How to build a call list that actually reaches people

Where call list data comes from

The quality of your call list is the single biggest predictor of how many people actually participate in your telephone town hall. Before you can validate, clean, or segment any data, you need to understand where it originated. Common data sources include:

• Voter file (electoral districts): Compiled from Elections Canada or provincial electoral agencies, these lists contain registered voters within a riding or electoral district. They are the gold standard for constituency engagement but require periodic refresh — voters move, phone numbers change, and cell phones have largely replaced landlines in younger demographics.
• Member list (unions, associations, credit unions): Membership databases maintained by your organization. Accuracy depends heavily on how recently members updated their contact information. Members who joined more than 3–4 years ago without updating are a primary source of dead numbers.
• Resident database (municipalities, healthcare regions): Pulled from utility billing records, property rolls, or health authority registrations. These are often large — covering hundreds of thousands of households — but can lag by 6–12 months as people move.
• Purchased or licensed data: Third-party data providers can supplement gaps in your own records, particularly for cell phone numbers. Data licensing agreements vary; Converso can advise on compliant sources for different sectors.
• Self-submitted opt-in lists: The cleanest data you can have. If your organization collects phone numbers at point of membership, event registration, or online form submission, that data tends to have the highest accuracy and the strongest legal basis for outreach.

Carrier-level number validation — Active Number Query (ANQ)

Active Number Query (ANQ) is the most important step in preparing a call list. ANQ pings carriers directly — not through a test call — to determine whether a given phone number is currently active and assigned before a single outbound dial is placed. This differs fundamentally from simply trying to call a number and recording whether it rings.

What ANQ identifies and removes from your list:

• Disconnected numbers: Numbers that are no longer assigned to any subscriber at any carrier
• VoIP-only lines: Numbers that route through internet-based services and are unlikely to be answered by a live person in real time
• Ported numbers not updated: Numbers that appear in one carrier's records but have since been ported to a different carrier under a different subscriber
• Duplicate entries: The same number appearing multiple times under different names or addresses in your source file
• Invalid format numbers: Numbers that don't conform to North American Numbering Plan standards — typos, truncated entries, or misformatted exports from legacy databases

ANQ validation typically removes between 8% and 22% of numbers from an average client-provided list, depending on the age and source of the data. For lists that haven't been refreshed in 3+ years, the removal rate can exceed 30%. Every invalid number you remove is a dial you don't waste — and a better participation rate on the dials you do place.

Data hygiene steps before you dial

Beyond ANQ, a well-prepared call list goes through several hygiene steps that improve dial efficiency and protect your organization's reputation:

• Deduplication: Remove identical numbers regardless of how the associated name record is formatted. A member who appears as "J. Smith," "John Smith," and "Smith, John" should receive one call, not three.
• Format normalization: Standardize all numbers to E.164 format (+1XXXXXXXXXX) to ensure your dialing system processes them correctly. Numbers exported from different CRMs, spreadsheets, or legacy databases often arrive in inconsistent formats.
• National Do Not Call Registry cross-reference: All outbound commercial calls in Canada must honour the CRTC's National Do Not Call List (DNCL). Political parties, registered charities, and survey calls have exemptions, but the specific rules depend on your organization type and the nature of the call — confirm this before your event.
• Internal suppression: Remove anyone who has opted out of calls from your organization, regardless of whether they appear on the DNCL. Maintaining your own suppression list protects relationships and reduces complaints.
• Age-based segmentation (where applicable): Some campaigns target specific age cohorts. If your data source includes date of birth or estimated age ranges, segment accordingly to improve message relevance.

Geographic filtering and targeting

Most telephone town halls target a specific geographic area — a federal or provincial riding, a municipality, a health region, or a utility service territory. Geographic filtering ensures you're not calling people outside your event's scope, which improves participation rates and prevents community confusion about why they received a call.

• Postal code filtering: The most common method. Forward Sortation Areas (FSAs — the first three characters of a Canadian postal code) map to specific neighbourhoods, municipalities, and rural delivery areas. Converso can filter your list to include only numbers associated with FSAs within your target area.
• Electoral district boundaries: For political calls, Converso can cross-reference your list against Elections Canada boundary files to confirm which numbers fall within a specific riding — even where postal codes straddle riding boundaries.
• Municipal or regional boundaries: For municipal government events, filtering by city limits, county boundaries, or regional district areas ensures you reach only residents within your jurisdiction.
• Radius-based filtering: For emergency response or community-specific events, Converso can filter by a radius from a specific point — useful for events targeting residents near a specific facility, affected area, or community centre.

Geographic accuracy matters most when your list is large and your event is locally specific. A provincial member association with 80,000 members province-wide running an event for a single region needs precise filtering — or they waste dials and confuse members who aren't relevant to that event.

