What is generative artificial intelligence (AI)?
Generative artificial intelligence (AI) is a technology that helps you produce all sorts of content- text, images, audio, simulations, videos, or synthetic data. These algorithms are based on AI-led machine learning models that predict the next word sequence based on previous word entries or the next image/ video based on previous images/videos. This prediction capabilities in real-time combined with simple and easy-to-use interfaces has lured enterprises to create almost life-like images, videos, and content. As human input is next to negligible with generative AI, it unfolds opportunities (and challenges too) across industries, especially retail and eCommerce where delivering personalized experiences is a must-have.
The timeline of artificial intelligence maturity until generative AI
Initially, AI was the solution to automating manual processes and performing routine tasks faster and with higher accuracy than any human. Then, AI matured, commenced studying past datasets to perform actions in real-time, all while self-learning from current interactions to forecast interactions in the future. The current capabilities of Amazon’s Alexa and Apple’s Siri are a result of billions of past calculations that continually improve due to its self-learning prowess.
Then, and the most-talked about currently is generative AI. To be able to achieve the hyperscale level of personalization in real-time, artificial intelligence had to mature on several levels. Its subsets like machine learning empowered softwares to train on human-provided datasets and self-learn in the present, whereas natural language processing allowed machines to generate content and images based on textual inputs. Combined together, it resulted in generative AI, an invincible and intelligent technology that changes everything we know about human creativity and decision-making.
What generative artificial intelligence is not
According to Gartner, by 2025, the percentage of data generated by generative AI will amount to 10% of all generated data. The very basic foundation of these technologies is the real human creativity which builds up intelligence over time.
Yet, enterprises today have a half-baked understanding of generative AI. For starters, the entire basis of generative AI’s capabilities like on the data set it is fed, which can often result in wrong, illogical, erroneous, and unethical outputs. Such a prospect potentially impacts a brand’s reputation and exposes them to legal risks. It is why the implementation of generative AI in online retail needs to be calculative and under vigilant check. Moreover, we need to understand that whatever generative AI does is based on probability and logical reasoning. Generative AI tools provide responses based on the available data sets and matching it with the context specified by a user, i.e., the next logical step in the sequence. While generative AI is continuously improving, it has a long way to go before it can run marketing departments completely.
What sense does generative AI make in online retail?
The growing number of online shoppers don’t just enjoy the convenience and comfort, but also the personalized experiences delivered across channels, based on their specific piques and interests. Across industries, marketers evaluate at attributes that matter the most to customers. For the online retail and eCommerce industry, the attributes that drive growth and user loyalty is personalization across products, recommendations, search results, marketing emails, and shipping options. With this knowledge, online merchants know the processes where embedding generative AI technology can result in ROI-driven outputs. For example, generative AI for eCommerce would result in personalized shopping experiences to fit every customer.
How online retailers can take advantage of generative AI for eCommerce
As the craze around generative AI achieves fever pitch, online merchants need to devise ways to implement generative AI to their eCommerce operations. Since your competitors are already doing so, here are some use cases you can accomplish by integrating generative AI to your online store.
#1: Deliver product recommendations the way your shoppers desire
Shoppers today have tasted personalization and are delighted with how it makes them feel. From personalized product recommendations to tailored content, discounts and deals, generative AI presents several opportunities for online merchants to recommend products/services to shoppers based on their purchase history, historical data, most searched products, browsing behavior, wishlisted items, and other data points. Adobe Sensei and Salesforce Einstein AI are two powerful personalization tools from Adobe and Salesforce that help brands in curating highly personalized shopping experiences, thus driving sales and customer retention.
Such AI-driven tools analyze user data, previous purchase reports, and other data streams to tailor recommendations that appeal to shoppers and align with their interests. For example, you can tailor personalized discount strategies based on total cart values or deliver content that your shoppers most frequently search for.
#2: Run targeted marketing campaigns, tailored for each shopper
There was a time when a one-size-fits-all marketing campaign could drive shoppers to your stores or even websites. However, now times and even user demands have evolved. They no longer want to be on the receiving end of generic marketing strategies for products/services that they don’t need or never search for. Modern (might we add tech-savvy) shoppers know their real value and won’t hesitate to check out your competitors if you fail to deliver the custom experiences they desire. Enter targeted marketing campaigns. You can segment your audiences based on behavioral and demographic details and tailor marketing campaigns to their specific interests. This way, you can ensure the positive ROIs of your marketing campaigns and assured sales.
#3: Consistent product descriptions that improve SEO rankings
An online store is a digital aisle of unending products that requires infinite browsing sessions only to find a few-select items that appeal to a shopper. This is where concise but equally informative product descriptions can help. The traditional practice was to get writers to research descriptions, write appealing new drafts and add necessary SEO keywords to it. While this practice served well, often vendors ended up uploading inconsistent product descriptions that cost them sales and a precious customer.
It is why retailers, long before generative AI for eCommerce, adopted the practice of A/B testing product descriptions to find the most engaging variations. And with recent advancements in generative AI technology, they can standardize descriptions across sellers and retail marketplaces. Writers can now direct generative AI tools with specific instructions on creating product descriptions, those are tailored with your brand tone and grammatically correct.
