Migration Playbook

Podium Helpshift

Podium to Helpshift: The Complete Migration Playbook

A 36-step runbook across six phases — track your progress, and open the right tool at every step.

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TL;DR

Podium to Helpshift migration requires a custom API-based ETL pipeline — no native path exists. Podium Conversations become Helpshift Issues, Contacts become User Profiles. Reviews and Payments have no target. Budget 80–160 engineer-hours.

There is no native migration path between Podium and Helpshift; the platforms share almost no structural overlap. Podium operates on a location-based, multi-channel messaging model centered on SMS and webchat for local businesses, while Helpshift uses an app-based, issue-centric model designed for in-app mobile support. Podium Conversations must be transformed into Helpshift Issues, Contacts into End User Profiles, and Locations into Apps or Tags — with Reviews, Payments, and Campaigns having no Helpshift equivalent and requiring external archival. A custom API-based ETL pipeline is the only reliable approach for full-fidelity migration, typically requiring 80–160 engineer-hours for a mid-size dataset of 10K–50K conversations.

Read this first

Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.

TL;DR: Podium → Helpshift Migration

Podium is a messaging, reviews, and payments platform for local businesses. Helpshift is a mobile-first, in-app customer service platform built for apps and games. They share almost no structural overlap. Podium Conversations become Helpshift Issues. Podium Contacts map to Helpshift End User Profiles. Podium Locations map to Helpshift Apps or Tags. Reviews, Payments, and Campaigns have no native Helpshift equivalent — archive or discard them. There is no native migration path. A custom API-based ETL pipeline is the only reliable approach for full-fidelity migration. Budget 80–160 engineer-hours for a mid-size dataset (10K–50K conversations) and expect 2–4 weeks elapsed time.

Reviews, Payments, and Campaigns are dead ends

Helpshift has no concept of review management, payment processing, or marketing campaigns. Export these from Podium and archive them in your data warehouse before migration. They cannot be imported into Helpshift.

Custom Issue Field types in Helpshift

Single line text (255 chars max), Multi-line text (100,000 chars max), Number, Date, Dropdown, and Checkbox. Plan your Podium attribute mapping around these six types. If a Podium attribute doesn't fit cleanly, use Multi-line text as a catch-all. Helpshift supports up to 20 global custom user fields and 30 app-level custom user fields. CIF dropdown values must be pre-configured in the Helpshift Dashboard — the API will reject payloads containing undefined dropdown values. (support.helpshift.com)

Helpshift API access is gated

The Integrations feature must be explicitly enabled by Helpshift for your account. Contact your Helpshift Account Manager before starting development. Typical enablement time: 1–3 business days, but can take up to a week during peak periods. This can add days to your timeline — request access in Week 1.

The runbook

Work top to bottom. Tick steps as you go — your progress is saved in this browser.

01 Discovery Establish why you are moving, what "done" means, and who signs off. 0/6

Objective A written scope with agreed success criteria, a named owner per workstream, and a budget approved by finance.

  1. Pull the real numbers out of Podium

    Support ops 1 day

    Export counts for tickets (open and closed separately), contacts, organisations, attachments, macros, triggers, automations, views and SLA policies. Note the oldest ticket date — history depth drives the whole timeline. Estimating from memory is the single most common cause of a blown migration window.

    Data Profiler Get real record counts instead of estimating from memory
  2. Decide what history actually moves

    Support lead 2 days

    Agree a cut-off with the support lead: all history, last 24 months, or open tickets plus a read-only archive. Every extra year of closed tickets adds API time and cost without adding much agent value. Get this in writing — it is the decision people relitigate mid-cutover.

    A "move everything" default is what turns a two-week migration into a two-month one.

    COI & ROI Calculator Build the 36-month business case you will need for sign-off
  3. Confirm Helpshift can hold your support model

    Solution architect 2-3 days

    Walk your current workflow through Helpshift: multi-brand, business hours, SLA targets, CSAT, side conversations, public vs internal notes, and any channel you depend on (voice, chat, WhatsApp, social). List anything with no native equivalent — those are project risks, not configuration details.

  4. Build the business case

    Project sponsor 1-2 days

    Model licence delta, migration effort, agent retraining, and the cost of staying put (Cost of Inaction). Executives approve a number, not a plan, and you will be asked for it again at the go/no-go.

