Getting up close and personal: How hyper-personalization is driving the next generation of digital applications

As technology continues to converge with our everyday lives, demand for more intuitive digital services is rising. Consumers now expect brands to provide them with more convenience and relevance than ever before.

Personalization within their digital offerings is a key way for businesses to do this, as McKinsey reports that almost three quarters of buyers now expect personalized interactions. However, personalization is just the beginning. To truly meet customer expectations, organizations must go one step further and aim for hyper-personalization.

Suits you Sir -- Taking customer service to the next level

Hyper-personalization is a more detailed form of personalization that takes customer service to the next level. It is the most sophisticated way brands can tailor their experience to individual consumers. At its best, hyper-personalization will use real-time data, Artificial Intelligence (AI) or predictive analytics. This enables a company’s digital services to receive the most up-to-date information and context of a specific user, before taking the right action. Currently personalized applications could include fitness apps using health and fitness data of an individual, to create a customized workout plan. Or a clothing retailer offering a personal stylist service, where clothes are sent to the customer in line with their specific preferences. But true hyper-personalization will go even further. For it to become a reality, we need a new breed of applications.

This new generation of digital services will require adaptive applications. These are applications that contextually adapt their behavior and features in real-time. This context could include user preferences, environmental conditions or changing circumstances. Able to dynamically change function to suit the user’s needs, the main goal behind adaptive applications is to provide a hyper-personalized and context-aware customer experience. To achieve this dynamism, adaptive applications are powered by AI, Machine Learning (ML) and real-time analytics.

Bringing in a new age of customer service, adaptive applications have the power to transform brand-to-consumer interactions. For instance, a personal health app could tailor workouts on the fly based on weather conditions, physical progress, or other activity an individual has done that day. This could see the app intelligently recommending an indoor workout, instead of a run outside when it’s raining. Another example would be a fast-food retailer’s digital app sending push notifications of a special offer for boxing fans at the start of a big fight night. But to enable these adaptive applications to work, enterprises must have the right data architecture in place.

Building the right foundations with effective access to data

The beauty of adaptive applications is that they can quickly make intelligent decisions on what consumers want or need. However, these applications won’t be able to do that if organizations can’t provide them with easy access to the trusted data, in the correct format. Too often, many businesses store their data in disconnected silos in different systems. This means data can be too complex to access, taking time and extra resources. Not only that, but it’s also hard to know whether the data being accessed is the right information and whether it is stored in the relevant format or language. Hence data silos must be eradicated. This will enable adaptive applications to receive the right information needed for accurate decision-making and avoid issues relating to AI bias or hallucinations.

Another issue is that many businesses are suffering with database sprawl. This is when companies have a multitude of applications, all with their own databases, which may be operational, transactional or analytical in nature. The challenge is when adaptive applications want to access this data. It’s difficult to move information from one database to another due to the different languages, management methods and processes that each one uses. Essentially, database sprawl makes it too complex to access the information required to carry out immediate analytics. Again, this could lead to inaccurate decision-making and potential hallucinations, due to not having the full picture. Having disparate database point solutions also requires more resources and increases costs.

An additional need for adaptive applications is the ability to process data close to where it’s collected – at the edge. This is crucial for the speed at which adaptive applications must make intelligent decisions. Being able to process data at the edge means it takes less time for an application to receive data. Therefore, enterprises need a data architecture that can process data both at the edge, and centrally, with the utmost speed. It is this ability, which will make adaptive applications the best they can be.

Analyst firm Forrester acknowledges these challenges, noting they act as a barrier, compromising the delivery of timely data, and resulting in missed business opportunities. This is concerning given the pressing need for hyper-personalization. To address these issues, organizations should invest in a modern database service that can handle a range of tasks. This will remove any data silos and reduce database sprawl. It will ensure adaptive applications can receive the right data at the speed and in the format needed. Failure to improve their architecture, will just mean adaptive applications can’t provide the tailored customer experience brands need. Instead, businesses risk hallucinations and inaccurate decisions that could seriously derail customer satisfaction and loyalty.  

Getting close and personal to stay ahead of the competition

It’s vital that enterprises have the correct ingredients to power hyper-personalization, so they can keep exceeding expectations and stay ahead of the competition. Having the right architecture is key to the effective performance of adaptive applications. And these adaptive applications will ensure that some companies can provide hyper-personalization, whilst others can’t. It is only with the right pieces in place, that organizations can thrive and provide the hyper-personalized experience that the consumers of today now want.

Image credit: Tashatuvango/Dreamstime.com

Rahul Pradhan is Vice President, Product and Strategy at Couchbase.