#4: Optimized product images for high-end purchases
Product images form an integral part of PDP pages, with each image requiring an entire arcade of models, photographers, designers, editors, and creative staff for the photoshoot. This is one place where generative AI can empower online merchants to generate personalized product pages via textual inputs and historical image data. Adobe Firefly, the latest innovation of creative generative AI models from Adobe empowers creators to express their ideas with higher efficiency and no constraints. All you have to do is describe the image you want and bring your creative vision to life. Now, you can generate realistic images based on a subject, style, or location, or color that you specify. You could use these materials for commercial purposes that makes it a useful element in media, design, advertisement, marketing, education, etc.
The advent of generative AI for eCommerce images will empower brands to generate images in real-time. For example, an apparel brand can generate images of different age group people wearing their clothes to appeal to similar shoppers. As customers provide more personal data to generative AI models, it will refine its searches to fit their context of searches.
#5: Monitor and optimize product prices to close more sales
It is an established fact that shoppers track and compare prices of similar products online or in-store before they finally close a purchase. In fact, they don’t mind the hunt if they get their favorite products at an amazing price. Online retailers need to take note of this price sensitivity and always stay agile with their pricing game. With generative AI algorithms, you can track competitor price movements, analyze pricing trends, and demand patterns to further optimize product prices to prevent losing shoppers to your competitors.
#6: Improve inventory and supply chain management
There have been ongoing talks on transforming inventory and supply chain management and for a good reason. Post the pandemic, supply chains have been riddled with issues pertaining to geographical restrictions while the warehouse racks are flooded with dead inventory. Combined with delayed deliveries, most brands find it challenging to strike the right balance between supply and demand. There are several scenarios where generative AI for eCommerce can add to the current supply chain tech stacks for enhanced visibility and tracking.
- Generative AI with conversational capabilities (like a chatbot) can help answer the pressing question, ‘Where is my order?’ Generative AI for eCommerce can quickly and easily resolve order queries.
- Generative AI can analyze your current sales data to make accurate recommendations for efficient inventory management. AI studies your historical data, market trends, and user sentiment data to help brands optimize their inventories and make informed manufacturing and production decisions.
- With generative AI for eCommerce forecasting product demands, you can optimize and scale your supply chain networks to be ready for peak traffic and stagnant days.
#7: Leverage AI’s conversational capabilities to answer user queries
While the chatbot capabilities of AI might seem yesteryear-like, generative + conversational AI can improve your current level of customer support and service. Other than the perks of reducing staffing needs and having a support representative active 24/7/365, chatbots have undergone significant evolution since 15-20 decision trees to infinite ones. With advanced generative models, online retailers can play around different conversational styles to match the shopper, personalize every message for further engagement, and answer queries with human-like empathy and emotions to be perceived as a human-to-human conversation. All these factors combined result in better chat experiences for your shoppers, which further translates to higher cart completions and better sales.
#8: Create more cross-selling and upselling opportunities
By now, you’re aware of generative AI’s capabilities around product recommendations, conversational search, and how it delivers personalized content to shoppers based on their personal interests, history, and preferences. Now, this content could be in the form of texts, images, or other media, all while resulting in intelligent shopping journeys. Further on, generative AI in online retail can analyze all these current data sets to suggest the next logical purchase step in a user’s purchase journey. This results in higher cross-selling and upselling opportunities, all in efforts to accelerate sales and ROIs.
#9: Generating auto-fill transaction flows for each customer
Currently, web pages follow a generic and fixed structure, meaning they showcase the same content, images, and banners to each user despite their varying preferences and choices. Generative AI for eCommerce allows retailers to deliver condensed site experiences to each customer depending on their interests. This means, every shopper would see a custom site where products are filled in automatically depending on the customer data stored on the backend. This further would result in a hyperscale-level of personalization as per a shopper’s behavioral and demographic data.
#10: Prevent fraudulent and phishing activities
As hackers and spammers find their way to your online store, it can often result in fraudulent purchases or returns, decreasing profit margins and resulting in loss of customer trust. Generative AI algorithms in online retail can detect and prevent such illicit and fraudulent activities by identifying unauthorized users with or those with suspicious histories and block them from accessing your online stores. In the long run, this saves brands money and margins.
Going forward with generative AI for eCommerce
There is no second guessing the rapid and accelerated evolution of the retail world that too in the face of challenges such as evolving shopper expectations, price sensitivity, growing online competition, dynamic market trends and so on. Truth be told, retailers are experiencing a hot box moment, where they are ready to experiment with everything that promises them more sales in less time and budget.
While generative AI does hold a promising potential, especially in the retail and eCommerce industry, it needs to be studied and monitored excessively before implementing it to core operations. Remember, every technology comes forth with its own set of challenges and uncertainties, and until they are fully understood, one should not take the plunge. As experts in the eCommerce space, we hold immense capabilities in helping you understand the role of generative AI for your business and can help implement leading tools for the same. Connect with our seasoned consultants and let’s take that plunge into generative AI, together.