    Helpdesk Migration Planner Turn ticket volume into a dated Podium → Helpshift timeline
  5. Name owners and set the go/no-go date

    Project manager 1 day

    One named owner each for data, configuration, integrations, and agent enablement, plus a decision-maker who can call a rollback. Put the go/no-go meeting in calendars now, 48 hours before the freeze.

  6. Archive externally

    Reviews, payments, campaigns, conversations older than 24 months.

Podium → Helpshift specifics

Mobile-first support
Podium is designed for local-business SMS and webchat. When the product is a mobile app or game, Helpshift's native in-app SDK is the right foundation. Helpshift provides SDKs for Android, iOS, Unity, React Native, Unreal Engine, Cocos2dx, and Xamarin.
In-app messaging over SMS
Podium's messaging is channel-dependent (SMS, email, webchat). Helpshift's messaging is embedded directly inside the app, reducing channel fragmentation and keeping users in-product.
AI and bot automation
Helpshift's bot engine supports intent-based automation, FAQ suggestions, and Custom Issue Field-driven routing. Podium's automation is limited to review invites, auto-responders, and marketing campaigns.
Issue-based pricing
Helpshift charges per issue created, not per seat or per location. For high-volume support teams with significant bot deflection (>40% deflection rates are common with well-tuned Helpshift bots), this can be substantially cheaper than Podium's per-location pricing.
Structured issue management
Helpshift offers Smart Views, SLAs, Automations, Custom Issue Fields, and agent queues. Podium's inbox is conversational but lacks structured ticketing workflows.

Don't move on until

  • Record counts confirmed for tickets, contacts, organisations and macros
  • Success criteria signed off by the support lead
  • Freeze window provisionally booked with the business
02 Data Audit Find out what is actually in the data before you try to move it. 0/6

Objective A profiled, cleaned export with every quality defect either fixed at source or explicitly accepted.

  1. Take a full Podium export and profile it

    Data engineer 1-2 days

    Export to CSV or JSON and profile every file: row counts, null rates per column, distinct values, and type consistency. Compare row counts against the API totals from Discovery — a gap here means your export is silently truncated, usually by pagination.

    Data Profiler Profile the Podium export for nulls, outliers and type drift
  2. Validate file structure before anyone writes a transform

    Data engineer 1 day

    Check delimiters, quoting, encoding (expect UTF-8, watch for BOMs and Latin-1), duplicate headers, and embedded newlines in ticket bodies. Ticket descriptions with raw newlines and commas break naive CSV parsers and silently shift columns.

    A single unescaped quote in one ticket body can shift every subsequent column without any error.

    CSV Validator Catch broken headers and ragged rows in the raw export
  3. Inventory PII and set retention

    Compliance / DPO 2 days

    Scan for emails, phone numbers, payment card fragments, national IDs and anything else regulated in ticket bodies and custom fields — support tickets are where customers paste things they should not. Decide what gets migrated, masked, or dropped, and record the legal basis.

    Ticket bodies and attachments routinely contain card and ID data that never appears in a structured field.

    PII & Compliance Scanner Find regulated fields before they land in a new system
  4. Quantify duplicates, orphans and dead references

    Support ops 1-2 days

    Count duplicate contacts (same email, different casing), tickets whose requester no longer exists, organisations with no members, and attachments whose parent ticket is gone. Fix these in Podium where you can — migrating them just moves the mess.

    Data Cleaner Strip empty rows, stray whitespace and dead columns
  5. Clean and normalise the export

    Data engineer 2 days

    Trim whitespace, drop empty rows and columns, normalise casing on emails and tags, and standardise every timestamp to UTC ISO 8601. Timezone drift is invisible at load time and shows up weeks later as SLA reports nobody can reconcile.

  6. Produce a masked copy for sandbox work

    Data engineer 0.5 day

    Generate a realistic but fake version of the export for testing and for any vendor who needs sample data. Loading real customer PII into a sandbox is a breach in most jurisdictions, and sandboxes are rarely covered by your DPA.

    PII Masker Generate a safe copy for sandbox and vendor testing

Podium → Helpshift specifics

Contacts
Total count, fields populated (name, phone, email, attributes, tags), percentage with valid email addresses
Conversations
Total count, average messages per conversation, date range, percentage with attachments
Messages
Total volume, attachment count by MIME type, message types (SMS, email, webchat)
Locations
Number of Podium Locations, mapping to Helpshift Apps
Payments
Count and status (archive — no Helpshift target)

Don't move on until

  • Export parses cleanly with no ragged rows or encoding errors
  • PII inventory complete and retention decisions recorded
  • Duplicate and orphan records quantified and triaged
03 Field Mapping Turn two schemas into one signed-off mapping spec. 0/6

Objective A reviewed field-level mapping covering every object, with an explicit decision for every field that has no target.

