- to lower the uncertainty of management action
- and/or to help form ideas to bridge the gap between the existing and desired state of affairs.
Confining these efforts to the analysis of a single source of data does not provide enough intelligence to produce confident outcomes.
Google Analytics is a good example of an excellent tool that provides a great deal of transactional data that requires interpretation to suggest an action. When the interpreters have no data about the customers’ experience with the website, they would have to make assumptions about the motivations behind the transactional data. Every time an assumption substitutes for data, the confidence in a suggested action is diminished. I am not arguing for “paralysis thru analysis”, but there is a reason why GPS requires the minimum of three satellite signals, before it gives your position’s coordinates.
I used to look over Yelp reviews before selecting a new restaurant to check out, but 9 out of ten times my experience fell well below the expectations created by other customers’ perceptions. Since I have no access to data about the reviewers age, culinary experience, cultural background and priorities, the analysis of their perceptions cannot produce confident/meaningful recommendations to act. Hence, Yelp restaurant reviews are no longer a reference source for me.
Analysis of customer reviews of products published on Amazon and other sites like that can be very valuable to product and brand managers. They can find great insights for optimization of a product’s lifecycle, a brand’s product mix or advertising efficacy. However, the correlation between customer experience data and sales and returns’ data, will always produce much more confident calls to action.
The myth of “The One” has been propagated in our culture for a long time. That explains the popularity of books and movies that try to make us believe in a single source of wisdom, love and happiness, or whatever else they sell. Similarly, technology providers market their analytical tools for a single source of data as a “strategic” solution, but market intelligence is highly contextual and requires a multiplicity of sources to be meaningful.
Flashy dashboards, without blended data sources, cannot produce confident calls to action. Blending different models to analyze the same data will likely increase the confidence even more. It is important to remember that the effectiveness of your efforts depends much more on the data sets you choose to analyze in concert, than on the tools you choose for analysis and visualization.
