Last updated on 3rd November 2021
Last updated on 3rd November 2021
2020 was quite a year for the eCommerce sector.
While the retail sales figures globally suffered a setback, eCommerce had made its point loud and clear. It was not only here to stay, but was all poised for unprecedented growth.
All major markets saw abnormal standout growth as Artificial Intelligence (AI) and eCommerce converged to keep pace with the one thing that matters the most - the forever-changing consumer behavior.
Considering that Gartner had already predicted that at least 60% of organizations will adopt artificial intelligence for digital commerce by 2020, the disruption that AI is causing comes as no surprise at all. AI has ushered in a wave of innovation in both the B2B and B2C sectors, taking the eCommerce world by storm.
This white paper goes deeper to examine the role and impact of AI in eCommerce. It will look into the many nuances of AI and how it is the gateway to success for your online business.
AI-powered eCommerce is using AI technology to analyze different sources of business and customer data to come up with insights to make strategic decisions. These decisions help you and your eCommerce platform in creating personalized and relevant customer experiences.
When used properly, these insights also help you speed up your routine tasks by either automating them or eliminating unwanted steps.
Traditional eCommerce involves using the standard tools and platforms along with your skills & expertise to achieve the desired results.
While it helps in automating most of the things, relevance and personalization are still a distant dream. Sales and marketing teams still analyze a lot of customer data manually to personalize their communication for cross-selling and upselling.
One of the most important factors that set AI-powered businesses apart from traditional ones is their ability to fully track the business.
AI-powered business models are a fresh departure from traditional models. The business owners know exactly what their customers want, where they come from, what age group they belong to, things they recently purchased, and what's currently on their minds.
Data mining and harvesting were unknown territories to the traditional world, and analysis was rather crude. Then came AI and business owners saw an enormous opportunity here to come up with data-heavy strategies. They could now inspire shoppers on a personal level, enticing them with products that would have been lost in the clutter on an overly crowded online shelf.
Armed with frequent and fresh algorithms and AI-powered personalization, they could now reach out to their customers with better products and stellar service. They could learn from the past to predict future outcomes.
AI gave them the niche to create their own world that would have been impossible to achieve for most in the traditional world of retail. The beauty of AI is that it does not require you to be big and bold to be seen. It just needs you to be relevant and proactive to become the showstopper on a global runway.
Now that you understand what AI-powered eCommerce is, let’s move on to the specifics.
What makes AI tick and what makes it an eCommerce must-have?
AI clearly dominates the eCommerce landscape for all the right reasons
AI enables systems and business environments to adapt and improvise to use its intelligence to address new challenges in unfamiliar settings.
It is this exact intelligence that AI-powered platforms offer you to excel and exceed customer expectations.
Apple's Siri and Amazon's Alexa are popular examples of what AI can do for us even in our everyday lives. They can detect fraud, spot spam, and do significantly well even in the speech recognition arena.
There are however several other aspects at work that give AI its capabilities and without understanding them you will never know how AI works. These include:
Machine learning boosts your conversion rates. They provide product recommendations and make marketing campaigns more relevant. The market revenue of machine learning is proliferating at a CAGR of 50.8% from USD 18.4 million in 2019 to USD 216.6 billion by 2025.
It considers past activity along with historical data to draw inferences and speed up decision making. It identifies patterns in customer behavior and purchase history to arrive at a conclusion. This detailed analysis helps industries, including eCommerce, evolve and exceed customer expectations while helping business owners make better business decisions.
Yet another AI function and an important part of machine learning methods, deep learning analyzes data in multiple layers the way our brain does. The outcomes it predicts with such a structured, layered approach helps businesses take concrete steps towards achieving their goals.
Deep learning makes everything precise and enhances personalization.
Let's say you are browsing in an online store for a handbag.
You find one that's almost perfect, but you are not happy with the color.
So you click on the image of that bag and the site then, shows you several other handbags to browse through. Here, your actions and digital footprints act as the input and the handbag recommendations show up as the output.
These too work like human neural cells following the same principles to process inputs and form the core of deep learning algorithms.
They get their name from the fact that they emulate the way our biological neurons communicate with each other. They process information as sets of inputs to identify hidden patterns and correlations in raw data to come up with dependable inferences.
