Table Descriptions

Overview

Aampe is ready to share granular data about users, messages, and other events straight to your data warehouse. While there are many potential applications, customers generally find these datasets useful for

Reporting and monitoring
Causal inference and offline message evaluation
Inputs into various AI models (llm prompts, ML features, etc.)

Expand the tables below to see column descriptions, example queries, and more.

Active Tables

AAMPE_CONTACT_PROFILES

Aampe generates a profile for each user that has interacted with an agent.

The propensity for each label within a given label set reflects the agent’s estimate for how often that label will outperform the other label options. (If I were to simulate 100 messages from Aampe for each user, how often would the agent choose each label?)

Column	Type	Description
`contact_id`	STR	Unique person identifier
`propensities_offering`	ARRAY	User propensities for each offering
`propensities_valueproposition`	ARRAY	User propensities for each value proposition
`propensities_tone`	ARRAY	User propensities for each tone label
`propensities_timing`	ARRAY	User propensities for each timing window
`propensities_channel`	ARRAY	User propensities for each channel

The propensity arrays contain scores that sum to one and look like the following:

[
	{"label_id":5678, "propensity":0.5432, "label_name":"Food"},
	{"label_id":6789, "propensity":0.4568, "label_name":"Travel"}
]

User Profiles - Example Queries

// for a given user, what's their propensity for each offering label

SELECT 
  contact_id, 
  label_name, 
  propensity
FROM aampe_contact_profiles,
UNNEST(propensities_offering)
WHERE contact_id = '1a2b3c4d'
ORDER BY propensity DESC

AAMPE_MESSAGE_EVENTS

Agents save the details of each decision they make, including the parameters of the statistical models, sampling results, and the final decision result.

With a row for every message event, this table helps with day-to-day reporting and monitoring. It also plays a key role in offline analysis and causal inference.

Column		Description
`aampe_message_id (pk)`	STR	Aampe’s unique identifier for a message event
`provider_message_id`	STR	The event identifier from the message provider (e.g. Braze). Not available for all message providers.
`contact_id`	STR	Unique person identifier
`message_timestamp`	TIMESTAMP	When the message was sent
`received_timestamp`	TIMESTAMP	When the message provider confirmed a successful delivery.
`message_timezone`	STR	Timezone for `message_timestamp`
`message_formula_id`	INT	Numerical Identifier for a message formula (called “messages” in the Aampe composer.)
`message_formula_name`	STR	Name for a message formula (called “messages” in the Aampe composer)
`message_content`	STRUCT	`title`: title of message `body`: main message content
`message_diversity_score`	FLOAT	Computed by Aampe. When several message alternates are available within a chosen set of labels, we send the alternate with the best message diversity score. This ensures messages vary their language even if the offering or value proposition is the same.
`reward_baseline`	FLOAT	Computed by Aampe. This is the reward Aampe expects to observe if the agent does nothing.
`channel_assignment_id`	STR	Unique decision ID for channel selection
`channel`	STR	Channel
`timing_assignment_id`	STR	Decision ID for timing selection (potentially a joint decision with channel)
`timing_label_assigned`	STR	`label_set`: the decision being made (typically “day_time” for timing decisions) `label_id`: numeric ID for the timing label `label_name`: human-friendly name for the timing label `score`: Model score for timing-decision model `assignment_type`: description of the model output (is it exploratory or not)
`trigger_id`	STR	Identifier for trigger associated with message. There is always a trigger id, even if the message was not triggered by an event.
`messaging_type`	STR	Either “controlled” (scheduled message blasts). Or “automated” which means an agent decided the message to send and when to send it.
`copy_assignment_id`	STR	Decision ID for message copy elements
`tags`	ARRAY	Array of tags associated with the message event
`message_to`	STR	Delivery to address
`message_from`	STR	Delivery from address
`message_date`	DATE	Date of `message_timestamp` - for easier partitioning when needed
`click_action`	STR	Type: what happens when the message is clicked (e.g. deeplink) Value: deeplink URL or other api call resulting from click
`image_url`	STR	Image URL (when not included in `message_content`)
`reward_delta`	FLOAT	The extent to which the message event outperformed expectations (given by `reward_baseline`).
`trigger_name`	STR	Name of trigger (or else “no trigger”)
`copy_assignment`	STR	`action_set_family`: the agents decision set (typically “copy” for copy decisions) `action_set`: Label groups such as value proposition, offering, … `action_name`: the specific label `probability`: mean-concentration parameter of the Beta distribution for the chosen action `aggregated_signal`: another mean-concentration parameter of the Beta distribution for the chosen action

Aampe Messages - Example Queries

// for each message, what were the labels, label parameters, etc.?

SELECT 
    aampe_message_id,
    message_date,
    action_set,
    action_name as label_name,
    probability,
    aggregated_signal
FROM 
    aampe_message_events,
    UNNEST(copy_assignment)
WHERE 
    aampe_message_id = '1234-asdf'

AAMPE_MESSAGE_ATTEMPTS

Not all messages are delivered successfully. Some messages fail between Aampe and the message provider. Other messages fail between the message provider and the customer. The aampe_message_attempts table provides message-level details on which messages were delivered successfully.

Column		Description
`aampe_message_id (pk)`	STR	Aampe’s unique identifier for a message event
`provider_message_id`	STR	The event identifier from the message provider (e.g. Braze). Not available for all message providers.
`contact_id`	STR	Unique person identifier
`message_timestamp`	TIMESTAMP	When the message was sent
`message_date`	DATE	Date of `message_timestamp` - for easier partitioning when needed
`message_timezone`	STR	Timezone for `message_timestamp`
`channel`	STR	Channel
`message_formula_id`	INT	Numerical Identifier for a message formula (called “messages” in the Aampe composer.)
`message_formula_name`	STR	Name for a message formula (called “messages” in the Aampe composer)
`trigger_id`	STR	Identifier for trigger associated with message. There is always a trigger id, even if the message was not triggered by an event.
`copy_assignment_id`	STR	Decision ID for message copy elements
`message_content`	STRUCT	`title`: title of message `body`: main message content
`tags`	ARRAY	Array of tags associated with the message event
`delivery_status`	STR	Whether or not the message was successfully delivered

AAMPE_CONTACT_EVENTS_PARTIAL

This table contains events delivered to Aampe from the message provider. Depending on your message provider, channels, and Aampe settings Aampe, these events may include:

aampe_clicked
aampe_email_clicked
aampe_email_opened
aampe_email_unsubscribed
aampe_email_bounced

This is a subset of all Aampe events visible in the composer, hence the _partial suffix.

Column		Description
`event_instance_id (pk)`	STR	Aampe’s unique identifier for an event occurance event
`event_name`	STR	The event name (as seen in the Aampe composer).
`contact_id`	STR	Unique person identifier
`event_timestamp`	TIMESTAMP	When the message was sent
`event_date`	DATE	Date of `event_timestamp`
`metadata`	STRUCT	Numerical Identifier for a message formula (called “messages” in the Aampe composer.)

SSO

Send Data to Aampe

Connect Message Provider

CMS Integration

Embed Aampe in an App or Website

Receive Data from Aampe

Overview

Active Tables

User Profiles - Example Queries

Aampe Messages - Example Queries

​Overview

​Active Tables

​User Profiles - Example Queries

​Aampe Messages - Example Queries

Overview

Active Tables

User Profiles - Example Queries

Aampe Messages - Example Queries