Did Meridian AI Deliver on the Affinity Promise? An 8-Month Field Report

How relationship signals shift B2B win rates by double-digit percentages
The data suggests that warm introductions and relationship signals matter more than many sales teams give them credit for. Multiple industry reports show that deals sourced through referrals, mutual network introductions, or trusted partner recommendations close at materially higher rates than cold outreach. A conservative estimate from aggregated vendor and practitioner data points to conversion lifts in the 15-35% range for opportunities that start with an affinity signal versus those that do not.

The practical consequences are visible on the P&L. For a typical mid-market deal team averaging 100 sourced leads a month, a 20% lift in conversion translates into dozens more qualified opportunities and a meaningful reduction in cost per closed deal. Analysis reveals that the value of relationship-driven sourcing compounds over time: repeat interactions, faster cycles, and higher average contract value all point back to affinity as a multiplier rather than a mere input signal.

That is why claims from vendors about "winning deals through affinity" resonate. The phrase is not marketing fluff in the abstract. Evidence indicates that affinity is a measurable advantage when identified, operationalized, and matched to the right workflows. The tricky part is doing all three well.
4 core factors that determine whether affinity-based deal sourcing actually works
When you strip the tooling and hype away, affinity-based sourcing has a few essential components. Each one must be present and tuned for the approach to produce consistent outcomes.
1. Signal quality - the difference between a nudge and a smoking gun
Signal quality covers freshness, source credibility, and context. An old email list that shows connections is not the same as an active working relationship identified through recent collaboration or co-investment. The data suggests that signals tied to recent, verifiable interactions correlate much better with conversions than stale linkage graphs.
2. Signal-to-noise calibration - avoid drowning in false positives
Affinity engines can surface hundreds of potential matches. Without a filter tuned to your buyer profile, teams waste time chasing weak ties. Comparisons between teams that tuned filters and those that did not show conversion differences as high as 2x. The lesson: more matches are not better unless matched to your conversion priorities.
3. Workflow integration - turning signals into actions
Even a high-quality signal is useless if it doesn't route into a repeatable human process. The data indicates that firms that embed affinity alerts into existing CRM tasks, meeting cadences, and partner programs see faster time-to-meeting and higher follow-through. Analysis reveals a clear law: tool adoption without workflow changes yields low ROI.
4. Attribution and measurement - knowing what worked
Too many organizations adopt a tool then assume lifts will appear. Evidence indicates you need explicit attribution models - lead source tagging, experiment cohorts, and pre/post benchmarks - to separate luck from impact. Without measurable baselines, you cannot decide whether a vendor is helping or merely producing more noise.
Why Meridian AI delivered mixed results for our deal sourcing experiment
We bought into Meridian AI's pitch and the broad industry line about "winning deals through affinity." At the moment the product demo landed, it felt like a revelation - the promise of surfacing warm paths into target accounts appealed to both our head of sourcing and our busiest AEs. That moment changed everything about our evaluation plan. We set aside budget and expectations and gave the tool a real-world runway: eight months.

Here is what we learned, grounded in concrete examples and data from our rollout.
Expectation vs reality - the signal provenance problem
Meridian AI returned lists that looked great on paper: names, mutual contacts, recent interactions. But closer inspection showed many flagged ties were weak - a single shared event or a shallow co-attendance on a webinar. Evidence indicates these weak ties had conversion rates similar to cold outbound. The metaphor that helped our team understand this was radio tuning: Meridian could find stations, but often best LP portal automation solutions https://signalscv.com/2026/01/10-top-private-equity-crm-options-for-2026/ they were background static rather than clear signals.
Implementation missteps we made early on
We made mistakes. We plugged the output into our CRM with minimal mapping, assuming our reps would know how to act. They didn't. Without playbooks and routing rules, affinity matches sat unworked or were chased with generic outreach. The result: low engagement and frustrated reps. Analysis reveals this is a common operational failure - vendors deliver data, not playbooks.
What worked - hybridizing affinity with intent
When we paired affinity signals with intent signals - product research, hiring surges, job postings - conversion rates jumped. A concrete example: a target account flagged by Meridian for a strong executive tie also had job postings for a head of analytics and several intent indicators. The rep who took that lead booked an exploratory call within 48 hours and closed three months later. This contrasted with affinity-only leads, which were slower to convert.
Vendor claims vs measurable uplift
Meridian's marketing suggested material lift in pipeline velocity. Our measured uplift after eight months was modest: a 10-12% increase in meetings booked from sourced lists when workflows were applied, but only a 4-6% uplift in actual closed deals attributed to Meridian-only signals. Evidence indicates that the largest gains came from how we changed our process to use the signals, not from the raw signals themselves.
What deal teams learn when affinity tools don't immediately fix prospecting
What seasoned deal teams know about affinity signals that early adopters miss is not glamorous: it is discipline. The data suggests that a tool alone will not reform your pipeline. You need to translate signals into behaviors, then measure the result.