  1. Generate the first-pass Podium → Helpshift field map

    Solution architect 2 days

    Start from an automated match on both schemas, then review every row by hand. Automated matching gets the obvious 70% right and is confidently wrong on the rest — especially anything named "type", "status" or "custom_field_1".

    Schema Mapper Opens pre-loaded with the Podium → Helpshift field pair
  2. Map status, priority and channel values, not just field names

    Support lead 1-2 days

    Enumerate every value in each picklist on both sides and map them explicitly. Value-level mismatches are the defect class that survives all the way to production because the field itself mapped fine — a ticket that should be "Pending" arriving as "Open" reopens SLA clocks.

    Statuses with no target equivalent (on-hold, pending-customer) need a policy decision, not a best guess.

  3. Decide how custom fields land

    Solution architect 2 days

    Create the target custom fields first, matching type exactly (a dropdown mapped to free text can never be mapped back). Where Helpshift has no equivalent, decide between a new custom field, a tag, or a note appended to the ticket body — and record which.

  4. Resolve identity and threading

    Data engineer 1 day

    Decide how source IDs are preserved — most platforms will not let you set the primary key, so keep the original ID in a custom field. Without it, reconciliation becomes fuzzy matching and every future support question about an old ticket is unanswerable.

    Losing the original ticket ID makes reconciliation and rollback effectively impossible.

  5. Plan attachments, inline images and threading order

    Data engineer 1-2 days

    Confirm size limits, allowed MIME types, and whether inline images survive as attachments or need rehosting. Decide the comment ordering and author attribution rules: comments loaded out of order, or all attributed to the API user, destroy the conversation history agents rely on.

  6. Freeze and sign off the mapping spec

    Project manager 1 day

    Version the spec, walk the support lead through it row by row, and get explicit sign-off. Any change after this point goes through change control — mid-flight mapping edits are how partial loads happen.

Don't move on until

  • Every source field is mapped, deliberately dropped, or parked in a custom field
  • Status, priority and channel value maps agreed with the support lead
  • Mapping spec version-controlled and signed off
04 Test Migration Prove the pipeline on a small, representative slice. 0/6

Objective A pilot load into a Helpshift sandbox that reconciles cleanly and has been reviewed by real agents.

  1. Stand up a Helpshift sandbox that matches production config

    Solution architect 2-3 days

    Create the custom fields, groups, brands, business hours and SLA policies first. A pilot into a default sandbox tests nothing, because the failures you care about are all configuration mismatches.

  2. Pick a deliberately nasty pilot sample

    Data engineer 0.5 day

    Take 500-1000 records chosen for difficulty, not convenience: the longest ticket threads, tickets with the most attachments, non-Latin character sets, merged and split tickets, deleted requesters, and every status value. A clean random sample proves only that easy records are easy.

  3. Run the load with masked data and instrument everything

    Data engineer 1-2 days

    Log every API request and response with its source record ID. When 40 records fail out of 10,000 you need to know exactly which ones and why, without re-running the whole batch.

    PII Masker Never load real customer PII into a sandbox
  4. Measure real throughput against the rate limit

    Data engineer 1 day

    Record achieved records-per-hour under Helpshift's actual rate limits, including retries and backoff. Extrapolate to the full volume: if the maths says the full load exceeds your freeze window, you fix that now, not on cutover night.

    Published rate limits are ceilings, not throughput. Assume real-world rates are meaningfully lower once retries and backoff are counted.

  5. Reconcile the pilot and triage every failure

    Data engineer 1-2 days

    Diff source against target on record counts and field-level values. Every discrepancy gets a root cause and a fix — "probably fine" at pilot scale becomes thousands of broken records at full scale.

    Migration Validation Tool Diff the pilot batch against source before scaling up
  6. Put real agents in front of the pilot data

    Support lead 2 days

    Have two or three agents work sample tickets end to end in the sandbox. They find the things reconciliation cannot see: unreadable threading, missing context, macros that no longer make sense. Fix the mapping, then re-run.

