AI Outbound Calling for B2B Logistics — ×7 Case Study | PrimexAI 2026
AI B2B logistics · 2 case studies, one company

AI voice agents for B2B logistics

A regional freight brokerage with a 240+ truck network hit ×7 database reach. The AI systematically works the cold list and reactivates dormant accounts. Your reps get only warm, qualified leads — with no extra headcount and no bigger budget.

10,000+
contacts a month per AI agent — cold list and reactivation
24/7
dialing with no weekends, no lunch breaks and no dependence on how busy the team is
a fraction
of the fully-loaded cost of an SDR ($75–90K/yr) — at the same first-touch effectiveness
Where B2B logistics leaks revenue

4 leak points in cold and dormant lists

A freight brokerage builds up a list of accounts, but the reps are heads-down on live deals. The old list and cold contacts never become a real sales channel — the money just sits there.

Scenario 01

Reps are buried in live deals

Reality
  • the team handles inbound requests and closes current loads
  • no time or focus left for the old list
  • follow-up touches happen sporadically
  • parts of the list go months without a single touch
You have a list of accounts, but it isn't a sales channel — the money is parked in the archive.
The AI sales agent works the whole list systematically, with no gaps or pauses. It confirms what's still relevant and recalls the context of the last conversation.
Scenario 02

The cold list is huge — you can't work it by hand

Reality
Target companies on the list:
  • manufacturers and plants
  • distributors and wholesalers
  • retail chains and suppliers
  • companies with regular domestic shipments
Reps can physically reach only a sliver of the list. The bulk of contacts never even get a first touch.
The AI sales agent works 10,000+ contacts a month — many times what a person can. No extra headcount, no overtime.
Scenario 03

Weak discipline on follow-up calls

Reality
  • no answer — set aside
  • logged in the CRM as "no answer"
  • never called back because the hot deals come first
  • the contact is lost for good
The AI sales agent makes 2–3 call attempts at different times of day. Some contacts only pick up on the 2nd or 3rd try.
Scenario 04

Reps burn time on the wrong accounts

Reality
  • 50% of calls land on the wrong companies
  • 30% are a no on budget or lane
  • one qualified lead takes 5–10 dead-end conversations to find
Your most expensive resource — rep time — goes to filtering out the wrong accounts instead of closing.
The AI sales agent runs first-pass qualification: regular freight, lanes, volumes. Only warm leads reach your reps.
How it works

The AI works inside your CRM, like a member of the team

It follows your playbooks and scripts, logs tasks in the CRM and transcribes every call. No migrations, no retraining the team, no platform switch.

🧩

Inside your CRM

We plug into your CRM — HubSpot, Salesforce, Pipedrive and others. We work with your stages, fields, templates and segments — no migrations, no platform switch.

📋

On your script

We sign off the first-touch script with your sales lead and senior rep. The AI sales agent doesn't quote rates — it surfaces the need and escalates.

🎙️

Transcript and qualification

Every call is transcribed, with lanes, volumes, frequency and the decision-maker pulled out. A task lands in the CRM for the right rep.

2 case studies, one industry

A freight brokerage: 2 scenarios
Dormant-list reactivation and
cold-calling 52,000 contacts

Real projects inside one B2B logistics company. Reactivation drove +609% interest and +278% deals. Cold calling delivered ×7 database reach and +243% deals — with no extra headcount.

Case 1 · Dormant-list reactivation

How 10,800 dormant contacts turned into a source of deals

Client
A regional B2B freight brokerage, domestic shipping
Goal
Turn 10,800 dormant accounts into a working source of deals
Solution
The AI sales agent works the list systematically: confirms relevance, recalls context, surfaces interest
Before · Reps, by hand
Contacts worked780
Productive conversations211 (27%)
Confirmed interest96 (12.3%)
Qualified leads55 (7.1%)
Deals9
After · AI sales agent
Contacts worked / mo4,600
Contacts worked, total+490%
Productive conversations1,426 (31%)
Confirmed interest681 (14.8%)
Qualified leads409 (8.9%)
Deals34
Result: 34 deals from a previously dead list (up from 9 to 34, +278%). The archive became a steady channel of inbound requests.
+609%

Multiplied reach

The AI sales agent worked 4,600 contacts instead of 780 — 5.9× more. The list stopped sitting in the archive.