Fashion shopping app The Yes recently announced its decision to branch out of the smartphone space with a new neural network-powered website calling it 'adaptive shopping eCommerce'.
- Julie Bornstein (CEO and Co-Founder)
NLP is a science that concerns the interactions between computers and human language to enable machines to read, understand, and interpret a language.
Once a machine is able to comprehend what users are trying to convey or communicate, everything falls into place. Businesses can respond faster to customer needs in real-time with such advanced capabilities.
For instance, let's see how it helps business owners with social media listening.
There are a lot of conversations around holiday stress, vacation planning and budget shopping during the holiday season. Now marketers can definitely use these conversations as a hook and include phrases like holiday shopping, budget deals, and vacation planners in their messaging to ensure they connect well with their audiences.
NLP also facilitates better searches by giving more meaning to online searches.
You may sell a 'lazy' bean bag, but those searching for it may search it by the first word that comes to their minds and may search for it using the phrase 'cozy' bean bag.
NLP ensures it makes sense of everything you search for and provides relevant results even when the phrases you use for your searches are way too random.
Computer vision algorithms break down an image to study different parts of the objects and understand them. Machines then come up with very useful insights based on observations after analyzing a set of images.
Computer vision is helping in a big way by organizing the inventory, enabling customers to find the products, and enhance searches.
For instance, after finding the perfect handbag you could further your search by asking the virtual salesperson "Which shoes will complement this bag?"
Cognitive computing algorithms go a step further to mimic the human brain in the way it perceives and understands things. Understanding is based on text, speech, images, and objects to offer a more comprehensive analysis.
Cognitive systems can help analyze the location from where an order was placed and suggest an ideal shipping method based on the location of the inventory to save time and cost. Cognitive technologies also enhance the shopping experience by helping shoppers choose the right products.
For instance, if you have a vast range of sports shoes, eCommerce platforms powered by cognitive technologies will ask customers different questions to analyze their responses and suggest the right shoes based on style, activity, and even weather preferences.
This is akin to what North Face does in the fashion space for their widest array of jackets.
AI with machine learning and its many manifestations helps businesses imbibe accuracy into their business models.
AI gives eCommerce actionable insights to make it big in an overly crowded digital market.
It helps you elevate shopping experiences with myriad features and value additions such as personalization, search optimization, auto-generated product descriptions, and voice search.
It looks into the browsing patterns, purchase behaviors to make accurate predictions and help you plan your inventory & campaigns accordingly. However, it depends on accurate data sources to deliver with such precision and perfection.
In the previous section, we discussed at length how AI and machine learning together empowered the eCommerce world with actionable insights.
While it has already been established that the modern world of eCommerce is being tech-driven, we cannot afford to overlook the fact that everything eventually boils down to having high-quality data.
AI needs data - massive amounts of data pulled from random sources continuously to arrive at important conclusions and insights. In fact, data and analytics form the very foundation of your marketing campaign.
You need to collect, track, and analyze data to understand how customers engage across digital channels and the hurdles you need to overcome to reach them.
Let’s now discuss the many data sources you need to focus on to get solid, accurate data and pivot your eCommerce business towards greener pastures.
Customers search for something or the other all the time across multiple channels using all devices. Their search and browsing history leaves a digital trail that offers a wealth of information to enterprises.
Simple things like customer likes, dislikes, and geographical location can help us understand their behavior and make relevant recommendations.
In order to ensure that you are adequately stocked, it is important to understand past sales performance, inventory records, and current trends.
You need to have a firm grip on all important transactions, including shipping and purchase orders, product returns, and repeat orders. All orders need to be tracked simultaneously from packaging to delivery and precisely delivered.
AI bots ensure the data collected via automated order management systems is accurate for use. It ensures that customers are duly notified about the status of their deliveries and allows you to use the order and payment data for analysis.
You need to have this data to predict demands and plan inventory accurately.
Inventory management is an important aspect for evaluating profits.
Heavy financial investments in stockpiles or unnecessary storage place a tremendous amount of stress on your financial planning.
From a promotional planning perspective too, inventory management is crucial.
