- Advanced Analytics Frameworks
Analytics by Business Domain
- Competitive Intelligence
- Customer Lifetime Value
- Credit Early Warning
- Predictive Maintenance
- Predictive Manufacturing
- Predictive Quality
- Dynamic Pricing
- Trade Spending
- Cognitive Behaviours
- Sales and Operations Planning
- Meter to Cash
- Data-driven CFO
- Item Planning
- Next Best Action
- Predictive Walk-in
- Process Mining
- About us
Manufacturers would like to get better results for the money they spend, and they would like to spend less, but they are frustrated on every side. Worst of all, given the importance they attach to return on investment in every other area, manufacturers themselves rarely know what return they are getting on the money they invest in trade promotions.
While it is impossible for companies to eliminate trade spending entirely, trade promotions can be rationalized, and the money invested in them made as productive as any other prudent investment.
Manufacturers know that the more they spend on promotions, the more they'll sell. Many fail to notice that some market share costs more than it's worth.
There is a second concern that inhibits efforts to optimize trade promotions: manufacturers are hesitant to destabilize their relations with the retailers.
Typically, the manufacturer takes 80-85% of the total profit and the distributor takes 15-20%, so trade margins tend to be very narrow.
One way is by trying to align their interests with the interests of retailers in order to produce win/win promotions. It is not an easy task.
The most successful trade-promotion strategies are designed around specifics. Different geographical regions, different retail chains, different product categories, different brands-all make different demands on manufacturers and present different opportunities for cutting costs, improving alignment with the trade, and enhancing results. To realize an outstanding return on every marketing initiatives, companies must understand and exploit these differences, using an advanced analytics big data-driven framework.