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Funnels

Funnels allow you examine how events are performed in a series. Funnels help you to calculate the conversion counts from one event to another to identify where they get converted most of the time, where there are drop offs and etc. For example, in e-commerce, you would have users performing events like search, view product, add to cart, update payment and purchase. And you would like to analyze how many users reach each step and where there are drop-offs, before purchase.

Following section describes how to do funnel analysis in Sprinkle.

First step is to create a new model or update an existing model to add funnel fields. 


Go to the funnel tab, to select Funnel Field and Event Field.

Funnel Field: Funnel over what (usually on which/by whom events are performed)? (Ex :users or leads).

Event Field: The event field on which funnel needs to be applied(Ex : ecomm_event field which takes values Browsing, AddToCart, Purchase).


Now create a Funnel on this model by navigating to Reporting -> Funnel -> New

Click + Add Steps to add steps to your funnel. This will prompt you to select an event from the drop-down list.


Click on Add filter to add step filters to limit that step to events with in particular time or user properties.


Now choose measures of interest to count for the steps selected. Sprinkle supports Unique Count, Absolute Count, Approximate unique count as measures.


Now Save and Run the funnel report and view the report further.

Funnel step filters for negation:

Now users can also exclude some steps from the funnel, which they want to ignore.

They need to click on the Add Exclusion Steps button.


Then select the event based on which they want to exclude steps and also choose the steps from which they want to exclude the particular event. For example, users want to exclude the steps Add to cart and dependents from the steps for e-commerce shopping lifecycle events. They can select the Add to cart step from the Exclusion Step dropdown and All Steps from Between dropdown.


And then click on Save and Run. The event selected and its dependents would be excluded from the funnel. Now, in the report, only events before Add to cart would be visible.


import requests
from requests.auth import HTTPBasicAuth

auth =  HTTPBasicAuth(<API_KEY>, <API_SECRET>)
response = requests.get("https://<hostname>/api/v0.4/explore/streamresult/<EXPLORE_ID>", auth)

print(response.content)

library('httr')

username = '<API KEY>'
password = '<API SECRET>'

temp = GET("https://<hostname>/api/v0.4/explore/streamresult/<EXPLORE ID>",
           authenticate(username,password, type = "basic"))

temp = content(temp, 'text')
temp = textConnection(temp)
temp = read.csv(temp)

/*Download the Data*/

filename resp temp;
proc http
url="https://<hostname>/api/v0.4/explore/streamresult/<EXPLORE ID>"
   method= "GET"  
   WEBUSERNAME = "<API KEY>"
   WEBPASSWORD = "<API SECRET>"
   out=resp;
run;

/*Import the data in to csv dataset*/
proc import
   file=resp
   out=csvresp
   dbms=csv;
run;

/*Print the data */
PROC PRINT DATA=csvresp;
RUN;

import requests
import json

url='http://hostname/api/v0.4/createCSV'

username='API_KEY'
password='API_SECRET'

files={'file':open('FILE_PATH.csv','rb')}
values={'projectname':PROJECT_NAME','name':'CSV_DATASOURCE_NAME'}

r=requests.post(url, files=files, data=values, auth=(username,password))

res_json=json.loads(r.text)

print(res_json['success'])

import requests
import json

url='http://hostname/api/v0.4/updateCSV'

username='API_KEY'
password='API_SECRET'

files={'file':open('FILE_PATH.csv','rb')}
values={'projectname':PROJECT_NAME','name':'CSV_DATASOURCE_NAME'}

r=requests.post(url, files=files, data=values, auth=(username,password))

res_json=json.loads(r.text)

print(res_json['success'])

import requests

url='https://<hostname>/api/v0.4/explore/streamresult/<EXPLORE ID>'

username='API_KEY'
password='API_SECRET'

r=requests.get(url,auth=(username,password))
print(r)
print(r.text)

import requests
import pandas as pd

url='https://<hostname>/api/v0.4/explores/infoByFolder/<SPACE_ID>'

username='API_KEY'
password='API_SECRET'

r=requests.get(url,auth=(username,password)).json()
df = pd.DataFrame(r)
print(df)

import requests
import pandas as pd

url='https://<hostname>/api/v0.4/folders/byOrgName/<ORG_NAME>'

username='API_KEY'
password='API_SECRET'

r=requests.get(url,auth=(username,password)).json()
df = pd.DataFrame(r)
print(df.loc[:,['name','id']])

import requests

import pandas as pd

import io

url='https://<hostname>/api/v0.4/explore/streamresult/<EXPLORE ID>'

secret='API_SECRET'

r=requests.get(url,headers = {'Authorization': 'SprinkleUserKeys ' +secret } )

df = pd.read_csv(io.StringIO(r.text),sep=',')

import requests

import pandas as pd

import io

url='https://<hostname>/api/v0.4/segment/streamresult/<SEGMENT ID>'

secret='API_SECRET'

r=requests.get(url,headers = {'Authorization': 'SprinkleUserKeys ' +secret } )

df = pd.read_csv(io.StringIO(r.text),sep=',')

import requests

import json

url='http://hostname/api/v.o4/createCSV'

files={'file':open('path/file.csv’')}

values={'projectname':PROJECT_NAME,'name':'csv_datasource_name/table_name'}

secret='API_SECRET'

r=requests.post(url, files=files, data=values, headers = {'Authorization': 'SprinkleUserKeys ' +secret } )

res_json=json.loads(r.text)

import requests

import json

url='http://hostname/api/v.o4/updateCSV'

files={'file':open('path/file.csv’')}

values={'projectname':PROJECT_NAME,'name':'csv_datasource_name/table_name'}

secret='API_SECRET'

r=requests.post(url, files=files, data=values,headers = {'Authorization': 'SprinkleUserKeys ' +secret } )

res_json=json.loads(r.text)