Imagine an eCommerce site enticing you with something you really wanted – perhaps that perfect denim jacket you had been wanting so badly.
You find it, but the moment you decide to place an order; you realize it’s not available in your size. This happens more frequently with eCommerce sites that have put in very little thought and effort in managing their inventory.
The more diligent ones choose to optimize their strategies & resources to promote products and then track their popularity to stock additional units. They invest in data analytics to know exactly what their customers need and ensure they have it.
Data analytics goes a long way in making demand forecasts that can help plan promotional offers, conduct targeted sales, and analyze historical demand patterns to adjust inventory targets.
When powered by AI, ERP serves as a unified data hub, eliminating silos and streamlining everything from the time a customer adds to the cart to the moment they complete the checkout process.
ERP functions include calculating the exact shipping costs, updating customers about the status of their orders and delays if any, adjusting prices within product categories, marking down certain item categories, and keeping a tab on inventory count to avoid getting into out-of-stock situations.
The data gathered ensures stock is sufficient and you are well-prepared to handle a sudden spike in demand.
ERP integrations ensure the data is always up to date, never replicated, and can effectively create any desired dataset or report.
ERP data flow is important especially for larger businesses where data quality can affect the complexity of data maintenance. Even a minor error can leave you cleaning up the data and the ensuing mess of wrong data might lead to.
For instance, a wrong delivery address can lead to disgruntled customers.
AI helps build accurate master data for the ERP to function optimally.
The CRM market has exploded over the years and as per current predictions it will grow at a CAGR of 12% from $40.2 billion in 2019 to $82 billion by 2025.
When leveraged correctly, CRM data can help improve customer service and boost conversion rates. It can also help retain customers and generate new business opportunities. AI will use details like buying habits, geographical location, and the age of buyers to build customer personas.
For instance, a 60-year-old living in China is going to have very different shopping preferences as compared to a 25-year-old techie from the U.S.
AI collects this data to spot patterns and trends in their behaviors to offer them highly personalized shopping experiences via email marketing, targeted landing pages, and personal messaging with proper segmentation.
AI can also help in lead scoring, allowing you to track movements of customers as they move through the sales funnel to determine the probability of a purchase. You can accordingly offer personalized deals and offers to encourage them to complete their purchase.
Social listening offers instant insights that are straight from your customer through their social media posts. You get to know about the brands being discussed, products and topics of interest, and the general sentiment around your products and brand.
The modern customer is pretty much in the driver's seat now and knows well how to navigate towards more rewarding shopping experiences. You need to keep an open mind and welcome their choices with open arms.
The data garnered from such posts can help you design new marketing strategies and also boost the image of your brand with the right measures.
You may even assign a monitoring period or decide the timelines during which you wish to track a particular hashtag or an event. Social listening is a great way to nip a PR crisis in the bud and do the necessary damage control to create a positive brand image. It gives you a competitive edge to thrive in an overly crowded digital market.
The data collected from social media also helps you keep a tab on your engagement activities.
For instance, stats collected from Facebook and Instagram accounts can be used to promote relevant ads with demographic and behavioral targeting.
Data based on customer feedback and reviews is just what you need to address your shortcomings and take corrective action. eCommerce businesses have been using NLP and text analytics to sense the overall sentiment about the brand and leverage the insights to improve brand image.
AI differentiates genuine reviews from the fake ones to provide dependable, legitimate data.
While it has always been challenging to understand the sentiment behind certain words and phrases that could be laced with sarcasm, self-learning systems are now sifting through reviews and feedback to understand the sentiment as well as the tone of the text. This addresses the problem of misinterpreting cases of double sentiment.
Data collection and analysis are clearly shifting paradigms for the world of eCommerce.
AI powered by data analytics is helping enterprises across the globe understand their customers better and offer seamless shopping experiences along the way. The thing about data analytics is that it's not just limited to helping you make sound marketing decisions. It empowers you with insights to create value across the entire eCommerce business.
With the right data, you can identify changes in customer traffic patterns, plan inventory, and elevate the customer experience. You, however, need to have clearly defined goals for your online business.
Once the initial prep work is done, AI will ensure eCommerce success is just round the corner.
