00. How to Use This Guide
This guide translates GTM strategy into executable workflows in Tapistro. Each Master Step (A-E) represents a complete GTM capability
For every Master Step, you will find:
What it is – a short explanation of the purpose
When to use it – guidance on where it fits in your GTM workflow
Step-by-step execution in Tapistro
The example used throughout this guide is a Manufacturing company targeting mid-to-large manufacturers. This should be adjusted to suit the use case performed.
0. Helpful resources
Help Docs: Tapistro Support Center
Tapistro Support AI Agent – In the Product (bottom right)
A. Account List
What this means
This module defines how you translate your Ideal Customer Profile (ICP) into a precise, system-ready Account TAM inside Tapistro. It ensures that only the right companies (e.g. midsize manufacturing companies with steel products) enter your GTM engine, with sufficient enrichment, research, and prioritization.
When to use this step
Use this step at the very beginning of your GTM motion when the goal is to generate net-new accounts and contacts. It is critical when launching a new segment, entering a new geography, or refreshing an existing TAM.
A1. Build Basic Account List
How this works in Tapistro
This is executed using a Source + Journey ingest pattern.
Step 1: Create an Account Search Source
Define a new Source with Origin Type set to Account Search.
Name the source according to your naming convention (for Naming Convention best practices, see Appendix A)
For example: “Prefix_Mfg_Midmarket_Account Search_Jan2026"
Select relevant data provider (e.g., Explorium, OceanIO, TheirStack).
Each data provider has its own strengths for enriching particular fields or providing coverage in certain geos. To expand your coverage, create multiple sources with the same filters; one source per data provider.
E.g.: “Prefix_Mfg_Midmarket_Account Search_Explorium_Jan2026"
Configure firmographic filters. All fields are optional but more parameters will result in a more targeted list.
Industry (can select multiple especially if your target ICP straddles industry definitions)
E.g.: Manufacturing (optionally select sub-industries like Automotive, Industrial Equipment etc.)
Geography: United States, Canada, Germany, UK
Employee Count: 500–10,000
Use the Preview button to validate approximate account count and sample results.
Adjust the filters as needed
Pro tip: Include fewer parameters to pull in the widest list that can be filtered down later using AI:
Explorium Search Source:
Preview Window should look like this:
Step 2: Attach the Source to a Journey
Create a new Journey (or clone an existing Lead building Journey). Whether you are creating a new Journey or copying an existing one, name the Journey according to your naming convention.
E.g.: “Prefix_Mfg_Midmarket_Account Search journey_Jan2026"
In the default "Source Ingest” step, open the “Source ID” picker and select the Account Search Source you created.
Step 3: Validate before scaling
Run the Journey with a temporary account cap (e.g., 50 accounts).
The Process Limit window will open when you click the Run button from the Journey List view
Inspect sample accounts for:
Correct industry classification
Correct firmographic requirements
Overall quality of results
Make any adjustments to the source filters as needed before running for the full list
You will need one source + one journey for every vendor you choose to use.
Tapistro Entity: Sources, Journeys
Data Vendors: Explorium, ContactOut, OceanIO, TheSwarm, TheirStack, etc.
A2. Suppression Lists and Data Filters
What this step is
Think of this as the quality control phase for your Journey. This step takes your broader account search (for example, your Mfg_Midmarket_Account Search_ Jan2026) and removes any suppression accounts before enriching and finalizing the Sales-Ready TAM. This step is crucial to guarantee that suppression lists, like Current Customers or Active Pipeline, never end up in a cold outreach campaign.
There are three steps that are crucial for suppression:
Suppression Source
Suppression Journey
Data Filters
How this works in Tapistro
Suppression can be static (one time upload) or dynamic (fetching lists from your CRM). Different campaigns call for different suppression strategies, so best practice is to ingest suppression lists in segments. 
E.g.: run the following steps for (1) BOB and (2) all Active Pipeline accounts separately
Step 1: Ensure suppression data is available in Tapistro
This step can be used in any Account Search Journey. To fetch suppression data (e.g.: accounts with an active opportunity in Salesforce), you will need to run a list ingest Journey to bring it into Tapistro.
