How to create personalized application experiences, ignited by the cloud

Today, more than 80% of the TV shows and movies Netflix members watch are triggered via Netflix's personalization algorithms.

This impressive statistic isn’t just a fun fact — it’s the result of an incredibly successful personalization strategy. 

Personalization is more than just a buzzword for many product leaders and business executives. Done properly, it can improve growth and retention by making it easier for customers, prospects, or employees to find what they are looking for. 

Personalization programs and applications can be a great place for developers to showcase their skills. They can leverage the power of data to create tailored solutions that improve business results and challenge practitioners to think about new ways to deliver critical information. 

Below, we’ll cover some of the modern trends to consider when developing personalized application experiences, as well as why the cloud is the future of personalization.

Netflix: A foundation in personalization strategy

There are many intriguing stories about application development driving personalization, but one of the greatest examples is Netflix. A 20-plus-year journey that started with physical DVDs has spawned into a leading global streaming service with more than 220 million paid subscribers. 

In the early 2000s, developers started creating and blending algorithms to recommend movies to customers based on ratings, search data, and movie details. In 2006, Netflix even launched the “$1 million Netflix Prize” for any team that improved the root mean squared error (RMSE) for their Cinematch algorithm by 10%. 

Since this time, the models for Netflix have continued to evolve with new algorithms and data points that have yielded the creation of profiles, rating wizards, tailored UIs, and even personalized movie art. A commitment to using A/B testing and AI has supported the early hypotheses that personalization would improve retention by making it easy for members to find movies they’ll love.

Personalization has been a key component of Netflix’s business strategy and evolution from the beginning. But where is the future of personalization headed, for businesses and consumers?

Any screen and every channel, but connected

In 2016, then Chief Strategy Officer at Starbucks Matthew Ryan said on the topic of personalization, "Any screen can become a personalized screen moving forward." He was right — advances in technology have allowed new forms of personalization to be delivered not just through the web and mobile and wearable devices, but also through in-store interactions. 

New technology that enables retailers to pair real-time demographic information with potential purchase preferences is emerging. Cameras can try to guess your age, gender, or mood as you walk by and employ that information to show you targeted ads on in-store video screens. A family of four pulling up to a drive-through fast-food chain can be shown family meal deals through smart technology. In retail, smart shelves aim to deliver an interactive experience when choosing a product.

While the advent of new technology and channels is certainly creating business opportunities, it has developers and technologists thinking about how these data points are created, captured, and stored. Or, in the case of the above examples, promptly deleted to ensure the privacy and security of customers. It also raises questions about how this information is then correlated across other disparate sources to learn from customer feedback and create better recommendations in the future. 

Sephora is a great example of how the interconnectivity of application data can improve loyalty. The company’s mobile app encourages in-store consultations, with a companion feature to determine if a product or service is available in the store. It then offers the option to book a reservation with a representative on location. Sephora’s loyalty program is top-notch, and data is seamlessly integrated across every channel. Profile details — from names to purchase habits to quiz answers and more — are made available across employee applications. Every communication on every platform shows the customer's loyalty points, and offers are synchronized across different platforms. 

So how do organizations think about capturing this information from interactions across emerging channels to develop a cohesive customer vision? According to McKinsey, more than two-thirds of respondents to a customer survey indicate that their greatest personalization challenge is the gathering, integrating, and synthesizing of customer data. 

The solution to these challenges starts with having the tools to enable real-time ingestion and segregation of information. The ability to search across resources and build a scalable and economical system to manage data with ease and accuracy is essential. With those mechanisms in place, businesses can create repeatable patterns for innovation in accordance with established processes and compliance standards.

Avoiding the over-personalization problem

Have you ever come across an application, website, or email and felt that the company knew too much about you? This is a concern for many companies. According to a study by Accenture, nearly 30% of consumers said a brand had become "too personal," and 69% of these consumers would stop doing business with a brand or reconsider their relationship with the brand. 

How can companies avoid this hiccup? First off, by acting with empathy and acknowledging when an experience crosses the privacy line. It's also critical that customers feel you only expose information they've shared with you through their feedback or actions (i.e., their own recognized user journeys). 

It's also essential to understand any risks that come with personalization. For example, if you recommend a product offering, new feature, or investment to a customer, are they qualified to use or buy that product? In the case of financial services, not having adequate knowledge of credit ratings, affiliations, or prior investment history can put the customer or the financial institution at risk. 

Does a customer understand what they are buying and how it will affect their overall well-being? In the retail space, not having complete data on customers can misdirect them to products they don't need and might not fully utilize, or even products that are not in stock. Over-personalization may also prevent customers from fully taking advantage of new products, functionality, or services they want to use that fall outside of the personalization algorithm. 

It's essential to look for opportunities to refine the algorithm and leave room for feedback. Offering non-correlated products, features, or experiences to customers strategically (and sometimes randomly) can help refine what’s considered a good fit.

Looking to a future in the cloud

Personalization can take many forms, whether through ecommerce search, content recommendations, newsfeeds, curated lists, or in-store applications. McKinsey recommends several steps to succeed in personalization programs, including creating a data foundation, a decision model, and a design team. 

One of the most critical steps of a successful personalization strategy, however, is technology enablement: getting the various IT systems and applications to integrate and work together. Whether it is implementing new technology or building on top of legacy software, it's vital to build for the future — and that is where the cloud comes in. 

Across industries, technology leaders are benefiting from migrating workloads to the cloud, which allows them to offer new capabilities and insights to customers and employees in a much more flexible, integrated, and cost-effective way. The ability to rapidly onboard new services is a crucial advantage, enabling developers to adopt the latest technologies in machine learning, data management, and security.

As far as personalization is concerned, the cloud can help drive programs like loyalty management. Developers can integrate multiple data sources to enable a unified view of consumers across payments and channels. As validated by McKinsey research, the cloud can "power both real-time and batched data processing, thus solving both of the CIO's significant technological challenges." 

Operating in a cloud environment also helps deliver on objectives for lines of business that are leveraging personalization tools. CMOs can "utilize cloud-based capabilities to engage customers through personalized digital promotions based on real-time big-data analytics. For example, by integrating mobile and web analytics tools with loyalty programs, they can design the right promotions, use geospatial analysis capabilities to enable geofencing, and employ natural-language processing (NLP) for sentiment analysis."

Putting data to work for your business

Creating personalized applications, websites, and tools effectively relies on unlocking data, no matter the format or location. Learn more about how companies everywhere are leveraging Elastic Cloud to capture, search, visualize, and correlate data securely to accelerate results that matter.

Interested in seeing how the cloud could benefit your business? Start your free trial of Elastic Cloud today!