No wonder it is expected to grow beyond $15 trillion by 2030 with 80% of emerging technologies stemming from AI by 2021.
AI is evidently becoming mainstream as AI adoption continues at jet speed all over the world, with new and powerful AI benefits emerging constantly on the eCommerce landscape. We’ve put together the most important ones.
AI-enhanced analytics help you derive value from structured and unstructured data to adopt a customer-centric approach.
For instance, customer interactions, when used with structured data, can form the basis for solid analysis to learn valuable lessons on consumer behavior. It can help you identify the most profitable channels, high performing products, forecasting demand, etc.
Also, data derived from enterprise applications like ERP and OMS ensure a 360-degree view of enterprise operations in real time to ensure a seamless shopping experience.
AI allows you to segment and analyze customer behavior to detect potential churn, prevent losses, and offer business value. AI helps offer omnichannel selling to ensure that customer experience is consistent. No matter which device or method your customers choose to connect with you, AI keeps the experience smooth and unhindered.
With the Internet of Things (IoT), AI also gathers data from wearables, appliances, and other connected items to give you relevant information about your customers. From the items they purchase to their preferred mode of payment, you get a wealth of information to make smart business decisions.
We are all aware of how persuasive personalization can be.
AI along with machine learning now knows a lot about us thanks to our digital footprints. AI-powered eCommerce platforms leverage this knowledge to help us better.
So if a customer needs that pristine white shirt to crack an interview, you've got his back all thanks to AI. It helps you understand your customers and engage with them at multiple touch points to give them exactly what they need.
AI looks into past transactions, purchase history, & searches to expect and respond to their needs well. AI allows you to make product recommendations and send out personalized emails/ messages to boost your conversion rates and sales figures. It helps you offer customer-centric solutions by helping you segment customers and create targeted marketing campaigns.
Not just the products, but AI also identifies other aspects like best time to send, best email design to improve your marketing outcomes.
No matter how you choose to reach out to your customers - be it a website, email campaign, or a mobile app - AI will relentlessly monitor all devices and channels to offer a cohesive customer experience across all platforms.
A bit of help while shopping is always welcome. A specific item in a particular size or color sometimes can be a tad difficult to find and take up a lot of time. But with chatbots and virtual assistants, it's all so simple.
Chatbots interpret voice-based interactions with natural language processing (NLP) and address customer needs with self-learning capabilities and deeper insights.
While chatbots keep your online stores open 24X7, virtual assistants cater to the exact needs of customers when they step into your online store.
Chatbots are no longer an option but an absolute must for online businesses. They can be easily integrated into your ecosystem to help retrieve information pertaining to product details, shipping terms, etc. or assist with simple chores such as contact forms and order-related help.
Virtual assistants, virtual shoppers, and voice assistants, on the other hand, help offer that personal touch. They help in driving conversations, boosting sales, and giving customers a truly satisfying shopping experience with human-like conversations and personal assistance.
If you are still not convinced, find out how the virtual assistant of the highly popular Marks & Spencer helped drive £2m in sales. It helped customers use discount codes on their orders effortlessly avoiding the risk of cart abandonment.
- Akash Parmar (Enterprise Architect at Marks and Spencer)
While traditional inventory management was all about data pertaining to current stock, AI took inventory management to a whole new level.
AI-enabled inventory systems are perceptive and offer advice based on historical sales trends, changes in demands, current market trends, and potential supply related issues that can impact inventory levels.
The role of AI extends well into warehouse management, as automated robots relieve humans of mundane tasks. Robots manage stocks round the clock and take care of the dispatch of ordered items too. They talk like humans but never go on breaks.
From the moment a purchase is made, a robot will fetch the necessary items, box them, and send them to the delivery truck. AI-enabled robots improve accuracy, reduce labor costs, and minimize losses that can arise from damaged stock.
On-time delivery depends on how well you track your inventory. Often, sellers may oversell or shipments may take too long to deliver and prevent you from sticking to deadlines. AI ensures proper stock replenishment so that you never have to undergo stock-outs and meet customer demands before time.
