Forecasting demand potential can be hit-or-miss. Outside of retail panels or Usage studies, it is very difficult to measure demand , particularly at the grassroots, when you need to bring it down to the municipality level. Existing methods for market estimates , typically designed to measure market sizes at the national level, can be a long way off when you need to zoom it at a more granular level , for instance, at the municipality or barangay. And because these measures are typically based on panels and random interviews, one gets only a limited view of what is existing demand, not necessarily the full potential (including substitute products that consumers are already buying).
The client’s challenge: How to forecast demand potential at the level of the municipalities so they can prioritize their resource deployment against those areas where there is significant demand and huge upsides possible with a calibrated increase in investment.
A Market Potential Framework
Cobena designed its own market size estimation framework considering both demand and supply factors at the level of the municipality.. Using Gateway to access multiple data layers (government statistics on population, household income and expenditure data, municipality level measures of affluence, road maturity, etc.) mathematical models were created that forecasted five year potential demand at the municipal level, taking into account existing market size and historical measures of household consumption for the categories under study.
In analyzing demand factors, all possible determinants that could affect/influence market potential were considered. Baseline municipality attractiveness scores were created to rank each of the 1600 municipalities in the country based on their economic growth potential. These results were then bashed against current client sales performance to come up with a measure of how successfully the client is able to maximize the sales of their product against existing demand (ie. a measure of the client’s market share at the municipality level).
The most glaring opportunities: Identifying inherently attractive municipalities where client had limited or no established presence and computing for the incremental sales benefit just by making their products available.
Cobena also found trends in the most patronized distribution channels across regions, and saw which channels were most crucial in growing the client's business in each municipality. All these findings were mapped against a highly interactive dashboard that displayed the attractiveness of each municipality against how the client was able to maximize its sales in that area. Since the results were computed at the municipality level, they could be rolled up to cities/ provinces/ regions, and ultimately performance indicators could be computed at the national level. A colorful National map was handed over that allowed the client and its field force to see, at a glance, where they were under/over performing.