when every promotion competes for attention, decisions cannot run on instinct
If you are a retailer or a consumer packaged goods (CGP) brand, you deal with this paradox everyday. Every product fights for visibility, yet every promotion competes in a discount-heavy, attention-fragmented environment. A price drop may boost volume in one region, fall flat in another, or worse — cannibalise premium Stock Keeping Units (SKUs) entirely.
This is why traditional promotion planning feels increasingly like guesswork. Decisions often rely on fragmented POS data, partial retailer inputs, and teams scrambling through spreadsheets days before the promotion goes live. According to Salesforce, trade promotion optimisation (TPO) is now a top priority because brands lose significant value when promotions are planned without real-time insight.
What CPG leaders want instead is clarity; knowing which promotions work, where, and why.
the cracks in traditional promotion planning
Before AI-enabled TPO platforms matured, CPG leaders faced chronic challenges that slowed decisions and blurred visibility:
- No unified view of performance across channels, retailers, and regions
- Limited ability to forecast impact, especially when competition, seasonality, or weather shifts
- Slow post-event analysis, meaning learnings rarely influence the next promotion
- Execution blind spots, meaning the offer looks perfect on paper but falls apart at the shelf
These gaps cost money, momentum, and sometimes entire seasons.
A category head at global snacks company once described promotion review meetings as four teams presenting four different truths. With data split between syndicated dashboards, retailer emails, and internal reports, no one could agree on what actually worked.
AI-driven promotion optimisation eliminates this uncertainty.
how TPO makes retail decisions significantly smarter
AI-enabled TPO platforms turn retail complexity into structured, actionable intelligence.
Here is how the shift happens:
-
unified retail and promotional data
- predictive forecasting with real-world context
- scenario simulations before money is spent
- What will happen if they run a BOGO in the south but stick to coupons in metro stores?
- Will a display investment lift premium SKUs or cannibalise mid-range ones?
- How will a price change affect margin across the portfolio?
- closed-loop post-event intelligence
AI aggregates data from point of sale (PoS), loyalty, market share, distribution, pricing, and digital campaign performance into a single consistent view. When data aligns, decisions gain precision.
According to a recent Tredence analysis, AI models account for competitive pricing, store clusters, regional behaviour, and even macro-trends to forecast promotional impact with greater accuracy. This reduces reliance on last year’s performance and reveals uplift drivers hidden in plain sight.
Teams can compare:
AI surfaces the most profitable scenario, not the loudest opinion.
Instead of manual reports weeks later, AI automatically analyses performance, attributes success or failure, and feeds insights back into the next cycle. This creates a shift from reactive planning to predictive, ROI-led promotion management.
moments every CPG leader will recognise
Every brand team has lived versions of these stories:
- A beverage company launches a discount campaign, only to find the offer boosted volume in high-affinity stores but eroded margin elsewhere.
- A beauty brand runs a national promotion but later realises online-only shoppers responded far better than in-store buyers — an insight spotted too late.
- A dairy manufacturer struggles to compare regional performance because retailer data arrived in mismatched formats.
These are not failures of execution. They are symptoms of operating without unified, AI-ready data. TPO platforms prevent these blind spots entirely. They ensure every decision is rooted in real-world shopper behaviour, not assumptions.
why AI-driven TPO is now a strategic imperative
Retail dynamics will only grow noisier. Shopper journeys increasingly span store, app, marketplace, and social commerce. Competitive moves change daily. Promotions influence supply chain load, retailer relations, and brand equity simultaneously.
AI-driven TPO gives leaders:
- Predictive clarity on where to invest
- Portfolio-level visibility across categories
- Retailer-aligned decisions grounded in shared data
- Higher promotional ROI through targeted, evidence-driven planning
Modern growth depends on intelligent systems that learn continuously and guide decisions with accuracy, not intuition. TPO is no longer an efficiency tool. It is a competitive advantage.
how can Infosys BPM help?
Infosys BPM Analytics Services enables global CPG enterprises to modernise trade promotion operations with:
- advanced analytics and predictive models
- unified promotion and retail data integration
- scenario planning and optimisation frameworks
- automated post-event analysis
- demand, supply, and financial alignment
With our deep CPG expertise, Infosys BPM helps organisations move from instinct-led promotion cycles to strategic, insight-led growth.