Don't move on until

  • Pilot batch reconciles to 100% on record counts
  • Agents have reviewed sample tickets and confirmed they are workable
  • Measured throughput extrapolates to a viable full-load window
05 Cutover Execute the switch inside a controlled, reversible window. 0/6

Objective All in-scope data live in Helpshift, agents working in the new system, and a rollback path that stayed available throughout.

  1. Pre-load history before the freeze

    Data engineer 3-10 days

    Load closed tickets and contacts days or weeks ahead while Podium stays live. Only open tickets and the final delta need to move inside the freeze — this is the single biggest lever on window length.

    Helpdesk Migration Planner Size the freeze window from Helpshift's real API limits
  2. Publish the runbook with times, owners and abort criteria

    Project manager 1 day

    A timed sequence: freeze start, final export, delta load, channel switch, smoke test, go/no-go, agent switch. Name who does each step and the explicit condition that triggers a rollback. Decide the abort criteria before the night, when nobody wants to be the one to call it.

  3. Freeze Podium and take the final delta

    Support ops 2-4 hours

    Stop new ticket creation, let agents finish in-flight replies, then export everything changed since the pre-load. Announce the freeze to the whole business, not just support — someone always tries to raise a ticket during it.

    Tickets created during an unenforced freeze land in the old system and are the most common source of permanently lost data.

  4. Load the delta and open tickets

    Data engineer 2-6 hours

    Run the delta load, then reconcile counts before touching any channel. Do not repoint email until the delta has verified — an inbound ticket arriving mid-load is far harder to untangle than a few extra minutes of freeze.

    Migration Validation Tool Confirm the final delta landed before you reopen
  5. Repoint channels and verify with live traffic

    IT / integrations 2-4 hours

    Switch email forwarding and MX or connector settings, update chat widgets and web forms, and re-authorise integrations. Then send real test tickets through every channel and confirm each lands, routes and triggers the right automation.

    Email forwarding changes can take up to a full DNS TTL to propagate — check the TTL days in advance and lower it if needed.

    Cron Expression Builder Schedule the delta syncs that run through the freeze
  6. Run the go/no-go and switch the agents

    Project sponsor 1-2 hours

    Walk the exit criteria with the decision-maker, call it explicitly, then move agents over with a named person on hand for the first few hours. Keep Podium read-only rather than cancelled — cancelling the old contract on day one removes your only fallback.

Don't move on until

  • Full historical load complete and counts matched
  • Inbound channels repointed and verified with live test tickets
  • Rollback decision point passed explicitly, not by default
06 Validation Prove the migration is complete, then close it out. 0/6

Objective Documented evidence that data, workflow and reporting all survived, and a signed acceptance.

  1. Run the full reconciliation

    Data engineer 1-2 days

    Compare source and target on every object: total counts, counts by status, counts by group, attachment counts, and field-level spot checks on a random sample. Produce one report you can hand to an auditor.

    Migration Validation Tool Reconcile Podium and Helpshift record-for-record
  2. Verify field completeness, not just record counts

    Data engineer 1 day

    Re-profile the loaded data and compare null rates per field against the source profile. Matching record counts with a field that silently arrived empty is the failure mode counts alone will never catch.

    Data Profiler Prove field completeness held up through the load
  3. Rebuild reporting and compare against baselines

    Support ops 2-3 days

    Recreate your core dashboards — volume, first response time, resolution time, CSAT — and compare to pre-migration figures for the same period. Explain every variance; a changed SLA calculation is a real finding, not a rounding error.

    SLA and first-response metrics are usually recalculated from the loaded timestamps, so they will differ if any timestamp mapping was approximate.

  4. Test the workflow layer end to end

    Support ops 2 days

    Fire every trigger, automation, SLA escalation, macro and notification with a live ticket. Workflow does not migrate — it gets rebuilt — so it is untested until someone has actually watched it run.

  5. Confirm compliance and produce the audit trail

    Compliance / DPO 1 day

    Re-scan the loaded data for regulated fields, confirm retention and deletion policies are configured in Helpshift, and file the evidence with your PII decisions from the audit phase.

    PII & Compliance Scanner Produce the compliance evidence your auditor will ask for
  6. Sign off, then decommission on a schedule

    Project sponsor 1 day

    Get written acceptance against the Discovery success criteria. Keep Podium read-only for an agreed period (30-90 days is typical), take a final archive export, and only then cancel. Diarise the decommission date so it does not quietly renew.

