Google


Wednesday, August 22, 2012

Telecoms will push analytics


Telecom firms are starting to ponder what to do with the massive data they collect on an everyday basis. How can they gather anonymised insights from their data which they can package up and sell?

They know the following things about (especially paid smartphone) users:
Who they are and where they live
Where they went at what time
How much they use their phone and for what (that includes websites browsed)
Who they are connected to

The challenge for many telecoms is to bring this information into a Single Customer View (SCV) as it exists in silos (and different frequencies).

Using these four tiers of information, the telco can produce unique insights of the sort:
Who shops where and what time?
Where do those shoppers go before and after the shop?
What is the cross shopping (switching) of users?
What websites correlate with what shopping behaviour?
Who are the influencers in a network?
o So if I wanted to target only influencers, who would it be?
How do online (mobile) and offline shopping behaviour interact?

Change index for time series in Excel

I have created an Excel tool where you can compare several time series and you can change the index/base date by selecting it from the drop down or changing the slider. It also tells you which date delivers the highest growth.

Download https://docs.google.com/open?id=0B_YKhy3eG-qJQ0NEZXVZSGxMSHc

Wednesday, August 15, 2012

simple cross purchase code

If you have an item level data set and you want to explore cross purchase in SAS you usually need to sum and transpose your data first in several steps. Here is a simple SQL within SAS example using the max and case functions writing this succinctly, it won't necessarily run faster though.

proc sql;
create table x as
select custid, max(case when prodid=y then 1 else 0 end) as prod1, max(case when prodid=z then 1 else 0 end) as prod2
from items
group by 1;
quit;

proc freq;
table prod1*prod2;
run;