lack of good data:
Accurately measuring the effectiveness of marketing campaigns requires data on the different variables that may have historically affected the firm’s performance. However, corporations may not have data for several of the important marketing variables that have affected their sales in the past. An example is an electronics equipment manufacturer who may have data on its past media expenditures and large campaigns but have no information about the local newspaper and TV ads by individual retailers or local promotions offered by these retailers, all of which drives a great deal of traffic to their products. Building the tools and processes for the collection of such data is a difficult and time consuming process and it may be years before this information is tracked and collected to a standard required for analysis. However, not having the data on so many of these important variables makes it very difficult if not impossible to account for the effect of these and other media variables on their sales.
The emergence of the new social media channels further exacerbates this problem since the data from these channels are still unstructured and have yet to be accurately captured for analysis.
Apart from missing variables, the quality of the data that is available may also be suspect.
Missing variables and measurement errors introduce bias in the estimated impacts and care should be taken to minimize these kinds of errors.
-- Guest contributor Pat Bhattacharya, Managing Principal, Thinkalytics
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