Build a new Source for the suppression list ingest. This Source can be a direct CRM sync (origin type: Salesforce Object) or a CSV upload (origin type: CSV File).
A direct CRM source will be dynamic—pulling in new records as they get added to a segment within your CRM.
A CSV list upload is a one-time static ingestion.
Whether you chose CRM sync or CSV list, name the Source per your naming convention
e.g.: “Prefix_Jan2026_SFDC_Customers_Accounts”
Once your source is created, create a Journey to bring this data to Tapistro. Name the Journey using your naming convention.
Example: “Prefix_Jan2026_Suppression_Customers_Accounts”
In the default "Source Ingest” step, open the “Source ID” picker and select the CSV or CRM sync Ingest Source you created.
This is a single-step journey unless you want to enrich the suppression list.
If you have multiple suppression lists, ensure to ingest these (e.g., customers list, marketing suppression, competitors/pipeline accounts) using a Source + Journey pattern so they exist as filterable datasets inside Tapistro.
Pro tip: Verify that fields such as customer status, opportunity stage, account owner, region, and last activity date are pulled into Tapistro for easy filtering.
CRM accounts ingest via CSV source creation:
Step 2: Use Filter step to apply suppression inside an Account Search Journey
In the Account Search Journeys, add a Data Filter.
In any Journey, for any reason, you can configure a Filter step to remove an account or person from the rest of the journey workflow. Depending on the journey purpose, you may want to use a filter to remove:
Existing customers or competitors
Accounts with open or recently closed opportunities
Accounts recently contacted or explicitly suppressed
Any account or person based on a specific attribute
E.g. you can filter out accounts categorized as “Others” by your classification agent
When using the Data Filter step for a suppression list, navigate to the config box where it asks for an expression. Your expression will be unique based on the name of the suppression source you have setup. The expression can be written using the following pattern:
payload ->> ‘__source:<NAME>’ IS NULL
Example: payload ->> ‘__source:Jan2026_SFDC_Customers_Accounts’ IS NULL
If you have more than one suppression list, you can combine multiple sources in one filter with a small change to your expression:
(payload ->> ‘__source:Jan2026_SFDC_Customers_Accounts’ IS NULL) AND (payload ->> ‘__source:Jan2026_SFDC_Active_Pipeline’ IS NULL)
Data filter step in all Journeys with Account Search sources:
Data filter expression for suppressing CRM ingested accounts:
A3. AI Agents to Define the True ICP
What this means
This step allows you to characterize and, subsequently, filter accounts using attributes beyond standard vendor data. Tapistro AI agents classify each account, ensuring only truly relevant accounts remain in your Account TAM.
When to use this
Use this after building an account list (through source ingestion and source discovery steps) and after suppressing accounts not needed in the campaign. This should be used before any segmentation or person discovery. Doing this after suppression helps in optimizing credits.
How this works in Tapistro
Step 1: Create an Account Classification AI Agent
From the AI Agent tab, ensure you have “Account” selected and create a new agent.
Provide the name of the AI Agent according to your naming convention
E.g.: “Prefix_Manufacturing ICP Classification_Jan2026"
Define your Account AI Agent as an “Account Classification Agent” under the Evaluation Config type.
Provide the agent with input attributes which will dictate what data the agent consumes to make the assessment.
E.g. Use ’name’ and ‘domain’ as defaults or include fields like ‘description’.
Define classification categories and the description of each category, for example:
Option 1: Core Manufacturer
The company that designs, owns, and sells its own products under its own brand and uses manufacturing as a core part of its value creation. Manufacturing may be in-house or partially outsourced, but the company owns the product IP, roadmap, and go-to-market strategy.
Option 2: Contract Manufacturer
A company that manufactures products on behalf of other companies and does not own the end-product brand or IP. Their primary value is operational execution—production, assembly, testing, or packaging—rather than product ownership.
Option 3: Manufacturing Adjacent (logistics, distributor)
....
