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Now we have a precise representation of the market, it's about deciding where to fight for market shares and where to set back. Other layers are added to the stack, primarily Cost-to-Serve and Competition data. ROI per region can then be defined - the cost of gaining new market shares allows to prioritise areas between the easy wins and the long battles. We drive discussions, debates, we blend data and market insights so a market coverage expansion strategy is defined together with Sales and Marketing team members. A consensus around demand landscape expected evolution helps to align everyone around facts and figures and avoid blurry intents, too broad objectives and unsubstantiated growth targets.





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To get practical a market landscape needs to be broken down into operational areas that can be allocated to distributors, local sales team or commercial partners. Whether the landscape breakdown is initially made through administrative regions or through point-of-sales density, the intent is to draw geographical clusters that represent a even volume of sales and/or number of stores across the market. Then clusters can be merged, extended or adjusted to reflect the reality of the area (road connectivity, legacy distributor territory,...). This exercise helps to mitigate the risk of high dependency to specific distributors or partners in certain areas. Each cluster having a given demand volume evolution and a certain number of stores, the sales team can allocate clear territory to local managers and executive with a precise sales volume expectation over time.

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