Deduplication and suppression
Decide which records you want to receive, how often you want to receive them and which contacts or accounts should be excluded. LeadScale combines deduplication, frequency and volume controls with checks against your own data, all within the processing journey you define.
LeadScale’s Technical Services team works with you to design the rules and configure them in the LeadScale Engine. You can prevent duplicate records, limit the number of contacts accepted for a campaign or account, and check incoming data against CRM records, suppression lists and other datasets you control. The checks can run across all your sources, not just within a single supplier or destination.
Set the right frequency and volume limits
A repeat record is not always unwanted. You might accept only one email address per campaign, allow another response after a defined period, or accept several different people from the same company while preventing the same contact from being submitted repeatedly.
Frequency controls define how often a person, email address or account can qualify. Volume controls let you count and cap how many records are accepted for a campaign, account, audience, source or agreed timeframe. A rule could limit the number of contacts acquired from a target account in a month, for example, without excluding that account altogether.
Rules can use the identifiers and conditions relevant to your activity, such as email address, contact or company identifiers, campaign, source and time window. Where records arrive from several suppliers, the Engine can apply the same limits across them rather than relying on each supplier to count separately.
You choose what constitutes a duplicate, which repeat interactions are useful, what should be counted, when a cap is reached and what happens next. Technical Services helps turn those choices into a clear, auditable configuration.
Check against the data you already control
A record can be new to a campaign and still be one you do not want. It might match an existing customer, a contact already being worked by your sales team or a company that should be excluded from a particular activity.
Suppression checks compare incoming data with the datasets you nominate. These can include existing CRM records, customer or prospect lists, account exclusions, suppression files or other data under your control. The matching fields, treatment of matches and any permitted exceptions are agreed with you.
The Engine can onboard client-provided datasets through configured integrations, APIs or file routes. Your systems can supply the reference data needed for processing, rather than requiring each media partner or supplier to hold its own copy.
Prepare client datasets for reliable matching
Your reference data may sit across multiple CRMs, business units or files, particularly after a merger or acquisition. Before it can be used reliably, records may need to be mapped, standardised, combined or deduplicated.
Technical Services works with you to identify the authoritative sources, prepare the relevant fields and configure the matching logic. You decide which datasets are in scope and how they should be used. Changes to those datasets can be incorporated through an agreed update process.
Apply controls across sources and throughout the journey
Two suppliers can each submit a contact only once and still send you the same person. A campaign-level cap can also be exceeded if every source counts only its own submissions. Centralised processing lets the Engine apply the agreed rules across all connected sources.
Deduplication, frequency caps, volume limits and client-data suppression can be placed wherever they are needed in a composed journey. A check might sit between capture and CRM delivery, or be repeated after another system returns information that changes the decision.
The order can save unnecessary work and cost. For example, a record excluded by a client suppression list need not go through a paid verification or enrichment lookup. The Engine records the processing steps and outcomes so decisions can be traced.
Every check and its result can be included in the record’s audit history. For ambiguous matches, an authorised user can review the data through a controlled, audited human-in-the-loop process before a final decision is made.
Design the controls with Technical Services
- Define the outcome. Agree what counts as a duplicate, which records or accounts to exclude, the counting periods and the limits that apply.
- Onboard the reference data. Identify the CRM data, suppression lists and other client-controlled datasets needed for matching; map and prepare them for use.
- Configure and operate the flow. Technical Services sets up the rules, processing order, actions for matches or exceeded caps, and the required audit and reporting.
Only the records you want move forward
Records are checked against the frequency, volume and suppression rules you specify before they reach an agreed destination. Depending on your instructions, a record can be accepted, held for review, rejected or routed to another stage. The same controls can form part of wider ecosystem orchestration.
Governance and an auditable record of decisions
Client datasets and their use in processing are governed by the agreed access, handling and retention requirements. Audit trails capture the checks and decisions applied to records, helping you investigate outcomes and support compliance processes. Consent and provenance information can also be carried and used where relevant to the configured journey.
Frequently asked questions
Can we cap records by account, campaign or time period?
Yes. You can define limits by contact, email address, account, campaign, source or another agreed identifier, with counting windows and actions configured around your requirements.
Can you use our own CRM data and suppression lists?
Yes. We can onboard data from your systems or supplied files, prepare it for matching and apply the exclusion rules you specify. The same approach can use other client-controlled reference datasets.
What if a record is valid but matches a suppression rule?
A record can pass validation and verification yet still be excluded because it matches your data or exceeds a frequency or volume limit. What happens to that record follows your agreed rules.
Connections, processing rules, checks and consent records
- Technical data servicesHow the technical team connects your systems to the Engine.
- Engine configurationHow requirements become processing rules.
- Lead validationThe checks available and how their order is set.
- Consent and provenanceSource history, capture evidence and supplied consent information.
You define the outcome. We compose the journey.
What should your data flow accept, limit or exclude?
Tell us which records you want, which frequency or volume limits matter and what CRM data or suppression lists you need to check. Our Technical Services team will help design the controls and build them into your journey.
Or request a free audit of leads from a recent programme.