Kevin Richardson

• 15% — Growth in Marketing-driven Sales
• 16% — Media ROI
• 1.6% — Average 2-year Annual Increase in Lottery Revenue Contribution to Education for Same Media Budget
• -6.4% — Sales Loss from Sports Betting – Risk Quantified for First Time

This client was under pressure to achieve continued revenue increases, total and revenue share to education in the state, while holding media investment constant. In addition, new external factors, such as increased consumer interest in sports betting, were putting downward pressure on consumer purchasing.

The solution: An AI/ML algorithm was applied to highly granular sales, media channel, and non-marketing data. Further, custom data-reduction logic was used to measure multiple individual sales drivers while conserving available data points. Finally, the model yielded short- and long-term contributions for the various media investments, as well as cross-channel synergy measures. A scenario-planning tool then provided forecasts of future demand based on marketing inputs, along with reallocation of the media budget to drive revenue growth with the same spending.

I grew media-driven revenue by 15% for the same spend, with less upside from future optimization. Concluded client could “… boost sales & ROI, but options now more limited. Critical to simplify the mix, consolidate spending where it works hardest.”

• 10% — Mid-point Across Brands of % Sales Incremental from Media
• 1.1% — Mid-point Across Brands of Overall Media ROI
• +14% — Mid-point Across Brands – Upside from Scenario Planning in Media Incremental Sales
• +12% — Mid-point Across Brands – Upside from Scenario Planning in Overall Media ROI

These brands needed to deliver sales growth to their parent company while holding the line on spending. In addition, they were expected to have balanced media mixes, i.e., invest in media channels across all levels of the customer funnel. Competitors able to spend heavily on media were also an issue. Finally, market and budget realities sometimes limited data granularity for advanced analytics.

Approach: Collect as much relevant data as possible, then assess gaps or granularity issues as part of managing expectations for business queries that could be answered. Processed inputs were validated with client teams to ensure alignment. Creative but pragmatic thinking in model development was applied to define interactions, set and adjust priors, and so on, to obtain KPIs as accurate, reasonable, and actionable as possible given data limitations. Systematic scenario planning and optimization then quantified results from future marketing plans and found upside from reallocating the budget.

Scenario planning with MMM identified +14% incremental media sales and +12% mid-point ROI across brands. I combined upper-, mid-, and lower-funnel channels. Conclusion: A generally strong performance with upside opportunity.

• 50% — Share of Product Lines with Promotion ROI Above Company Average
• 45% — Share of Customers with Promotion ROI Above Company Average
• $1 — Range of Maximum vs. Minimum ROI Across Product Lines
• $0.68 — Range of Maximum vs. Minimum ROI Across Customers

The client, a relatively small player in the market based on sales share and paid media investment, had its trade promotion budget as its largest outside expenditure item. Despite this spending, recent sales for the portfolio and key segments had been trending downward. Leadership wanted metrics for historic spending efficiency and recommendations to improve results.

Core of the solution: A detailed grid with baseline and incremental sales; shipments and trade spending, trade spending ROI, and key “driver” metrics such as % base impacted by different types of in-store promotion, and % discount by account and product line. Note that these measures serve mainly as diagnostics. Financials were mapped to the POS with custom business rules. An Excel pivot “explorer” produced results for different data cuts. A PowerPoint overview communicated insights and recommended actions.

Confirmed concern: Overall trade promotion ROI was low, but revealed opportunities for products and customers with above-average results. Recommendation: Add events for +1 product line but maintain support of core segments with dominant shares.