How to migrate from Monday Sales CRM to Strkr

Monday boards drift. A workspace that started as a deal pipeline tends to accrue side boards for forecasting, account planning, QBR tracking, and whatever a sales manager wanted visible last quarter. Before you plan a migration you need an honest inventory of what is actually running the business versus what is decoration. Open every board tagged with sales, revenue, pipeline, accounts, contacts, or activities. For each one, write three things on paper: who touches it weekly, which columns are populated above eighty percent, and which columns are the source of truth versus a copy of something else. Boards nobody has touched in sixty days are archive candidates, not migration targets. Columns that stay empty are noise you do not want to inherit. The goal of this step is to arrive at a short list, usually five to eight boards, that represent the real system of record. Everything else migrates to the archive bucket, not to Strkr. This single audit is the most common place migrations go wrong. Teams that skip it carry two years of accumulated mess into a new system and spend the next quarter wondering why nothing feels better.

• List every Monday board touched in the last ninety days by anyone in sales or RevOps
• For each board, record column fill rate, weekly active users, and whether it is a source of truth or a mirror
• Flag boards that duplicate data living on another board; pick one survivor per concept
• Produce a one-page inventory of the five to eight boards that will actually migrate

Monday thinks in boards and columns. Strkr thinks in objects: accounts, contacts, opportunities, products, activities, and tasks. The hardest part of the migration is translating the first model into the second. Draw a mapping table on paper before anyone opens a CSV. Your deals board usually maps to opportunities, with the deal owner column becoming the opportunity owner, the stage column becoming the stage field, and the amount column becoming amount. Contacts live on a contacts board that maps to the Strkr contact object, and the company column becomes a link to the account object. Monday boards almost never carry a clean account layer, so most migrations invent one at this step by deriving accounts from unique company names across contacts and deals. Capture every single column, even the weird ones. A Monday column called priority with values low, medium, high usually belongs on the opportunity as a picklist, not a tag. A column called forecast category belongs on the opportunity forecast category field, which Strkr ships natively. Columns that are purely for Monday automations, like a formula flagging stale deals, do not migrate; the equivalent logic lives in Strkr hygiene rules and does not need a storage field. Spend an afternoon on this mapping. Rushing here produces the migration mistakes that are expensive to unwind after cutover.

• List every column across the five to eight surviving boards and its data type
• Match each column to a Strkr object and field, flagging columns that have no destination
• Decide what to do with no-destination columns: create a custom field, discard, or merge into an existing field
• Derive the account layer from unique company values across contacts and deals before mapping anything else
• Review the mapping with one frontline rep and one RevOps partner before touching Strkr

A clean import depends on a clean destination. Before you run a single CSV through Strkr, set up the receiving model: pipeline stages with exit criteria, required opportunity fields, picklist values, custom fields identified in the mapping step, and the owner lookup table that pairs Monday user IDs with Strkr user IDs. Pipeline stages are the single most important decision. Monday boards tend to have one giant stage column with twelve values ranging from "cold lead" to "paid invoice." Do not import that structure. Design a tighter pipeline in Strkr, five or six stages, each with exit criteria, before importing deals. Then write a mapping from old Monday stage to new Strkr stage so every deal lands in the correct new stage based on evidence, not based on whatever the Monday column happened to say. Required fields matter too. If you want amount, close date, next step, decision maker, decision date, and source required at creation in Strkr, you need to decide now how to populate those for historical deals that did not carry them in Monday. The usual pattern: backfill from the last email thread, mark unknowns as "legacy import" with a tag, and plan a cleanup sprint in week one post-cutover. Build the model empty, review it with sales leadership, then open the import gate.

• Create Strkr pipeline stages with exit criteria tied to your real buyer journey, not a copy of the Monday stage column
• Build a stage mapping table that translates every Monday stage value to a Strkr stage
• Configure required opportunity fields and the fallback plan for historical records missing them
• Create custom fields identified in the mapping step with the correct type and picklist values
• Build a user mapping table pairing Monday user IDs or email addresses with Strkr user IDs

Monday export is per-board, CSV, and quietly selective. Use the board menu, choose Export to Excel, open the result in a text editor to confirm UTF-8 encoding, and spot-check that long rich-text fields are not truncated. Export each surviving board once, with every column visible before you export. If you have grouped columns or hidden columns on the board view, make them visible first; Monday exports what is on screen, not what is in the data model. For boards with more than ten thousand rows, split the export into chunks and verify row counts match. The three Monday export gotchas that trip every migration: subitems export separately and need to be stitched back to parents by name, person columns export as display names and need to be reconciled to the user mapping table, and link columns export as the display text, not the URL target, so if you store call recording links or document URLs in link columns you need to export those boards twice and splice. Rename files on your laptop so there is zero ambiguity about which export is which: use board name plus date plus row count. Store everything in one folder locked by permissions you control. These files hold the keys to your sales history for the next two weeks; treat them like production data.