Don't move on until

  • Full reconciliation report attached to the project record
  • Reporting baselines match pre-migration figures within agreed tolerance
  • Formal acceptance signed and archive retention scheduled

Field mapping reference

The field-by-field mapping for each object. Use this as the starting point for your mapping spec.

Concept Equivalent 11 fields
Podium fieldHelpshift fieldNotes
Contact End User Profile (via User Hub) Name, email, phone map directly. Attributes → Custom Data or CIF.
Conversation Issue One or more Podium conversations per Helpshift Issue, depending on thread-splitting strategy.
Message Message (within Issue) Direction (inbound/outbound) preserved. Attachments require separate upload.
Location App or Tag One Podium Location can map to one Helpshift App, or use Tags for routing.
Tag Tag Direct mapping. Tags in Helpshift filter Issues into Smart Views.
Attribute (Contact) Custom Issue Field (CIF) or Custom Data Depends on whether data is per-contact or per-issue.
Review ❌ No equivalent Archive externally. Helpshift has no review management.
Payment ❌ No equivalent Archive externally. Helpshift has no payment processing.
Campaign ❌ No equivalent Archive externally. Helpshift has no marketing automation.
Note No native equivalent Serialize into issue messages prefixed with " [Internal Note]" or archive externally.
Webchat Widget Web Chat SDK Requires separate SDK integration — not a data migration item.
Podium Contact Helpshift End User Profile 8 fields
Podium fieldHelpshift fieldNotes
uid identifier Use as external identifier for deduplication
name name Direct mapping; trim leading/trailing whitespace
phone phone Normalize to E.164 format with country code (e.g., +14155551234)
email email Lowercase, dedupe
createdAt created_at Preserve original timestamp
tags [] Tags (on Issues) Tags are per-Issue in Helpshift, not per-user
attributes{} Custom Data or CIF Map each attribute to a CIF type
locations [] App assignment One Location = one App (or use Tags)
Podium Conversation Helpshift Issue 5 fields
Podium fieldHelpshift fieldNotes
conversation.uid Custom Issue Field Store Podium UID in a CIF for cross-reference
conversation.channel.type Custom Issue Field Map to "phone", "email", "webchat" — values must be pre-configured in Dashboard
conversation.startedAt created_at Set via API on creation
conversation.assignedUser assignee_name Map Podium user → Helpshift agent
Messages Messages within Issue Preserve order, direction, timestamps
Podium Message Helpshift Message 4 fields
Podium fieldHelpshift fieldNotes
message.body body Direct mapping. 100,000 character limit in Helpshift.
message.createdAt Timestamp Preserve in message body or metadata. API may not allow timestamp override — prepend to body if needed (e.g., [2023-04-12 14:00 UTC]).
message.sender author Map to "agent" or "user" based on sender type. Note: Podium contact and sender fields on the message object are deprecated — resolve identity from contact and conversation records instead. (docs.podium.com)
Attachments Attachment upload Requires separate API call per attachment. Download during extraction — Podium attachment URLs expire after seven days. (docs.podium.com)
Podium Helpshift 12 fields
Podium fieldHelpshift fieldNotes
contact.uid identifier Preserve as immutable key for deduplication
contact.name name Trim whitespace, sanitize UTF-8
contact.phone phone Normalize to E.164 (e.g., +14155551234)
contact.email email Lowercase, dedupe, trim
conversation.uid podium_conversation_uid Store in a single-line CIF (255 char max)
conversation.channel.type original_channel Dropdown CIF — pre-configure values: sms, phone, email, webchat
location.name store_location Dropdown CIF or Tag depending on routing needs
message.body body Direct mapping; sanitize; 100K char limit
message.createdAt created_at Prepend to body if API restricts timestamp override
message.sender author Map to Agent ID or Customer ID; use conversation/contact records (deprecated sender field)
tags [].label tags Normalize naming conventions; lowercase, hyphenate
note.body — Prefix as " [Internal Note]" or archive externally

Risk matrix

Per-object risk for this pair. Plan extra validation around anything marked high.

