How can AI make ecommerce more personalized?

Every entrepreneur looking to stay competitive in their niche has to bust out all the stops to make their product or service stand out. When it comes to improving lead generation and differentiating your business from the competition, personalizing your customer experience is the least you can do.

According to research, 80% of consumers prefer brands that deliver personalized experiences. [1] This shows just how important personalization is to both customers and brands. While there are enterprise tools that can help with personalization, you need to reinvent how you deal with your customers to make it big in eCommerce. This is where AI comes in.

Read on to learn some of the powerful and practical ways that retail businesses use AI to give their customers a touch of personalization.

What personalization in e-commerce is all about?

Personalization is about delivering customers’ unique shopping experiences based on commerce data. [2] Commerce data is an umbrella term for both customer and product data. Customer data refers to transactional, behavioral, demographic, and personal data from customers. At the same time, product data is information about a product. It’s readable, quantifiable, and structured in an exploitable format. Examples include product titles, images, and categories.

Both customer data and product data go hand in hand. When combined, the retailer can better understand the customer, after which they can guide and captivate them with tailored shopping experiences.

Personalization occurs in various forms:

• Personalized product suggestions on the brand’s homepage
• A hand-written gift card for first-time buyers
• Exclusive discounts for cart abandonment
• Personalized marketing emails
• Onboarding quizzes that offer a tailored product line to consumers

Learn more about The role of artificial intelligence in eCommerce

The role of AI in personalization

Artificial intelligence technologies are shifting the way businesses interact with customers. Below are 6 ways in which AI is making commerce more personalized:

Personalized product recommendations

As a business, you want to make more sales from your existing customers. That’s because an existing customer is more likely to order more than a new customer. AI-driven personalized product suggestions can help you achieve that.

When existing customers browse your website, AI-based algorithms get into action and analyze their browsing patterns, past transactions, interests, demographic, and other such data. Based on the data, the website then presents customers with content that would appeal to them the most. This increases the odds of spending more than they had planned.

Picture yourself as a customer to understand this concept. Assume you’ve been searching for a new suit in a clothing store, and finally, you find what you like. Soon after, the web page suggests some nice shoes to match the suit. You’re convinced the shoes are a perfect match for your preferred suit.

This entire process introduces the thought of buying both items from the same shop, which would be quite convenient. So you end up ordering the shoes along with the suit.

This is what the modern shopper expects when they go online to shop. In fact, according to research, 91% of customers say that they are more likely to order from brands that present relevant product recommendations and offers to them. [3]

Cross-device personalization

The modern consumer uses different devices when interacting with a brand. They may begin their product search on their smartphone and finish by making an order through their laptop or vice versa. Thus, consumer data becomes siloed or fragmented across several devices.

These siloed data sources present a problem for retailers to crack. It’s said that 30.9% of retailers cannot track consumers across many devices, and 38.2% can only track consumers for a limited time. [4] Thus, businesses find it difficult to personalize experiences across multiple devices or channels.

Fortunately, AI-driven personalization takes a multi-channel approach. In other words, AI technologies sit on top of several customer touchpoints such as websites, mobile applications, social media, or email campaigns. They track the consumer’s interaction across all these platforms and create a unified customer profile. This single consumer view helps retailers personalize their offerings across different devices and channels.

Conversational commerce

Conversational commerce leverages conversations between brands and clients via messaging and chat apps, such as WhatsApp, Facebook Messenger, Instagram, and Twitter, to offer personalized shopping experiences.

Consumers often prefer to avoid the canned responses from standard robots. That’s why conversational AI-driven personalization solutions are designed to feel human-like. In fact, users won’t even distinguish whether they’re talking to a live agent or a chatbot.

Conversational AI uses technologies such as machine learning (ML) and natural language processing (NLP) to study the way humans speak. It then aims to understand user intent before generating personalized responses to users. The responses stem from user conversations and are not limited to a script.

Meeting customers on chat apps where they love to hang out is important. This is because it provides an open and direct line of communication between businesses and their customers, enabling them to guide customers at every step of their purchase journey. Customers also enjoy individualized recommendations and customer support and can even buy merchandise from within these messaging apps. Apple’s Siri and Amazon’s Alexa are popular virtual personal voice assistants powered by AI.

Push notifications

Mobile internet access has surged in recent years, with 80% of all internet users owning smartphones [5] and 50% of smartphone users reaching for their phones first thing when they wake up[6].

The increasing mobile internet users and decreasing email open rates [7] present a new opportunity for businesses- they can leverage mobile marketing to pass their messages across with the help of push notifications.

Like SMS text messages, push notifications go directly to the smartphone user- they don’t get trapped in spam filters. And as a result, have an opening rate of 90%, which is twice as high as email marketing. [8]

Push notifications could be used with:

• Individualized product recommendations
• Exclusive discounts
• Proximity alerts
• Invitations
• Social media pages

However, not everybody is fond of push notifications as some are spammy – this is where AI comes in. AI-driven personalization technologies can analyze when customers click on push notifications and deduce what content interests them. This allows brands to segment users in a very personalized way based on their interests.

