Getting Multi-Channel Distribution Right by Kusum L. Ailawadi & Paul W. Farris

Author:Kusum L. Ailawadi & Paul W. Farris [Kusum L. Ailawadi]
Language: eng
Format: epub
Publisher: Wiley
Published: 2020-04-13T16:00:00+00:00

9.3.3 Feedback Effects and Longer-Term Distribution Elasticity

Search loyalty is not the entire story, however. Another important question to ask is how distribution depth is expected to change with distribution points gained or lost. In some cases, the gain in distribution breadth might be accompanied by increased depth compared to competing brands. Convenience stores, warehouse clubs, and airport shops typically have more limited assortments. So if a brand manages to be on their shelf at all, the result may be a more prominent position. In fact, if these structural differences between the first few and the last few points of distribution coverage are big enough, they may even offset search loyalty and reflect themselves in increasing rather than decreasing returns to distribution breadth.v

In other cases, adding more points of distribution may intensify the competition between retailers and reduce their margins so much that they reduce their selling effort and distribution depth suffers. Correctly estimating the longer-term distribution elasticity means that these effects have to be accounted for. There are also other feedback loops in the system of Consumer Pull, Distribution Push, and Performance that we introduced in Chapter 2. For example, higher distribution can make advertising more effective because consumers are reminded of the advertising when they see the brand stocked in the stores they shop at. And broader distribution begets higher sales, which encourages more retailers to stock the brand. The work by Berk Ataman and colleagues that we cited above captures this last performance feedback, but it is difficult to specify a system that can fully capture all the feedback effects and provide good estimates of longer-term distribution elasticity. And that longer-term elasticity is a key input to any kind of “optimization,” which we discuss next.

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