How to Build a Prospecting Workflow That Doesn't Depend on One Data Source

Most sales teams pick one enrichment tool, plug it into their stack, and treat whatever it returns as ground truth. If the tool says an email is valid, they send to it. If it can't find a phone number, they move on. The entire prospecting operation runs on a single provider's data.

That works until it doesn't. And when it stops working, you usually don't notice right away. Your bounce rate creeps up. Your connect rates drop. Your pipeline looks full but conversions are flat. By the time someone traces the problem back to data quality, you've already burned through a chunk of your list.

The single-source problem

Relying on one enrichment provider means you inherit all of that provider's blind spots.

Every data provider has coverage gaps. Some are geographic (weaker outside the US). Some are industry-specific (great on tech companies, thin on manufacturing or healthcare). Some are temporal (data was fresh six months ago but hasn't been re-verified since). When you depend on a single source, those gaps become your gaps. You just can't see them because you have nothing to compare against.

The other problem is less obvious: vendor risk. Enrichment providers change their data sources, adjust their pricing, modify their APIs, or get acquired. If your entire workflow is built around one tool and that tool changes something fundamental, you're stuck scrambling. It's not uncommon for teams to lose access to a provider overnight because of a pricing change and have no backup plan for their next campaign.

What a multi-source workflow actually looks like

The concept is simple. Instead of running every prospect through one tool and accepting whatever comes back, you build a process that checks multiple sources and compares results.

Platforms like Clay have built this multi-source approach into their core product. If you're already on Clay, you're probably doing most of this automatically. But if you're not on a workflow platform like that (and a lot of SMB sales teams aren't, given Clay's price point and steep learning curve), here are a few ways to set this up with the tools you already have.

The manual approach works for small teams. You run your prospect list through your primary tool, export the results, then run the contacts that came back empty or low-confidence through a second tool. You compare the outputs in a spreadsheet. This takes time but costs nothing beyond the tool subscriptions you already have.

The waterfall approach automates this. Waterfall enrichment tools query multiple data providers in sequence. If provider A doesn't find an email, the tool automatically tries provider B, then C, then D. You get back the best result from across all sources without manually running multiple lookups. This is what tools like ShareCo SalesSync do across 20+ providers. The tradeoff is that waterfall tools cost more per lookup than single-source tools, but the coverage is significantly better.

The hybrid approach combines both. You use a waterfall tool as your primary source for initial enrichment, then spot-check results with a second independent tool on high-value prospects. This gives you broad coverage from the waterfall plus a verification layer for the contacts that matter most.

Setting up the verification layer

After your enrichment tool returns results, you need to verify the data before it goes into a campaign. The easiest way to do this is to run your list through a bulk email verification service like NeverBounce, ZeroBounce, or BriteVerify. These tools check deliverability, flag role-based addresses (info@, sales@, support@), identify catch-all domains, and give you a confidence score for each email. Most charge fractions of a cent per verification. It takes minutes and catches the majority of bad data before it reaches your sending tool.

For the checks that verification services don't cover, you still need a manual or semi-automated layer. Check email domains against company domains. If your enrichment tool says someone works at Acme Corp but returns an email ending in @gmail.com or @previouscompany.com, that's stale data. You can catch this with a spreadsheet formula or by throwing the list into Claude or ChatGPT and asking it to flag domain mismatches.

Check phone number geography. If you're prospecting in Canada and the enrichment tool returns a US phone number for a Canadian-based contact, that's likely wrong. Geographic mismatches on phone numbers were one of the most common errors I found during the 25-profile comparison test. Apollo returned wrong-country numbers on three profiles in that sample.

After verification, run a small test send before committing your full list. Take 50-100 contacts and send a campaign. Track the bounce rate. If it's above 3%, your data still has problems. If it's under 2%, you're in good shape to scale.

Building the workflow step by step

Here's how to put this together as an actual repeatable process.

Step 1: Source your prospect list. Pull profiles from LinkedIn, Sales Navigator, or whatever source you use. At this stage you have names, titles, companies, and LinkedIn URLs. No contact data yet.

Step 2: Run initial enrichment. Push the list through your primary enrichment tool. For contacts that come back with email and phone data, move them to the verification step. For contacts that come back empty, either run them through a second source or flag them for manual research.

Step 3: Verify the enriched data. Run the domain-match check, role-based email filter, and phone geography check described above. Remove or flag anything that doesn't pass.

Step 4: Segment by confidence. Split your verified list into tiers. Tier 1: email and phone both verified, domain matches, everything looks clean. Tier 2: email verified but no phone, or phone but no email. Tier 3: data exists but has a flag (domain mismatch, catch-all domain, low confidence score). Each tier gets a different outreach approach. You can do this once, record the methodology and have your preferred AI tool do it every time thereafter.

Step 5: Test send on a sample. Pull 50-100 contacts from Tier 1 and send your first campaign. Measure bounce rate, open rate, and reply rate. These numbers become your baseline.

Step 6: Iterate based on results. If Tier 1 bounces at 1% and Tier 2 bounces at 4%, you know Tier 2 needs additional verification before sending. If Tier 3 bounces at 8%, you might decide to re-enrich those contacts through a different provider or drop them entirely.

What to track over time

Once your workflow is running, the metrics that matter are all comparative.

Bounce rate by data source. If you use multiple enrichment tools, track which one produces lower bounce rates. This is the most direct measure of data quality and it changes over time as providers add or lose data sources.

Coverage rate by segment. What percentage of your prospect list gets fully enriched (email + phone) on the first pass? If this drops below 60-70%, either your ICP is shifting into harder-to-reach segments or your enrichment provider's coverage is declining.

Time from enrichment to send. The longer enriched data sits before you use it, the more it decays. Someone who was VP of Sales when you enriched them three months ago might be VP of Sales somewhere else now. Aim to use enriched data within 2-4 weeks of the lookup.

Cost per verified contact. Not cost per lookup, but cost per contact that actually passes verification and is usable in a campaign. If your tool charges $0.10 per lookup but 30% of results are unusable, your real cost per verified contact is $0.14. This number helps you compare providers on an apples-to-apples basis.

When to add a second source

Not every team needs multiple enrichment tools from day one. If you're sending to a small list (under 500 contacts per month) and your bounce rate is under 3%, a single good provider is fine. Adding complexity before you need it wastes time.

The signals that you need a second source are concrete. Your bounce rate is climbing above 3% consistently. Your enrichment coverage is dropping (fewer contacts coming back with data). You're expanding into new markets or industries where your current tool has weaker coverage. Or you're scaling your outbound volume to the point where a 5% accuracy gap starts costing real money in wasted sends and damaged sender reputation.

When those signals appear, adding a second source is straightforward. Pick a provider that's strong where your primary tool is weak. If your main tool is US-focused, add a provider with better international data. If your main tool is strong on email but weak on phone, add one that specializes in direct dials. The goal isn't to have the most tools. It's to identify and close the gaps that are actually costing you deals.

The realistic expectation

No workflow eliminates bad data entirely. Even with multiple sources, verification layers, and careful segmentation, some contacts will bounce. Some phone numbers will be wrong. Some emails will land in spam folders.

The goal is to reduce the failure rate to a level where it doesn't materially impact your campaigns. For most outbound teams, that means keeping bounce rates under 2-3%, maintaining connection rates on phone that justify the time spent dialing, and having confidence that the emails you're sending are reaching real people at real companies.

Building a multi-source workflow takes a few hours to set up and saves you from discovering data quality problems after your campaign is already running.