When I first heard the phrase “mass personalization,” I thought that it seemed to be a contradiction of terms. How can it be mass if it is personalized? How can it be personalized if it is for the masses? But it is not an oxymoron after all. The movement to Big Data and, in particular, to Artificial Intelligence has meant that we can process billions and trillions of data points and – in discovering patterns in consumer behaviors – generate unique responses to specific triggers.
Mass Personalization: what is it really?
So, when we talk about mass personalization, we are talking about how the machines get it right for each individual. In other words, how we take the information collected and process it to make it personal for the right individual in the right place at the right time.
Examples of Mass Personalization
AI and machine learning are enabling mass personalization across many industries. E-commerce serves a really good example for mass personalization in effect. Let’s take Amazon as an example. It tailors offers based on my past purchases, interests, and more. When I log in – I see, “Hey Sameer, here are things you might be interested in!”
Makes life lot easier, isn’t it?
Similarly, Netflix suggests movies based on your interest, genre, artists and more. Yes, before Netflix – you went to Block-buster and got personal attention, where you could check out the DVDs, but Netflix made sure that personalization was possible on scale, – mass personalization!
Before Artificial Intelligence kicked in big time, marketing was a hit or miss activity. Marketers created campaigns with the hope it would resonate with their audience. There was hardly any way to know if their content would work. More importantly, the cost to reach, say, 2000 customers, was way higher than what it is today. With that in the background, personalization was impossible.
Mass personalization with AI
With the advent of technology, and, in particular, Data Science, it became a norm to include analytics in every step. You could now see the products that sell more, even the products that are likely to sell more, understand content consumption, etc.
AI has made it a lot easier for marketers to understand customer behavior and measure customer intent. You can now use AI to generate curated content that would resonate with their target audiences. The market need for mass personalization at scale and the technology advances in AI, have enabled brands and enterprises to finally deliver on the promises of digital transformation.
As new algorithm-driven intelligence improves, these AI-driven smart services have the capacity to deliver immersive experiences, and value exchange across different modes and cadences. Further, these systems can apply machine learning to improve their capabilities in future interactions.
How it actually works?
AI today helps you understand your customer in their context. It constantly captures information on where they are in the buying stages, the accounts that are likely to convert in this quarter, etc.
For example, at Fiind, one of our solutions specific to content marketing, called Content Marketing Intelligence is personalized to the target customer and that understands their behavior. The engine generates lead scores that details the customer buying journey including their pain points, needs, buying cycle, etc.
The machine learning engine uses these data points to suggest content, which we call “pitch points” that will resonate with your target customer, more so if you are into account based marketing campaigns.
All said, this is possible only if you collect the right customer data at the right touch points. Great marketing is all about great personalization, and being able to do it on scale.
Looking forward to hear your views!