AI analyzes trends for best-selling products as it directly impacts procurement. This helps address returned products and reduces the size of the catalog. It also helps improve space utilization as you store only as required.
AI-enabled supply chain automation can help you make better business decisions regarding delivery schedules, shipments, and logistics.
With machine learning capabilities, you can ensure your customers find exactly what they are looking for. Even from a logical perspective, it makes sense to display the most popular products and product categories first.
Machine learning considers common searches along with keywords and phrases used for those searches to create accurate product descriptions so that products show up in search results when customers go looking for them online.
AI-based eCommerce platforms prioritize click rates and existing conversions to place high-rated products on top of the page. Customers can search 'By Relevance' or 'By Featured' to find what they want.
Due to machine learning's accurate predictive powers, the probability of selling listed products increases to a great extent. Also, appropriate recommendations increase your sales figures.
You can remind your visitors about products they showed interest in but forgot to add to the cart by the time they reached the checkout, or wish to promote a product that complements their purchase perfectly.
A scarf or a tie, for instance, may be perfect accessories for an outfit, so why not recommend them? Chances are, your customers would be more than happy and buy them right away.
In the event they do not buy something they showed interest in, machine learning will look into relevant data to analyze their behavior and find out what could have possibly worked in the past to convert similar profiles into buyers.
This helps in enticing customers with re-targeting, upselling, and discounts via emails or personalized catalogs.
AI helps you continuously come up with new ideas to make people buy. All you need is an AI-powered platform that can take out the guesswork and give you the technological edge your eCommerce business deserves.
AI liberates you from the limitations of traditional business models to go global and expand your reach. It automates and speeds up a lot of initiatives to help you reach your customers faster. Research and surveys have consistently proved it is impossible to succeed in the eCommerce world without AI.
Check out the next section for some interesting facts and figures
In a survey by Mckinsey, 50% of respondents admitted to having adopted AI in at least one business function as companies continue to reap significant value from AI. It has now penetrated virtually all sectors worldwide and has seen more enthusiastic participation amid the COVID-19 crisis.
It’s time we dug deeper into the facts and figures surrounding AI to evaluate its impact. After all, figures don’t lie. So let’s begin.
From healthcare to finance, every sector has adopted AI with open arms.
AI use cases continue to grow to enable deeper insights and better experiences for all. AI with machine learning capabilities is enabling eCommerce businesses to tide over pandemic-related challenges with resilience.
The global retail eCommerce traffic saw a record 22 billion monthly visits in June 2020 with demand for everyday items going through the roof.
Global AI in the fashion market is expected to touch $4.4 billion by 2027 as it continues to elevate the customer experience for brands all over.
As brands fight it out to ascertain their dominance in the fashion world, AI gives them the edge to make it to the top.
Alibaba's FashionAI deep learning kiosk was helping customers decide what they should buy with suggestions and recommendations during China's Singles Day weekend, while AI-powered augmented reality applications were helping online shoppers with virtual try-on.
Serial returners are clearly crushing profits compelling brands, and online business owners rethink their strategies. They continue to bear this cost as in most cases customers with the highest return rates are also the most profitable.
Luckily, AI is helping companies address this issue to a great extent by giving them an opportunity to experience the product they are buying virtually.
What's interesting to know is that a massive 90% of consumers will happily share their behavioral data with brands if it translates into easier, cheaper shopping.
Personalization is an absolute win-win, as it allows brands to offer special discounts and promote new products based on individual preferences.
The recommendations will be more accurate and the discovery experience would be more enjoyable for customers.
Rather than handpicking all the attributes and deciding what 'may' work best from a sales and experience perspective, you need to simply dump all the data you have into one big data lake and let AI take it from there.
While doing so, it saves consumers a great deal of time & effort in resolving issues. It also provides the necessary assistance as and when required.
Chatbot-enabled business messages enjoy an 85% average open rate and a 40% click-through rate.
Chatbots are extremely effective for re-targeting customers considering that barely 2% of shoppers actually purchase during their first visit. Also, re-targeting via chatbots enables businesses to increase the conversion rates by an incredible 128%.
L’Oréal recently announced its collaboration with Facebook to integrate ModiFace virtual try-on tech and offer a makeup experience to Instagram shoppers via augmented reality. H&M took to Kik to get chatty with its customers and become their virtual stylist.
