How Sephora and Starbucks used Artificial Neural networks for marketing.
Brief introduction about Sephora
Sephora is a French multinational retailer of personal care and beauty products. Featuring nearly 3,000 brands, along with its own private label, Sephora Collection, Sephora offers beauty products including cosmetics, skincare, body, fragrance, nail color, beauty tools, body lotions and haircare.
Number of locations: over 2,600 stores
Founded: 1970, Paris, France
CEO: Christopher de Lapuente (31 Mar 2011–)
Brief Introduction about starbucks
Starbucks Corporation is an American multinational chain of coffeehouses and roastery reserves headquartered in Seattle, Washington. As the world’s largest coffeehouse chain, Starbucks is seen to be the main representation of the United States’ second wave of coffee culture. Wikipedia
Founded: 31 March 1971, Pike Place Market, Seattle, Washington, United States
CEO: Kevin Johnson (3 Apr 2017–)
Customer service: 1860 266 0010
Headquarters: Seattle, Washington, United States
Founders: Gordon Bowker, Jerry Baldwin, Zev Siegl
Subsidiaries: Teavana, Seattle’s Best Coffee, MORE
How Artificial Neural Networks are Improving Marketing Strategies
By adopting Artificial Neural Networks businesses are able to optimize their marketing strategy. Systems powered by Artificial Neural Networks all capable of processing masses of information. This includes customers personal details, shopping patterns as well as any other information relevant to your business.
Once processed this information can be sorted and presented in a useful and accessible way. This is generally known as market segmentation. To put it another way segmentation of customers allows businesses to target their marketing strategies. Businesses can identify and target customers most likely to purchase a specific service or produce. This focusing of marketing campaigns means that time and expense isn’t wasted advertising to customers who are unlikely to engage. This application of Artificial Neural Networks can save businesses both time and money. It can also help to increase profits.
How Sephora and Starbucks used Neural networks to improve their marketing
The flexibility of Artificial Neural Networks means that their marketing applications can be implemented by most businesses. Artificial Neural Networks can segment customers on multiple characteristics. These characteristics can be as diverse as location, age, economic status, purchasing patterns and anything else relevant to your business.
One company making the most of this flexibility is cosmetics brand Sephora. The email marketing campaign is tailored to the interests of each customer on the mailing list. This allows them to offer a seamless, targeted marketing campaign. This approach means that at a time when many companies are struggling Sephora is flourishing.
Through unsupervised learning, Artificial Neural Networks are able to identify customers with a similar characteristic. This allows businesses to group together customers with similarities, such as economic status or preferring vinyl records to downloaded music. Supervised learning systems allow Artificial Neural Networks to set out a clear aim for your marketing strategy. Like unsupervised systems, they can also segment customers into similar groupings.
However supervised learning systems are also able to match customer groupings to the products they are most likely to buy. This application of technology can increase profits by driving sales. Starbucks has used Artificial Neural Networks and targeted marketing to keep customers engaged with their app. The company has integrated its rewards system location and purchase history on their app. This allows them to offer an incredibly personalized experience, helping to increase revenue by $2.56 billion.
Reference- https://algorithmxlab.com/blog/10-use-cases-neural-networks/