How Fashion & Apparel E-Commerce Brands Can Use Product Recommendations to Increase Revenues – Part 1

Personalization is no longer merely a buzzword for modern-day marketers, like you. It needs to act as the foundation of all your marketing activities, especially in industries like e-commerce, where it acts as the driver of marketing success.

1:1 personalized experiences are what all your customers need and seek. Each customer has a set of unique wants, tastes, attitudes, and preferences. It is critical for you to recognize these unique attributes and activities of each customer and serve up relevant experiences accordingly. 

When customers see products that are tailor-made to suit their requirements, it not only increases the chances of purchase, but it also compels them to come back to your website for more.

This is the start of building a sustainable relationship between your brand and your customers. Making them feel special is not beyond you!

77% of customers have chosen, recommended, or paid more for a brand that provides a personalized customer experience. This indicates that customers are keen on associating with brands that can understand their behavior and offer them a personalized experience at different stages of the customer lifecycle. Most customers are also open to sharing their data, if your brand provides them a seamless end-to-end purchase experience.

Let’s flip the narrative. Put yourself in the shoes of your customers.

As a customer, wouldn’t you love to see an e-commerce platform provide you personalized content or product recommendations when you open their website? 

an e-commerce platform providing its customer personalized product recommendations

The key to customer delight is through delivering a 1:1 omnichannel personalization experience to them. 

COVID-19: The Paradigm Shift in Fashion E-Commerce

Before the global COVID-19 pandemic wreaked havoc on businesses around the world, the online fashion and apparel industry had started performing exceedingly well as customers migrated to buying online.

With everything available readily on the website, it became convenient for customers to make their purchases online through a few clicks on their device. However, like most industries, these fashion brands also had to undergo huge losses due to the pandemic as they saw their sales fall by nearly 70% in March, 2020 alone.

The lockdown restriction and the uncertain economic conditions that prevailed ensured that customers were no longer looking to purchase apparel. Their priorities had evolved. Now as the economic situation has started to pick up again, the likelihood of customers getting back to buying apparel has improved. Given the general air of paranoia though, most customers are unlikely to venture outside to do their shopping at the stores and might instead prefer to shop online to remain safe. 

This situation is playing right into the hands of online fashion brands, as customers resume or start shopping online again.   

  • What can brands do to stay ahead of their competitors and ensure their customers are satisfied with their product offerings and overall customer experience?
  • What would customers shopping online expect from the brands?

The answer to both these questions is Omnichannel Personalization.

Customer Data: The Foundation for Omnichannel Personalization

Omnichannel Personalization aids product discovery. 

Each of your customers has to be treated individually. As a marketer, you need a thorough understanding of the customer’s persona by studying their behavioural patterns, shopping intents, purchase habits, and all other relevant actions and inactions to create a 360o unified customer view.

You need to gather and track the right customer-level data-points to build a solid foundation. Each time a user logs onto your website, the following data-points will help you build a unified customer view:

  • Demographic data: Customer name, age, gender
  • Geolocation data: Place from where the website is accessed, timezone, IP address, etc
  • Device-level data: Device type and model, browser type, OS version, etc
  • Behavioral data: which includes products searched for, viewed, added to cart, or purchased or abandoned. Preferred payment method, response to previous multi-channel marketing campaigns, etc

At Smartech, we enable you to do all that and more. Our AI engine – Raman – also takes into account additional data-points such as clickstream data and customer eyeball data. This means that along with gaining visibility on what customers click and explore, Raman is able to factor in what customers ‘see-and-don’t click’ or ‘don’t-see-and-don’t click’. 

The more the customer-level data-points being leveraged, the higher the degree of personalization.

All these diverse data-points become the foundation for generating the most relevant and contextual product recommendations – deployed through personalized widgets – across different pages of your website. And, as highlighted previously – it is this level of personalization that improves product discovery and the probability of customers clicking on products that are most relevant to them.

Let’s take a look at some solid personalization use cases that fashion e-commerce platforms can leverage:

  1. Target New First-Time Website Visitors with Relevant Discounts or Promo Codes

Imagine a new customer coming to your website for the very first time. This means that you have little to no behavioral data to work with. But, you can leverage other data-points such as geolocation, browser type and version, device, etc.

