Nearshore Americas

Advanced Analytics: A Booster for Trade Promotions

Technology has been advantageous to organizations in many ways, but few compare to the transformative power that data presents. 

Big data that allows businesses to turn numbers into actionable insights is a veritable game changer. It is no surprise that industry leaders have used data consistently to create winning strategies for increased return on investment (ROI).

When empowered with the right analytical tools and solutions, businesses can execute their trade promotions strategies in a seamless manner, acquiring tactical and strategic advantages in the market. 

Trade Promotions Management In a Nutshell

Trade Promotions Management (TPM) refers to the processes and technologies that consumer packaged goods (CPG) manufacturers leverage to plan, manage and execute their promotional activities in collaboration with their retail partners. Promotions typically include:  

  • Physical displays in stores
  • Price discounts or offers
  • Bulk purchases
  • Onsite events
  • Retailer sales competitions

TPM focuses on three key areas:

  • Developing the guidelines for funding and budget structures to plan and execute promotions.
  • Building a multilevel plan for promotional expenditure and volume. 
  • Activating promotions in phases ranging from execution to monitoring and adjusting the promotional activities based on their performance.

The Importance of Analytics in TPM Solutions

Trade promotions are among the biggest investments for CPGs. Businesses spend nearly 20% of their revenue on promoting goods and services to retailers, amounting to over US$500 billion in spend globally. Predictably, TPM is crucial in driving effective sales strategies.

However, about 59% of businesses lose money on promotional activities that are not data-driven; whereas successful CPG promotions can deliver 5x returns when designed by using critical insights offered by data synthesis. Clearly, there is substantial scope for businesses to bridge this gap and improve ROI through effective retail data management.

Traditional TPM data sources are somewhat fuzzy. They offer fragmented data from disparate supply chain nodes, and there is little transparency regarding their actual impact on sales and profitability. The inability to get the right insights results in suboptimal strategies, leading to loss of revenue and margins. 

Businesses need to re-evaluate their TPM approach and integrate it with AI-driven analytics. This enables the business and its key decision-makers to obtain predictive, prescriptive and descriptive insights from available data and optimize their promotional strategies.

Trade Promotion Optimisation Through Advanced Analytics

The problem with traditional TPM methods is that, in the absence of predictive analytics, they cannot factor in issues such as price hikes, potential supply constraints or diminishing customer loyalty due to e-commerce growth. Marketing teams may excel at creating and running promotions, but baseline forecasts are typically left to guesswork. Effective use of data and analytics helps drive efficiencies of scale, giving back Account Executives and Marketing teams time to focus on customer interactions and business expansions.

Integrating trade promotion with analytics and machine learning allows businesses to automate retail data management. Effective trade promotion analytics drives accurate, prescriptive, predictive and descriptive insights and enables marketing teams to recognise impactful value drivers in promotional campaigns. 

TPM solutions integrated with AI and machine learning can help businesses in:

  • Managing promotions with intuitive workflows.
  • Harmonizing transactional data with predictive and prescriptive analytics as trade promotion analytics software can integrate disparate datasets and factor in historical data, resulting in a “single source of truth”.
  • Optimizing their existing promotional activities through “what if” scenarios and post-event analytics.

Businesses that invest in effective trade promotion analytics solutions report better visibility of opportunities and risks, improved demand forecasting and greater control over TPM performance. This can result in an increase in revenue by up to  ~5% and (most importantly) up to  ~10% sustained improvement in trade spend ROI. 

Here are some trade promotions management best practices that businesses can adopt for the right outcomes:

  • Ensuring accurate data input. Data accuracy helps determine if the final outcomes are ideal or suboptimal.
  • Training employees to adopt AI and leverage the full power of analytical solutions to drive short-term wins and long-term value.
  • Bring in the right stakeholders and advisors during the design phase.
  • Choosing the right metrics that allows leaders to analyse promotions holistically instead of focusing only on shipment volumes.
  • Choosing the right TPM service provider.

TPM with analytics is the biggest game changer in the CPG industry today. We are witnessing a shift in the CPG industry, where predictive and prescriptive analytics have become the norm. Their promise of ~5% improvement or ~10% sustained growth, cannot be ignored.

Sign up for our Nearshore Americas newsletter:

Major CPG players are adopting these innovative practices to reinvent their business processes and, in turn, becoming game changers in trade promotion.

With big data, industry leaders are starting to fill the gaps and turning trade promotion management insights into powerful and successful stories.

Vinu Nair

Vinu is Infosys BPM’s Industry Principal in the US. A part of the Infosys BPM family for about a decade, he has worked in multiple domains.
Vinu holds customer delivery at his core, and over the recent years has taken a keen interest in understanding and implementing technology business processes in small yet impactful ways for both internal and external customers. Very recently, he has taken a role with Digital Transformation Services, helping technology-driven transformations and automations for our customers in the Consumer Packaged Goods, Retail and Logistics segments.

Add comment