When Apple speaks, everyone listens – and this last week was no different. With the introduction of Apple Pay, the tech giant is betting on its strong brand recognition and a loyal customer base to succeed in a fiercely competitive market. Given the company’s reputation for pushing emerging technologies mainstream, we may see Apple Pay’s tap-and-go payment method become the preferred mobile payment system for retailers and consumers.

The Apple difference

On the consumer front, Apple is paving a smooth road to adoption. In addition to building the near field communication (NFC) technology directly into its device, Apple launched the service with a slew of big-name partners, including Whole Foods, Macy’s, Bloomingdale’s and McDonald’s. The company also partnered with major credit card companies and banks to allow iPhone users to easily store and manage their credit card accounts. By partnering with brands that offer basic items, such as food and clothing, as well as financial institutions, customers may adapt to the idea of using Apple Pay rather than a credit card more quickly than they have in the past. As this becomes habit, retailers will feel the pressure to invest in NFC readers to enable tap-and-go mobile transactions.

To succeed, Apple must also nurture adoption of Apple Pay among retailers. Mobile payment services have historically suffered from the chicken-and-egg conundrum – who must adopt the technology first, the consumer or the retailer? For instance, retailers willing to enable new Apple iPhone 6 users to use Apple Pay must invest in near-field communication (NFC) readers, which come at a costly $499 a pop. Large brands will make this investment rapidly, but it does pose a problem for mid to small businesses with tighter budgets. However, if Apple Pay takes off among consumers, the price of NFC readers will drop over time and make it a viable solution for retail brands of all sizes.

As an added bonus, Apple Pay can solve the inefficiencies of long checkout lines in brick-and-mortar stores – especially valuable during the holiday season! If retailers invest in the technology, it will alleviate this burden for shoppers and brands. Some retailers have already taken aim at the problem with other solutions. Last month, Wal-Mart and Target announced plans to create more efficient checkout processes by adding more staff during peak traffic hours during the holiday season. While this is one way to approach the problem, Apple has taken it a step further by enabling the right set of tools and technologies to solve the problem during critical retail seasons.

Click-bait, be gone! This past week Facebook introduced a significant change to its newsfeed algorithm to eliminate click-bait headlines and spam articles from cluttering users’ feeds. The goal is to provide Facebook’s 1.23 billion users with more relevant content that will keep them engaged on the social network. After all, the more active users engage on Facebook, the more ad space the social network giant can sell. This seemingly minor alteration reflects Facebook’s commitment to advertisers and is a surefire way to keep users from fleeing the network. Earlier this year, the company reportedly lost more than 11 million young users, and this algorithm update is likely an attempt to keep remaining users happy. Facebook’s updated algorithm also reflects a larger shift in how all businesses must interact with customers -- prioritizing relevant, personalized content in the user experience.

Relevance matters

It’s no secret that personalized content is critical to online experiences, particularly in the e-commerce retail space. What’s interesting is that personalization is no longer limited to the retail industry. As Facebook notes, the new changes to its newsfeed will weed out stories that are ‘spammy’ and instead, prioritize updates and articles that users want to engage with. To do this, Facebook must measure engagement in several ways. In addition to clicks, the company examines critical behaviors that may indicate a post’s value. This includes how many comments a post gets, how long users stay on a given site or video, how many shares it gleans and what people are saying about it. This is no different from how advanced personalization tools leverage big data insights to collect and understand consumer shopping behavior online. In an e-commerce environment, for example, how long a shopper looks at shoes versus suits might indicate what he or she is shopping for. Based on this insight, the retailer can make a real-time offer for free shipping on recently viewed shoes. In this day and age, consumers crave personalized and relevant content. The best way to deliver that is to understand the customer’s behavior on and offline, and then administer relevant content based on that insight.