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Ecommerce Platform Migration, Web development
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Ecommerce
1/12/2024
How Enterprises Benefit from a Magento-to-BigCommerce Migration
5 min read

Managing an eCommerce enterprise store is no walk in the park, and neither is choosing the right platform for that purpose. Magento has long been considered one of the most powerful and customizable platforms for eCommerce enterprises. However, today we find enterprise owners debating the need for a Magento to BigCommerce migration. 

Today’s customers expect seamless transitions between online and offline shopping channels. Whether you consider scalability, seamless integrations, or omnichannel capabilities, the industry simply does not accept any compromises.

In this blog, we examine the limitations of Magento and detail the best practices enterprises adopt for migrating from Magento to BigCommerce.

Why You Should Migrate from Magento to Bigcommerce 

Magento has its Limitations

  • Since Magento is a self-hosted platform, your business faces challenges in managing, hosting, and maintaining the servers.
  • Magento does not provide technical support, meaning your site is exposed to security breaches leading to unexpected downtime.
  • Without seamless integrations, the extensions in Magento’s marketplace are not always compatible with your system.
  • Magento brings challenges in terms of scalability as your offline and online channels in different regions are not in sync.
  • The cost of managing multiple stores on Magento is very high if you consider hosting, security, and development resources.

BigCommerce Saves the Day

  • The cloud-based infrastructure of BigCommerce takes away your burden. The fully hosted platform takes care of hosting and server management for you.
  • BigCommerce also reduces the administrative burden on your business by providing technical support and updates whenever required.
  • BigCommerce backend seamlessly integrates with your storefront to provide your customers with the best shopping experience.
  • With BigCommerce, your physical and online stores in different locations are connected to provide you with real-time insights under one dashboard.
  • Since BigCommerce operates on a subscription-based model, the cost of running your enterprise store is much lower than it is using Magento.

When it comes to security, it’s a completely different story over at BigCommerce. The robust security of the platform makes it one of the most reliable infrastructures for your enterprise. Not only that, but BigCommerce also offers world-class performance and uptime, meaning you never have to worry about backing up or restoring your data.

It comes with a number of strong SEO tools that help your enterprise rank higher up. These tools allow you to edit page titles, headers, meta descriptions, and URLs.

How Awesome GTI Benefitted from the Migration to BigCommerce

According to Wayne Ainsworth, eCommerce Manager at Awesome GTI, “Our entire migration process from Magento to BigCommerce only took a few months. That was a great turnaround time for us because we were still 100% operational during this entire transition process.

Since making the switch, we’ve had 1.3 million sessions, and 4 million pageviews — and it’s consistently growing. Our online store’s performance is remarkable: bounce rate is reduced, session duration is up, and daily sessions are increasing. The growth we wanted to see is there.” 

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Planning the Migration Process 

The Magento to BigCommerce migration consists of a few steps that are quite specific, but it is a straightforward process. You might even find more than one way to perform the migration, but every method involves backing up, moving, and updating your data.

Conduct a thorough assessment of the existing Magento setup

Before taking the first steps of the migration process, you need to identify the features and functionalities that you need while moving forward. An easy way to do this is by categorizing your existing system’s features into important, secondary, and not required. 

Defining migration goals and Key Performance Indicators (KPIs)

Here are some examples of KPIs you can use to plan your migration:

  • Improving site performance
  • Enhancing user experience
  • Adaptability to market changes
  • Making your ecosystem more scalable
  • Cutting down the cost of web hosting
  • Connecting physical and online channels

Identifying potential challenges and developing a mitigation strategy

When it comes to switching between platforms for your eCommerce enterprise, the data migration part is the most risky one.

Your data includes your products, passwords, orders, and other saved information. You need to consider each of these data types individually so that you don’t leave anything behind. 

  • Product data consists of information about individual products, grouped products, and their configurations.
  • You have to take care of the passwords for customers’ accounts on your eCommerce site. These are not easy to import and you are most likely going to ask your customers to create new ones. 
  • Not just orders, but everything linked to the orders must be transferred to the new platform to avoid inconvenience. 
  • You also need to consider the personal details of customers saved on your Magento site so that this doesn’t cause any problems moving forward.

A third party would never know your products like you do. This means you will have to put in some extra effort and communicate your objectives clearly. Another important part of planning your migration is taking it slow. The more time you spend on planning, the less you will have to spend dealing with inconsistencies later on. Take your time to review site customizations, extensions, and anything else you will need in your BigCommerce platform.

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Creating a detailed migration timeline and budget

Now you need to set a budget for your migration, which will depend on the list of features you have categorized as most important.

In this case, priorities define the sequence with which you will be developing your features after migrating to BigCommerce. But that’s not all, you also need to create a project timeline. Make sure to create space for testing and updating features where required. 

The next step before moving towards data migration is creating a backup. You can do this by going into the Magento dashboard and selecting System -> Cache Management.

