Hyper-personalization – A New Norm in Customer Service

MAC — Mobility, Analytics and Cloud —an abbreviation which has become quite popular these days and reflects the most popular technologies of today. With mobility, plethora of products have gone wireless and can be used on the move. Databases, have evolved from being structured and limited in size to unstructured and scalable to accommodate for data generated by over 4 billion mobile devices across the world. Maintaining such huge database servers is expensive and hence cloud is the first choice for data storage. One can access data from at anywhere, anytime, in any form and from any devices. With such wealth of data, it is obvious that one can draw meaningful insights and that’s where analytics plays a vital role.

With everything being available to end customers at their fingertips, businesses are competing neck-to-neck to make the best offer to each customer.

With customer data available through various sources, businesses can actually offer products/services tailored to meet an individual’s choices, based on behaviour, buying patterns, etc. This level of personalization is termed as hyper-personalization. However, it is not new to businesses. Traditional retail businesses perform market basket analysis to calculate RFM i.e. recency, frequency and monetary benefits behind each customer visiting stores. But with digital technologies in place, these studies are no more herculean tasks to perform. Amazon, Uber, Avis, and Mercedes are few companies that have adopted hyper-personalization and suggest offerings based on individual’s choice and preferences. Let’s look at how hyper-personalization have become a new norm.

Seismic Shift in Consumer Behaviour:

Cell phones and high speed internet have a psychological impact on consumers and they expect quick results, want the brand they interact with to identify them and personalize their experience to make them feel special.Instead of reaching out to traditional contact centres, customer now a days prefer social media to seek solutions to their queries. Virtual stores are preferred over physical ones due to ease of accessibility. Business have noted these changing behavioural patterns and using MAC technologies to know their customers better.

Data abundancy and change in data patterns:

Billions of cell phones when connected to the internet generate millions of gigabytes of data with information such as location, recent activities, check-ins, likings, etc. If we extrapolate this to a country and then to the globe one can just imagine the magnitude of dataavailable. This has led to widespread adoption of big data as opposed to usual in-premise databases. Data is the new currency and when one has such huge data it is only wise to capitalize on it.

Social Listening through Social Media

As per Statista’s report, it is estimated that there will be around 2.77 billion social media users around the globe by 2019, up from2.46 billion in 2017. This is driving new-gen companies to adopt a free business model through social media to capture a major share of the pie. So much that some of social media analytics algorithms are so advance that they capture the activity, behaviour, sentiment, and can predictthe users’ next move.

While above are the major elements driving hyper-personalization, the following factors help in actualizing it:

How can TechM Help?

SOCIO is TechM’s cloud-based social media analytics platform. SOCIO helps businesses study key attributes such as customer sentiment and demographics to design personalized products and services.

Overview of SOCIO

Key Features of SOCIO

  • Comprehensive 360° solution for social media management and analytics
  • Actionable and proactive insights that help build the brand
  • Quicker go-to market for personalized services/products
  • Strong integration with re-marketing algorithms for a customer purchase through hyper-personalization
  • Personalized positioning of services/products based on geographic and demographic datahyper-personalization
  • Sentimental analysis based on comments, reviews, and feedback improving probablity of personalization
  • Adopt just in time with analytics for customer lifecycle journey