with something like an R-squared indicating their 'accuracy.'
How would I go about starting? What reading would be essential to understanding this? Is there an approach/tool I can use that'll allow me to do a basic version of these sorts of analyses [and what would they be called] rapidly? I'm just looking for trends and hints of where it might be best to focus our energy; it can be rough.
Finally, does anyone know of a resource for basic data mining? analysis? for advertising in particular?