The broken funnel just got even more compounded, and you can’t ignore it.
Attribution, lead quality, handoffs and conversions are top concerns across revenue leaders today. The common denominator that feeds all challenges? Ranked #1, CRM or data quality issues.
Now we have AI raising the stakes on all of it and compounding issues across the funnel. Pointing an agent at a funnel that’s already cracking doesn’t fix the breaks. It scales them faster than a human can fix.
The end goal: trusted data that’s readable and actionable by both humans and AI.
Convertiv
Convertiv
Traction Complete
Bring together every team and review what’s broken.
The funnel breaks in the seams that connect one team’s work to the next: leads disconnected from contacts, duplicates landing as routing fires, and handoffs that lose context.
“Everyone has owned a piece of the journey, but no one owned the journey holistically.”
“For me, the tell isn’t in a report per se. It’s the 15 minutes of a pipeline review. If you spend the first 15 or more minutes trying to reconcile instead of making decisions.”
One record for reps, all context for clear and trusted action
“We did not eliminate the lead object, but we eliminated reps from having to think about it.”
Keep the lead object or go contact-only? Every business answers this differently, and both standard options fail somebody: contact-only strips marketing of the place it nurtures and builds data points, and a visible lead record makes reps manage an object that was never theirs to manage.
The handoff between the two is the auto-convert step. When a lead clears the qualification threshold, the flow converts it on the rep’s behalf and assigns the person as the primary contact on the opportunity. Sales reps see one clean transaction instead of a lead-to-contact relay, and every engagement lands on one record, ensuring the reporting behind handoff holds up.
Fix the records everything else inherits
Data integrity is the pillar everything else stands on. Routing, scoring, and attribution all inherit whatever record quality you start with.
“That is getting down to a single record of a person, a single record of an account, ensuring there are hierarchies.”
Connect Leads
Match, merge, and convert records before you route. Built in Complete Leads, this flow fires whenever a lead enters Salesforce, and only a clean, converted record ever reaches a rep.
Here’s an example where you can also use AI to standardize, validate, or normalize as a part of the flow to help create better reporting and outcomes.
“Standardize the {Current:Lead.Title} to a properly formatted job title. Correct abbreviations or typos and apply standard casing.”
Connect Account Data
Connecting accounts reveals the duplicates that exist within your CRM: like three records that share the same name but have three different owners. Until those records are merged, routing fires on the wrong one and reps work the same account without knowing it.
An AI enrichment step stamps a domain and parent domain on the account; this flow then works through several matching steps and flags what it finds for a person to approve.
Each match step falls through to the next on no match; a final no-match result writes its own flag. The source flow also adds a contact-domain match before giving up. Approval gates every hierarchy change.
“Enrich this account for hierarchy matching. Return two values only: Complete_AI_Data__c.Domain__c = <base domain or blank> · Complete_AI_Data__c.Parent_Domain__c = <base domain or blank>. Return domains only (no http/https, no paths, no subdomains). If multiple corporate domains exist, choose the most commonly used corporate domain (e.g., pg.com over procterandgamble.com). Leave blank if unknown. Do not return explanations or extra text.”
Deduplicate Accounts
Account hierarchy data is not the same thing as Account Hierarchies in your CRM. AI can augment account hierarchies from CRM patterns and email domains, then route them to an admin to approve before they commit. Having this visibility of the actual family tree helps you identify duplicates, merge duplicate accounts, and avoid territory disputes and route errors that break your speed-to-lead. If sales can see it on the account record, even better.
Give reps the context behind the score
Prioritization decides what a rep sees at handoff, and when a record reaches a rep at all. A score and a grade on their own don’t tell them anything. But behind that number is a history of webinars attended, whitepapers downloaded, and the difference between a first call that starts warm and one that starts from zero.
“I’ve got Tom Palmieri, his score is 80, and his grade is a B. What does that mean? What are those touch points in between that made him elevate to this transaction where he raised his hand?”
Surface the touchpoints behind the score so each handoff carries meaning. On top of that, leverage AI to add recent M&A activity or other information about the lead at the account level, arming your sales team with valuable intel.
