Kristen Indihar, Marketing Associate, UpSellit
Consumers hold all the power in the world of e-commerce. Marketers celebrate every piece of data, knowing it’s the key to better understanding their shoppers, and they’re coupling that data with AI to unlock and provide powerful insights about customers.
AI uses human-like understanding to problem solve and execute results on a level that’s unmatched by any technology seen before. In a 2020 global AI survey, 43% of respondents predicted artificial intelligence would transform their workplace in the next few years, and the global AI market is expected to reach more than half a trillion U.S. dollars by 2024.
The insights AI helps create also means extra time for e-commerce teams to focus on other initiatives, meaning spending and resources can be strategically allocated. Leaning on technology also ensures that incoming results are increasingly data-backed, opening up more avenues to increase revenue.
The emerging imperative for hyper-personalization and AI-driven experiences
There’s a direct correlation between marketing with personalization tactics and increasing e-commerce revenue. For example, 63% of marketers report an increase in conversion rates due to personalization. And while personalized tactics make an impact, hyper-personalization is quickly becoming the new standard for e-commerce brands.
Static personalization looks at basic data, such as a customer’s name or location, to present special messaging. At the same time, AI provides a hyper-personalized experience by analyzing page views, browsing patterns and other significant behaviors from each website visitor.
These analyzed behaviors provide insight into abandonment tactics, dynamic product recommendations, email remarketing and additional strategies that incorporate extremely specific messaging for the user. As more and more e-commerce brands add AI to their toolkits, hyper-personalization is increasingly part of the baseline tactics for staying competitive.
AI and the customer experience: Taking the guesswork out of experimentation
Customers’ needs are ever-changing, and it isn’t easy to feel confident in a strategy without the power of something like AI to optimize it consistently. Without insights from AI, the risk is that hidden gaps will work their way into marketing strategies, or at minimum, brands will miss out on opportunities to heighten the customer experience.
No matter the industry, there’s often some form of distraction that can lead shoppers astray during their session. AI’s deep understanding of multiple datasets provides invaluable testing and optimizing variables, helping to determine the most impactful strategy and mitigate those distractions.
When implementing new campaigns, AI also helps guide shoppers to the messaging most relevant to their journeys in real-time. If technology decides the user is abandoning a purchase, AI can determine whether an incentive will give them a push. When shoppers seem hesitant about price, machine-learning algorithms can present them with product alternatives that will convert them.
AI doesn’t just lend itself to backend development but can shape the entire front-end customer journey in a seamless, impactful way. Marketing teams can tailor online strategies to fit the mold of a company’s goals, and AI will follow along with precision.
AI and multivariate testing
In an example from the fashion industry, AI is predicted to amount to $4.4 billion by 2027. A significant role AI plays for fashion brands is using multivariate testing with product recommendations. Multivariate testing views each shopper as they are — individual people with individual needs. Therefore, dynamic product recommendations have become a popular strategy to increase AOV and improve the customer experience.
Using hyper-personalized, dynamic product recommendations based on shoppers’ browsing patterns creates a unique customer journey. AI looks at page views, wish lists and other personalized information to present the shopper with items that round out their purchases with complete looks and sets.
Dynamic recommendations provide a personal touch experience by recommending products that visitors may have otherwise missed. For example, one AI-driven recommendation engine proved the impact of suggestion as part of the buyer journey with proven uplifts of $762,000 in 30 days.
The key is to deliver personalized recommendations throughout the funnel to fulfill each shopper’s individual needs. In-page suggestions assist shoppers earlier in the buyer journey, while mini cart recommendations highlight complementary items that make easy add ons. Out-of-stock recommendations generate solutions for inventory concerns by leveraging similar in-stock items that move shoppers back to checkout. Each tactic fulfills a specific need to create a well-rounded strategy.
AI provides continuous data that brands can use to gather results from one area of testing and experimentation to then apply to other parts of the funnel. AI is a form of technology that goes beyond one intended purpose and takes on many forms, from front-end engagement to back-end sophistication.
It’s a win-win when leaning on AI — the shopper knows brands are listening while brands experience uplifts in customer loyalty and incremental revenue.
Strengthening AI through partnerships for the future of online shopping
Customers must be the main focus. Once brands understand their shoppers and give them a hyper-personalized experience, they’ll be customers for life.
With AI technology often reliant on partnerships, it’s important to identify strong partners.
For example, in a 2021 internal retailer survey, 70% of UpSellit’s retailer partners revealed they chose to rely on a conversion optimization agency because they didn’t have the development resources for internal testing and ongoing experimentation.
It is critical to select a partner with insightful data to enhance conversion strategies without the company exhausting its own time. And a partner that offers resources to monitor analytics and growth adds clear lines of communication and eliminates any doubts on performance.
Communicating expectations and goals at the start is also important. A strategy call is a perfect step to discuss objectives and collaborate as a team, setting up a partnership for success and establishing trust for long-term success.
Through the power of AI, newfound insights will open the doors to a streamlined customer journey, fine-tuned strategies, increased conversions and online revenue success stories for years to come.
Sponsored By: Upsellit