I have a data set that I want to parse for to see multi-touch attribution. The data set is made up by leads who responded to a marketing campaign and their marketing source.
Each lead can respond to multiple campaigns and I want to get their first marketing source and their last marketing source in the same table.
I was thinking I could create two tables and use a select statement from both. The first table would attempt to create a table with the most recent marketing source from every person (using email as their unique ID).
create table temp.multitouch1 as (
select distinct on (email) email, date, market_source as last_source
from sf.campaignmember
where date >= '1/1/2016' ORDER BY DATE DESC);
Then I would create a table with deduped emails but this time for the first source.
create table temp.multitouch2 as (
select distinct on (email) email, date, market_source as first_source
from sf.campaignmember
where date >= '1/1/2016' ORDER BY DATE ASC);
Finally I wanted to simply select the email and join the first and last market sources to it each in their own column.
select a.email, a.last_source, b.first_source, a.date
from temp.multitouch1 a
left join temp.multitouch b on b.email = a.email
Since distinct on doesn't work on redshift's postgresql version I was hoping someone had an idea to solve this issue in another way.
EDIT 2/22: For more context I'm dealing with people and campaigns they've responded to. Each record is a "campaign response" and every person can have more than one campaign response with multiple sources. I'm trying make a select statement which would dedupe by person and then have columns for the first campaign/marketing source they've responded to and the last campaign/marketing source they've responded to respectively.
EDIT 2/24: Ideal output is a table with 4 columns: email, last_source, first_source, date.
The first and last source columns would be the same for people with only 1 campaign member record and different for everyone who has more than 1 campaign member record.
PostgreSQL also provides on an expression as DISTINCT ON that is used with the SELECT statement to remove duplicates from a query set result just like the DISTINCT clause.In addition to that it also keeps the “first row” of each row of duplicates in the query set result.
COUNT ( * ) counts all the rows in the target table whether they include nulls or not. COUNT ( expression ) computes the number of rows with non-NULL values in a specific column or expression. COUNT ( DISTINCT expression ) computes the number of distinct non-NULL values in a column or expression.
For each group in a query, the LISTAGG aggregate function orders the rows for that group according to the ORDER BY expression, then concatenates the values into a single string. LISTAGG is a compute-node only function.
ILIKE performs a case-insensitive pattern match for single-byte UTF-8 (ASCII) characters. To perform a case-insensitive pattern match for multibyte characters, use the LOWER function on expression and pattern with a LIKE condition.
I believe you could use row_number() inside case expressions like this:
SELECT
email
, MIN(first_source) AS first_source
, MIN(date) first_date
, MAX(last_source) AS last_source
, MAX(date) AS last_date
FROM (
SELECT
email
, date
, CASE
WHEN ROW_NUMBER() OVER (PARTITION BY email ORDER BY date ASC) = 1 THEN market_source
ELSE NULL
END AS first_source
, CASE
WHEN ROW_NUMBER() OVER (PARTITION BY email ORDER BY date DESC) = 1 THEN market_source
ELSE NULL
END AS last_source
FROM sf.campaignmember
WHERE date >= '2016-01-01'
) s
WHERE first_source IS NOT NULL
OR last_source IS NOT NULL
GROUP BY
email
tested here: SQL Fiddle
PostgreSQL 9.3 Schema Setup:
CREATE TABLE campaignmember
(email varchar(3), date timestamp, market_source varchar(1))
;
INSERT INTO campaignmember
(email, date, market_source)
VALUES
('a@a', '2016-01-02 00:00:00', 'x'),
('a@a', '2016-01-03 00:00:00', 'y'),
('a@a', '2016-01-04 00:00:00', 'z'),
('b@b', '2016-01-02 00:00:00', 'x')
;
Query 1:
SELECT
email
, MIN(first_source) AS first_source
, MIN(date) first_date
, MAX(last_source) AS last_source
, MAX(date) AS last_date
FROM (
SELECT
email
, date
, CASE
WHEN ROW_NUMBER() OVER (PARTITION BY email ORDER BY date ASC) = 1 THEN market_source
ELSE NULL
END AS first_source
, CASE
WHEN ROW_NUMBER() OVER (PARTITION BY email ORDER BY date DESC) = 1 THEN market_source
ELSE NULL
END AS last_source
FROM campaignmember
WHERE date >= '2016-01-01'
) s
WHERE first_source IS NOT NULL
OR last_source IS NOT NULL
GROUP BY
email
Results:
| email | first_source | first_date | last_source | last_date |
|-------|--------------|---------------------------|-------------|---------------------------|
| a@a | x | January, 02 2016 00:00:00 | z | January, 04 2016 00:00:00 |
| b@b | x | January, 02 2016 00:00:00 | x | January, 02 2016 00:00:00 |
& a small extension to the request, count the number of contact points.
SELECT
email
, MIN(first_source) AS first_source
, MIN(date) first_date
, MAX(last_source) AS last_source
, MAX(date) AS last_date
, MAX(numof) AS Numberof_Contacts
FROM (
SELECT
email
, date
, CASE
WHEN ROW_NUMBER() OVER (PARTITION BY email ORDER BY date ASC) = 1 THEN market_source
ELSE NULL
END AS first_source
, CASE
WHEN ROW_NUMBER() OVER (PARTITION BY email ORDER BY date DESC) = 1 THEN market_source
ELSE NULL
END AS last_source
, COUNT(*) OVER (PARTITION BY email) as numof
FROM campaignmember
WHERE date >= '2016-01-01'
) s
WHERE first_source IS NOT NULL
OR last_source IS NOT NULL
GROUP BY
email
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