4 Revolutionary Technologies That Are Driving Personalization in Retail

E-commerce Development, Technology

The concept of personalization isn’t new, yet we can see many of the retailers still miss the mark when we talk about tailoring the shopping experiences of the customers.

Personalization has been associated with digital commerce inherently where technology and data often go hand in hand. 

“Do you know, a survey by Infosys showed that 31% of the consumers wish, that their shopping experience was more personalized as compared to current but not only that 20% agreed that they have never witnessed any kind of personalized offers, promotions based on previous purchases, while 19% of the population has never experienced product recommendations based on their past purchases.”

What is Personalisation In Retail? 

Personalization in retail is defined as the process of utilizing personal data to offer tailored experiences to the customers in a retail environment. We all know every path to buy the product is different and personalization in retail aims to serve each individual according to their needs and behavior. 

This is achieved by: 

  • Accumulating data on your customers, for instance, location, browsing history and gender.
  • Analyzing the data, to determine their preferences.
  • Serving a relevant, and personalized customer experience based on that data. 

For retailers, personalization is specifically complex, due to a number of places and ways a customer can shop. In a number of industries, many companies that offer personalization only have a few products and one place to sell them i.e; online. 

Retailers do have countless products and not just one brick and mortar location, but many.  

Some instances for personalization in Retail:

The retail brands are competing to provide the most relevant experiences to their customers: 

1: Send out-of-stock recommendations:

The “out of stock page” is not yet considered in the context of personalization, but it should be. Even if you have already removed an “out of stock” product from your navigation, catalog, hero images, etc. it can be found through other means like search and social. 

Maybe you are used to adding recommendations to your product detail pages, but you should also consider adding them to your out-of-stock pages. 

  • Try displaying those products which are similar to ones that are out of stock. 
  • Up-selling a premium version of the out of stock product. 
  • Cross-selling an accessory related to the out of stock product.
  • Popular products that are currently available on your site now. 

And like always the goal is to keep the user from abandoning your site. Generally, an out of stock product page is considered to be a guaranteed bounce. So the above-mentioned steps are just a way to turn around a missed opportunity. 

2: Retarget your customers before they go:

Personalized off-site retargeting is popular with brands in every sector of the industries because it has the ability to draw customers’ attention back to the particular website. But have you thought about on-site retargeting?  While many businesses take advantage of pop-ups to keep their visitors from abandoning their site. 

Today’s tools enable you to set up the pop-up function, based on elements such as cart content, session number, browsing history, both the past and the present.

So why couldn’t you? 

Like for instance, if your customer has never ordered from you before, consider providing them with a discount on their first purchase. Like if they wish to buy a bag and they have added it to their cart, provide them with a discount.  

3: Personalize the homepage and navigation:

As the data available on website visitors, there are many, retail businesses that still send their target audience to the same homepage, where every visitor, has to struggle with the same navigation for the products they want to shop. 

If you are considering the location, no customer should ever have to select the country, they are logging in from. 

Still, this is something major, that some retailers make their customers do. 

The customer should not only land directly to the country page from which they are shopping, but also the category for sex they’ve shopped for most often. 

This would skip several steps ahead, as the user doesn’t have to navigate through the menu.

Ideally, when they arrive at that page, those categories of products should be highlighted, the customers have shown preferences, for instance, Amazon does this well, yet there many retailers for those, the experience is still highly generic. 

4: Make your posts shoppable:

According to the research, more than three-quarters of people buy things they’ve seen on social media. So, this is good news for you if you own a retail brand, especially with the introduction of the shoppable posts. 

Shoppable posts that feature images of the product, should be accompanied by a link to a product page so that the visitors can click on to purchase. 

In general, at first, the shoppable posts were built for Instagram, but hey hold on! That does not mean you can’t create them on other platforms. But it can happen that they may not come with similar features, for example, the clickable labels for each and every product in your image, but that also doesn’t mean you can’t label designs yourself, say twitter or Pinterest with a link in the description for shoppers.    

5: Allows for continuous shopping: 

Since we know, customers are very selective, so it is advisable to let them shop on their own, get out of their way. Most of them are choosy, so it is possible that they don’t convert at the very first moment, so allow them to choose from where they left, can bring them back to the customer’s journey. 

The big players in this arena are popular for personalizing their homepage in this way. And when the customers move back to the site, whatever they were browsing earlier will appear on the homepage automatically. Also, it is the same way we customize a homepage based on the category like location, sex, product type, etc. 

Striking Examples of Personalization in Retail:

In order to better understand the value of the data analytics, in the retail sector, let’s take a tour of the five use cases in different leading retail enterprises:- 

1: Customer behavior analytics for retail: 

There are some data-driven customer insights, that are very crucial to handle the challenges like enhancing the conversion rates, campaigns to generate revenues, ignoring customer churn, as well as minimizing the customer acquisition costs. 

But for sure there are multiple interaction points through which the customers can interact with the companies, social media is there, stores like e-commerce stores, and more. Now this kind of interaction points can increase the variety of data types you gave to aggregate. 

