Building an Effective Personalized Retail Strategy
Customers are expecting deeper and more personalized retail experiences from merchants. But how can retailers ensure that every customer receives a shopping experience that best fits them?
As more people turn to online retail for their shopping needs, they are expecting more from merchants and want human, customized, and personalized retail experiences. A personalized retail experience takes the expectations, needs, tastes, and history of customers in order to provide them with a better shopping experience. However, a successful retailer often goes beyond, for example, providing tailored product suggestions based on just one data point, such as purchase history. Instead, they build a strategy that ensures, replicates, and builds upon personalized retail experiences by analyzing and integrating customer behavior data from internal and external systems as well as social media platforms.
Ensuring Personalized Retail Experiences by Integrating Customer Data
The online retail industry has an endless flow of invaluable data that it can unlock to provide a personalized retail experience for customers. Customers are becoming more comfortable with sharing personal data with retailers to create those experiences. In fact, 63% of millennial customers are open to sharing data with retailers that use the information to send offers and discounts. Customers are willing to unleash valuable data to retailers – at no cost – and retailers can increasingly take advantage of this opportunity to create a unique customer experience.
However, taking advantage of this data and obtaining a single view of the customer is not as easy as it sounds. The average retail customer owns multiple devices and often switches between them during their customer journey. In the process, the customer usually consults multiple purchasing channels––whether it is in stores, online or mobile. Similarly, retailers make use of various systems and applications, both in the cloud and on-premise. To provide the level of personalized retail required, retailers must collate information from different systems and applications in order to offer customers real-time personalization and a better customer experience, especially as they move across devices and purchasing channels.
This means that if a customer frequently shops online, for example, retailers should provide product suggestions that are leveraging the customer’s location and search history. If a customer prefers to use their smartphone, however, retailers must be equipped to deliver personalized coupons and offers straight to their mobile device. And a retailer needs to utilize real-time data to show if an item online is available in stores, or they risk ruining the relationship with the customer. These scenarios demonstrate that there are many ways that a customer journey can begin and end. This complexity makes integrating customer data all the more important because, without it, retailers are unable to truly know their customer and therefore create personalized retail experiences for their customers.
Customer data integration can take many shapes and forms, with point-to-point integration being one common approach to integration. However, this approach is problematic due to the complex IT architecture that it creates over time. With point-to-point, integrations have a 1:1 relationship. This results in the exponential rise of endpoints as more data, systems, applications, and devices are connected––leading to complexity and brittleness. This not only hinders IT agility but also prevents retailers from developing an IT architecture that is future-proof. The latter is important as it is a vital element in ensuring survival in the retail industry, especially as customers adopt all kinds of new technology and new ways of interacting with retailers.
Retailers looking to ensure personalized retail experiences must look beyond point-to-point integration and consider connecting their customer behavior data through a new approach: API-led connectivity. This approach facilitates plug-and-play integration and connects and exposes assets seamlessly by packaging them as managed APIs. These assets then serve as modern APIs that can be easily discovered through self-service and controlled through customized governance. With API-led connectivity, retailers are able to integrate customer data from disparate sources and unlock the value of that data to create better personalization on their own platforms. In addition, API-led connectivity makes change easy by using APIs to make connecting assets as easy as putting LEGO blocks together; if something needs to be added, changed, or subtracted, assets can be plugged or unplugged with ease.
Using Social Media Platforms to Further Personalized Retail Strategies
Personalized retail is also moving beyond traditional methods of interaction in an effort to create delightful communication experiences for shoppers. An estimated 58% of customers state that technology has altered their views of how retailers can interact with them. Customers now turn to social media platforms to gain a personal relationship with a brand. This means that retailers must unlock data from social media platforms as well in order to provide that coveted personalized experience.
Retailers are already incorporating social media into their own personalized retail strategies. This helps retailers improve their conversion rates and reach new customers in an innovative manner. Most retailers utilize various management platforms – such as Hootsuite, TweetDeck, and others – to analyze and manage customer data from social media platforms to better understand and market to their customer base. One study surveyed 2,800 marketers regarding their social media marketing strategies. Approximately 80% of respondents stated that using social media increased their traffic and 92% of respondents revealed that these efforts led to more business exposure. Social media is, therefore, a powerful tool. But as the number of social media management platforms increases, so does the difficulty of integrating data from disparate sources.
As noted, personalized retail requires retailers to collect, integrate, and analyze data from external platforms – including social media – in order to improve the customer experience. This necessitates an approach to integration that is agile, future-proof, seamless, and capable of connecting on-premise and cloud applications to external systems – such as social media management platforms – to ensure the retailer is built for the future.
As mentioned, one effective way to achieve this integration is through API-led connectivity. MuleSoft’s Anypoint Platform™ is a market-leading solution that enables retailers to start their journey towards API-led connectivity by allowing them to connect, orchestrate, and enable any internal or external endpoint. The platform also furthers IT agility by enabling retailers to launch new initiatives, connect applications, and unlock data across their company up to 3x to 6x faster––bringing retailers one step closer to creating a personalized retail experience.
Ultimately, the seamless integration of customer behavior data and social media data represent just two methods that retailers can use to further their personalized retail strategies. As online retail continues to grow, retailers are becoming more innovative––whether it is through AI-powered personal assistants, social media influencers, or tailored loyalty programs.
The key to achieving personalized retail in all these efforts lies in adopting an approach to integration that allows enterprises to connect, analyze, and use data from multiple applications and systems to build richer relationships with their customers.