If one had to explain e-commerce personalization in simple terms, here’s how one would do it:

Imagine you walk into a physical brick-and-mortar store; what impresses you the most?

How the store engages you and treats you like you are their most special customer, right? 

If you get what you are looking for, easily and quickly, without searching for it, then you’re likely to walk out with a satisfactory shopping experience. 

Suppose the proprietor or the salesperson can quickly understand your individual needs, expectations, and preferences – and shows your products based on your likes and, thus, helps you save both time and effort. Wouldn’t you revisit the store?

Well, that’s exactly what online customers look for – An end-to-end personalized shopping experience that’s tailor-made only for them. They expect e-commerce brands to understand the needs and preferences that are unique to them. And, that’s a sure-shot way for brands to keep new customers engaged and existing customers coming back to purchase more and more.

In fact, on average, more than 50% of online retail users:

1. Find more interesting products on a personalized online retail store

2. Are more likely to return to a website that offers personalized product recommendations

3. Believe that retailers who personalize the shopping experience provide a valuable service

4. Prefer to shop on a website that offers relevant recommendations

Suffice to say e-commerce personalization is critical to combat competition, falling customer engagement, and rampant switching behavior. 

In fact, personalization has assumed even greater significance in a post-COVID-19 lockdown era. An era in which customer behavior is evolving on a seemingly weekly basis. An era in which new audiences across demographics and geographies are migrating to online shopping. it is an era in which tech-savvy shoppers can order precisely what they want right off their smart devices, from the comfort and safety of their homes or offices.

These trends have witnessed more significant momentum during the festive and holiday season—a time when e-commerce retail sees an annual cyclical jump in sales and revenues.

What are the Challenges for E-Commerce Marketers?

1. Rising Customer Acquisition Costs: Marketers and brands are spending almost 25-30% of their marketing budget on acquiring new customers through a mix of paid and organic efforts. This makes customer engagement and retention even more critical

2. High Cart Abandonment Rates: According to Statista, the global online shopping cart abandonment rate was a whopping 69.57% in 2019. Moreover, in my conversations with e-commerce marketers, almost 98% of users leave the website or mobile app without making a single transaction. That’s a lot of wasted marketing dollars and effort in driving relevant traffic to your website or app downloads for nothing

3. Rising Competition: In the highly competitive and price-sensitive market today, it is extremely difficult to build platform stickiness. Customers either don’t come back enough or may easily switch to another competitor offering better value for time, effort, and money.

How Can AI-led Personalization Help?

As mentioned earlier, the most effective way to acquire, engage and retain your customers is to offer them personalized experiences that are consistent and memorable. 

And to make this happen, you need to leverage two incredibly powerful weapons in your marketing arsenal – large amounts of customer data and AI algorithms that feed on this data to help you deliver hyper-personalized customer experiences.

The surest way to deliver customer delight is by delivering relevant and contextual product recommendations across every digital touchpoint of the user journey, starting with your website.

Here’s how a solid personalization strategy can gain momentum for e-commerce platforms:

1. Re-order the Category Page based on individual search, browsing, and purchase behaviour

For any e-commerce platform that operates at scale, there are a large number of products in the product catalog. When visitors can’t find or face difficulty in finding what they are looking for, they leave the website. 

In other cases, they spend a lot of time searching for items that they want, instead of being directed to what they might be interested in, fast.

Using behavioral data insights, AI engines can now predict what the customer might be interested in and can help marketers re-order or re-shuffle the sequence in which the products are displayed. This leads to a 60-80% increase in Click-through Rates (CTRs)

Since the most relevant products are shown at the top, the customers are more likely to add them to their cart or complete a purchase.

For instance: Based on gender, an e-commerce platform can reorder their product categories to show gender-specific clothing categories or based on past/live browsing behaviour, past searches – e-commerce players can reorder the product categories for every individual customer. This helps with instant product discovery and increases the chances of purchase.

1

2. Build a Personalized Boutique for Every Customer:

This kind of customization takes personalization to a whole new level. Going beyond creating a personalized Home Page or a Product Display Page, you can create a unique digital shop or virtual storefront for each and every user.

Curating a personalized boutique requires a powerful AI engine fuelled through reinforced, real-time learning that takes into account what individual customers like and dislike, what they ignore and act upon.

