Showing posts with label analytics. Show all posts
Showing posts with label analytics. Show all posts

Saturday, July 26, 2008

Customer data model for analytics

Which DATA INPUTS are required to answer the business question

Out of the plethora of business questions which frame the 'optimal contact strategy for a stores loyalty card' holders, What data inputs are required to answer the business question. In this case its

1. Loyalty card membership information
2. POS Data of loyalty card holders
3. Purchase channel

Ellaborating Loyalty card information further we have
- Loyalty card number
- Customer name
- Member since
- Profession
- Age / Date of birth
- Sex
- City
- State
- Zip

Ellaborating POINT OF SALE data furtger we have
- Store identifier
- Purchase date
- Total Purchase amount
- Product identifier
- Product quantity
- Product value

Wednesday, July 2, 2008

Customer behavior analytics - A framework

Customer behavior analytics is an area where there is a lot of new found interest . Given the fact that a lot of organisations have collected terrabytes of detailed raw customer transaction information using CRM,ERP,Online and home grown applications, its imperative leverage the insights bueried in tons of raw data. The starting point in understanding customer behavior information is to define the questions which frame the issue at hand. Some questions framing this issue at hand are


QUESTION-1 : Which are the top 5 revenue impacting customer behavior patterns ?

QUESTION-2 :What specific channel interventions can I put in place when I encounter these behavorial pattern ? How do I operationalize my customer insights ? Which are customer facing decisions which can be optimized by the insights ?

QUESTION-3 :Given that there are tons of areas to fish for insights where do I begin ? Do I look for insights in store sales ? online clickstream info ? call center complaints ? payment information ? campaign responses ?

QUESTION-4 : What are some best practices when one undertakes the journey to generate penetrating customer insights from raw data ? What are some of the landmines to avoid while generating customer insights ?

QUESTION-5 :What solution architecture can I use to implement a customer behavorial targetting system ? What are the components of this system ? How does one define the logical architecture for a customer behavorial targetting system ?Which tools do I use - SAS ? Kxen ? R ? MSFT Datamining services ? SPSS ? Oracle Data miner ?

QUESTION-6 : Is there a method to the madness ? Can we evolve a structured methodology to surface customer insights ?

I would encourage readers to submit their questions so that we have an exhaustive list of issues which we can address in a systematic fashion. We can then take ONE QUESTION AT A TIME and seek answers to the same
This entry was posted on July 2, 2008 at 6:25 pm