{"site":{"name":"Koji","description":"AI-native customer research platform that helps teams conduct, analyze, and synthesize customer interviews at scale.","url":"https://www.koji.so","contentTypes":["blog","documentation"],"lastUpdated":"2026-06-17T18:14:15.726Z"},"content":[{"type":"documentation","id":"3403ae02-44ae-4e0f-b4d8-053c1d8d6037","slug":"ai-research-for-logistics","title":"AI Customer Research for Logistics and Supply Chain: Shipper, Carrier, and End-Customer Insight at Scale","url":"https://www.koji.so/docs/ai-research-for-logistics","summary":"Logistics providers, freight forwarders, 3PLs, and last-mile companies can run customer research at scale with AI interviews instead of account-manager anecdotes or slow surveys. High-value studies include shipper win-loss, account retention, carrier and driver experience, last-mile recipient feedback, new-service and pricing validation, and platform onboarding. Koji runs voice or text interviews in the participant's language, probes each answer, and analyzes hundreds of conversations into a themed report. Text interviews cost 1 credit, voice 3, free tier 10 credits.","content":"Logistics providers, freight forwarders, 3PLs, and last-mile delivery companies can run customer research at scale with AI interviews - capturing why a shipper moved volume to a competitor, how carriers and drivers experience your platform, or why a delivery recipient rated an order poorly, without staffing an account-management call campaign or waiting on a slow survey vendor. A platform like Koji conducts voice or text conversations with shippers, carriers, and end customers, probes each answer with adaptive follow-up questions, and turns hundreds of conversations into an analyzed report in days. In a margin-thin industry where one lost enterprise shipper can mean millions in annual revenue, that intelligence pays for itself the first time it saves an account.\n\n## Why logistics has a customer-understanding gap\n\nLogistics companies are operationally data-rich and insight-poor. You know every shipment status, transit time, and exception code - but the systems never tell you *why* a shipper is quietly redirecting freight, why a carrier stopped accepting loads on your platform, or what would make a recipient choose your delivery option again. Operational data describes what happened; it cannot explain intent, satisfaction, or the reason behind a decision.\n\nThe traditional fixes do not scale. Account managers gather feedback anecdotally and inconsistently, and only from the relationships they already have. Annual relationship surveys get buried in the inbox of a busy logistics manager and return thin, low-context scores. And nobody is systematically interviewing the two groups that matter just as much as the buyer: the carriers and drivers who supply capacity, and the end recipients who experience the final delivery.\n\n## High-value logistics research use cases\n\nAI interviews replace those slow, partial methods. The highest-ROI studies for logistics and supply-chain teams include:\n\n- **Shipper win-loss research.** Interview shippers you recently won or lost. Probe the decision criteria - rate, transit reliability, visibility, claims handling - and the alternatives they compared you against. Koji's adaptive follow-ups turn \"your pricing\" into \"your spot rates were fine but your tracking visibility was two days behind FreightCo.\"\n- **Account retention and churn-risk interviews.** Reach key shippers before renewal to surface dissatisfaction while there is still time to fix it.\n- **Carrier and driver experience.** Carriers are customers too. Interview them about load board usability, payment speed, detention, and app friction to protect your capacity supply.\n- **Last-mile and recipient experience.** Send a short voice or text interview to delivery recipients to understand the experience behind a low rating - missed windows, damage, communication gaps.\n- **New-service and pricing validation.** Test a new service tier, surcharge, or technology feature with scale and ranking questions before you roll it out.\n- **Onboarding and platform usability.** Find out where shippers or carriers stall when adopting your TMS, portal, or booking app.\n\n## Why AI interviews beat surveys and account-manager anecdotes\n\nLogistics customers - shippers, carriers, drivers, recipients - are busy, distributed, and hard to schedule. That is exactly where AI-moderated interviews win:\n\n- **Reach people you cannot get on a call.** Share an interview link with drivers between loads or recipients right after delivery. Voice interviews are ideal because a driver can complete one hands-free in a few minutes, capturing real-world friction that never reaches your account team.\n- **Scale without headcount.** Koji conducts every interview in parallel, 24/7, in the participant's language, from a single link. There is no scheduling and no per-call cost, so you can hear from hundreds of customers in the time an account manager reaches a dozen.\n- **Depth a survey cannot reach.** A relationship survey gives you a score; Koji captures the number with a scale question and then probes the why with adaptive follow-ups, so a lost-account post-mortem becomes specific and fixable.\n- **Consistent and comparable.** Every participant gets the same well-designed interview, so a recurring complaint about, say, claims-resolution time surfaces as a clear theme in the report rather than as a one-off remark from a single rep.\n- **Automatic analysis.** Instead of manually reading hundreds of transcripts, you get a report with themes, representative quotes, sentiment, and quantitative breakdowns - segmented by shipper, carrier, or region.