Search & Discovery Writer
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If you’ve ever been addressed this way in an email, you know that nothing feels less personal and warm than badly implemented (or blatantly missing) personalization.
And it’s safe to say that the impact of poor personalization has only grown more noticeable since the start of the COVID-19 pandemic, as more people have gone online to buy things on companies’ websites (and mobile apps) and inadvertently ended up comparing their lackluster digital shopping experiences with those they’ve enjoyed with Amazon or Google.
Personalization no longer means just basic cookie tracking or the automation of inserting someone’s name at the top of a marketing pitch. Now it means tailoring the entire online experience to the visitor. A personalization platform could encompass everything from greeting people at the digital door to sending them away thrilled by the delightful (if expensive) adventure they just enjoyed.
Consumers now consider anything less than highly personalized service subpar. They’ve grown used to streamlined omnichannel marketing techniques, shortened buying processes, invitations to interact with businesses through apps and chatbots, and instant responses to their questions.
How much have people’s expectations about personalized digital experiences increased in the past few years? A lot. Thanks to services such as Amazon’s product recommendations and Google’s ever-changing search algorithm, online shoppers often cite personalization as an important priority when they’re making a purchase.
In fact, even back in 2018, as documented by Accenture, the vast majority (91%) of 8,000 consumers worldwide said they were more likely to shop with brands that provide personalized offers and recommendations. And that was way before the pandemic seemed to unify large swaths of the population in their desire to set off on online shopping expeditions.
How can companies looking to succeed in this substantially transformed marketing environment win at personalization?
The first-choice solution is clearly to provide users with a digital experience tailored to their needs by using a personalization engine.
Technically speaking, a personalization “engine” is just a type of software component that provides specific search results for specific users. It applies digital behavioral context about people to content so that it can then show people more-relevant results.
For example, let’s say two shoppers on a sporting goods website both enter “cleats” in the search bar.
Without a personalization engine, the site might gloss over specific user behavior and show them both some of the most-purchased cleats and cleat-related items.
However, let’s assume Shopper A has earlier been checking out shin guards and soccer jerseys. Hmm…it’s likely she’s looking for soccer cleats. Meanwhile, Shopper B has been looking at cycling equipment, so he’s probably wanting cleats for clip-in cycling shoes. These two types of cleat have different purposes, yet they both appear in the two shoppers’ search results for cleats.
When it comes to the customer journey, a personalization engine rises above a standard search engine by noting Shopper A’s previous searches for soccer-related items and categorizing her behavior with that of other people who viewed or bought similar items. It observes the customer behavior and presents something more relevant (soccer cleats) in the individual’s search results.
Meanwhile, Shopper B is put in a different category, one for people who’ve viewed or bought cycling equipment. The result? Both of these athletes are happy to quickly find their cleats and move on to the next item on their list.
Gartner defines personalization software as a program that can “apply context about individual users and their circumstances to select, tailor, and deliver messaging such as content, offers, and other interactions through digital channels in support of three use cases — marketing, digital commerce, and customer experience.”
So basically, software powered by artificial intelligence that’s focused on identifying trends in consumers’ behavior, and then, based on the data collected, showing people search results that should best align with their intent.
A personalization engine works in a similar way to the way a regular search engine functions: it uses an algorithm to understand users’ requests and finds relevant content based on their search queries. However, a personalization engine differs in the way it “decides” which items to present to the user.
Before the visitor may even get to the search bar, as they perhaps move around the site, they are watched; their behavior is monitored and details are noted about what they do. It’s spying per se but the data is anonymous; the person is tagged as user3331, for example. Data is also collected based on the search queries they enter. This collection of data is then used to categorize the person’s behavior and intent so that the site can show them more-relevant items.
Personalization tools can also be used to create more-personalized experiences at other digital touchpoints, such as at checkout, when the person may be open to considering related add-ons.
You can see great examples of how an effective personalization engine works on YouTube and Netflix to enhance customer satisfaction through user segmentation.
These platforms both use personalization to suggest viewing options based on the customer profiles of other viewers who’ve watched similar shows and videos. Their customer data platforms match users’ viewing patterns with those similar to theirs and then recommend content that the others have watched.
This approach makes it more likely that people will find something they want to watch, that they will enjoy watching it, and that they will thereby stay on the site longer (and often chuckle fondly about how well the site “knows” them).
Despite the fact that consumers are, for all intents and purposes, madly in love with being personally wooed, many companies’ online enterprises still have yet to nail the nitty-gritty of personalization. Most aren’t at the expertise level of Amazon (yet, anyway), which uses “deep” personalization (a less-marketing-focused approach), for instance, to put relevant product suggestions in front of customers in real time. But companies would sure like to emulate Amazon’s merchandisers’ practices.
And some do get close. Many popular brands are using sophisticated machine-learning personalization techniques as part of their marketing campaigns to provide the right search results to their customers.
This intriguing technology was already starting to become standard before the pandemic, but in the huge digital transformation and shift to higher levels of dependence on technology that occurred between 2019 and 2021, personalization has emerged as an absolute necessity. While a personalization engine was a nice-to-have before the start of the pandemic, now it’s simply a requirement for keeping up with the ever-advancing benchmark of digital transformation.
So how can you get started creating rewarding, personalized experiences for your online users?
The rewards could be well worth jumping into the personalization pool. According to Adweek, marketers say personalization can raise revenue by up to 15% and reduce acquisition costs by 50%.
However, some marketing teams need more help to get their personalization efforts off the ground. Gartner notes that roughly 63% of digital marketing leaders admit they’re struggling to provide personalization. Which can be a real problem that not only doesn’t impress prospective customers but patently turns them off, just like the first crazy line of this blog post. Not good for customer retention.
Fortunately there are great personalization software solutions out there that encompass all of this good stuff. What many businesses desperately need is a search API that’s fast, informative, and relevant for customers, comes with analytics and customization, and is easy for companies to use. Algolia is one option, with a whole library full of clients who are happy to testify to the effectiveness of their personalized search.
For instance, Decathlon Singapore uses Algolia personalization to handle a vast number of products and deliver an experience tailored to individual customers. According to its ecommerce project leader, Richard Migette, “For a retailer like us with more than 25,000 products in our catalog, a solution that improves each of our users’ experiences along their search journey adds tremendous value.”
To find out more about the prospective power of personalization for customer engagement on your site and the many ways that giving visitors great digital experiences can help you optimize for success, increase your conversion rate, and more, contact our team for some personalized attention.
Sr. SEO Web Digital Marketing Manager