In this article:
- Levi Strauss has applied AI to target product offerings and pricing more precisely and profitably
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Katia Walsh, the Chief Strategy and AI Officer at Levi Strauss, recently explained how the company is capitalizing on insights identified by AI to the Wall Street Journal. For example, this strategy allows the brand not to lose out on what could be profitable in one region, even when it is not so in another – and to not have to resort to steep discounts to make sales, causing them to “pay the price of generalization”.
The article offered one example of this for a particular T-shirt that the company had considered taking off the market. It was not a big global seller, but it was “popular with female consumers in China.” By referring to “machine-learning analysis,” the Journal pointed out, the company realized that it paid to keep it for sale in China where it does sell well.
This kind of insight is usually beyond human ability because of the huge volume and variety of products that the brand sells – “online and in some 50,000 retail locations in more than 110 countries,” in Levi Strauss’ case, as the article pointed out.
So many locations combined with online sales also bring up complex logistical considerations, and machine learning helps with that, too. Applying a trick that major retailers like Walmart have learned, it will sometimes ship the item from a store that’s closer to the customer’s home than the distribution center is.
There are two benefits to that approach. One is that it “helps the company better manage store inventory—and control shipping costs.” The second, as the Journal points out, is that of faster shipment, which always increases customer satisfaction and boosts loyalty.
What we love about it, of course, is how it’s yet another example of the possibilities AI opens up for brands and marketers. Combining person-power and machine-power allows both sides to focus on what they do best.
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