AI skims through heaps of data to identify threats and even predict ways to address them.
With a 159 percent year-on-year increase in luxury sales, the ecommerce giant is all set to tackle counterfeit crime. This is an important step considering that £3.2 billion were spent last year on counterfeit designer brands in the UK alone.
AI-powered mobile robots are transforming spaces into data-driven environments, managing repetitive tasks effectively while enabling better planning and decision-making.
Amazon boasts of the world's largest fleet of mobile robots to manage myriad tasks in its warehouses.
Logistics management is an important area that needs continuous improvements to speed up delivery and efficiency in the eCommerce sector. AI plays a big role here, helping brands reach hard corners effortlessly while allowing them to keep a close tab on their inventory in real time.
Negative reviews can damage your business especially since 79% of consumers trust online reviews as much as personal recommendations from friends and family.
When you garner a high star rating or a positive review, you can expect more customers provided the reviews are recent.
It is important to filter fake reviews for which you require AI.
Several businesses, including Amazon, are leveraging AI to fight ‘astroturfing’ or fake reviews.
Clicking a picture of something you like and then using the visual search engine to direct them to the right results is not only very convenient but also helps them find what they are looking for in the fastest possible manner.
A classic case in point is the Pinterest Lens that allows users to click anything that piques their interest and see relevant information pertaining to it.
The way you price your products has an enormous impact on the profitability aspect of your business.
Considering that competitive pricing drives the purchasing decision for 80% of shoppers, dynamic pricing has emerged as an important strategy for eCommerce decision-makers.
Dynamic pricing enables you to adjust your pricing as per industry standards, consumer expectations, market trends, conditions, and predictions. Digital businesses are adopting dynamic pricing as their go-to strategy to stay competitive.
37% of global shoppers confess to comparing prices today and AI-powered, algorithm-driven pricing is helping businesses arrive at the right pricing to stay relevant and competitive.
AI empowers you with data and insights to offer personalized services and recommendations that can help shoppers get smart about their shopping.
It helps you adjust prices and strategies based on seasons, demand, trends, and competition. As new products, markets, and opportunities continue to emerge, AI gives you the edge to rev up your revenue and forge deeper connections with your customers across channels.
In its The Living in an AI World 2020 study, KPMG brought to the fore the many aspects of AI including challenges and barriers in AI adoption.
While the adoption rate varies globally, the depth of engagement is overwhelming.
As per the study, 85% of respondents believe in the potential of AI to improve organizational efficiencies and 80% divulge it is being used to ease customer issues.
Yet, only 43% of respondents believe their employees are ready to adopt AI. Amidst this mixed climate of optimism and skepticism, barriers to AI adoption continue to trouble digital businesses.
While AI takes the lead in performing all the cognitive functions associated with the human mind, not all humans are game for this significant change. Not surprising, as the foundational blocks necessary to build and integrate AI-driven systems within enterprises are missing.
AI-driven digital commerce is already making headway in the eCommerce scene, and the exponential acceleration of AI adoption is vital.
By shifting the focus to identifying challenges and overcoming them, we should be able to traverse the road to AI adoption quickly and smoothly.
By now, everyone knows AI has plenty to offer across every sector and business function. AI has been getting continuous traction in retail and eCommerce for the myriad benefits it offers. But it evokes extreme anxiety too within enterprises.
Like it or not, AI is the only way to drive value and advantage. But enterprises are finding it hard to address the 'preparedness' gap. Despite all the AI awareness, they are also a tad scared of the risks associated with implementing AI. They need to tackle these risks head-on to turn the tide and make AI benefit them.
This switch in mindset is easy if you look at the 3 main reasons for adopting AI:
To automate processes and functions
To optimize efficiencies
To enhance the ability of your workforce to do more and do better
While it is easier to understand the processes that can benefit from AI, it is equally important or even more important, to foster a culture of AI adoption with the right mindset.
Don't feel threatened by automation; it's meant to give you power. Don't look at it like some robot apocalypse wherein the whole place will be infested with robots that will mess up the way you work. The challenge is to introduce AI swiftly so that people don't even realize that something has changed and yet feel the enhanced speed and efficiency as they work.