Option 4: Others
All others
Validate: Click the ‘Preview’ button within the edit window of the AI Agent and select a few options from your list of accounts to review initial results. Adjust category definitions if needed.
Preview window output:
Step 2: Apply AI Agent inside a Journey to classify all ICP accounts
Add a “Tap AI” step in your journey and use the picker to select your Classification AI Agent.
The same Classification AI Agent can be used across multiple journeys
This step will classify all accounts by creating a new field populated with one of your defined categories.
If you’ve used a classification agent to help categorize the accounts pulled in from the various vendors, you may also want to add an additional filter that removes certain categories from your TAM list.
For example, to remove any account categorized as “Others,” use the following expression:
payload -> 'computed:558' ->> 'Prefix_Manufacturing ICP Classification_Jan2026' != 'Others'
where you replace it with your AI Agent ID and name.(Use this if citations and reasoning are not toggled on)
A4: Compile the final Account TAM with Calculated Attributes
You have arrived at the final step of your account list build! Up to here, you have built sources + journeys. You’ve built classification agents to categorize accounts and learned how to use advanced filtering for suppression lists. Now, we bring everything together to form one master TAM list. To do this, we will give each account a stamp of approval then create a unified journey that pulls all approved accounts into an automated workflow.
Note: these last steps are only needed if you used multiple data vendors (and therefore multiple sources + journeys) to get full TAM coverage.
Step 1: Stamp of Approval
At the end of each of your account search journeys, after your classification agents and essential filtering steps, you can end each branch with a final TapAI step with a ‘Calculated Attribute’ agent.
From the AI Agent tab, ensure you have “Account” selected and create a new agent.
Provide the name of the AI Agent according to your naming convention
E.g.: “Prefix_Manufacturing TAM_Approved for Cold Outreach"
Define your Account AI Agent as a “Calculated Attribute Agent” under the Evaluation Config type.
Enter the expression: 1=1
This will create a new field (called “Manufacturing TAM_Approved for Cold Outreach") on every account that passes through this step in a journey, and it will return the value ‘TRUE’
This agent should be placed as the final step of every account search journey used for a TAM-building campaign.
Creating the Calculated Attribute:
Adding in Journey:
Step 2: Pull List into Master TAM Journey
This step pulls all accounts with the stamp of approval into one source so you can send all accounts through workflow automation journeys. This is executed using a Source + Journey ingest pattern.
Define a new Source with Origin Type set to ‘Account List.’
Name the source according to your naming convention
For example: “Jan2026_Mfg_Midmarket_Approved_TAM"
In the Condition Expression box, you’ll use the Agent ID of your Stamp of Approval agent to write your expression:
e.g. (payload ->> ‘computed:84’)::BOOL = true
This will pull all approved accounts, from multiple list building journeys, into one source.
Step 2: Create Your Master TAM Journey
Create a new journey (e.g. Prefix_Jan2026_Master TAM_Outreach Journey) and add your Account List source to pull in your master TAM list!
Tapistro Entity: AI Agents, Journeys (with Data Filters and Conditional Branching)
A5. Account Research
What this step is
This step replaces manual research that your team would normally do on an account.
How this works in Tapistro
This is executed using Account-level Q&A AI Agents applied inside Journeys.
Step 1: Create account research AI Agents
From the AI Agent tab, ensure you have “Account” selected and create a new agent.
Name each agent using your naming convention.
Example: “Prefix_Jan2026_Mfg_Account_Summary”
Remember, if you plan to use the same agents across multiple journeys, name accordingly
E.g.: “Prefix_Default_Mfg_Account_Summary” for the go-to agent that can generate a summary for all new manufacturing accounts
Provide the agent with input attributes which will dictate what data the agent consumes to make the assessment. E.g. Use ’name’ and ‘domain’ as defaults or include fields like ‘description’. This is available as a dropdown menu.
Define your Account AI Agent as an “Account Q&A Agent” under the Evaluation Config type.
For a manufacturing use case, example research agents include
AI Account Summary – produces a concise overview of what the manufacturing account does and where it operates.
Expansions or Acquisitions – identifies new locations recently added.