Bilingual segmentation

For events in bilingual communities — particularly in Quebec, New Brunswick, Eastern Ontario, and Manitoba — bilingual segmentation routes callers to the appropriate language prompt automatically, without requiring them to press a button to select a language.

• Language flag in source data: If your member database or voter file includes a preferred language field, Converso uses that directly to route inbound callers to the correct language track.
• Census-based language inference: Where no language flag exists, Converso can use Statistics Canada's mother tongue data at the dissemination area level to estimate the probability that a given household is a French-first household. Numbers in predominantly Francophone areas are flagged for French-first routing.
• Surname-based inference: In some membership contexts, surname data can supplement geographic inference to identify likely Francophone households where the geographic data is ambiguous.
• Parallel French/English event streams: For fully bilingual events, Converso can run simultaneous French and English streams — the same host, translated in real time, with participants routed to their preferred language the moment they answer the call.

Suppression lists and do-not-call compliance

A suppression list is a file of phone numbers that should never receive outbound calls from your organization — regardless of whether they appear on your main call list. Maintaining a robust suppression list is both a legal requirement and a best practice for protecting your organization's reputation.

• CRTC National DNCL: Converso applies the national registry as part of standard data processing for commercial outreach. Political, charitable, and survey calls are governed by different rules — consult with Converso on your specific call type before assuming an exemption applies.
• Internal opt-outs: Any member, constituent, or contact who has previously asked not to be called must be added to your internal suppression list. This list should be maintained and updated after every event as new opt-outs come in.
• Deceased or inactive members: For membership organizations, maintaining a process to flag and suppress deceased members' numbers prevents distressing calls to bereaved families and reduces invalid dials.
• Event-specific suppression: For recurring campaigns, Converso can suppress numbers that have already responded to a recent outreach — for example, avoiding calling members who already voted in an ongoing ratification process.

After every telephone town hall, Converso provides a post-event file that includes any new opt-out requests captured during the event. Clients should import this file into their CRM or membership database immediately to keep their suppression list current.

Realistic participation benchmarks

One of the most common questions clients ask is: "How many people will actually join?" The honest answer depends on several variables — but here is what Converso has observed across hundreds of events:

• Average participation rate range: 2%–8% of the total numbers dialed will join and stay on the call for at least 5 minutes. High-salience events (emergencies, contract ratifications, contested budget decisions) regularly reach the upper end of this range.
• Large municipal benchmarks: Well-maintained resident lists for large municipalities — combined with a timely, locally relevant topic and a trusted institutional caller — regularly achieve answer rates in the 25–40% range. The Government of Alberta's budget consultation events, for example, have achieved a 27.2% answer rate across 3.5 million outbound dials province-wide.
• Member lists vs. general public: Calls to a defined membership — union members, credit union members, professional association members — typically achieve higher participation rates than calls to a general residential list, because the relationship between the caller and the recipient is stronger.
• Time of day: Evening events (6:00–8:30 PM local time) consistently outperform daytime events for residential audiences. For professional or physician audiences, lunch hours or early evenings work better.
• Day of week: Tuesday through Thursday evenings are the strongest. Monday evenings and Friday evenings underperform across most audience types.
• Pre-event promotion: Clients who send an email, SMS, or postcard to their list before the event — giving people a heads-up that the call is coming — see participation rates 20–40% higher than those who rely solely on the outbound call itself.

What Converso's data team does vs. what clients provide

Understanding the division of responsibility helps set realistic timelines and avoids last-minute scrambles. Here is how the work is divided:

• Client provides: The raw call list in CSV or Excel format, including at minimum: phone number and, where available, name, postal code, and preferred language. The client is responsible for ensuring they have legal authority to call the numbers on their list.
• Converso's data team handles: ANQ validation, deduplication, format normalization, suppression list cross-reference (DNCL + client-provided suppression file), geographic filtering to the specified target area, bilingual segmentation, and upload to the dialing platform in the correct format.
• Converso can source data: For clients who do not have an existing call list, Converso can work with licensed data providers to build a list based on geographic, demographic, or occupational criteria. Sourced data is subject to appropriate legal review and is typically used for public-sector consultations and advocacy campaigns rather than membership communications.
• Converso returns after the event: A cleaned post-event file noting which numbers answered, how long each caller stayed, their poll responses (anonymized), and any opt-out requests captured during the event.

The more complete and current the data a client provides, the better the results. Converso's data team can work with imperfect data — but every step of cleaning takes time. Providing a well-maintained list 7–10 business days before your event gives the team room to surface issues and resolve them without disrupting your event timeline.