ObjectRiskNotes
Contacts / End User Profiles low Name, email, and phone fields map directly between Podium Contacts and Helpshift End User Profiles via User Hub, making this a straightforward extraction and load.
Conversations / Issues high Podium's open-ended, location-bound conversations must be transformed into Helpshift's lifecycle-driven Issues with thread-splitting decisions, making this the most complex entity to migrate accurately.
Messages high Podium's message API rate limit of 10 requests per minute creates a severe extraction bottleneck, and preserving direction, timestamps, and threading within Helpshift Issues requires careful transformation logic.
Attachments high Attachments must be individually downloaded from Podium and re-uploaded to Helpshift via separate API calls, with no guaranteed URL compatibility or bulk transfer mechanism.
Tags low Tags map directly between both platforms and can be used in Helpshift to filter Issues into Smart Views, requiring only a straightforward value transfer.
Locations / Apps medium Podium Locations can map to Helpshift Apps or Tags, but the mapping strategy requires upfront architectural decisions that affect routing, reporting, and agent assignment across the target platform.
Custom Fields / Attributes medium Podium Contact Attributes must be mapped to either Helpshift Custom Issue Fields or Custom Data depending on whether the data is per-contact or per-issue, requiring per-field analysis.
Internal Notes medium Helpshift has no native internal note entity, so Podium notes must be serialized into issue messages with markers or archived externally, risking loss of agent-facing context.
Reviews high Helpshift has no review management capability whatsoever, so all Podium review data must be exported and archived externally or it will be permanently lost.
Payments and Campaigns high Helpshift has no payment processing or marketing automation features, so these Podium entities have no migration target and must be archived in an external data warehouse before cutover.

The hard parts

What makes this specific migration difficult, beyond the mechanics.

Incompatible Data Models

Podium's location-based, open-ended conversation model must be transformed into Helpshift's app-based, lifecycle-driven issue model (New → In Progress → Resolved → Rejected), requiring significant schema mapping and thread-splitting logic.

Severe API Rate Limits

Podium's message-related API endpoints are capped at 10 requests per minute, meaning a dataset with 100K messages can take approximately 167 hours of API extraction time without parallelization.

No Equivalent for Key Entities

Podium Reviews, Payments, and Campaigns have no Helpshift counterpart whatsoever and must be exported and archived externally before migration, creating data loss risk if not planned for.

Attachment and Media Handling

Message attachments from Podium conversations require separate download, re-upload, and association with the correct Helpshift Issue message, as there is no pass-through URL mapping between the platforms.

Internal Notes Lack Native Support

Podium internal notes have no native equivalent in Helpshift and must be serialized into issue messages with prefixed markers like '[Internal Note]' or archived externally, risking loss of agent context.

Helpshift Pagination Ceiling

Helpshift's GET /issues endpoint enforces a pagination ceiling of 50,000 issues per query window, requiring careful batching and validation strategies for larger datasets during post-migration verification.

Tools used in this playbook

All free, all run entirely in your browser — nothing is uploaded.

FAQ

Can I migrate Podium data to Helpshift using CSV?

Only partially. Podium's native CSV export covers contacts but not full conversation threading or message bodies. Helpshift has no self-service CSV import for Issues — you must use the REST API or send files to Helpshift support. For any migration requiring conversation history, a custom API-based ETL pipeline is required.

What Podium data cannot be migrated to Helpshift?

Reviews, payments, and marketing campaigns have no equivalent in Helpshift. These must be exported from Podium and archived externally (data warehouse, cloud storage) before migration. Helpshift is a support platform, not a reputation or payment management tool.

Does Helpshift have a bulk import API for issues?

No. Helpshift Issues must be created one at a time via the POST /issues API. There is no bulk issue import endpoint. The User Hub Bulk APIs allow importing up to 10,000 user profiles per request, and the Bulk Edit endpoint supports up to 5,000 issue IDs per request for post-load updates.

How long does a Podium to Helpshift migration take?

For a mid-size dataset (10K–50K conversations), expect 2–4 weeks elapsed time and 80–160 engineer-hours for a custom API-based migration. A managed migration service can compress this significantly. Small datasets under 1,000 records can be migrated in under a week.

How should I handle Podium's continuous SMS threads in Helpshift?

You have two options. A 1:1 mapping (one Podium Conversation = one Helpshift Issue) works for short conversations. For multi-year SMS threads with hundreds of messages, use time-based chunking — split conversations into separate Issues based on inactivity thresholds (e.g., a 7-day gap creates a new Issue) to produce cleaner, more actionable tickets.

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