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- Deliver hyper-personalized consumer experiences
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By4 Min Read
July 10, 2018
Whether it’s the right set of songs on a Discover Weekly playlist on Spotify, a TV show or movie you may be interested in on Netflix, or a useful product recommended on Amazon, personalised recommendations on these platforms can really help users navigate through the plethora of choices that are vying for our attention at any given moment. Scientific studies on personalised recommendations throw light on a phenomenon called RAS or Reticular Activating System, a concept of selective attention our brain follows, where we only give preference to things that matter to us the most. RAS is what helps us orient ourselves to focus and prioritise things. RAS helps us react only to those things that are the most relevant to us.
With personalisation, brands are trying to doing the same, which is to successfully reach out to their audience amongst the information overload that we’re subjected to everyday. Not just that, but relevant personalisation could have other far reaching effects on us. It can make us feel valued, as though these brands actually understand and care about us. It can give us a sense of control, owing to the feeling that these brands are catering to our needs, and we have the ability to finally choose or influence what information we see or receive. These personalised recommendations can also be very helpful, especially when they act as reminders for something you need, but forgot about, or when you discover something useful to you that you may have never thought of yourself.
With personalisation, brands are trying to successfully reach out to their audience amongst the information overload that we’re subjected to everyday.
It’s important to note that, personalised recommendations aren’t just for the consumers. Several studies have pointed out, businesses who have been actively working on personalisation have been faring much better than those who haven’t. If we revisit the examples of Spotify, Netflix and Amazon, I had mentioned earlier, not only are they widely known for their work in the field of personalised recommendations, they are also well known as leaders in their respective industry.
In fact, a study by PwC states, 12% of consumers chose their favourite brands based on personalised offers. Another study by Infosys said, 59% of shoppers believed personalised experiences had a significant influence on their purchase. Furthermore, as personalisation is all about understanding and fulfilling the needs of consumers, it can have a significant impact on the overall customer experience, which can consequently show up on your bottomlines.
59% of shoppers believed personalised experiences had a significant influence on their purchase.
Although, the data backs it up, and most businesses claim personalisation to be a priority, many are yet to proactively work towards this objective. If your business is among those, enabling personalised recommendations is just the place to begin your personalisation journey.
While businesses such as Amazon, Netflix and Spotify may have spent million developing the Artificial Intelligence technology that makes their personalised platforms work, today, enterprise technology providers such as Capillary are enabling businesses with the power of AI to do the same at a fraction of the cost.
Personalising online commerce
Personalised recommendations on your e-commerce website or app is a must have today. You can boost product discovery through ‘target blocks’ which are sections of your website that can display relevant products for your consumers based on their purchase history and browsing behaviour. On your homepage, “Trending Products” and “Popular Products” target blocks can be used to highlight certain products whereas, individual product pages could have ‘Similar Items’ and ‘People Who Bought This Also Bought’ to serve relevant recommendations to consumers.
Recommendation target blocks for ‘Similar Items’ and ‘People who bought this also bought’ can also help you increase transaction value as it’s also a good way to upsell or cross sell to consumers. Similar strategy can be applied to your cart completion page where target blocks, “Quick Picks” or “You May Also Like” can help increase basket size. Capillary’s own study on a customer using our AI powered recommendation engine to personalise recommendations on their website had revealed, a 7.5% increase in sales per customer, a 12% increase in conversion rates and 22% increase in overall sales when compared not having any personalised recommendations.
AI powered personalised recommendations on an ecommerce website netted a 7.5% increase in sales per customer, a 12% increase in conversion rates and 22% increase in overall sales
Enabling personalised cross-channel communication
Just like your website or app, product recommendations can be served up on your interactions and engagement with your consumers. Having a single view of consumer across channels can help you understand consumers and deliver the right product recommendations, at the right time, through relevant channels, which can greatly increase hit rates on campaigns. At Capillary, we noticed that brands using our AI powered personalisation engine saw 2X greater incremental sales on their personalised campaigns. Read more about campaign personalisation here.
AI powered personalisation engine provided 2X greater incremental sales on personalised campaigns
Personalising offline interactions
There is huge potential to be had in personalising offline customer interactions that many retailers often miss. Empowering store associates or wait staff with apps that can help them identify customers and deliver relevant recommendations based on customer needs can go a long way into increasing in-store customer satisfaction as well as conversions.
As consumer get more used to having things their way, such personalised experiences are going to become the norm. Retailers who act quickly and stay ahead of the personalisation game have a better chance of sticking out amongst the crowd.
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Whether it’s the right set of songs on a Discover Weekly p