This is Why AI is the Answer to Your E-Commerce Problems
By Pankaj Gaur
Artificial Intelligence (AI) has started slowly embedding itself into all aspect of our life – be it self-checkout kiosks, virtual assistants on web portals, or smart homes – AI is all around us.
With big names like Google, Microsoft, etc. investing heavily in AI and new innovations around it, it is highly anticipated that AI will kick into overdrive in next couple of years. Gartner predicts that by this year, 85% of all customer interactions will be handled by AI.
AI has three key elements:
- Data Mining
- Natural Language Processing (NLP)
- Machine Learning (ML)
These elements help e-commerce businesses improve results. Most of the leading e-commerce businesses are already using AI to better understand their customers and their behaviour, generate new leads, and provide an elevated personalized customer experience for better sales conversions.
Let’s take a close look at how AI can solve 12 common e-commerce issues.
1. Personalized Experience
Personalization is the process of creating customized web experiences tailored to a visitor’s needs.
AI enables you to engage customers with personalized experiences through the sophisticated filtering of your website content, products, promotions, etc. based on the customer’s data, behaviours, and interest.
One example of AI in personalized experiences is product recommendation. This allows relevant, contextual, and specific products based on the customer are presented on the e-commerce portal.
Another example is personalized notifications where profile-based, promotional, or help notifications could be sent to the customer or prospects based on their activities, behaviours, and history.
2. Respect Privacy
When we talk about personalization and consumer data, there is often a concern with user privacy. The implementations of tougher rules and acts like GDPR, CCPA, etc. have highlighted the importance of user privacy and made it stronger than ever. They take transparency regarding the customer data to a new level, however, the brands cannot afford to abandon user personalization and its role in a successful e-commerce business. AI can be a saviour and help bridge the gap between personalization and privacy.
It’s been observed that users are more comfortable sharing their information if there’s reciprocity – they must feel as though they’re receiving something of value in return. i.e. Amazon Alexa. She can interact with users and provide news and information based on interests and behaviours. For such an experience, along with transparency powered by AI, users easily understand the benefit and are happy to share their details.
3. Search Functionality
One of the major functionalities in an e-commerce portal is the search feature. AI can take it to an entirely new level.
Usually, the search performed on e-commerce portals is disappointing and the results shown are often missing the mark. AI can be used to provide an intelligent and customer-centric search experience through natural language processing (NLP) to narrow, contextualize, and improve search results.
Another use of AI in search functionality? Visual search. AI enables customers to click a picture of an item and search for it in an e-commerce portal. The portal can then run a search for the exact same item (or at least similar items and recommendations).
4. Machine Driven Engagement, Assistance, and Support
Whether it is the status of an order or refund or the suggestion of a product for an abstract need of the consumer, consumers today look for convenience and expect immediate resolutions for their issues or queries.
This “conversational commerce” is assisted quite a bit by AI-powered programs like chatbots and virtual assistants. While the use of chatbots and virtual assistants generates an exceptional user experience by providing a personal touch, it also reduces costs quite a bit. According to Juniper Research, chatbots will save more than $8 billion annually by the year 2022.
5. Smart Logistics
One of the main critical success factors in any e-commerce business is efficient purchase planning and inventory management. This is required to ensure that customers will get the product they want, when they want, with minimal turnaround time.
AI and ML can be used to process the historical data, customer behaviour, competitor pricing, trends, etc. to do forecasting and even predictive analytics to reliably predict turnover, demands, etc. and plan inventory purchasing effectively.
6. Predict User Behaviour for an Optimized User Experience
An optimized user experience is very important for a frictionless buying process. Understanding customer goals and insight into their needs can help design AI powered solutions to improve user experience across customer touchpoints.
AI can also help predict customer behaviour to allow for an optimized user experience through personalized offers, discounts, proposals, and newsletters meant to influence buying decisions.
7. Filter Fake Reviews
In today’s world, reviews can very heavily influence a buyer’s decision to purchase or not. With that said, fake reviews are a big issue for online retailers.
A simple way AI can help combat these is by putting weight behind verified and helpful reviews. By focusing on the prominence and weight of reviews from verified customer purchases and those marked as “helpful” by other users, AI can boost genuine reviews to the top.
8. Retarget Potential Customers for Better Sales Result
It’s no secret that paying attention to marketing leads and a proper follow up can increase sales numbers. Many businesses are so overloaded with unmanaged customer data and possible leads that they do very little with that info. Using AI, this goldmine of customer data can be intelligently converted to information to then be used by sales teams for a better-enhanced sales cycle.
One of the key improvements in sales is direct engagement of business with customers. AI and ML can be used to parse this data and allow sales team to retarget potential customers.
The e-commerce industry is growing exponentially, which also means growth in the volume of customers and their associated data. Managing such huge data and providing an efficient and consistent experience to the users is a challenge. AI can automate repetitive tasks like publishing new products on multiple channels, identifying and ranking loyal customers, giving offers to loyal customers and prospects, generating sales reports, forecasting, etc.
10. Assortment Intelligence
With such growth and fierce competition in the e-commerce industry, customers are now able to check for the best prices available in the market. Retailers are changing their pricing strategies and adopting assortment intelligence to retain their customers.
There are quite a few AI-powered assortment intelligence tools that allow retailers to track their competitors’ inventory, pricing patterns, product supply, etc. and can help those retailers ensure they’re providing the best possible experience to allow for customer retention.
11. Fraud Detection and Prevention
Not only can AI solutions detect patterns and user behaviours, they can learn from it. When you get a notice from your credit card company asking about a potentially suspicious charge, that’s all thanks to AI detecting and learning from your credit card transactions and utilizing those patterns to identify possible fraudulent transactions.
12. Tackle Counterfeit Products
A big problem within the growing e-commerce industry is counterfeit products. This is especially prevalent when a consumer is buying from a third-party seller. This not only affects the user experience when that counterfeit product performs poorly, but it also negatively impacts the consumer’s perception of the brand.
Machine learning algorithms can be implemented to spot counterfeit products, their sources, their advocates, and various channels while offering to take further corrective actions.
Artificial intelligence is changing the way we approach online shopping and selling. AI, when applied right, will increase customer retention, provide awesome customer experience, and improve efficiency.
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