Here are the key lessons our team internalized during the eight-month test.
Affinity is a multiplier, not a replacement
Comparison shows that affinity signals improve the effectiveness of high-quality outreach but do little for low-effort outreach. The right analogy is fertilizer: it boosts yield when you have healthy soil; it does not replace planting. Treat affinity as a way to prioritize and enrich human-led engagement.
Close the loop on attribution early
We implemented a lightweight attribution schema mid-test and the difference was immediate. We started tagging leads with "affinity-source" and running weekly reports comparing conversion rates and time-to-close. Analysis indicates that even simple attribution unlocks strategic choices - which accounts to continue feeding into the tool, which workflows to optimize, and which signals to deprioritize.
Process beats feature lists
We saw tools with richer dashboards but no change in conversion because teams didn't change how they worked. Evidence indicates that a 30-minute rep playbook tied to each affinity alert produced more benefit than a feature upgrade. In plain terms: people and process create value from data, not the other way around.
5 measurable steps to evaluate and deploy affinity-based deal sourcing tools
If you're about to test Meridian AI or a similar vendor, follow these measurable steps. Each step includes a clear success metric so you can decide quickly if the tool deserves a longer runway.
Run a 90-day pilot with a control group
Designate two matched cohorts: one using the affinity tool plus your standard stack and one using standard sourcing alone. Success metric: meetings-per-100-leads for both cohorts. The data suggests differences in this metric are an early signal of viability.
Define signal thresholds before you turn the tool on
Set minimum freshness, interaction depth, and mutuality criteria. Success metric: percentage of surfaced leads meeting threshold. Aim for a threshold that yields a manageable number of prioritized leads rather than flooding reps.
Embed two specific playbooks into CRM tasks
Create exact scripts and sequences for affinity-warm introductions and for affinity-plus-intent outreach. Success metric: response rate within 7 days. Low response rates indicate signal or messaging problems, not necessarily product failure.
Measure end-to-end conversion, not vanity metrics
Track sourced lead to opportunity to closed deal. Success metric: sourced-lead-to-closed-deal conversion and average cycle time. The goal is to see whether affinity shortens cycles and improves win rates, not just increases lists.
Run an experiment to hybridize signals
Test affinity-only versus affinity+intent signals. Success metric: relative uplift in meetings and qualified opportunities. Our experience shows the hybrid approach outperforms affinity alone in nearly every case.
Operational checklist before you sign a one-year contract
Think of this as a pre-flight checklist. Skipping any item increases the risk you will spend budget and see little return.
Map how affinity alerts will flow into existing CRM records and ownership. Create two rep playbooks specifically for affinity-sourced outreach. Agree on attribution tags and dashboards before go-live. Define a cull policy - what to do with low-signal matches to avoid wasting rep time. Plan a 90-day review with concrete metrics and an option to pivot or cancel. Final assessment: Is Meridian AI worth the hype for deal sourcing?
Short answer: it depends. Evidence indicates that affinity engines can create real advantage, but they rarely act as a plug-and-play multiplier. Our eight-month test showed Meridian AI produced measurable gains when combined with process changes, precise thresholds, and hybrid signals. Those gains were modest relative to marketing claims but meaningful when you value every converted account.

If your organization has weak sourcing discipline, no attribution, and reps who resist structured playbooks, you will likely be disappointed. If you treat affinity as an input to a thoughtful sourcing machine - with controls, playbooks, and measurement - the tool can move the needle on pipeline quality.

Thinking back, the most honest lesson is this: the vendors sell signals, not outcomes. You buy signals; you must build outcomes. Our team took eight months to learn that. The time felt long in the middle but valuable in the end because it forced us to stop assuming software alone would fix our most persistent problems.

Evidence indicates that with a short pilot, clear metrics, and a willingness to change how teams work, affinity-based sourcing tools are worth testing. Treat them like specialized equipment: useful when integrated into a practiced workflow, less useful when expected to do the heavy lifting on their own.