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The ‘New’ Personalization: Why and How Today’s Businesses Must Deliver Predictive, Real-Time Customer Experiences

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For retailers, marketplaces are the new shop window. And today’s brands have moments — not minutes — to attract, engage with and retain a potential customer before the buying window closes.

Half of all global ecommerce sales occur on digital marketplaces, and consumers come to  online marketplaces seeking a solution — not a specific brand. In fact, nearly 90% of Amazon product views come from search rather than branded ads or merchandising. This behavior played out during the pandemic, when shoppers searched online for everything from food delivery options and groceries to hand sanitizer and wearable face masks. COVID-19 accelerated the adoption of digital technologies by several years — indeed, it has been reported that 10 years’ worth of ecommerce progress was made in the span of three months during 2020 alone.

When a consumer finds and lands on your company’s site, how do you turn this visitor from a browser into a paying customer — and how do you do this as quickly as possible? 

Most companies today rely on traditional personalization, which is fueled by a company’s current product catalog and customer profile information, developed over three months or so of interaction on the site. 

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The problem is that this type of website coupled with an outdated customer profile (which can take months to build) and traditional customer “personalization” is simply not cutting it. Customers want you to know and surface what they want; they do not want to go foraging across a website searching for the “thing” they’re seeking. Companies must engage with, win and convert site browsers to customers in real time — yet many retailers are unable to achieve this today.

Retailers are tasked with anticipating a shopper’s intent, predicting what product or service they want and then serving up the most relevant product recommendations, offers or suggestions. Yet these companies struggle to convert site visitors to customers. Take my recent attempt to buy printer paper for my husband’s home office. During my online search, I received random results, including several for “one ream” only. If a retailer could have quickly identified me as a small business/home office user on my first visit and presented me with a small business offer for 10 reams, I would have bought. I abandoned my shopping cart and the retailer lost the business.

Personalization matters to today’s shoppers — and it matters a lot. In a recent survey, 42% of respondents said that it was “very important” or “somewhat important” to see personalized content, such as recommendations or offers during their visit. However, retailers are working with a dearth of explicit or implicit information on their potential customers, making “personalization” a challenge.

Additionally, retailers face significant roadblocks when working to evolve their personalization strategy: 42% report an inability to track targeted customers through their entire journey, 35% find it difficult to attribute marketing performance to individual campaigns or channels, 32% struggle with creating a single view of the customer with other marketing channels and 26% grapple with managing data quality or an inconsistent level of data quality across various sources.

Meanwhile, customers expect a buying experience that is tailored to them, from pre-purchase to ordering and beyond. Real-time search results are only the beginning; the customer wants a dynamic, relevant and personalized experience.

This expectation intensified during COVID, and brands must now predict customer intent and quickly understand their preferences in moments. When I first arrive on a website and as I interact with it, the site should dynamically change with each move I make. Behind the scenes, machine learning algorithms should work to anticipate my next “ask” based on my actions, even if it’s from a cold start because I’m a first-time or infrequent visitor.

This predictive, real-time, digital experience is what enables retailers to demonstrate a better understanding of customers, improving the customer experience and satisfaction and ultimately earning loyalty in the process. Especially when you think of the types of businesses that serve multiple diverse personas (e.g. one customer I was talking with recently served consumers, small businesses and teachers, all of whom have different needs).

Today’s technology was not built to instantly give shoppers exactly what they want on their first site visit or after their first search. But tomorrow’s predictive retailer websites, which will power the “new personalization,” will. This new personalization envelops a predictive, dynamic digital experience that offers customers relevant recommendations, suggestions and search results based simply on what they are searching for — all in real time. And, according to McKinsey,  this personalization has the potential to create $1.7 trillion to $3 trillion in new value.

Real-time artificial intelligence (AI) is what will drive this new personalization — standard machine learning modeling won’t suffice. Traditional AI is complex to integrate within your existing technology stack and requires a team of data scientists. Also, retailers have difficulty measuring the value their business derives from one-size-fits-all AI.

Retailers will benefit most from AI models as a service that enable them to optimize conversion and drive personalization from the moment a shopper first visits their site. In this case, a retailer can select an applicable AI model (say for a cold start scenario), connect existing data sources and then trigger real-time predictive actions.

Retailers that implement AI models as a service will be able to deliver real-time predictive, dynamic customer experiences while increasing conversion rates with existing resources. This real-time personalization is critical to powering omnichannel and cross-channel shopping environments. Customers will expect retailers to anticipate their needs in real time and provide real-time personalized recommendations while also respecting their privacy.

The new AI-powered personalization will empower retailers to surface the right offer at the right time to the right shopper. The post-pandemic consumer expects nothing less, and only those businesses that focus on evolving their personalization efforts (both from a technology and customer POV) will convert first-time visitors to loyal customers quickly before the window of opportunity closes.


Bernadette Nixon is CEO of Algolia. She is an entrepreneurial and driven CEO with a strong track record of growing and scaling global businesses and is focused on doing that at Algolia. Prior to Algolia, she served as CEO at Alfresco, where she led the open source content services provider in redefining its go-to-market strategy, launching strategic new products and building a world class team to scale the company’s growth. Nixon has also held leadership positions at SDL PLC., OpenText, Metastorm, CA Technologies, InterQuad, NCR and the United Nations in Geneva. She received her BA in Business Studies and Marketing from the University of Hertfordshire.

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