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With invent.ai, retailers model demand, customer behavior and inventory across stores and channels—making promotions more targeted and perfectly timed to drive sales and protect margin.
Here's how it works:
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Promotions by invent.ai
AI-powered promotion planning that drives demand—while protecting margin, inventory and customer loyalty. Design data-driven promotions that balance financial goals with real-time demand—so you can boost lift, reduce waste and deliver offers that resonate with every customer.
2-4%
higher gross margin dollars
2-7%
more revenue
5-20%
higher conversion rates
Promote with purpose
Promotions are powerful but often imprecise—built on historic lift curves, blanket discounts and disconnected inputs. The result: campaigns that miss demand signals, drain margin and fail to connect with customers.
Invent.ai’s promotions solution cuts through the noise with AI, consumer data and machine learning to create localized, margin-aware campaigns at scale. Whether running one event or thousands across stores and channels, it balances demand signals, inventory and financial goals to maximize lift, protect profit dollars and strengthen customer loyalty.
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AI-powered promotions that hit the right customers at the right time
Why choose invent.ai for promotions?
Invent.ai combines predictive analytics, real-time signals and automation to ensure promotions are effective and efficient across channels. Our solution enables retailers to:
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Forecast and simulate promotional outcomes before execution
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Tailor promotions by store, region or channel to reflect demand
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Balance inventory availability with promotional lift
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Protect brand and margin with precision targeting
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Continuously learn and adapt with AI-driven insights
The result: better-targeted promotions, optimized inventory and higher margins.
The science behind it
Invent.ai transforms promotions with AI- and ML-driven decisioning, forecasting and scenario simulation. By analyzing sales history, customer behavior, inventory levels and regional trends, the platform identifies which offers will perform best—at the right time, in the right stores and channels.
Automated clustering, scenario modeling and recommendation engines replace manual planning with data-driven precision. Retailers can test different discount levels, timing and store allocations before execution, ensuring campaigns meet both demand and revenue goals.
