What mistakes do we make when evaluating our marketing strategies?
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What mistakes do we make when evaluating our marketing strategies?
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Possible answers (10)
. Confident statements of our incompetent team members mask their professional qualification ().
. A common mistake in evaluating the effectiveness of any campaign is the congruence bias. An error occurs when one or more team members assess the situation as a whole, taking into account only the data they have directly impacted. As a result, third-party events that could have the same, and sometimes more impact on the results are ignored.
. Colleagues responsible for analyzing the results unconsciously manipulated or misinterpreted the data.
. We were wrong in our conclusions because we analyzed the results obtained only in one of several categories. In fact, the data we did not receive has distorted our understanding of the whole situation.
. From the very beginning, we were "tied" to some numbers. As a result, we created incorrect expectations, KPIs, etc.
. We unconsciously changed our data analysis methodology because of the high contrast of the latest results in relation to the previous ones.
. At one of the previous stages of the analysis, we did not correctly determine the correct sample size (the minimum number of participants in our experiment). As a result, by extrapolating the data from the sample to the general group of users, we got an incorrect picture of reality.
. We did not correctly calculate the time required to obtain the desired result. There are two possible options here: 1. The promotion campaign itself was shorter than the time necessary; 2. We did not wait for the right time to evaluate its results.
. We relied on the respondents' responses, which were given following the effect of social desirability. As a result, they did not reflect the real picture that interested us.
. We may have made a number of small but fundamental mistakes at various stages of developing our data analysis framework. Later, we greatly overestimated our ability to "clean up" already distorted data.
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Questions related to in-house team members cooperation (product, development teams and others).
Questions related to product development stage (from concept to first public release).
Questions related to sales, marketing funnels, prospects and leads communication, and overall product packaging.
Questions related to user interaction with actual product and its features.
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