Give a suitable name to your AI agent and define the question.
For the answer type, you should select ‘String’. It will ensure that the result is a dynamic and structured text.
Validate: Click the ‘Preview’ button within the edit window of the AI Agent and select a few options from your list of accounts to review initial results. Adjust the prompt or input attributes if needed.
Step 3: Apply research agents inside the Master TAM Journey
Within your Master TAM journey, add a new Tap AI step for each Q&A AI Agents you defined.
In your Journey, add a “Tap AI” step and use the picker to select your Q&A AI Agent.
The same Q&A AI Agent can be used across multiple journeys
This step will do research on all accounts by creating a new field populated with answers to your defined questions.
Pro tip: Ensure these steps run after TAM finalization and any segmentation so only eligible accounts are enriched.
Tapistro Entity: Q&A AI Agents (Account), Journeys
A6. Account Signals
What this step is
This step identifies buying signals and momentum across right fit ICP accounts.
How this works in Tapistro
This is executed using a combination of native Tapistro steps and Q&A AI Agents for signal discovery, all applied inside Journeys.
Step 1: Select Enrichment Step Types for certain signals
For certain signals, Tapistro offers best-in-class data partners which can be accessed by choosing a certain ‘Type’ within journey steps. These Types include:
Account Job Enrichment: looking for any open roles that fit your criteria (keywords in the description, or specific titles)
Account Ad Search: Whether an account is running Ads on digital media platforms
Account Job Enrichment Signal / Job Postings Signal are both steps inside the Journey, not AI Agents.
Step 2: Create Signal Discovery AI Agents
For fetching all other signals, you will want to use Q&A AI Agents. AI Agents can be used for account signals such as “Recently posted news, article, blog etc about [relevant topic]” or “Poor performance in recent financial statement.” These are dynamic web searches that can be used to score accounts or consumed by content generation agents to make outreach even more personalized and relevant.
To create a Signal agent, go to the AI Agent tab, and ensure “Account” is selected. Create a new agent for each signal you want to track.
For each agent:
Name the agent using the naming convention.
Example: “Prefix_Mfg_Account_RecentLaw”
Set Evaluation Config Type = Account Q&A Agent.
Provide Input Attributes such as name, domain, description.
Set Answer Type = String so results are structured and reusable.
Define the Question based on the signal type.
For a manufacturing use case, an example signal agent would be:
News: Recent laws
Agent Name: “Prefix_Mfg_Account_RecentLaw”
Question: “What new shipping, tariff etc laws have been passed that would impact this company. Identify any changes in the market that pertain to this type of company specifically”
Validate each agent by clicking Preview and testing on a few accounts to ensure signals are recent and relevant.
B. Person List
What this means
This module translates your account strategy into Buying Committee Coverage. By defining personas based on job titles and categories, you ensure Tapistro identifies, enriches, and prioritizes the exact stakeholders your team needs to reach. It moves your Journey from "where to target" to "who to engage."
When to use this
Use this module only after the Account TAM is finalized. Person search should not precede account qualification. This allows you to look for decision makers only in your qualified accounts.
B1. Define Personas
What this means: Personas
Personas are the discovery logic for your buying committee. They translate your GTM assumptions- roles like Operations, Engineering, or Finance into actionable search criteria.
How this works in Tapistro
Step 1: Create a new Persona
Go to Personas and select New Persona.
Select Create Persona. A persona definition screen should open.
Provide a name using your naming convention.
Example: “Prefix_Default_Mfg_Personas”
Set the Maximum Persons value to limit how many people should be found per account.
This prevents over‑pulling contacts from very large accounts.
Now you'll define each group relevant for your targeting
Set Maximum Persons per group
E.g. if SDR is one of your personas, you might only want to pull 5 SDRs and then move on to other persona groups
For each group, at least one of the following must be provided: Title, Keyword, Seniority, or Department for each role you add.
For each group, add a role and define the persons you want to look for. Each role should be treated as a separate kind of Job title/ decision maker.
Titles – Add approximate title matches.
Examples for manufacturing: Operations Manager, Plant Manager, Director of Manufacturing, VP Engineering
Keywords – Add exact words that must appear in a profile.
