Tuesday, October 06, 2015

Ninja Metrics uses analytics to boost Springboard’s retail and ecommerce revenues

This interesting article outlines how Ninja Metrics, an innovative and exciting analytics company, is applying its methods that've been successful in the gaming industry to the retail industry. Ninja Metrics' takes an algorithmic approach to customer acquisition; in the gaming industry specifically, the company has figured how to identify gamers who don't spend any money on games, but have "social value" in that they are so involved and active on the gaming scene that they generate excitement and engagement with other users. To gaming companies, while this non-paying, active gamer isn't contributing much revenue to the bottom line himself, he is through the revenue generated by users he influences to game who indeed to pay. In this sense he is a social influencer. 

The article draws a simple but illuminating analogy to someone at a bar who is clearly the life of the party, but isn't himself spending much on drinks. The bar owners don't care because he or she is the reason others come to the bar, stay at the bar longer and spend more on drinks. In quantifying the value of this customer, the bar owner has to consider the value of the "social network" he brings to the bar as opposed to his individual spend.

The crux of the article is on the Ninja Metrics taking its approach into the retail industry (a much bigger market) through its partnership with Springboard retail, a cloud point-of-sale and retail management company that processes $200million in sales in the US. The idea is that they can drive incremental sales to retailers first my linking the transaction of one user to next and accurately identifying when a purchase made by one consumer is as a result of a prior purchase by another. Overtime, retailers would be able to identify the most influential and valuable shoppers and leverage their network to drive incremental revenue. 

Ninja Metrics' model has been successful in the gaming industry (85% to 90% accuracy), and it'll be interesting to see if they are able to achieve similar levels of accuracy in the retail context.

Link to full article:


1 comment:

Sonie said...

Interesting piece -- and similar to the approach YouTube has taken in using homegrown YouTube stars as influencers on the platform.