• Make every column and every row visible on each board before exporting
• Export each board as CSV, confirm UTF-8 encoding, and check for truncated long-text fields
• For boards over ten thousand rows, split the export and reconcile row counts
• Export subitems separately and plan to stitch them to parents by name or ID
• Rename each file with board name, export date, and row count; store in a permissioned folder

The exports do not drop straight into Strkr. You need a transformation layer: a spreadsheet or a short script that reads each Monday CSV, applies the mapping decisions you made in step two, and produces a Strkr-ready import file per object. For the account object, dedupe companies across contacts and deals, assign a canonical account name, and create a stable account ID that both contacts and opportunities will reference. For contacts, map Monday person records to Strkr contact fields and resolve the account link using the ID you just assigned. For opportunities, apply the stage mapping from step three so every deal lands in the correct Strkr stage, fill required fields from Monday columns where possible, and tag records with "monday_legacy" so you can find them later for cleanup. For activities and notes, the usual move is to migrate the last twelve months into Strkr activity records and leave older history as a read-only export file linked from the account record. Nobody needs 2019 call notes in the daily workflow, and loading them pollutes activity timelines. Validate every transformed file before import: run row counts, check that every opportunity has a valid account ID, confirm every stage value matches a real Strkr stage, and verify every owner value matches a Strkr user. Fix issues in the transformation files, not in Strkr after import.

• Dedupe accounts across contact and deal exports; assign a canonical account name and stable account ID
• Map contact records to Strkr contact fields and resolve account linkage
• Apply the stage mapping table so every opportunity lands in the correct Strkr stage
• Tag every imported record with "monday_legacy" and the Monday board of origin for traceability
• Validate row counts, stage values, owner values, and foreign keys before touching the Strkr import tool

Never import into production first. Spin up a Strkr sandbox or a dedicated staging workspace, run the full import there, and compare it against Monday for a defined parity window. The parity test is where migrations earn their trust. Pick the last ninety days of closed-won and closed-lost deals from your Monday export and verify every one of them appears in Strkr with correct amount, close date, stage, owner, and account linkage. Pick the top twenty open deals by amount and verify next step, decision maker, and expected close date carried over. Pick ten random contacts and walk their activity history forward from today backward to confirm nothing material is missing from the last twelve months. Any delta becomes a transformation fix, not a Strkr fix. Rerun the import after each round of fixes. Expect three rounds. Teams who stop at round one almost always discover a data problem in week two of production that could have been caught in the sandbox for free. The parity test also doubles as training: sales leaders who walk their own territory in the sandbox before cutover land in production with far more confidence and far fewer "where is my pipeline" tickets.

• Spin up a Strkr sandbox or staging workspace with the production configuration applied
• Run the full set of transformed imports into the sandbox
• Spot-check the last ninety days of closed deals, top twenty open deals, and ten random contacts against Monday
• Log every parity gap, fix the transformation files, and rerun the import
• Walk two frontline reps through their own territory in the sandbox before scheduling production cutover

Monday automations do not come with you. Every "when stage changes to closed-won, notify Slack" rule, every form that creates a lead, every Zapier recipe that pushes new deals to the finance board, every Gmail integration that logs threads to the deal: all of it needs to be rebuilt in Strkr before cutover, not after. Walk the Monday automation center and list every recipe. For each one, decide whether it belongs on the Strkr side as a workflow rule, a notification, or an integration. The common patterns move cleanly: new lead from web form becomes a Strkr form submission that creates a lead or opportunity, stage change triggers Slack notification becomes a Strkr workflow with a Slack integration, scheduled report email becomes a Strkr dashboard subscription. Zapier recipes often collapse because Strkr ships native integrations for the systems that mattered: calendar, email, Slack, data warehouse. Rebuild in Strkr with the fewest moving parts, test each one in the sandbox against a known trigger, and only then schedule the Monday-side disable. Do not try to run Monday automations and Strkr automations in parallel for more than forty-eight hours. Dual-firing automations create duplicate records, duplicate notifications, and the kind of trust damage that haunts a migration for a quarter.

• List every Monday automation, form, Zapier recipe, and integration touching the sales workspace
• Classify each one as Strkr workflow, Strkr integration, Strkr notification, or deprecate
• Rebuild each surviving automation in Strkr and test against a known trigger in the sandbox
• Schedule Monday-side disable to happen within forty-eight hours of Strkr cutover, never earlier
• Audit the first forty-eight hours post-cutover for duplicate records or missed notifications

Cutover is a planned event, not a slow drift. Pick a date, usually a Friday afternoon or a quarter boundary, and announce it two weeks ahead. On cutover day: run the final incremental export from Monday capturing anything changed since the last sandbox import, run the final transformation and import into Strkr production, verify spot-check parity on the top twenty open deals, flip the Monday automations off, flip the Strkr automations on, and send the all-hands message pointing everyone at Strkr. Make the Monday workspace read-only immediately. Not later, not after a grace period: read-only on cutover day. The single most common post-cutover failure is a well-meaning rep updating a deal in Monday on day three because that is where their muscle memory is. Lock the write path and the muscle memory follows. Week one is active babysitting. Hold a daily fifteen-minute standup where reps raise anything that looks wrong, pair every raised issue with an owner on the migration team, and track resolution in a shared doc. Expect roughly fifty data corrections and five configuration tweaks in the first five days. That is normal. Week two the pace drops dramatically; week three you archive the migration doc and start running the business.

• Pick a cutover date two weeks out and announce it twice: once at two weeks, once at one week
• Run final incremental export, transformation, and import on cutover day
• Verify top twenty open deals, flip automations off in Monday and on in Strkr, send all-hands message
• Set Monday workspace to read-only on cutover day; do not leave a write path open
• Hold a daily fifteen-minute standup in week one to triage issues raised by reps