Once the data is analyzed, it can yield the insights you have never seen before. For instance, who are your influential customers, what exactly motivates them to buy your product, how they behave and the most important is, what is the best time to reach your potential customers? 

2: Personalizing the In-Store Experience With Big Data: 

Hey, do you know the merchandising is considered to be an art form, and there is no direct or straight method to measure the impact of the merchandising decisions? Well yes, it’s kind of true. With the growth of online sales, a recent trend has emerged, wherein, the shoppers do their physical research of the products in-store and buy the products later online. 

The advent of technology has provided new ways to analyze and measures the impact of merchandising efforts on the stores. 

Have you gave it a thought yet, a data engineering platform can help retailers to optimize merchandising tactics, personalize the in-store experience, with more loyalty apps that drive timely offers that insist the customers complete the purchases, with the goal of increasing the sales channel platforms. 

These insights can drive cross-selling, maximizes promotional effectiveness, etc. 

However, we can gather these insights from

  • Websites 
  • Cameras
  • And much more 

 The omnichannel retailers, through the help of data engineering platforms, can: 

  • On customer behavior, the impact of the various marketing and merchandising tactics can be tested.
  • To identify the needs and the interest of the customers use, purchase and browsing history. 
  • Keep a track of the customer behavior and time offer to the customers can keep the purchase within the fold of the retailer. 

3: Customer journey analytics: 

There are various channels available like mobile, social media, e-commerce, etc, through which the customers can access any kind of information they need within seconds. With this, they know what they should buy and from where they would get it. 

Also based on the information which is available to them, the customers make the purchase decision and they can compare the products as well and then buy according to their convenience. 

The expectations of the customers are high, as they expect from the companies they are dealing with, to provide them consistent information, seamless experiences, across all the channels that represent their history, preferences, and interests. The best the quality, the higher would it drive the sale. And according to the trends, marketers need to understand and adapt, how they connect with the customers. This data-driven helps you understand each customer’s journey across the channels. 

  • Whats is actually happening at every step in the customer’s journey?
  • Who are your influential customers and how they behave? 
  • How and when is the best time to reach them? 

The key technologies in personalizing retail: 

What is personalization? Well, I think the prompt understanding of the customer’s needs and requirements, in a way it would provide, analytics and streamline data. Let’s take a look at different technologies:- 

1: Artificial Intelligence and Machine Learning- 

Through AI and ML, the workflows are automated, and they can drive better decisions. With the implementation of the AI and ML, the retailers can now track the behaviors and the lifestyle of the customers, improving the productivity of the employees and managers, some trends include:- 

  • Customer insights and journey mapping: 

The machine learning can collect a huge amount of customer data in order to understand them better, and according to that personalizing the product recommendations, designs and shopping experiences. 

  • Virtual personal assistant:

Conversational chatbots can collect the data related to the customer queries in real-time so that digital retailers can now cater to a huge number of customer queries. And it also boosts the response time and query resolution. 

  • Predictive analysis: 

Data analysis about customer’s sales history, marketing campaign, website interactions, and customer support, merchandising, etc. 

2: Voice recognition technology: 

The voice recognition technology has been rising, with the launch of numerous voice-powered devices, such as Amazon Alexa, apple home, Siri, the voice recognition technology has been revolutionalizing shopping by making it more accessible as well as conversational. Through this, the retailers got new opportunities, to target more audiences by optimizing their digital listenings for voice search. 

The marketing opportunities include: 

By using the conversational oriented keywords, the retailers can target a huge audience, also the retailers are able to optimize their SEO score, and enhance their voice search rankings on SERP’s. 

  • Platform listings: 

The Amazon and Flipkart have product listings, which can be optimized to improve the chances of being recommended by voice searched assistants, for example, Amazon Alexa

  • Content marketing: 

If your goal is to create the niche content which is particularly targeted for voice searches, the retailers can enhance the footfall on their websites and can create an inbound marketing stance. 

3: Computer vision and Sensor Fusion: 

The computer vision and sensor fusion-powered deep learning, the heavy surveillance, and sensors, Amazon a retail giant is focused on the implementation of a next-gen shopping ecosystem with the aim of eliminating the redundant steps related to the purchase strategies, supply chain, and inventory management.  

The interesting fact here is that the technologies work here as self-driving cars. Moreover, it leverages a great level of surveillance on the shoppers, to eliminate the human cashiers from the workflow of the store. 

Moreover, there is not any intervention of facial recognition, as the stores would still use the thousands of cameras, to keep track on the activities of shoppers.

The computer vision powered, the core system will identify every object in front of it. 

4: Robotic process automation: 

The robotic process automation has already paved the way for better productivity in order to cater to the administrative processes like product scanning, data analytics and also, inventory management. It would establish and enhance the relationship with the customer, makes auditing quicker and easier, reduces administrative costs, etc.  The use case of the technology would include, returns processing, workflow management, customer support management, ERP integration, and supply chain management. 

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The verdict:

Through successful mapping, the technological backdrop in retail and planning requires continuous and constant knowledge about consumer behavior.  With the help of revolutionary technologies and engineering platforms, the retailer can get a deeper chance to understand their customer data, which would ultimately, in turn, lead to valuable business insights.