For example, a clothing brand may send out different push notifications to users. They can base the pushes on users’ browsing history and purchase history. The idea is to create personalized and fitting messages based on the needs and expectations of every user. By doing so, push notifications no longer become an inconvenience.

Targeted marketing

Unlike traditional marketing where adverts are sent out to a broad audience, targeted marketing creates a buyer persona from the user’s browsing pattern and interests, which is then used to recommend products according to what the intended audience actually wants.

According to a survey, consumers were asked to choose between random online ads or targeted advertisements. Over 40% of consumers chose targeted ads, while 27.6% said they preferred either. [9] This may explain why behaviorally targeted advertisements improve open rate by 2x, and click through rate by 5x.[10]

AI-enabled targeted marketing wades through huge volumes of data to offer detailed customer segmentation. This allows you to tailor your marketing content — ad messages, blogs, and videos —to reach customers who are more likely to take the desired action.

Here are three primary ways to segment audiences and target them with impactful ads:

• Demographic segmentation: Age, Marital Status, Religious Affiliation, Income level, Race, and Gender.
• Geographic segmentation: Country, State, City, Area Code, and Zip Code.
• Psychographic segmentation: Social class, Beliefs, Values, and Interests.

Site search personalization

The modern consumer is tech-savvy and already has a good idea about what they’re looking for. According to research, 43% of visitors will use your website’s search box to find a specific product, [11] which presents the opportunity to provide a personalized site search.

AI-powered personalized search leverages each user’s unique profile to come up with relevant product suggestions. It considers metadata such as:

• Past search history
• Brand preferences
• Purchase history
• Product ratings
• Browser location (country, region, zip code)
• Time of day
• Gender
• Query

The search results must be relevant to the user’s intent, which requires query understanding.

AI-powered personalization site search solutions use a series of techniques to work out the meaning of a user query. These include:

• Natural Language Processing (NLP)
• Semantic query understanding
• Word embeddings
• Query segmentation
• Vectorization
• Scoping

Spelling errors often present a problem for most sites. About 10-25% of search queries have misspellings. [12] But AI-powered optimized search deploys NLP to figure out the nuances of human language and display relevant search results.
The AI-powered personalization optimized search could, for example, figure out that “runner’s shoes” and “running shoes” share a similar meaning and will display properly spelled results. This reduces the bounce rate and increases the likelihood of the user adding the product to their cart.

Final thoughts

Business personalization aims to understand every customer at an individual level and devise a data-driven strategy that makes customers feel a personal touch when engaging with your brand.

That being said, the data you need to make commerce more personalized is embedded within various touch points where you interact with your customers. These include your website, mobile apps, social media, and other platforms. AI makes life even easier by processing large volumes of commerce data and creating unique buyer personas or profiles.

Hence, you can directly address the consumer instead of generalizing target audiences. This paves the way for consistent, tailored experiences at every consumer interaction. Ultimately, it improves customer loyalty, leading to better sales. See more about AI consulting services.

References

[1] Epsilon.com. 80% of Consumers are More Likely to Make a Purchase When Brands Offer Personalized Experiences. URL: https://bit.ly/3Uz58LP. Accessed November 7, 2022
[2] Bloomreach.com. What is Commerce data and Why is it Important to Ecommerce Personalization. URL:  https://www.bloomreach.com/en/blog/2022/what-is-commerce-data-and-why-is-it-important-to-e-commerce-personalization. Accessed November 7, 2022
[3] Accenture.com. Accenture Pulse Survey. URL: https://accntu.re/3he24Wm. Accessed November 7, 2022
[4] Digitalcommerce360.com. Marketers Waste 21% of Their Marketing Budgets Because of Bad Data. URL:  https://bit.ly/3WK7k4n. Accessed November 7, 2022
[5] Smartinsights.com. Mobile Marketing Analytics. URL:  https://www.smartinsights.com/mobile-marketing/mobile-marketing-analytics/mobile-marketing-statistics/. Accessed November 7, 2022
[6] Expresspigeon.com. Email Marketing Statistics. URL: https://expresspigeon.com/email-marketing-statistics/. Accessed November 7, 2022
[7] Blogmarketingacademy. Email Open Rates. URL: https://www.blogmarketingacademy.com/email-open-rates/. Accessed November 7, 2022
[8] Blog.e-goi.com. Infographic Push Notification. URL: https://blog.e-goi.com/infographic-push-notification/. Accessed November 7, 2022
[9] Greinsmedia.com. Digital and Targeted Advertising Statistics. URL: https://www.grenismedia.com/blog/45-digital-and-targeted-advertising-statistics/. Accessed November 7, 2022
[10] Convertrank.com. Buyer Persona. URL: https://convertrank.com/buyer-persona/. Accessed November 7, 2022
[11] Forrester.com. Must-have ECommerce Features. URL: https://www.forrester.com/report/MustHave-eCommerce-Features/RES89561. Accessed November 7, 2022
[12] Linguistics.stackexchange.com. What Percentage of Words or Queries are Misspelled in Search Queries. URL:  https://bit.ly/3hmk4xW. Accessed November 7, 2022