How to improve promotion planning and drive more ROI through artificial intelligence

Moving to higher-value activities, increased loyalty and big growth.

Improving promotion planning and promotions themselves. It’s what all retailers want. Yet the path to agile promotion planning is elusive for many.

In the first blog of this series, How agile promotion planning increases forecast accuracy, reduces ineffective promotions and more, I covered the general ineffectiveness of retail promotions. Then, in The stages of promotion planning: Why beginner methods fall short of driving incremental sales, I reviewed Stages Zero and One, where finally at the end of Stage One, we start to see some increase in the efficacy of promotions along with a few other benefits. In this final blog of the series, I cover the last two stages and the improved promotions, increases in sales/margin growth and other ROI that comes with them.

 

Stage Two: Intelligent promotion planning answers “What will happen if I take these actions?”

This stage enables retailers to start generating predictive forecasts by modeling historical performance and extrapolating for the future. It attempts to answer the “What will happen if we take these actions?” question. This is where machine learning comes in. It helps to continually enhance forecast accuracy. In this stage, marketers seek promotion recommendations around a specific metric, like sales or margin against last year’s actuals, for example.

Key considerations and benefits:

  • Robust and integrated customer segmentations – Critical at this stage, as retailers build on their view of incrementality by adding in customer impact scores that provide an understanding of whether or not the activation engaged households that tend to participate in promotions. Some retailers will even take this step a bit further by looking at incremental household lift.
  • Tracking customer responses is key – This also creates a holistic view of the indirect effects of promotions. Retailers begin to understand behaviors like switching and forward buying. Knowing these elements provides the most realistic view of true promotion performance.
  • Deal management integration – Retailers begin to improve the efficiency of the process and reduce the time category managers spend going back and forth negotiating deals with CPG partners.
  • More accurate forecasts emerge (along with the associated what-if scenario planning) – They reduce out of stocks as well as the associated inventory and working capital needs.

Retailers arriving at Stage 2 can typically reduce ineffective promotions by 10-15% and achieve at least 2-5% growth.

 

Stage Three: Artificial intelligence answers “What actions should I take?”

The last stage of agile promotion planning leverages artificial intelligence (AI) to confidently address the question of “What actions should I take?” AI plays a critical role by recommending the best possible promotions based on more robust modeling, machine learning, and business rules. Because retailers have billions of data and decision points to consider, AI is truly the only way to seamlessly and quickly handle this complexity, identifying patterns to analyze and diagnose complex problems with accuracy that far exceeds human capabilities.

The benefits of AI and machine learning:

  • Machine learning takes forecasting to a new level – It constantly updates the models in realtime with additional data feeds that continuously refine the forecast accuracy and optimize trade spend.
  • Collaboration process at this stage is managed by AI – It performs many of the backend/administrative tasks typically done by individuals (or worse that are not currently done because of the amount of time and effort it takes today). For example, AI continuously monitors internal and external data sources for signals that provide more granular alerts or prescriptive recommendations at an item or store level – empowering retailers to course correct more quickly.
  • Optimizes spend allocation – Along with an integrated system, AI optimizes spend across circulars, displays and personalized offers, maximizing the ROI for each tactic.
  • Retailers move from static ad zones to dynamic ad zones – They determine optimized local promotions based on identifying and tracking actions of key competitors.

There is a game-changing impact when retailers reach Stage 3 where they often reduce ineffective promotions by 15-20% in addition to sales and margin growth of 5-10%.

 

Agile promotion planning = increased ROI, increased competitiveness and higher-value activities

Evolving from traditional promotion planning approaches to agile promotion planning creates a true competitive advantage by eliminating inefficiencies, minimizing errors, and enabling more innovative and profitable planning – thanks to AI-powered insights and recommendations. Of course, retailers who want to uplevel their performance must be willing to embrace the change management required to move into stages 2 and 3. Typically, selecting the right partner to assist in this process greatly reduces the friction of the process. ROI on future performance – or even the ability to stay profitable in the face of increasing automation and optimization from the likes of Amazon and others – will more than pay for the cost of change and any related growth pains.

With less time and money spent on administrative tasks, inefficient negotiations, and uncertain promotion plans, retailers who embrace the journey to agile promotion planning focus their energy and resources on more value-added activities, such as new item introductions, store visits, and customer-centric merchandising – all of which will lead to more traffic, greater loyalty, bigger baskets – and ultimately double-digit profitable growth.

Promotion Planning Maturity Model

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