E-commerce sellers are used to gauging site analytics and sales reports to try and predict the very elements customers most prefer. Here are just some of the myriad ways AI can make your life easier by telling you all you need to know about your consumer base.
E-commerce merchants are always searching for ways to learn more about their audience. You might find yourself wondering which products your customers crave most? Other questions might include:
- What prices are your customers most likely to buy at?
- What inventory is necessary to satisfy your consumer base?
- Most importantly, how should you run your business to improve efficiency and maximize revenue potential?
AI can help. Artificial intelligence technology employs deep-learning algorithms that analyze data on a massive scale. These tools can give e-commerce prospects what they want, when they want it; and are always learning, all the time.
AI and Consumer Insights: The Amazing Power of Predictive Learning Technology
Search Intent: Tools like Visii’s Explore take into account a prospect’s search history, purchase history, interactions with your platform, geolocation, and even data gleaned from the user’s social profiles to piece together a personalized journey based on the customer’s preferences and predict future purchases. The algorithms employed help to eliminate false search results and ensure your audience always finds exactly what they’re looking for, in turn pushing the items they are interested to them while eliminating search fatigue and cart abandonment.
Customer Preferences: Product recommendations are getting increasingly smarter and more relevant thanks to AI, as we can see with e-store giants like Amazon and Alibaba. Using deep-learning algorithms, these tools take notes and provide personalized suggestions with every new action a shopper takes and also track the movements of their typical audience. Better recommendations help to develop loyal customers and increase sales , which is why AI technology like Similar, a tool that generates on the fly product recommendations by analyzing the features and content of a e-store’s images and which most appeal to their audience base, is a necessity for ambitious e-store owners.
Buyer Intent: 33% of marketing leads aren’t followed up by a sales team, according to a recent report. AI systems like Mintigo take data from marketing, sales, and CRM platforms to readily mark those customers most likely to make a purchase. Pre-qualified buyers can then be shown personalized and dynamic ads that will bring them back to your platform and entice them to click-to-buy. By knowing what type of customer is most likely to buy certain products, or be impacted by certain ads, AI allows e-stores to not only suggest relevant and preferred products but also target certain audience segments with more personalized marketing.
The “Right” Message: Sales teams have always worked to deliver the proper messages to consumers to facilitate the sale. These days, there are so many platforms and buyer’s journey touchpoints that delivering the proper message at just the right time and on the proper platform may seem daunting (especially as the company grows and more consumers are added to the mix).
Sales teams have always worked to deliver the proper messages to consumers to facilitate sales. These days, there are so many platforms and buyer’s journey touchpoints that delivering the proper message at just the right time and on the proper platform may seem daunting (especially as the company grows and more consumers are added to the mix).
IBM’s Watson learns and delivers the very messages consumers need by asking prospects intelligent questions, analyzing real-time consumer input, and conducting its own research to offer just the thing your customers need to complete the checkout.
Personalization Signals: When it comes to delivering key messages to customers, deep-level personalization is paramount. We’re not just talking about using the prospect’s name, purchase history and other obvious signals. Deep-level personalisation, rather, refers to the analysis of how consumers interact with your brand online.
Tools like ZetaHub use this machine-learning analysis to basically follow consumers as they traverse the many touchpoints of the buyer’s journey, from your e-commerce platform to email, social, and beyond. AI can deliver the kind of real-time content your consumers crave (just when they need it, and in the medium they prefer) to keep them on the hook and buying long into the future.
How to Help: Virtual assistants have long been in play by e-commerce store owners, but AI-based VAs deliver far more value.
Siri, Google Now and Alexa have already introduced consumers to the act of speaking directly to their phones, laptops, and even appliances. These systems use natural language processing to act as human-like personal shopping buddies. These systems can truly impact a shopper’s experience by providing further personalisation, real-time support, and superior customer service. What’s truly mind-blowing is that these systems can work on a 1:1 scale, even if they’re working with thousands of consumers at once. Take Alibaba, for instance, which employs AI that processes 175,000 transactions per second!
The “Perfect” Prices: Many of your e-shoppers will balk or buy based on price alone. PerfectPrice is an AI tool that predicts the ideal price-point to entice the maximum amount of sales. The system continuously analyzes competing products and other signals on mass-scale to deliver just the prices customers need to make a positive buying decision.
Revenue Forecasts: AI tools like Clari utilize predictive-learning technology to deliver accurate sales forecasts and risk assessment to help you run your business more efficiently. The system learns over time, so there’s no need to add data to improve its predictions; the system does the learning, programming, and prediction all on its own.
Warehouse Operations: Managing inventory and ensuring no products are lagging behind can become a constant chore for even the most tenured e-commerce store owner.
Deep-learning technology, such as the type offered by Unleashed, tracks and organizes all your important data - from inventory and out-of-stock product notifications to accurate, location-based shipping information - and all on the fly.
Fraud: Not only can AI be used to identify and eradicate fake reviews, but machine-learning tools like Signifyd can identify fraudulent transactions, including false positives, which indicate otherwise legitimate transactions marked as scams. AI continuously learns from every transaction and data point customers make with your platform to keep abreast of any hackers intent on robbing you of your hard-earned revenue.
What do all of these insights mean?
The above means that artificial intelligence is a must-have for e-store owners wishing to offer speed, assurance, accuracy, and a memorable shopping experience. With the right technology, you’ll be able to deliver this kind of streamlined digital shopping trip on every platform and in every instance.
Conclusion
The combination of AI and retail is a match made in heaven, with the alliance predicted to generate over $26.5 billion by 2025. For e-commerce sellers, artificial intelligence allows for a 1:1 transaction per customer, and at any scale. This kind of personalized experience wasn’t possible before, and machine-learning is only getting smarter by the day.
With these insights being revealed at incredible speeds and epic proportions, you now have myriad options for boosting your results and remaining ultra-competitive long into the future. Now is your chance to learn more about your audience and discover just why they might buy from you. Machine-learning can then use that information to keep customers buying and returning for greater revenue and return.
Isn’t it time you put machine-learning and AI to work for your e-commerce business
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