Consistency, not sprints

Calling became a steady, repeatable process that doesn't hinge on how busy the reps are with live deals.

Context from the last call

The AI would remind them: "You requested a quote on the Chicago–Dallas lane back in February — is that route still relevant?" — and trust jumped sharply.

Repeat call attempts

2–3 attempts at different times of day. Some contacts only answered on the 2nd or 3rd try — a rep simply doesn't have that bandwidth.

Case 2 · Cold-calling 52,000 contacts

How to scale cold outbound ×7 without growing the team

Client
The same B2B freight brokerage, target list of 52,000
Goal
Systematically work the cold list — manufacturing, distribution, wholesale, retail chains
Solution
The AI sales agent runs the first-touch script: finds regular freight and the decision-maker, filters out the wrong accounts
Before · Reps, by hand
Contacts worked / mo1,600 / 52,000
List coverage3% / mo
Productive conversations272 (17%)
Need identified83 (5.2%)
Qualified leads50 (3.1%)
Deals7
After · AI sales agent
Contacts worked / mo11,400 / 52,000
List coverage22% / mo
Productive conversations2,109 (18.5%)
Need identified524 (4.6%)
Qualified leads331 (2.9%)
Deals24
Result: 24 deals a month from the cold list (+243%). With no growth in the sales team.
×7

Scale of reach

11,400 contacts a month instead of 1,600. The full 52,000 list gets worked in 4–5 months — by hand it would have taken 3 years.

One first-touch script

The AI sales agent runs every call on the same approved logic: decision-maker, lanes, volumes, frequency, current carrier.

Filtering out the wrong accounts

Reps get an already-qualified list — 24% of the base turns into a productive conversation.

Not better conversion — more reach

Conversion into productive conversations is comparable (17% → 18.5%). The lift comes from volume, not a jump in quality.

Benefits

Remove the ceiling of your sales headcount

100% of contacts worked

Cold and dormant lists stop sitting in the archive. Every contact gets a first touch within a month, not a year.

No extra sales headcount

Reps only step in on warm, qualified leads. Your expensive people spend their time closing, not filtering.

Steady calling discipline

The pace doesn't depend on how busy the team is with live deals. The monthly reach target gets hit, every month.

💰 ×7 database reach with the same sales team — it pays for itself in the first month on any B2B logistics operation.
Deployment process

Simple onboarding in 4 steps

From the first call to fully automated pipelines — with no CRM migration and no platform switch for the team.

Step 01

Define the goal

With your sales lead and senior rep we shape the script: the goal of the campaign, qualification criteria, escalation points, CRM fields.

Step 02

Connect the CRM and list

Integration with HubSpot, Salesforce, Pipedrive and others. List segmentation: dormant / cold / by lane / by volume.

Step 03

Run the pilot

We test on 500–1,000 contacts. We listen to the calls, tune the script, measure conversion — and build out the economics.

Step 04

Scale up

We turn on the main flows (5,000+ contacts a month), set up repeat attempts and quality control.

FAQ

What sales leads usually ask

In B2B logistics, the people on the client side (logistics and procurement managers) are usually focused on the substance — lanes, volumes, rates. The AI sales agent holds the conversation at the level of an experienced rep and escalates to a human the moment the client is ready for a commercial discussion.

Yes — that's one of the core scenarios. The AI sales agent gets past the gatekeeper to the decision-maker (logistics manager, head of procurement, VP of supply chain), captures their title, name, contact and interest. A task lands in the CRM for a rep, with the context ready to go.

HubSpot, Salesforce, Pipedrive and other CRMs, plus custom systems via REST API. If you run your own platform, we build a connector in about a week.

2–4 weeks for a basic scenario: sign off the script, integrate, run a pilot on 500 contacts, tune. A full launch at a scale of 10,000+ contacts a month takes 4–6 weeks.

On the diagnostics call we run the economics on your numbers: average contract value, margin, lead-to-deal conversion, list size. In our experience, payback runs 2–3 months for operations with a list of 5,000+ contacts.

We'll help build a targeted list: pulling from business databases and industry directories on your criteria (NAICS code, regions, revenue band, warehousing). We do this as a separate step before the calling campaign starts.

We'll show how an AI sales agent fits your B2B logistics operation

45 minutes on Zoom. We run the payback and the upside on your numbers, and hand you a step-by-step plan to grow profit with AI.

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