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Mass Personalization: The Technologies You Need Are Already in Place

Mass personalization is on the radar of all major businesses. Does it have what it takes to change consumption across the globe?

In today’s highly saturated and competitive market, the “one size fits all” concept is rapidly losing relevance. Regular consumers and enterprises are now seeking products and services with a much higher degree of tailored content and features addressing their needs, and with much greater accuracy. And while advanced customizability seemed to be good enough in the past, nowadays it falls short of what consumers are expecting.

The answer to this new challenge may be in mass personalization at scale. Unlike customization, which caters to the needs of large user cohorts and their special requirements, personalization focuses on the needs of a particular individual. With all the advanced technology available today, the task of getting an intimate understanding of customers’ needs has never been more realistic and financially promising.

The needs and wants of today’s market

The benefits of mass personalization are two-sided: businesses can expect a dramatic growth of their customer base and revenues, while consumers will enjoy the luxury of getting services and products that are “made to measure”. The right name in the greeting of a marketing email doesn’t cut it anymore. Consumers’ expectations now go far beyond that.

Today’s consumer expects service providers and manufacturers to go the extra mile, exploring and analyzing their history of purchases, areas of interest, search queries, preferences, and other traces of their online activities — all in a low-key, non-invasive manner. However, they don’t mind cooperating.

According to a study by Deloitte, as many as 20% of consumers wouldn’t mind paying 20% extra for personalized services. An even higher percentage is willing to voluntarily share their personal information in exchange for a more comprehensive personalization of products and services. With extremely relevant offers landing right in their inboxes or popping up on their favorite online store website, consumers will be making the right choices much faster and getting an incomparably better customer experience to boot.

On the supply side, personalization in technology holds huge financial promise for all kinds of businesses, online and offline alike.

The value of personalization is in the trillions of dollars

Source: McKinsey & Company

It is evident that the implementation of mass personalization at scale requires a lot more than just the proper adaptation and application of a particular personalization technology. It involves the coordinated efforts of marketing and technology teams, adoption of new management practices, modification of corporate processes, and, potentially, even alteration of organizational structure.

Personalization vs mass personalization: What’s the difference?

In the most basic terms, personalization is the practice of providing customers with the most relevant representation of products and services they are seeking through the use of machine learning and personalization products, as well as other tools and techniques. Personalization aims for improved customer experience (CX), shorter sales cycles, increased conversion, dramatically higher effectiveness of sales operations, and substantially higher customer loyalty.

We’re in the start of the move from mass production to mass personalization.

livier Sappin, CEO CATIA at Dassault Systèmes

Mass personalization is essentially the same process, but scaled up to cover a company’s entire range of products and representing an overall approach to doing business. An example of mass personalization on the web would be Netflix with its state-of-the-art AI-based content-matching algorithms; Amazon, which builds its product offerings around the user; or even Grammarly, with its intelligent personalization products and grammar-checking tools that track users’ progress over time and suggest improvements.

The forecast for the mass-personalization trend looks very strong, with a near-13% yearly growth rate

Source: Technavio report

The tech drivers of mass personalization

The success of mass personalization relies primarily on a company’s ability to build effective data collection and processing pipelines that orchestrate data flows, and to then draw meaningful and actionable insights from them. Product personalization software feeds on detailed user behavior logs, and this asset should be used to the fullest through big data and artificial intelligence.

Depending on the industry and business goals of a company, implementing a particular personalization technology will require an individual approach; however, mass personalization on the whole rests on several indispensable technical disciplines.

Internet of Things (IoT)

IoT is now used extensively in a broad range of devices and systems, from smart home kits and intelligent appliances to connected cars and modern workplaces. And when it comes to personalization in technology, the Internet of Things does a great job monitoring and logging user behavior in real time, sending valuable bits of information to the cloud for further processing.

Manufacturers analyze this data to infer what future needs a user may have in a particular context or what products or services could complement their current one.

Cloud computing

The alpha and omega of today’s IT, the practice of capturing, processing, and storing data in the cloud is an essential element of every company’s digital strategy. With round-the-clock global access to virtualized IT resources and a highly configurable infrastructure, personalization products can be scaled as needed to meet dynamically changing program requirements.

