How to use time series forecasting to improve your demand assessment

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In the second part of our Innovation in #MRX series we demonstrate how to use time series forecasting to better inform product uptake and competitive scenarios up to 10 years into the future. Understanding likely demand for a new product or service is essential to help develop the right brand strategy. Techniques such as conjoint and fixed product profile assessments are great for evaluating the market landscape and opportunity, but are they enough? Can we predict the future with greater accuracy?

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Time series forecasting is one of the latest market research innovations we have been championing at Research Partnership and we would like to share the benefits of this technique with you.

Analytics Director Misti Paul and Associate Director Will Tolley demonstrate how to use a combination of sophisticated techniques with primary and secondary data to better inform product uptake and competitive scenarios up to 10 years into the future.

What are the key takeaways?

Understand the theory behind time-series forecasting and how it compares to other techniques.
Learn how this sophisticated technique can provide a realistic view of the future market.
Assess what types of data are required in order to carry out time-series forecasting.
Find out when it’s applicable and when to use other demand techniques instead.

Webcast: MRX time machine: How to use time series forecasting to improve your demand assessment

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Webcast: MRX time machine: How to use time series forecasting to improve your demand assessment

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Watch the webcast

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