Monthly Addepar client letter drafts for advisor review
On the first business day of every month, draft a personalized performance letter for each top-tier household and queue an advisor review task in Salesforce.
Integrations
Addepar
Google Docs
Salesforce
Type
Categories
- Finance
- Operations
On the first business day of every month, in the morning, run a monthly performance letter drafting pass across my top-tier households in Addepar. For each qualifying household, produce one Google Doc draft plus one Salesforce follow-up task on the primary contact so I can review, tweak the tone, and send. Never send the letter automatically.
For each household, work through these steps in order.
1. Pull the household and the entities I cover under it (accounts, trusts, holdings) using addepar.List Entities. Filter to top-tier households using whatever segment tag, AUM threshold, or static list I have configured.
2. Run my saved monthly Portfolio View against the household for the prior calendar month using addepar.Get Portfolio View Results. Capture return versus benchmark, contribution by asset class, biggest gainers and losers by contribution to return, and cash flow activity (contributions, distributions, fees).
3. Use addepar.List Positions and addepar.Query Transactions to find the household's largest realized moves (closed positions and biggest sells with gains or losses over the prior month) and largest unrealized moves (current-position movers). These become the concrete anchor points the letter cites.
4. Find the primary contact for the household in Salesforce using salesforce.SOQL Query. Match the Salesforce Account by household name or external id, then query the primary Contact so I know where the follow-up task lands.
5. Draft the letter as a new Google Doc using google-docs.Create Document (title it like "Monthly letter for {household}, {prior month} {year}") and then google-docs.Batch Update Document to insert the body. File it in the client's folder in Drive. Write in warm, plain language and mirror the tone and structure of my previous letters. If I provide sample past letters or a short style guide, follow that voice closely.
6. Create a Salesforce follow-up task on the primary contact using salesforce.Create Task. Title it "Review monthly letter for {household}", include the Google Doc link in the description, set the due date to the same day, and assign it to the advisor who owns the relationship.
Hard compliance rules the drafting agent must respect. Never send the letter to the client. Always leave a draft Google Doc plus a Salesforce review task. Do not fabricate market commentary or invent themes that the underlying Addepar numbers do not support; if a month is quiet, say so plainly. Ground every claim in the actual portfolio view results, positions, and transactions. Use the same voice and structure I already use with clients.
What it does
- Runs your saved monthly portfolio view for the prior calendar month and pulls each household's return versus benchmark, contribution by asset class, biggest gainers and losers, and cash flow activity
- Writes a warm plain-language performance letter as a new Google Doc filed in the client's folder
- Creates a follow-up task in Salesforce on the primary contact so the advisor can review, tweak the tone, and send
- Nothing is sent automatically, so every letter stays a draft until the advisor approves it
What you’ll need
- An Addepar login for the household and portfolio data
- A saved monthly Portfolio View in Addepar covering return versus benchmark, contribution by asset class, and cash flows
- A Google account for drafting the letter in Google Docs
- A Salesforce login where the household's primary contact lives
- A short style guide or a few past client letters so the draft mirrors your voice
How to customize it
- Which households count as top-tier: a segment tag, an AUM threshold, or a static named list
- The tone and structure the letter follows, so it reads like the advisor already writes
- The Google Drive folder each letter lands in and how the Salesforce review task is titled and assigned
Use cases
- AI Reports
- Content Generation