In order to build robust product personalization software, companies can leverage the power of standard solutions offered by CSPs and combine them with professional cloud development services from qualified third parties.

Big data tools and pipelines

Big data and data science are at the core of personalization services. Companies use a variety of tools to properly process, store, and analyze data coming from a multitude of sources: shopping carts, online stores, partner networks, social networks, smart vehicles, apps on users’ phones, sensors, voice assistants, and many more.

With this information at hand, data analysts and scientists can really make the most of the personalization of products and deliver tangible value to consumers and businesses alike by identifying and retrieving recurring patterns and bias towards particular products or services.

Artificial intelligence and machine learning (AI and ML)

It would be virtually impossible to manually process countless streams of data and perform effective analysis without some form of automation, and this is where machine learning and artificial intelligence really shine. AI-based systems are perfectly equipped to tap into vast arrays of data to detect anomalies or reveal seemingly indiscernible behavioral patterns.

Companies that succeed in combining machine learning and personalization products are more likely to ensure high accuracy of analysis and business forecasting, which leads to growing sales and considerably higher customer satisfaction levels.

How it works

Now that we’ve taken a look at the benefits of mass personalization, let’s consider a few examples of mass personalization.

Source: Technavio report

Bespoke shoes

ECCO, a renowned Danish shoe manufacturer, offers an advanced shoe personalization experience through its QUANT-U service, a joint project with Dassault Systèmes. The service is based on three distinct steps (data capture, sole modeling, and 3D printing) and enables consumers to achieve 100% wearing comfort.

At step one, which lasts a few seconds, the user steps onto a scale-like platform equipped with sensors for initial measurements (24 parameters, including foot length, width, and shape). Once done, the user then walks on a special mat to measure additional parameters: pressure points, support points, etc. All of these measurements are then processed by a learning algorithm based on Dassault Systèmes’ 3DEXPERIENCE platform.

The final step is the printing of the sole using a German RepRap machine and top-quality silicone. The soles can be printed in 3D anywhere in the world and are available for in-store pick-up or worldwide delivery.

Highly personalized video streaming

Netflix is the most popular international streaming service in the world and is known for its highly innovative approach to user experience personalization. With intelligent algorithms weaved into the very fabric of the service at many levels, the platform knows its audience very well — some say, even better than its subscribers know themselves.

Netflix offers content personalization based on multiple parameters: previously viewed content, watching patterns, favorite genres, directors, and actors, among a multitude of others. Based on this data, the content catalog changes every time a user logs in, and it’s not just the selection of titles that is reshuffled. The thumbnails are also re-generated to showcase the highlights that are of the highest relevance to the user.

The service pushes big data, AI, and ML to the limit and conducts over 250 A/B tests per year to make the most out of its vast collection of content, retain subscribers, and grow its membership.

Custom earbuds

Ultimate Ears offers deep product design personalization for the entire range of its audiophile-grade headphones. Customers can choose between the more affordable, but less hardcore CSX self-fitting option based on an at-home fitkit, or go all in and have their earbuds sculpted by professional audiologists. In this case, the user’s ears are scanned by the company representatives. They then 3D-print the body of plug-in monitor headphones that perfectly fit the user’s auditory canal, thus providing the ultimate level of wearing comfort, both for day-to-day and professional on-stage use.

There are many more examples of personalized products and services out there, and they all rely on the KYC principle manifested in this or that form. Some of them use a single core technology, but most of them lean on a combination of big data, cloud computing, AI/ML, and IoT to build a digital picture of users and consumers.

Bottom line

As you can see, the personalization of products and services yields tangible benefits for all. On top of this, switching to a personalization-based way of doing business does not entail the adoption of an entirely different stack of technologies or investing time and money in risky experiments. In fact, you may be surprised to find that you actually have most of the personalization ingredients in place.

If you feel ready to follow that avenue, start by devising an implementation roadmap and move in incremental steps. Measure your progress along the way by comparing the extra value you generate with investments needed to carry on with the personalization project. There will be a balance point where you will start getting very distinct gains from your newly adopted strategy — and that’s when you will be able to start moving towards product and service personalization at scale.

Original article here.

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