Based on such data-points, you can offer discounts to such first-time visitors or unregistered customers on certain products. There are few attractive pulls for a new visitor than getting to avail a discount from the first transaction itself. 

If the deal is enticing, the new visitor is likely to register and nudged into making his/her first purchase. This also gives you the chance to gather more data on such a customer – data that can be harnessed to personalize future experiences and interactions with your brand.

A brand offering enticing discount deals to its customers

You can also choose to offer first-time visitors an enticing promo code to encourage first-time purchase on the website. By targeting only new website visitors and not repeat customers with such discounts and offers, you start personalizing their e-commerce experience from the start.

A brand offers first-time visitors an enticing promo code to encourage first-time purchase on the website.
  1. Show Relevant Product Recommendations on the Home Page 

“Never judge a book by its cover”. This is a quote that we hear quite often. However, this is not the case for an ecommerce website’s home page as customers form an opinion of your website based purely on your home page. 

The home page is the face of your website. What better screen real-estate to grab your customers’ attention than the home page itself?

Showcasing relevant product recommendations on the home page can increase CTRs by almost 90-120%.

We also come across the quote- ”First impression is the best impression”’. If this indeed is the case, then why not provide your customers a lasting experience on their very first visit on your website? 

An engaging home page will go a long way towards building a strong image of your brand on your customers’ minds. 

  1. Highlight the Most Contextual Latest Products

New products have a higher chance of selling faster. With the power of AI, Machine Learning algorithms can factor in the most relevant new products that can be shown under the ‘New Arrivals’ personalized widget to customers on your home page.

a brand showing new products under the ‘New Arrivals’ personalized widget on its home page.
  1. Deliver Product Recommendations through Web Push Notifications

When a customer lands on and begins browsing through your website for the first time, you can encourage him/her to opt-in to receive the most relevant offers, discounts, and product recommendations via web push notifications. 

On receiving opt-in, web push notifications offer you another important channel to provide personalized product recommendations through.

Personalized recommendation of a pair of shoes to customer.
  1. Personalize the Navigational Flow of your Website
personalized navigational flow by providing relevant product recommendations

You can also leverage the customer-related data-points such as age, gender, browsing history, etc. to personalize the navigational flow by providing relevant product recommendations based on the tastes and preferences of your customers. 

relevant product recommendation based on customer's past data

Here, Amazon, has analyzed my previous browsing history on the website and understood that I am interested in football. Sensing this interest of mine, it has given relevant product recommendations in the form of football jerseys of the upcoming season.

Now since I had viewed football jerseys during my previous visit on Amazon, but dropped off without buying, it provided me similar suggestions on my next visit on the home page to push me towards completing the purchase. 

  1. Personalize the Product Search Experience

It is important for customers to not only be provided with relevant product suggestions but also for those products to be personalized based on the customer’s interests. If the customer is not getting what he is looking for, there’s a high probability that he might move on to another brand to look for those brands. Therefore, it’s imperative that brands direct their customers to what they want for faster. 

Two customers might be looking for the same product but yet might need to be given different product recommendations. 

2 customers looking for the same product but given different product recommendations.
2 customers looking for the same product but given preferred product recommendations.

Here are two customers looking for casual shirts being shown completely different shirts based on their preferences. The first customer had clearly displayed an interest in checkered shirts during previous browsing sessions while the second customer had shown a preference towards simple, solid shirts. 

Showing the first customer solid shirts or the second customer checkered shirts would defeat the purpose. This is why the AI engine must be robust in discovering these browsing patterns of customers. 

Parting Thoughts

These are some of the most effective personalization use cases that you can deploy for your fashion and apparel e-commerce platform. This though, is just the tip of the iceberg!

1:1 personalization offers you lots of scope to experiment. As it has to be a well-thought out strategy that extends across every single digital touchpoint that your customer encounters.

You can deploy personalized widgets on different webpages and marketing channels, and also leverage the power of omnichannel personalization.

In Part 2 of this blog series, we’ll explore many more fascinating use cases of personalization strategies that fashion and apparel brands adopt. So, watch this space for more!

In the meantime, why not see the magic of personalization for yourself?

To understand how we can help your brand develop and deploy a game-changing personalization strategy, powered by AI, get in touch with us today!  

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