Examples: factory, production, Automation
Department – Use department filters instead of enumerating every title.
Examples: Operations, Engineering, Procurement
Seniority – Restrict to decision‑makers or go after entry-level employees
Examples: Manager, Director, VP, C‑Level
These filters allow Tapistro to target stakeholders precisely without listing every possible job title variation.
Persona by titles:
Persona by seniority:
Validate: Click the ‘Preview’ button within the edit window of the Persona and select an account from your list of accounts to review initial results. You will see some sample Persons from your defined roles. Adjust role parameters if needed.
This step ensures personas return relevant and departmentally correct contacts.
Tapistro Entity: Personas
B2. Run Personas in Journey
What this means
This step builds the Person TAM across all TAM accounts.
How this works in Tapistro
Step 1: Add Person Search to the Master TAM Journey
Open the Master TAM Journey that pulls from the approved, complete TAM.
Add a Person Search step and select the finalized persona from the picker.
Name the step for clarity: e.g. PersonSearch_Mfg Persona
Configure the step with the enrichment waterfall. You can choose any of: Wiza, Explorium, ContactOut, TheSwarm, Apollo, TapAI.
The enrichment waterfall will only go to the next source if the max personas is not yet hit.
For credit optimization, the Tap AI source is only recommended when you're struggling to find persons. Avoid using as a default.
Add a Person Email Validation. From the source picker, select either Hunter or NeverBounce.
This ensures outreach systems are protected, and deliverability remains high.
Run the Journey for a small sample of accounts to validate:
Roles found (Ops, Engineering, Finance)
Email availability
Seniority mix
This applies the persona logic (titles, departments, seniority, keywords) to every right fit account while allowing validation before scaling.
Review fill‑rate (people found per account, email coverage, seniority mix).
If fill-rate is low, add additional vendors to your waterfall or choose the TapAI option
Pro tip: Always run your Journey for a sample account such as 10 to preview. This allows you to iterate based on the actual output and helps in saving credits.
Tapistro Entities: Personas, Journeys, AI Agents
B5. Person Research
What this means
Adds qualitative insight to individual stakeholders in the accounts.
How this works in Tapistro
Use Person Q&A AI Agents to summarize background and relevance for each person.
Create a Person Q&A AI Agent.
Name it using your convention:
Example: “Mfg_PersonSummary”
Provide Input Attributes for both person level and account level. Both are available as dropdown menu.
You can also refer to other AI agents created to use that executed information in other agents.
Question example: “For the given person create a coherent summary from their account details and their profile information.”
Answer Type: String
Use Preview to validate a few accounts.
Add this AI Agent as a Tap AI step after the Person Search and enrichment step in the Master TAM Journey.
Tapistro Entities: Journeys, Q&A AI Agents
B6. Person Signals
What this means
This step mirrors the account signal step, helping you identify buying signals and momentum on the individual level.
How this works in Tapistro
This is executed using Person Q&A AI Agents for signal discovery.
Step 1: Create Person Signal Discovery AI Agents
From the AI Agent tab, select “Person” and create the Q&A agents to search for Person Signals.
Note: personal signals are limited due to privacy restrictions and 3rd party platform logins. Before creating a custom person signal, check with Tapistro support to confirm viability.
For each agent:
Name it using the naming convention.
Set Evaluation Config Type = Person Q&A Agent.
Provide Input Attributes from the dropdown menu.
Set Answer Type = String.
An example Signal Agents include:
Person News (Signal)
Name: “Mfg_PersonNews”
Question: “Find me recent news on this person such as promotion, features, PR articles, achievements.”
Validate each agent using Preview on a small set of contacts.
Step 2: Apply inside the Master TAM Journey
In the Master TAM Journey (after the person search):
Run any Person Q&A Signal Agents
Running this journey at this point ensures your team starts with a qualified account view and a deep-dive analysis of the decision-makers that matter most.
Tapistro Entities: AI Agents (Person), Journeys
C. Content
What this means
This module converts account and person intelligence into personalized messaging that GTM teams can deploy at scale.