A personalized product boutique page is a specially curated list of products that every customer is most likely to click-on, add-to-cart, or purchase. And, gets refined on each interaction that individual customers have with it. This can actually help e-commerce brands boost Click-through Rates (CTRs) by over 120%. And, why not? It’s like a virtual pop-up store tailor-made to a unique customer!

Not only should a robust AI engine account for what customers “see-and-click”, but also account for what they “see-and-don’t click” and “don’t-see-and-don’t-click”. These are real-time signals that make the AI engine more intelligent and intuitive.

For instance: For an e-commerce platform that specializes in footwear, a college student who has historically purchased sneakers and casual shoes will see a very different personalized boutique versus a corporate professional who is more on the lookout for formal shoes. These recommendations need to be driven by unique preferences and intents as well.

3. Build a Personalized Boutique for Every Customer: 

This kind of customization takes personalization to a whole new level. Going beyond creating a personalized Home Page or a Product Display Page, you can create a unique digital shop or virtual storefront for each and every user. 

Curating a personalized boutique requires a powerful AI engine fuelled through reinforced, real-time learning that takes into account what individual customers like and dislike, what they ignore and act upon.

A personalized product boutique page is a specially curated list of products that every customer is most likely to click-on, add-to-cart, or purchase. And, gets refined on each interaction that individual customers have with it. This can actually help e-commerce brands boost Click-through Rates (CTRs) by over 120%. And, why not? It’s like a virtual pop-up store tailor-made to a unique customer!

Not only should a robust AI engine account for what customers “see-and-click”, but also account for what they “see-and-don’t click” and “don’t-see-and-don’t-click”. These are real-time signals that make the AI engine more intelligent and intuitive.

For instance: For an e-commerce platform that specializes in footwear, a college student who has historically purchased sneakers and casual shoes will see a very different personalized boutique versus a corporate professional who is more on the lookout for formal shoes. These recommendations need to be driven by unique preferences and intents as well.

Personalized boutique for a college student:

third

Personalized boutique for a professional looking for formal shoes:

fourth

4. Deliver contextual recommendations at every step of the customer lifecycle through various channels

E-commerce brands need to extend the concept of personalization beyond their website or mobile app – delivering 1:1 product recommendation at every single stage of the customer lifecycle across channels – even when he/she is not directly acting on the e-commerce platform.

In such a scenario, a high-conversion multi-channel mix including email, app push notifications, social media ads, etc. to continue delivering tailor-made product recommendations is a must. 

This approach helps accomplish the following:

1. Creating top-of-mind brand recall in an already cluttered market

2. Increasing the probability of bringing customers back to the e-commerce website or mobile app and actually making a purchase

3. Gathering deep-dive insights into customer behavior – through their interactions with such marketing campaigns – to optimize the channel mix for higher ROI

The Bottomline

The world, as we know it, is changing. Customer behavior is evolving. The marketing playbook is being re-written as we speak.

But, one thing that hasn’t changed is the fact that the customer is still king. And, e-commerce brands need to take customer-centricity to another level – bordering on customer-obsession.

And, the onus of that falls fairly and squarely on e-commerce digital/mobile marketing and product experience teams – that need to go beyond the tried-and-tested. They need to communicate and deliver value consistently. They need to individualize the entire customer experience. 

And, with a robust AI engine doing all the heavy-lifting, that pipedream can now be translated into reality, now more than ever. Also, there are far many use cases that AI-led product recommendations can address within the ambit of e-commerce. This is merely the tip of the iceberg!

Of course, adopting AI will not solve all e-commerce growth challenges. It’s merely a vital cog in the larger wheel of personalized customer experience delivery! 

Pradyut Hande

A B2B SaaS Marketer, Mobile Growth Consultant, Guest Speaker, Podcaster, and Author, Pradyut currently leads Product Marketing at Netcore Solutions, a leading marketing technology company. He has been featured in the list of “100 Most Innovative Martech Leaders, 2019” by the World Marketing Congress. His guest articles have been featured in leading industry publications such as HackerNoon, YourStory, and The Economic Times.

Posted in Guest Articles By Pradyut Hande   Date November 16, 2020

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