Business planning

Systems Intelligence provides data and analytics services that go beyond media optimisation. Our business modelling can feed annual or regular business forecasting. We can provide support for new product launches including recommended media budgets required to hit targets along with initial business forecasts. We also work with brands to help un pick the most important factors in their product proposition and therefore how to optimise it.

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Powered by our Marketing Mix Modelling, we offer a powerful business forecasting service to clients. Our forecasting platform offers clients the ability to forecast their sales by week or month for future periods, based on a given media laydown. Assumptions can be easily flexed to create multiple scenarios that can be saved and compared.

If monthly MMM is subscribed to, built into the platform is the functionality to reconcile your forecast vs. actual performance, providing a clear view on why a forecast was under or over predicted which can be used to continually refine forecasts.

Our business forecasts help clients in a wide range of situations, from annual business planning and budgeting to capacity management.

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Launching a new brand or product comes with a lot of unknowns. Systems Intelligence can take away many of these by providing support on budget setting and forecasting. Our analytics support in this area is designed bespoke to the brand in question and its needs. ​

Often clients will have a business objective in mind, in terms of a sales or awareness target for the launch. We can support with a data-fuelled and robust recommendation of the media budget required and optimal laydown. Our business forecasting can predict how quickly the target can be realistically hit. ​

We can do all of this based on our huge set of media benchmarks, providing an unrivalled knowledge of how media builds brands. ​

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There are a complex set of factors that drive a consumer’s choice of brand and product in competitive markets. Our conjoint analysis can unpick the drivers of the purchase decision from a proposition perspective. Taking mobile service providers as an example, it can disentangle the importance of the brand, the monthly fee, the upfront handset cost, monthly minutes, texts and data included, additional offers such as cinema 2 for 1s. All things that consumers have to weight up when choosing a brand and package. ​

​As the analysis quantifies the importance of each factor, the outputs can be used to fine tune the product proposition to be more attractive to consumers, without necessarily increasing the cost to the business. New propositions can be tested with the simulator that is provided, to provide a forecast of the expected changes in demand. ​

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