\n\n## Designing a logistics study with structured questions\n\nKoji supports six structured question types - open_ended, scale, single_choice, multiple_choice, ranking, and yes_no. A shipper win-loss study might combine a single_choice question for the primary decision factor, a ranking question to order rate, reliability, visibility, and support by importance, a scale question for likelihood to consolidate more volume with you, and open_ended questions with deep probing for the story behind the decision. Because each question carries a stable ID, the quantitative answers roll up into charts you can track over time while the qualitative themes are coded automatically across every interview.\n\n## What logistics research costs with Koji\n\nKoji uses a straightforward credit model: a text interview costs 1 credit and a voice interview costs 3. The free tier includes 10 credits so you can pilot a win-loss or carrier-experience study before committing, and paid plans start at EUR 29 per month. A quality gate ensures only conversations scoring 3 or higher consume credits, so incomplete sessions never cost you. Against the value of a single retained enterprise shipper, a full research program is negligible.\n\n## Getting started\n\n1. Pick one decision to inform - for example, which service gaps are costing you shipper renewals.\n2. Choose the audience: shippers, carriers, drivers, or recipients.\n3. Let Koji's AI consultant draft the brief and interview plan, or paste your own questions.\n4. Add structured questions for the decision factors and metrics you want to track.\n5. Share the link or embed it post-delivery, then route the analyzed findings to sales, operations, and product.\n\n## A logistics example: from a lost shipper to a fixed gap\n\nConsider a mid-size 3PL that just lost a six-figure shipper at renewal and is hearing vague secondhand reasons from the sales team. Instead of guessing, the account team sends a Koji voice interview link to the departing logistics manager and to ten similar at-risk accounts, asking each to walk through their decision and rate the factors that mattered.\n\nThe report is specific where the sales debrief was fuzzy. A ranking question shows that tracking visibility, not rate, was the top decision factor for the lost account and for three of the at-risk shippers. Open-ended probing surfaces the exact failure: status updates lagged the physical shipment by a day or more, so the shipper could not give their own customers reliable ETAs. A scale question confirms that the at-risk shippers would consolidate more volume if visibility improved.\n\nThat is a clear, prioritized fix - invest in real-time tracking before touching price - backed by the customers' own words rather than internal opinion. The 3PL routes the visibility theme to product, the at-risk list to account management for proactive outreach, and re-interviews the same shippers after the tracking upgrade ships to confirm the gap has closed. Because the study reaches carriers and recipients with the same ease, the company can extend the loop across its whole network, turning isolated account losses into a systematic understanding of what keeps freight on its platform.\n\n## Related Resources\n\n- [Structured Questions Guide](/docs/structured-questions-guide) - the six question types and when to use each\n- [Win-Loss Analysis Guide](/docs/win-loss-analysis-guide) - run shipper win-loss research that gets past surface answers\n- [AI Research for Manufacturing](/docs/ai-research-for-manufacturing) - the adjacent industrial-B2B playbook\n- [B2B Customer Research with AI Interviews](/docs/b2b-customer-research-ai-interviews) - reach buyers and channel partners at scale\n- [Voice of Customer Research Program](/docs/voice-of-customer-research-program) - build an always-on listening program\n- [Customer Retention Research](/docs/customer-retention-research) - turn insight into retained accounts","category":"Use Cases","lastModified":"2026-06-17T03:19:05.629362+00:00","metaTitle":"AI Customer Research for Logistics & Supply Chain (2026) | Koji","metaDescription":"How logistics, freight, and 3PL teams use AI interviews for shipper win-loss, carrier and driver experience, last-mile recipient feedback, and retention - at scale.","keywords":["ai research for logistics","logistics customer research","supply chain research","shipper win-loss analysis","3pl customer research","carrier experience research","last-mile delivery feedback"],"aiSummary":"Logistics providers, freight forwarders, 3PLs, and last-mile companies can run customer research at scale with AI interviews instead of account-manager anecdotes or slow surveys. High-value studies include shipper win-loss, account retention, carrier and driver experience, last-mile recipient feedback, new-service and pricing validation, and platform onboarding. Koji runs voice or text interviews in the participant's language, probes each answer, and analyzes hundreds of conversations into a themed report. Text interviews cost 1 credit, voice 3, free tier 10 credits.","aiPrerequisites":["A clear sales, operations, or product decision to inform","An audience to interview: shippers, carriers, drivers, or recipients","A Koji account (free tier includes 10 credits)"],"aiLearningOutcomes":["Identify the highest-ROI logistics and supply-chain research use cases","Run shipper win-loss interviews that reveal real decision criteria","Reach carriers, drivers, and delivery recipients you cannot easily schedule","Validate new service tiers and pricing before rollout","Choose structured question types for trackable logistics metrics"],"aiDifficulty":"intermediate","aiEstimatedTime":"9 minutes"}],"pagination":{"total":1,"returned":1,"offset":0}}