One question that could be on everybody's mind is - ‘where to begin?’ considering that AI can be used for just about everything.
A good way to start is - integrating AI into systems like ERP or CRM or eCommerce stores your people are already using. Chances are they might not even realize AI is already in there. But once they experience its benefits, you can get them interested in expanding it to other systems and processes.
Not having the necessary skills is yet another challenge enterprises are currently grappling with.
Perhaps the fear of job loss is too deep-rooted to see AI for what it actually is. The truth is AI will not replace humans but give them the edge to work smartly and stay competitive.
Among the top challenges iterated in a Gartner research , lack of skills (56%) was the biggest one. Enterprises were initially enthusiastic about building AI systems themselves, but now many are seeing the wisdom in deploying AI using embedded tools in intelligent enterprise applications.
You can either hire the right talent or outsource it to an external expert.
The talent you need also depends on the level of maturity you are at regarding AI adoption. Output from AI models can be probabilistic, which means you need to have a better understanding of AI to ensure its correct implementation.
The role of Data Analysts, for instance, would be as important as that of a Product Managers since you would require them to churn large volumes of data to arrive at more logical conclusions.
You might want to use AI-powered platforms like ewiz commerce that manage all your chores without needing exclusive in-house talent.
It is expensive to build and maintain AI systems as you would require money as well as developers to do so. AI-powered tools come in handy here since they are accounted for in systems that you are already using.
The cost of development further adds up to the AI project's implementation cost.
Readily available SaaS products can prove to be more cost-effective since they usually have a turnkey model for deployment backed by solid research and insights. They can help you work within a budget without straining your resources for development, iterations, and deployment.
Companies are also leveraging cloud-based AI vendors that offer ready-to-go AI services to avoid spending time on building your own infrastructure and algorithms.
If you are up for some number crunching and are ready to do the math, you will realize the benefits of AI far outdo the cost of implementation.
It is important that team members across functions agree before you roll out any AI implementation plans. This would mean having well-defined, common AI objectives that are clearly communicated across business units.
An AI-focused strategy should be part of your company goals, and not just limited to a department or system.
While it is a known fact that AI top performers reap significant value from their AI projects, there is one more reason they are so successful. AI top performers do not create their AI projects in silos but rely on cross-functional teams that come with new and different perspectives that go a long way in solving major business challenges.
All AI initiatives need large volumes of data to draw the right inferences and come up with the best responses to a situation.
Without sufficient data, it is impossible to address the complex issues AI is expected to resolve for online businesses. It is therefore important to have clear goals to identify data sources, define the range of data to be acquired and cleaned before it can be finally processed by AI.
For instance, you are looking for reasons to understand what may have caused a website outage. But if your data is all about mobile app performance, even the best AI system cannot offer satisfactory answers.
Another important concern pertaining to data is security, which is apparently slowing down AI adoption.
While 90% agreed that their companies need to implement a code of ethics to govern AI work, 45% believed they could reap major benefits from customer service chatbots in the next two years.
Data collection, aggregation, and processing are all important parts of the data matrix and should be addressed correctly. It is important that you invest time in data mapping to know about its whereabouts.
If your organization is serious about adopting AI, it would be advisable to hire a team of data analysts to clean, update and manage the data sources. Also, most of the AI platform providers offer these data services as part of their package.
It will also help to have some legal guidelines on how the data will be used.
Remember, AI needs to be lawful, ethical, and robust. It is important to have an ethical, human-centric AI model that is aligned with your values and strong enough to deal with future growth challenges.
You would be surprised how AI-generated recommendations may sometimes seem counter-intuitive and make you realign your business goals simply because you were operating on such limited data.
AI can have a wide-ranging impact on eCommerce. Luckily, the road to AI adoption is easy if you adopt a 'test and learn' approach and encourage cross-functional collaboration.
Don't look at AI as a plug-and-play technology that will give you immediate returns. AI needs to be leveraged effectively to transition from fear to trust.
It is the key to uncovering hidden potential and exploring uncharted territories. All you need to do is balance between relying on technology and working with your people.