When to use this
Use this after the Final Person TAM is created and consent rules are applied.
C1. Email Content Generation
What this means
Instead of static templates, Tapistro uses AI Content Generation Agents to craft messages tailored to each buyer’s context- their role, company signals (e.g., news, technologies), and engagement history- saving hours of manual writing while improving relevance and ultimately response rates and conversion.
When to use this
Use this step after B (Person List) is complete, once Person TAM is enriched and scored, but before you activate them in channels (email, outreach tools, etc.).
How this works in Tapistro
Step 1: Create an Email Content AI Agent (Refer to Appendix B for detailed info and prompt templates)
Step 1: Create the Content AI Agent
Navigate to AI Agents and select Person as the entity type.
Click New Agent to open the content agent definition screen.
In the Response Value Type field, select string.
Name the agent per your naming convention:
Example: “Prefix_Jan2026_Mfg_Email1”
Set the Evaluation Config Type to Person Content Generation AI Agent - this tells Tapistro the output should come from a free-text AI response tailored to each person.
Provide Input Attributes that the AI can use to personalize content, such as Namke, Account Name, other AI agents.
If your journey includes a signal (e.g.: a Q&A agent looking for recent financial news about a company), you can reference the output of that AI agent in your Input Attributes. .
In the Type field, select emailFull or emailPS. Use the former option to generate a medium to longer message with more details, such as an email body. Use the latter option to generate a very short message, such as a sentence for an email PS.
In the Tone field, select one of the available tones based on your objective.
In the Goals field, provide a detailed prompt describing what you want the AI Agent to generate.
Please refer to Appendix B for detailed prompts
Pro tip: The Content Generation AI Agent can capture details such as a company’s tech stack, recent hiring trends, and persona role making outreach smarter than static templates.
Step 2: Validate the agent
Within the AI Agent UI, click Preview.
Select a few contacts from your Person TAM.
Review the generated content for:
Personal relevance (correct title / company)
Tone and structure (aligned to your brand)
Objective communication
Proper call-to-action
Why: Previewing before production lets you refine questions or inputs without wasting Journey credits or sending undesired content.
Configuration:
Step 3: Add content generation to the Master TAM Journey
Open the Journey you have been working on, where personalization will happen.
After scoring steps, add a Tap AI step. Name the step per your conventions.
From the picker, select the Email Content Agent you created.
Save the Journey.
This ensures every right fit person flowing through that Journey gets a custom message.
Step 4: Optional: Sequence and Follow-Up Content
You can repeat the same pattern to generate:
Follow-up email content
Define agents like “Prefix_Jan2026_Mfg_EmailContent_Email2”
Reference the previous content gen agent in your input attributes for a seamless sequence
LinkedIn message drafts
Define different Content Generation agents with prompts tailored to those channels.
Each of these agents feeds into Journey steps as Tap AI steps.
Follow up email:
Tapistro entity: Content Generation AI Agent, Journey
D. Channels - Activation via Outreach
What this means
This module activates your TAM list by sending AI generated content to an outbound engagement platform - Outreach.io. Destinations in Tapistro are the mechanism through which you route final Person and Account data into external systems.
You’ll build one or more Destinations in Tapistro that map fields into Outreach and then add them as the final step in the Journey.
When to use this
Use this once:
Person TAM is finalized consent status
Personalized content is generated (Section C)
You are ready to send sequences or lists into Outreach
D1. Create an Outreach Destination
Step 1: Navigate to Destinations
Go to Destinations in Tapistro.
Click New Destination.
Step 2: Choose the Destination Type
Select Outreach.
Name the destination using your naming convention:
Example: “Prefix_Jan2026_Mfg_Outreach_Push”
Step 3: Configure Connection (Ignore if already done)
Authenticate and connect to your Outreach account.
This typically involves an API key or OAuth login.
Once connected, you’ll see lists and mailboxes configuration available for mapping.
Step 4: Map Tapistro Fields to Outreach
Add the sequence ID and mailbox you want to use for this campaign.
