Hyperpersonalize or Stagnate: Is this the future of retailers?

Retailing and brands are all about understanding customer needs. And customer needs are becoming diverse and varied. A one-size-fits-all approach will not work any longer. Retailers and brands need to micro-cluster their customers, understand what precisely they need, and then hyper-personalize their offerings. AI(Artificial Intelligence) and Machine Learning have a huge role here.

Kishore Rajpgopal
Kishore Rajpgopal
Founder & CEO

Only 9% of the retailers have adopted hyperpersonalization. There is obviously something stopping the rest from making the move. From the way we market to the way we consume, technology has reinvented all aspects of retail. Today’s consumer seeks relevance and context. That’s precisely whey you need to hyperpersonalize your marketing strategy.

Let’s explain this point with the help of an example.

Last year, Toys R Us made an announcement that they would close at least one-fifth of their shops. The increasing competition, changing retail landscape, and the lack of funds required to innovate caused the shut down (Business Insider) According to Dave Brandson, they needed to take some tough decisions to reinvent their brand, along with incorporating a radical business strategy. (Evergage.com) According to BI, it was also important for the company to boost their in-store experience and improve the online experiences if they wanted to compete with the likes of Amazon.

How would hyperpersonalization help their case?

Anyone can sell toys but, someone with expertise in this segment can educate you on what toys to buy. Toys R Us know the toy market better than anyone else. They can tell the users the attributes of the toys better than even their competition, and help the users buy the right products. They should not stop at suggestions; they should help the customer complete the purchase.
Basically, hyperpersonalizaton would have helped them take actions based on the trigger received, thus fulfilling the user’s goals in real-time.

Like Toys R Us, a lot of retailers who are wary of adopting hyperpersonalization may stagnate.

The reasons are pretty clear- changing retail landscape, increasing competition and different needs expressed by the different segments. Hyperpersonalization would give them a better perspective, and make the brands contextual, thus boosting conversions.

How it works?

 

Data collected at the customer interaction point combined with the behavioural and demographic data helps the AI and ML systems learn more about the customer’s preferences. It allows them to create the customer profiles, and send them alerts and messages that are relevant to them. this will lead to conversion on proper nurturing. Once converted, new data is collected that is again combined with the historical data and analyzed to update the customer profile.

Business Benefits of Hyperpersonalization

  • Increased conversions: When you send alerts or emails when the customer is about to purchase your product, then chances of conversion go up. Hyperpersonalization helps understand the right time to connect with the customer, and convert them
  • Improved retention: As you use customer journey as the premise for data collection and analytics, you know what message would interest and engage them. hyperpersonalizing interactions give way to better engagement and loyal customers.
  • Focused and strategic acquisition: You know who your customers are, and what they are looking for. With hyperpersonalization, you can narrow your focus to acquire handful of leads that will definitely convert.
  • Insight based sales: Only after generating good and qualified leads, do you need to give it over to the sales team. This simply means, you don’t need to put in a lot of work to convert through sales.

Brands that have Successfully Adopted Hyperpersonalization

Brands that have succeeded in adopting hyperpersonalization

#1 Amazon Go

If you are one of those who hate grocery shopping, then you should try Amazon Go. They have seamlessly integrated their mobile app with the in-store shopping to make it more convenient to the user. Understanding the single pain of grocery shopping in a mart, they decided to make tracking the groceries, adding it to the cart and paying for them easy. Enter the store using a QR code, pick the items, add them to your bag, and move out. Your app will add the items

automatically, and you will be charged for the items you have picked from the shop. The technologies at use include deep learning, combined with computer vision and sensor fusion.

#2 Starbucks

Starbucks is known to drive customer experiences through technology. They have adopted hyperpersonalization through deep learning to offer better experiences and gain loyalty of their customers. Starbucks is a goldmine of data. The My Starbucks Rewards Program application was released with an aim to understand the customers better, and offer them reward points whenever they pay via the app at the stores.

The app collects data of the customers online as well as offline, and has been acting as the point of contact for a while. With the historical and new data available on the app, the brand has hyperpersonalized their recommendations and offering. They have even started personalized games for the customers.

#3 Netflix

Netflix has been suggesting and recommending programs based on your choice of series or movies as well as your browsing behavior. The deep learning method to offer suggestions has helped Netflix improve mobile experiences and engage their audiences in a better way.

#4 H&M

This fashion brand understands the customers before personalizing the shopping experience and the clothes for them. the retailer connects with the customers via an app called Kik, which asks the user a few questions. The answers to these questions helps the retailer understand what the customer is looking for. This strategy helps increase value for the users, and boost conversions for the retailer.

Published on Sept. 24, 2019





































Get Started

Pain Problems to Solve

Select 3 problems

Over Stock
Product Expiration
Out of Stock
Innefficiant planning for growth opportunities
Leaving money on the table Due to Improper Markdown
Cant Figure out latent Demand
What more merchandise could sell
Food Wastage
Not Responding Speedily to fashion Trends
Over Exposure to Competitor Pricing

Benefit Expected

Select Top one or two

Better Full Price sell through (Less Discounting)
Higher OSA (on shelf Availability)
Higher Inventory Turns
Lower Store or DC inventory
Higher Basket Sizes
Higher Customer Loyality (More Repeat visits)
More Effective Planning