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2021 digital marketing customer experience trends tilts towards hyper-personalisation, by PivotRoots’ Yogesh Khanchandani

By Yogesh Khanchandani, co-founder & chief business strategy officer at PivotRoots.

In this world of chaos where privacy has become a myth, Hyper-personalisation is one trend that is seeing an increase in adoption by many organizations that strive to deliver relevant messages to its audience.

As an off-shoot of personalization, an age-old disruptive marketing concept in itself, hyper-personalization is now steadily emerging as a turnkey strategy amidst the overstimulation that happens to consumers across various interaction channels both digital and non-digital. It becomes imperative to block this white noise and solve for problems like indifference, choice paralysis and attention spans. Sameness is pervasive and competing on innovation is still a grey area for many brands that deal with legacy infrastructure and technology.

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Hyper-personalization tackles the above issues in food delivery, education, retail and taxi businesses, to use real-time data to deliver information based on perceptions rather than being a custom solution provider to a finite customer segment defined by analytics. Possibilities are endless and it can deliver customer digital content, niche product and servicing information or email marketing information.

Considering email marketing is still a popular marketer choice to engage with its consumers, Statistics from SmarterHQ reveal that 70 per cent of the younger generation of consumers, or millennials, are not particularly thrilled by emails sent to them by brands. That’s not all, according to Retail TouchPoints, 36 per cent of consumers say retailers need to do more to offer personalized experiences. Instapage also points out that 74 per cent of customers get frustrated when the content received on websites isn’t personalized. These and many other statistics pretty much speak for themselves. The question to ask here is how do we judge what is “relevant” for the customer. Others argue on its subjectivity but the point remains it’s not the content or the frequency but the context in which the customer is currently that can control the churn.

Lots have been said about Netflix and its recommendations algorithm in recent times. Case studies have been written on the billion dollars that Netflix spent to build this AI-based AI smart algorithm. Not many know the strong insight behind it. Users on Netflix were unable to choose what content to watch and would lose interest in 60 to 90 seconds. Netflix knew the impact it could cause to its subscription and popularity and realized it needed steps to mitigate this risk. The brain is lazy; pattern recognition, shortcuts, recommendations mean less energy needed to make a decision. This is the insight Netflix used to come up with a recommendation engine which enabled it to understand the customer’s context and choice of viewing information and not make one product but a million products adapted to every customers taste unique for each profile.

Integrating hyper-personalization

For hyper-personalization to be successful as a marketing tool and building due to relevancy, many factors have to be incorporated. The underlying factors for this mode of marketing include artificial intelligence, predictive algorithms, automation and data analytics.

Since hyper-personalization keeps evolving, the factors and combinations also keep changing from time to time.

About 86 per cent of companies have cultivated their customers’ trust using personalization. According to Epilson, 80 per cent of buyers are highly likely to make purchases from a company that offers personalized experiences.

When a company uses hyper-personalization, they know what their clients want, hence make prompt recommendations on these customers’ social media platforms, search results, or through emails.

According to a recent study, Ninety-one per cent of consumers have been seen to shop more for brands recommended to them simply because most of these brands are relevant and aligned to their needs.

From the statistics outlined in the article, it is clear that brands can reach their conversion goals by simply adopting a hyper-personalization strategy. Consumers out there react favourably to content that resonates with their pain points – as a marketer, you just need to know how to interpret the data and identify how to effectively deploy it.

Critical steps to follow while designing a blueprint for hyper-personalization

  • Design the correct data lake

The first step towards hyper-personalization is to identify the audience whose attention your brand intends to capture. From here, data on these customers can be collected through the data collection methods adopted by the company.

  • Segment the customers

After collecting data on the customer, the next step is to use the expertise and deploy the data for the process of personalization.

The audience is divided into smaller groups based on location, recent interactions, expenditure, and demographics among other factors.

  • Personalizing messages and recommendations

Your hyper-personalization strategy needs an enabler (data) to deliver the desired results. CRMs and CDPs are two important platforms to help identify data across customer journeys.

After capturing data and subgrouping the audience, the next step is creating personalized messages and sending them through different mediums.

It’s during this step that the company starts popping up recommendations on the customer’s feed and redirecting them to the various platforms where they can get the products.

  • Analyzing

From the different approaches of hyper-personalization that were adopted in the brand’s campaigns, the company examines and calculates the one that was most successful.

The method that connected well with the customers and led to the most conversions is adopted, as the others are worked upon for improvement.

Trials are also extremely important to building a solid hyper-personalization strategy. They help brands look for key insights that, in turn, drive efficiencies by up to 15 per cent. Use a simple process such as “Insight > Hypothesis > Execute > Evaluate”. The first challenge is usually on key insight, which you can derive by setting the right persona parameter.

To wrap up, hyper-personalization is a win-win for both the brand and the consumer. Thanks to this AI-driven marketing concept, brands are now in a much better position to narrow down their digital marketing campaigns with an attractive return on investments while the consumer benefits from content that’s aligned to their needs.

This significantly helps brands boost their customer experience since the customer now get a simplified list of things they need instead of having to choose or navigate through many items that they have no use for.

Hyper-personalization is a great way to attract customers and retain them. A customer who feels cared for is likely to come back and make more purchases from time to time.

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