Trend Analysis with SQL

Hi,
I have created a table with customer nos and the monthly summaries of their basket values, no of items purchased and no of visits for a period of two years.
So I have now a summary table that looks like:
Cust_no,purch_month1,..,purch_month24, items_month1,..,items_month24, Visits_month1,..,visits_month24
Total_purch, total_items, total_visits.
From this table I want to analyse the purchase and visits trends and then categorise them to, for example, loyal customers, loyalty-loosing customers etc.
This means I need a function that analyses values from a single row and then group the behaviour to get the counts.
Do you know of any function that can do this sort of activity?
Thanks
Sathyan

Not sure what you mean by RFM analysis ?
How would you define those terms - "Bell Shaped" - "Positive/Negative Slope" - what if it has 2 bell shapes in the curve - does that count or not ? or 3 or 4 bells ? what if it has a positive and a negative slope or 2 positives and 1 negative ?
If you can define specific rules for your terms then you can implement them in code, e.g. if there are more than 2 consecutive points where the values go up then there exists a "Postive Slope" to the curve.
Jeff

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    based on sql query.
    Now,when this page is opned, as user had not entered any thing, report region shows "no data found" message. Is it possible to remove that message or
    may i conditionally disaply report region i.e if data is inserted then only report region is dispalyed.
    Thanks

    >
    i was trying with select count(1) in expression.
    >
    Just for your info, COUNT() (without any grouping obviously) with always return 1 row. If there are no result for the query then 1 row will be returned with a value of zero - so there are results returned.
    Secondly, why were you using COUNT(1) rather than COUNT(*)? That is is faster is a very common misconception and not true. If you need to know how many rows have been returned, use COUNT(*). If you need to take nulls into account (ie. not include them in your count) then use COUNT(column_name) and name the column that you are interested in specifically.
    Cheers
    Ben

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