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ShipBob processes millions in daily GMV across thousands of merchants. Knowing who needed attention and why was nearly impossible.
ShipBob is a global leader in third party logistics, handling fulfillment operations for many of the world's best known brands along with thousands of SMB merchants. At ShipBob's scale, translating millions of data points into precise, proactive revenue actions for every merchant required a new kind of intelligence
Within weeks, Ambral was live in production across ShipBob’s merchant base, continuously modeling the behavior of every merchant and proactively identifying upsell and expansion opportunities, revenue risks, and the next best actions for their team.
5,000+
Merchants
250M+
Orders fufilled with ShipBob
2 weeks
Ambral to production value
Thousands of merchants, endless complexity
ShipBob serves thousands of merchants across major enterprise brands, mid market accounts, and a long tail of SMBs. Given the size of their merchant base and business complexity, having a clear picture of what's going on with every merchant at all times was always a challenge, despite sitting on a mountain of data.
For ShipBob's largest enterprise accounts, entire teams were dedicated to each merchant, but it was impossible to make sense of the endless data that lived across CRMs, support tickets, meeting transcripts, data warehouses, operational dashboards, email inboxes, and 20+ internal systems. For SMBs, the problem was even more profound. Account managers each served large books of business, and delivering a fully personalized and proactive experience to every merchant required tools that simply didn't exist yet. In both cases, the result was the same: revenue at risk went undetected, and expansion opportunities slipped away before anyone had the full picture.
Weeks to production value
Using their data ingestion engine, Ambral started by unifying ShipBob's data, integrating with every major source, attributing the data to respective merchant records, and deriving traceable logs of historical account manager actions. The result was a continually evolving "digital twin" of each merchant, capturing business trajectory, support history, sentiment, stakeholder relationships, and financial performance synthesized into one continually updated merchant state.
The Ambral team then worked to understand what exceptional account management at ShipBob actually meant. Using years of historical data from account manager actions, merchant outcomes, upsells, contract renewals, and churn events, Ambral built a baseline of what account manager actions led to GMV growth at ShipBob's scale.
From there, Ambral was rolled out to a pilot group of ShipBob's most experienced account managers. Every time an AM acted on a recommendation, overrode it, or added context, that feedback was used to improve future signals and Ambral got smarter with every interaction.
Ambral started generating initial signals within two weeks, was fully live in production at ShipBob within 24 days, and has already been used at ShipBob to drive expansions, automate QBR decks, and increase the book size of each AM.
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Kevin Marvinac
VP, Strategy and Operations
"It's almost like having a personal analyst who's really senior and sophisticated do three months of work on every account but we're doing it overnight, every night, for every account."
Ambral is now utilized daily as the source of truth for merchant intelligence across ShipBob's entire organization, powering weekly account reviews, QBR generation, pricing decisions, AM performance evaluations, and contract renewals. Ambral has already been used to proactively save churns months in advance and capture multi-year expansion contracts.
While ShipBob initially approached Ambral for account management, its impact didn't end there. Executive teams across product, marketing, and operations now use Ambral to get up to speed on any merchant in seconds. The merchant state Ambral maintains will also soon be fed directly into the agentic AI systems being built across ShipBob's engineering, support, and operational teams. Every internal system that needs to make a decision about a merchant will be expected to query Ambral first.