Configure Signals attributes

To use Signals, you need to define which attributes to calculate, and then apply the configuration. Signals will calculate the attributes from your real-time event stream.

Let's imagine that for this use case our data science team came up with the following set of attributes. They'll be calculated against the domain_userid device attribute key. Choosing this attribute key allows Signals to calculate attributes from events across multiple sessions for each prospect.

Feature name	Description	Type	Aggregation
num_page_views	Number of page_view events	int	counter
num_pricing_views	Number of page_view events of the /pricing page	int	counter
num_customers_views	Number of page_view events of the *customers* pages	int	counter

Install Signals Python SDK#

Run %pip install snowplow-signals.

Define attributes#

Next, define the attributes to calculate.

# Imports
from snowplow_signals import Attribute, Criteria, Criterion, AtomicProperty, EntityProperty

# Define an event
sp_page_view = Event(
    vendor="com.snowplowanalytics.snowplow",
    name="page_view",
    version="1-0-0"
)

# Define attributes
num_page_views = Attribute(
    name="num_page_views",
    type="int32",
    events=[sp_page_view],
    aggregation="counter"
)

num_pricing_views = Attribute(
    name="num_pricing_views",
    type="int32",
    events=[sp_page_view],
    aggregation="counter",
    criteria=Criteria(
        all=[
            Criterion.like(
                AtomicProperty(name="page_url"),
                "%pricing%"
            )
        ]
    )
)

num_customers_views = Attribute(
    name="num_customers_views",
    type="int32",
    events=[sp_page_view],
    aggregation="counter",
    criteria=Criteria(
        all=[
            Criterion.like(
                AtomicProperty(name="page_url"),
                "%customers%"
            )
        ]
    )
)

Group the attributes into an attribute group with the domain_userid device attribute key.

from snowplow_signals import StreamAttributeGroup, domain_userid

user_attributes_group = StreamAttributeGroup(
    name='prospect_scoring_tutorial',
    owner='your_email@example.com',
    version=1,
    attribute_key=domain_userid,
    attributes=[
        num_page_views,
        num_pricing_views,
        num_customers_views,
    ],
)

Next, define a service for retrieving the calculated attributes. Again, provide your own email address for the owner field.

from snowplow_signals import Service

prospect_scoring_tutorial_service = Service(
    name='prospect_scoring_tutorial_service',
    owner='your_email@example.com',
    attribute_groups=[user_attributes_group],
)

Details

For Signals Customers: test attribute group on your warehouse data

If you're using Signals in the Console, you can test the attribute outputs on a subset of recent event data. The test command uses the last hour of data from your atomic events table. Here we're restricting the results to events with the application ID website. This filtering is optional.

sp_signals_test = sp_signals.test(
    attribute_group=user_attribute_group,
    app_ids=["website"]
)
sp_signals_test

The result should look similar to this:

Deploy configuration to Signals#

Apply the attribute group and service configurations to Signals.

applied = sp_signals.publish([user_attribute_group, prospect_scoring_tutorial_service])

# This should print "2 objects applied"
print(f"{len(applied)} objects applied")

Signals will start populating your Profiles Store with attributes calculated from your real-time event stream.

Look at your attributes#

note

This section expects that you integrated sp.js into a website and have events flowing to the collector. If you're using Signals Sandbox your collector URL for sp.js is next to the Signals token.

Go to your website, and use the Snowplow Inspector browser plugin to find your own domain_userid in outbound web events.

Use your domain_userid to retrieve the attributes that Signals has calculated just now from your real-time event stream.

sp_signals_result = sp_signals.get_service_attributes(
    name="prospect_scoring_tutorial_service",
    attribute_key="domain_userid",
    identifier="00000000-1111-2222-3333-444455556666", # UPDATE THIS
)
sp_signals_result

The result should look something like this:

{
    'domain_userid': '00000000-1111-2222-3333-444455556666',
    'num_page_views': None,
    'num_pricing_views': None,
    'num_customers_views': None
}