Everyone has AI on the brain due to ChatGPT and other applications of AI in everyday commerce, such as in fast-food drive-thrus. These breakthroughs have obvious implications in the realm of content creation, but it’s unclear just how much generative AI will affect e-commerce marketing as a whole.
But AI has been changing marketing for years in ways that are getting less attention than generative AI-driven content and image creation. For example, the realm of data analytics has been transforming as AI allows e-commerce brands to not only crunch more data but also project future marketing performance. When it comes to analytics, AI and ML are already having a critical impact on e-commerce marketing.
To get beyond the hype and see how AI is really affecting e-commerce today, let’s explore the different areas of AI innovations in e-commerce and assess how AI can help companies bolster marketing.
AI has been offering day-to-day conveniences for e-commerce brands and their customers for some time now
If you’re a scaling e-commerce brand, the odds are high that you currently use plenty of AI-driven products and services to streamline certain business processes. You may have a customer service chatbot that quickly addresses customer concerns, or perhaps your website uses personalized product recommendations to highlight goods that your customer may be interested in based on browsing and buying history. Simple conveniences like these are likely why 62 percent of customers say they’re willing to use AI to improve their experiences.
Many e-commerce companies have also been taking advantage of solutions to operational tasks like inventory management and fraud detection that used to require hours or even days of manual processing and analysis. Once seen as the cutting edge of AI and automation, these services are a no-brainer now, as they allow companies to delegate mundane and time-consuming tasks to automated services—and instead focus on the finer high-order points of successfully scaling an e-commerce company.
Analytics is where AI is most deeply impacting online brands
Automated solutions are valuable when it comes to making your customers’ experience more user-friendly and offloading certain time-consuming tasks, but the most critical advantages of AI come in the realm of marketing analytics. This has been a focal point for companies developing e-commerce-oriented AI solutions.
Not only do these solutions allow e-commerce companies to save time that would be otherwise spent collecting and analyzing the data, but they also detect patterns and generate insights not immediately apparent to human analysts. These capabilities include the following:
Churn Management
Using AI, e-commerce brands can better manage churn by identifying the customers who are at risk of leaving and enacting proactive measures to retain them. AI-powered algorithms can analyze data related to customer behavior (like purchase history, browsing history, and engagement with marketing campaigns) to identify patterns and predict churn. E-commerce brands can then use this information to take targeted actions, such as offering personalized incentives to retain these customers.
Customer Segmentation
AI helps e-commerce brands with customer segmentation by identifying distinct customer segments based on their behavior, preferences, and demographics. Once these segments are identified, the company can create personalized marketing campaigns that cater to the needs and preferences of each segment (or cohort).
Marketing Attribution
Marketing attribution allows companies to analyze data from multiple channels and touchpoints to provide comprehensive insights into the efficacy of various marketing efforts. AI can help e-commerce brands understand how a customer arrived at your product or service and what steps led to their decision to purchase (or “convert”). This allows companies to optimize their marketing strategies and better allocate their resources for maximum impact and return on ad spend (ROAS).
Beyond just understanding past performance, AI and ML can help e-commerce companies look forward
Many of the e-commerce marketing solutions that AI is helping with are focused on understanding past performance. They help you gather and analyze data on customer behavior, product performance, and marketing efficiency.
But even with AI strengthening its efficacy, these solutions may not be enough on their own for companies looking to harness the technology’s full potential and offerings. E-commerce brands need to know what to do with the information once they have it, and recommendations and predictions should be just as accurate and comprehensive as the analysis informing them.
AI and machine learning (ML) are transforming predictive analytics in e-commerce by enabling businesses to make data-driven decisions, optimize their strategies, and deliver personalized experiences that drive engagement, loyalty, and revenue. AI and ML currently offer predictive capabilities such as:
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Customer Lifetime Value (CLV): AI and ML algorithms can analyze customer data to predict how much a customer is likely to spend over the course of their relationship with a business.
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Future Revenue: AI and ML can also be used to analyze historical sales data and identify trends that can be used to predict future sales. This allows e-commerce companies to plan inventory, staffing, and marketing campaigns based on predicted sales volume.
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Probability of Purchase: This analyzes the behavior of users on a site based on the channels they used and the purchase outcomes for these visitors. It indicates the likelihood that a customer will make an initial or subsequent purchase on your site using a given marketing channel.
Scaling e-commerce businesses have likely experienced success by keeping up with—and adopting—the latest offerings in AI-driven commerce technology, whether that be customer service tools like chatbots or analytics tools like emerging ML-driven marketing attribution platforms.
However, keeping up with the latest AI-driven e-commerce solutions means recognizing the importance of e-commerce-specific marketing solutions that not only collect and analyze data, but also use that data to make predictions and recommendations. ChatGPT may be stealing headlines, but analytics, and analytics-driven projections and recommendations, are where the heft of AI’s impact on e-commerce marketing lies.
Phil Dubois is the CEO and co-founder of AdAmplify, a provider of the next generation of marketing attribution software. Used by online stores, AdAmplify’s software shows which channels and campaigns are working, which aren’t, and where there’s opportunity for growth. Driven by machine learning (ML), Dimensions highlights trends, interprets results, and projects the future revenue potential of a store’s marketing channels.
