loyalty program
Sony announces PlayStation Stars, a loyalty program for gamers
We really feel like this is just the best time to be launching this type of program, in terms of us having the healthiest player base, the PlayStation 5, obviously, is a huge success and we really wanted to do something that can honor and celebrate PlayStation's history, and now's the best time to do so,
How to increase customer loyalty? Lead with conversational AI in your customer experience. - Watson Blog
The digital-first shopping experience gives consumers unprecedented access to the brands they love and choice between all available options. Meanwhile, brands can now speak directly to their customer base and collect data that helps them personalize and optimize every customer support interaction. It’s cheaper to sell new products to repeat customers who have already been exposed to and persuaded by your brand messaging than to reach entirely new customers. That’s why customer loyalty programs, from free products to punch cards to point systems, have been a major part of the brand experience for centuries. Today, all rewards programs are mediated by digital experiences, and customer loyalty strategies must take a holistic approach toward synthesizing all customer touchpoints, whether that’s a brick-and-mortar store, an e-commerce site, a social media presence, or a mobile app. The way to accomplish this is through intelligent workflows driven by AI (artificial intelligence). How conversational AI helps drive customer loyalty Historically, loyalty programs…
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Data literacy: What it is and why it matters
Did you miss a session at the Data Summit? What do you need to do to increase the data literacy of your organization? In a world where your personal data (and the preferences and biases buried in that data) are used to influence your behaviors, beliefs, and decisions, data literacy is a fundamental and indispensable skill. And it's not just corporations that need this training. Data Literacy should be taught in universities, in high schools, in middle schools and even in adult education and nursing homes.
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Data Literacy Education Framework – Part 1 - DataScienceCentral.com
What do we need to do to increase the data literacy of our organization? In a world where your personal data, and the preferences and biases buried in that data, are being used to influence your behaviors, beliefs, and decisions, data literacy becomes an indispensable fundamental skill. And it's not just corporations that need this training. Data Literacy should be taught in universities, in high schools, in middle schools and even in adult education and nursing homes. Data literacy training needs to educate EVERYONE into how their personal data is being collected, analyzed, and used, so as to not be duped into actions, behaviors, and beliefs by organizations and people who understand how to manipulate your personal data to their benefit.
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Levi's Katia Walsh Shares Real Insight Regarding Digital, Data and AI
Levi's loyalty program, which launched in 2020, has built a customer pool that now includes 5 million members; using AI, this facet of the company's business is more personalized to each client than ever before. A company that has followed a progressive course over its 168-year history, Levi Strauss & Co. has played an important role during revolutionary moments within history. From creating an integrated employment force in the mid–20th century or ensuring greater supply-chain transparency in the 1990s to encouraging United States citizens to vote in 2020, the San Francisco–based denim leader has remained committed to progress. This part of the brand's mission made it a perfect fit for Chief Global Strategy and Artificial Intelligence Officer Katia Walsh, who considers herself to be an unlikely fashion professional but has felt aligned with Levi's principles. As a student journalist growing up in communist Bulgaria, Walsh was reprimanded in school at 15 years old for writing a story that displeased local officials.
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AI in Focus: Starbucks
A decidedly non tech coffee merchant like Starbucks probably isn't the first name you think of when it comes to widespread adoption of Artificial Intelligence. But with 31,000 stores worldwide and 400,000 partners serving 100 million customers a week, the scale and complexity are a challenge for CEO Kevin Johnson. Johnson has over three decades of experience in tech with companies like IBM, Microsoft, and Juniper Networks. It's no surprise he's leveraging AI capabilities for a sustained competitive advantage. Starbucks has embraced AI as far back as 2017 with what ultimately became Deep Brew.
Four ways AI can help you keep pace with changing consumer behaviours - Marketing Tech News
Consumer behaviour looks entirely different than it did a year ago. Lockdowns and shelter-in-place orders gave people more time to browse online, discover, and fall in love with existing and new brands. More than ever, consumers expect relevancy -- and their tolerance for unpurposeful experiences has plummeted. Loyal customers don't want every last bit of your content -- they want tailored experiences that offer the best products and information. They want meaningful quality rather than irrelevant quantity.
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Five Emerging Trends In Retail Technology
Consumers want shopping experiences that feel personal to them, whether they are shopping online or in-store. Retailers are in a race to use technology to match consumer expectations and win more business. With new advancements in technology, retail will continue its state of constant disruption. Most consumers dread having to call a customer service phone number. Instead, 55% of Americans -- and 65% of millennials -- want chatbots involved in the customer service process, especially when it makes the customer service process more efficient.
Machine Learning in Retail: How to Maximize the Potential of ML Aliz
For decades retail companies have been exploiting analytics within the different segments of their businesses, including marketing and operations. Such analytics are dusty, however, and have now come to an end. Traditional analytical methods are outdated; they require a lot of manual steps and the insights extracted cannot be easily generalized. Using analytics ultimately provides a low return if you include the amount of manpower needed allocating to run them. Machine learning (ML) can be viewed as an extension of analytics.