That added context comes from enrichment. This flow runs a Data Agents step using just an account name and domain, and writes firmographics back to your designated fields.
“Return the annual revenue for this company or brand without any explanation. Revenue should be in USD. If you do not know, return a response of Unknown.”
“Return the number of employees for this company or brand. This should be a numeric value without decimal points. If you do not know, return a response of Unknown.”
“Return the Country where this company or brand is Headquartered without any explanation. Ensure that the format is in the ISO 3166-1 alpha-2 code format. If you do not know, return a response of Unknown.”
“Which industry from the below list does this business or brand most closely belong to? choose only one value with no additional explanation. If you do not know, return a response of Unknown.”
Route accurately, and make SLAs stick
Firing assignments is just half of routing. Every lead routed inherits the matching upstream, and every SLA is only as fair as the clock behind it.
“Ensuring that routing is accurate, ensuring that SLAs are adhered to… not just react to that data, but actually proactively look at the data and say, okay, maybe our SLAs are a little too tight. Maybe it needs to go from 8 hours to 10 hours, or 12 hours.”
Most traditional routing engines track speed-to-lead with formula fields that ignore a rep’s geography and or fire alerts after hours. The smarter rebuild routes on real business hours by time zone, escalates on breach, and rolls performance up for reporting.
Attribution that survives the whole journey
When a person re-qualifies through multiple cycles, each new cycle can break the link back to the original context, and attribution dies by the time the deal closes. Every campaign report inherits those broken links.
“We’re measuring those discrete transactions… and we’re adding people as contact roles to ensure that everything that they’ve done carries over. So all of that entire engagement history, that system context, goes all the way through to when it’s a closed one opportunity.”
layer
When data and processes work again
The clearest signal the rebuild worked showed up in how people behaved in the room.
“There’s no more reconciliation on the first 15 minutes of a pipeline call because everybody trusts the data.”
The questions change from “can we trust this number?” to “what do we do with it?” Shadow spreadsheets start to disappear, cross-functional meetings get shorter, and leadership spends less time validating the past.
Data Agents are the how. Trusted data is the why.
The order of operations never changed across the whole rebuild: connect the funnel, agree on the data that matters, keep a human in the loop, and let AI work on a foundation it can trust. Data Agents run that sequence continuously inside Salesforce, so users can constantly maintain the data layer and improve what gets written.
“It’s been a great way to partner up and bring in Traction Complete to effectively mass clean and mass dedupe, but also proactively clean and dedupe and assign and route.”
Hierarchy Mapping
Builds corporate structure from ownership and operating relationships, including subsidiaries your provider doesn’t track.
Match Intelligence
Finds account records that represent the same company, including matches your existing rules and providers would miss.
Enrichment
Fills missing fields from your calls, contracts, the web, and our proprietary database, tailored to how you sell.
Normalization
Standardizes names, titles, and fields across every record so matching, reporting, and segmentation work as needed.
Validation
Catches bad records and verifies accuracy before anything is written. No provider is 100% correct.
Classification
Applies your industry, vertical, segment, and territory definitions to every account so data reflects how you sell.
Detection
Monitors news and filings for M&A and restructures so your records reflect the market as it happens.
Account Scoring
Scores accounts for ICP fit, prioritization, and survivorship so reps know which records to focus on.
“Is my data better?”
Every play in this guide points back to one test you can run on any record, any workflow, any AI output. That’s the whole job: help revenue teams rebuild trust in the data layer, so the AI you point at it compounds value instead of the mess.
Watch the full Co/Lab recording
The complete conversation with Shamus, Tim, Tom, and Bec, including the audience Q&A this guide couldn’t fit.
Schedule an AI GTM strategy session with Convertiv
A 45-minute working session to review your current AI GTM capabilities, discuss roadblocks and share highest-impact opportunities and recommended next steps.
See Data Agents live with Traction Complete
Join a live demo of Data Agents: deduplicating, standardizing, validating, classifying, normalizing, and enriching your data.