The output of each Content Generation AI agent will map to a new variable in Outreach.
Contact the Tapistro Support team for details of Tapistro to Outreach projections.
D2. Use the Outreach Destination in a Journey
Step 1: Add a Destination Step
Go to the Journey steps.
Add a new step and select the type Destination.
Select your Prefix_Jan2026_Mfg_Outreach_Push destination from the picker.
Save the Journey.
Tapistro Entity: Destinations, Journey
E. Feedback Loop - Closing the GTM Loop
What this means
This module brings interaction and engagement data from Outreach back into Tapistro so it becomes part of the living GTM intelligence layer - not just a reporting artifact.
When to use this
Use this after Outreach activation begins. This will run continuously while campaigns are live and even after they end.
E1. Ingest Outreach Engagement into Tapistro as a Source
What this means
Outreach becomes a data source inside Tapistro. Every open, click, or reply becomes a signal attached to a person and account.
Step 1: Create an Outreach Source
Go to Sources and click New Source.
Set Origin Type = Outreach
Name it using convention
Example: Outreach_Source
This source will continuously pull:
Opens
Clicks
Replies
Email IDs
Timestamps
Sequence IDs
Person + Account identifiers
Mappings:
In the Tapistro Field Name add outreach:last_event_type
In the Signal Field Expression add payload ->> 'event_type'
E2. Create the Outreach Nurture Journey
What this means
This Journey converts raw engagement events into Signals unified on the Profile of each person. This is where Outreach activity becomes GTM intelligence.
Step 1: Create a Nurture Journey
Create a new Journey
Name it per your convention:
ex: AlwaysOn_Outreach_Events
In the first step of Source Ingest, select the source created above from the picker.
Add a Data Filter step that will enable the events from email to flow into Tapistro.
Configure the expression in the filter:
payload->>'event_type' IN ('EMAIL_BOUNCE', 'EMAIL_LINK_CLICK', 'EMAIL_OPEN', 'EMAIL_REPLY', 'EMAIL_SENT' , ‘OPT_OUT’)
Save and run the Journey on schedule.
Now every open, click, sent, bounces, opt-outs and replies will flow into this Journey and get added to all profiles in Tapistro, creating a coherent view of actions and responses. Please
F. Sync to CRM
What this means
This produces CRM-ready files (Accounts and Persons) that sales can upload into Salesforce or any CRM.
Tapistro does all exports through an entity called Destinations.
F1. CRM Sync
How this works in Tapistro
Step 1: Create a Destination
Go to Destinations.
Click Create Destination.
Select CSV Export.
Exports are always account-only or person-only. If you want to export both, run this process twice. To export data go to any of the tab such as activations, accounts, persons and use the download button from the menu icons on the right.
Name using convention:
Prefix_Jan2026_CRM_Export_Accounts_Mfg
Step 2: Add the CRM Export/Sync step in the Master TAM Journey
Add a Destination step in the Journey to configure the final push out of Tapistro. From the picker select the Destination created for CRM export CSV.
F2: Ingest data back to Tapistro
What this means
After the CRM upload, Tapistro needs CRM IDs and lifecycle data to continue orchestration.
How this works in Tapistro
Step 1: Create a CRM Ingest Source
Go to Sources.
Click Create Source.
Select CSV Ingest.
Name it:
Prefix_Jan2026_CRM_Ingest_Mfg_Accounts
Step 2: Upload CRM file
Upload the CRM-exported CSV.
Preview if all fields are being mapped. Add any if the system does not authenticate. Validate and save.
Step 3: Map fields back into Tapistro
CSV Upload workflow will auto suggest mapping. Some fields might not be mapped which user can map.
Step 4: Attach the Source to a Journey
Create a new Journey and name the Journey according to your naming convention.
E.g.: “Prefix_Jan2026_CRMIngest_Mfg_Accounts".
In the default "Source Ingest” step, open the “Source ID” picker and select the CRM Ingest Source you created.
Save the Journey and run it.
This will provide Tapistro with the necessary account level data to track any signal movements and enable profile unification.
Tapistro entity: Destinations, Journey