Click on the image to enlarge it.
We wrap up this four part case study, analyzing an online-only golf brand, by asking the question "What would it take to grow Accessories so that sales were equal to Apparel?"
The Accessories merchant won't like the answer.
The scenario in the image is one where I doubled the corporate repurchase rate for Accessories-only buyers, from 30% per year to 60% per year.
I also increased new buyers to Accessories-only by a factor of 2.5x.
By doing this, Accessories generates the volume that Apparel generates. Also notice that Golf Clubs greatly benefits from this strategy.
Realistically, it is not likely that one can increase the annual repurchase rate for any one segment of customers by more than maybe twenty percent. Therefore, the retention increase is unlikely to ever happen.
Furthermore, increasing new customers by a factor of 2.5x is probably very expensive.
This suggests that, in the next two or three years, it is highly unlikely that the new Accessories merchant can hope to grow the business in a dramatic manner, no matter how much the merchandise assortment is improved.
This is a key area where traditional web analytics fails our business leaders. A Multichannel Forensics analysis aids the CEO by realistically telling the Executive team "what is possible".
In this case, the Accessories leader should have modest bonus objectives.
The data strongly suggest that the better the Accessories leader performs, the better that Golf Clubs will perform. These two leaders should have incentives that depend upon each other, since customers switch back and forth between these two merchandise divisions.
New CEOs and Executives need to understand what kind of trouble they are getting themselves into. This case study clearly illustrates how challenging it will be for the new Accessories Executive to grow the business.
The case study also indicates how "dependent" various merchandise divisions are upon each other. Success in one division causes success in another division. The online CEO or Executive cannot understand these dynamics by studying traditional web analytics. Only a well-constructed multichannel forensics analysis points out these important "dependencies".
Case Study, Part 1.
Case Study, Part 2.
Case Study, Part 3.
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