Managed Marketplaces · AI for Account Managers
Platforms connecting buyers, sellers, and sometimes third-party service providers, where the operator actively controls quality, safety, and the end-to-end experience.
Proactive AI for
marketplace account managers
While your AMs are buried in spreadsheets trying to figure out what happened, Cimba is already telling them what to do next, surfacing the merchant at risk of churn, the promotion that will move GMV, and the next best action for every partner in their book.
More GMV from every account manager, even your best ones
Give every AM real-time merchant intelligence and next-best-action recommendations. Every AM works from the same live merchant intelligence as your best AM, across order volume, merchant retention, and promotional ROI.
Inventory risks in their merchant book, surfaced before they hurt GMV
When a merchant's top items are trending toward out-of-stock, AMs are the first to know, and the first to act. Cimba surfaces inventory risk signals across each AM's merchant book so they can recommend action before a stock-out hits sales.
Every partner conversation that leads to action, not a status update
AMs arrive at every merchant meeting already knowing what's changed, why it changed, and what to recommend. Conversations shift from figuring out what happened to deciding what to do next.
CASE STUDIES
How marketplace AMs use Cimba
Managed Marketplaces · AI for Account Managers
Every AM, performing like your best AM
How Swiggy closed the performance gap across 2,200 account managers
The best account managers close the loop fast, they spot the merchant whose orders are slipping, know which promotion will work, and act before the partner asks. Most can't. Cimba changed that ratio.
2,200
AMs with real-time merchant intelligence
10
Business units deployed
< 1 week
To launch each new workflow
The Challenge
Account managers at marketplace platforms are effectively quota-carrying, but their ability to hit GMV targets depends on insights they don't control. Each AM manages 50–100 restaurant partners and is expected to diagnose performance issues, identify growth opportunities, and act on them in real time.
The problem: every meaningful insight requires analyst support. Why did this merchant's orders drop? Which promotion works for this restaurant type? How does this partner compare to similar merchants in the same city? The answers take days. The partner conversation happens today.
The result is a predictable performance gap. The best AMs develop workarounds. The rest leave GMV on the table, and the gap between top and average performers widens as the merchant base scales.
The Cimba Solution
Swiggy deployed Cimba's AI for AM agent, giving every account manager a real-time command center grounded in live production data.
Instead of queuing analyst requests, every AM can now instantly surface:
- Why a merchant's GMV is declining, and the specific action to reverse it
- Which promotions drove the highest ROI for comparable merchants in the same zone
- Next-best-action recommendations tailored to each partner's situation
- Performance benchmarks against similar merchants by city and category
- Menu and campaign opportunities before the partner has to ask
Cimba integrates directly with Swiggy's data infrastructure, with row-level security ensuring each AM sees only their own merchant book, and full audit logs on every query and recommendation.
How They Use Cimba
Account managers use Cimba to arrive at every partner conversation already knowing what needs to change, and why. Check-ins become growth sessions.
- Why is this merchant's GMV down this week, and what should I recommend?
- Which promotion would drive the most incremental orders for this restaurant type?
- How does this partner compare to top performers in this category?
- What's the next best action for a merchant who missed targets last month?
Partner conversations shift from reactive status updates to proactive growth decisions, with every AM performing closer to the top of the distribution.
Swiggy is one of the largest food delivery platforms in the world, operating across 700+ cities in India and connecting millions of customers with restaurant partners.
Swiggy deployed Cimba to close the performance gap across their account management organization, giving every AM the intelligence of their best AM, grounded in live production data and governed for enterprise scale.
“Cimba enables our account managers to answer complex merchant questions instantly and take action during partner conversations.”
WORKFLOWS
AM workflows built for automation
Account managers hitting GMV and quota
Your account managers each handle 50–100 merchants. The best ones close the loop fast, they spot the restaurant whose orders are slipping, know which promotion will work, and act before the partner asks. Cimba gives every AM a governed command center that proactively surfaces which merchants need attention, why GMV is moving, and the specific next best action to take.
Merchant performance diagnostics in real time
When a merchant's numbers move, AMs need to know why, not in two days after an analyst runs the query. Cimba surfaces root cause analysis instantly: order volume trends, category benchmarks, pricing anomalies, and promotion attribution, with no analyst in the loop.
Promotion and campaign intelligence
Which campaigns worked for merchants like this one, in this zone, at this price point? Cimba surfaces promotion ROI data by merchant type, city, and category, so AMs can recommend the right lever at the right time, not just the most recent one.
Real-time AM command center
Every AM gets a live view of their merchant book, who's at risk, who's growing, and what to do about it. Degrowth analysis, promotion recommendations, and competitive benchmarks surface instantly from live production data, without analyst support.
MORE WORKFLOWS
Other high-impact use cases
Cimba extends across the full AM workflow, from territory health to next-best-action recommendations and promotional intelligence.
Territory performance benchmarking
Compare merchant performance across an AM's book to identify which partners are overperforming, underperforming, and why.
Merchant health and churn prevention
Proactively identify at-risk merchants by analyzing performance trends, engagement signals, and health scores, so AMs can intervene before a partner goes quiet.
Next-best-action recommendations
Surface the specific action, promotion, menu change, operational fix, most likely to move GMV for each merchant based on live performance data.
Promotions ROI analysis
Surface which promotions are driving incremental orders versus subsidizing demand that would have happened anyway, by merchant type, zone, and campaign.