In the CPG industry, “trade” refers to the transaction between manufacturers and retailers, and trade promotion is the cumulative marketing efforts that are executed in stores to increase the demand for the products. Trade promotion takes into consideration multiple factors that have the potential to influence customers like pricing, display fixtures, value-added bonuses, and more.
Trade Promotion Optimization (TPO) is analyzing past performance to create models as a predictor of future performance. TPO is about choosing the best combination for every product, area, and SKU in order to create promotions that are maximized for volume, sales, profit and a plethora of other important parameters within a given budget constraint.
1 Trillion spend on trade promotion.
2/3rd promotions are ineffective.
Primarily driven by retail sales data, i.e., point of sale data and financial data.
Predicts the total sales and baseline sales by each product line for each retailer..
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The users can choose products, select objectives, and set parameters. The AI then generates a plan optimized to cater to all the requirements.
It involves photo collection, understanding the store floor space, store shelf space, SKU placement & assortment, shelf pricing, discounts and then making recommendations based on real ground-level data.
CPG companies spend a lion’s share of their revenue on trade promotions, yet, two third of all trade promotions are considered to be ineffective. Here’s a quick rundown of the perennial roadblocks that stop them from becoming “profitable”.
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Manual store audits
Siloed data systems
Lack of accurate, real-time in-store insights
Inability to make data-driven decisions
Competitor cannibalization
Incorrect trade payouts
Lack of real-time field force tracking
“40% of CPG trade promotions spending doesn’t drive the desired results.”
— Nielsen Holdings
The CPG space is highly dynamic and fiercely competitive and hence an optimal utilization of time & resources is critical. Trade Promotion Optimization (TPO) is a practice of ensuring profitability by honing the processes and leveraging technologies to ideate, plan, manage and execute trade promotions.
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Data capturing and harmonization
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Promotion Effectiveness Measurement
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Promotion Analysis
Planning
Optimization
With advancements in Image Recognition powered by Artificial Intelligence, it is now possible to powerfully harness real-time store data, and detect and invest optimal resources in the high-yielding corners of trade promotions.
Images from the stores
Trade promotions and the corresponding quantity of sales
Volume or value of sales, profits targets.
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Real-time relationship management with retailers.
Massive savings on settlements and deductions: Visual proof and automation of visuals to pinpoint the retailers & stores, by city, by region that are not compliant for each category, brand, retailer, and region on a daily basis.
Real-time feedback on modifying trade promotions: If the competition has better trade promotions, the TPO strategy changes dynamically.
Precise trade promotion recommendations using ground-level data: Understand the store floor space, store shelf space, SKU placement & assortment, and shelf pricing & discounts. Recommendations are made based on ground-level data to track the trade promotions.
Causation analysis: Comprehensive analysis of strategies that worked, the ones that did not, and the underlying cause for the same.
What happened in the Trade Promotion?
What should be the frequency of Trade Promotions?
Where did the promotion go wrong?
What may happen in the future and what to do about it?
What is the appropriate promotion mix strategy for the next quarter?
How to increase the trade promotion ROI?
Infilect’s flagship product, InfiViz, is an advanced Image Recognition AI tool that helps sales and business leaders of CPG & FMCG brands with real-time and accurate in-store retail execution insights. With its highly trained algorithm, InfiViz can provide predictive and prescriptive analytics to boost trade promotions and add layers of efficiency to the same.
Actionable In-Store Execution Insights in Real-Time
Multi object and Dynamic shelf tracking
AI-driven Sales Recommendations
Automated Store Audits
Real-Time Shelf Metrics with Over 97% Accuracy
Per-Store Level Retail Insights
Proven Efficacy Even in Low Light Conditions
Recommendations For Smarter Assortment Planning
100% Compliance Adherence & Monitoring
Retail Distribution Insights for Both General & Modern Trade
Comprehensive Competitive Intelligence
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