To back up your data, you can use one of two methods:

  1. Go to the File Manager in your web hosting control panel
  2. Use a File Transfer Protocol (FTP) application.

Data Migration Strategies

Transferring Product Catalogs, Order History, and Customer Data

Although creating your new BigCommerce account is easy, transferring your data is not. If your data transfer process goes wrong, your site performance will be affected for weeks, or even months. The complex migration process needs to be carried out in steps, where you should first transfer product catalogs and other information. In conjunction with the data transfer, you must continue to test the functionality before and after migration. 

It is also advisable to start the migration and complete a light site design before moving forward. Once you have migrated your data, the next steps are setting up the integrations and developing the UI and UX for your eCommerce site. 

Yes, the process is quite complex, which is why shopdev’s BigCommerce developers are here to assist you.

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Data Mapping and Data Integrity

Ensuring data integrity and accurate data mapping is crucial during the Magento to BigCommerce migration. For instance, you have to map your existing data by entering the Magento Source Store information. 

This includes entering the URL of your existing Magento store and installing the connector into your Source Cart. For accurate data migration, you need to provide a few more details such as your API Path, API token, and login credentials. As a result, you can receive the data you need from your Magento site. 

Customization and Design Considerations

When it comes to eCommerce stores, the look and feel are some of the most important factors to consider. After all, the first thing your customers will notice when they visit your web store is the UI. As you might have guessed, there are some design differences between Magento vs BigCommerce. But here’s where things start getting tricky in your migration. 

Design and Themes

If you are used to the high level of customization provided by Magento, you’re going to face some limitations with BigCommerce. While Magento is an open-source platform that allows developers to access the source code freely, BigCommerce does not. 

The customizability in Magento is limitless, while BigCommerce, a SaaS platform, only allows you to adjust themes using some bits of code. On the plus side, BigCommerce currently offers 15 free themes and 100+ paid options, which are mobile responsive and easily customizable.

Replicating the Look and Feel in BigCommerce 

With the design differences in mind, you still do not want to drift away from the original look and feel of your eCommerce store. In order to replicate the design and custom functionality of your Magento store in the BigCommerce platform, you need to choose the BigCommerce themes that nearly match the template and design you were using previously.

Upon selecting the right theme in BigCommerce, you can then proceed to customize it according to your brand’s design language. The BigCommerce theme editor allows you to make changes to the design of your store, such as adjusting the layout, colors, and fonts to replicate the theme of your Magento site.

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Optimizing the user experience during and after migration

While your eCommerce store is migrating from one platform to another, your customers’ expectations remain the same. Therefore, it's important to maintain a great user experience during and after the Magento to BigCommerce migration. 

First of all, you need to keep your customers informed of what’s to come. You can send out updates through social media channels or emails to inform them about possible downtime. However, downtime is something you will need to avoid. Make sure you implement redirects on pages that are not working while you migrate your site, and also take steps to maintain product URLs. 

That’s not all, you also need to ensure that the mobile responsiveness and performance of your site are not compromised at any point. During the migration, your customer support team must be ready to answer any questions your customers might have. Finally, when you have migrated to BigCommerce, make sure to collect feedback from customers to pinpoint areas that need improvement.

SEO Considerations

SEO optimization is the first thing that comes to mind when you think of growing any kind of online store. For Magento users, migrating to BigCommerce is good news in terms of SEO. As BigCommerce offers some great SEO tools, your enterprise has a better chance of ranking higher on Google. Both Magento and BigCommerce allow editing page titles, alt text, images, descriptions, and URLs, but the SEO-friendly features of BigCommerce take you a step further. 

The impact of migration on search engine rankings

Unless you carefully plan and execute each step of your migration, the process will take a toll on your SEO rankings. For instance, the URLs for your products and pages will change when you move your site from Magento to BigCommerce. Search engines will not be able to discover and index your product pages like before, and there might also be content duplication issues. 

Not only that, but Google also looks for secure websites that have an SSL certificate. This means that if your Magento site has an SSL certificate, your BigCommerce site must have one in order to achieve the same SEO ranking.

301 redirects and best practices for preserving organic traffic

So how can you avoid the impact of the migration on your store’s SEO ranking? This is where 301 redirects come into play. When your product URLs change, you need to implement 301 redirects to map the old Magento URL with the corresponding BigCommerce URL. This helps Google understand the changes in page authority and register the new URL.

Apart from the 301 redirects, you also need a detailed SEO strategy that includes best practices to preserve your store’s organic traffic. This includes metadata optimization, continuous site performance monitoring, and keyword research. You will also need to create a new XML sitemap for your BigCommerce site to help Google discover your pages.

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Testing and Quality Assurance

Once your Magento to BigCommerce migration is complete, you need to implement a thorough testing procedure. The BigCommerce store needs to be tested for bugs, errors, and responsiveness on both web and mobile platforms. 

The importance of testing during and after migration

When you consider migrating any eCommerce site, the testing phase is often left out. However, testing is actually the most important part of the entire process. Unless you go through this process, you have no idea of the functionality of your new site. 

This means you won’t be able to answer when a customer runs into a 404 error and asks you why the page isn’t working as expected. In order to avoid such an occurrence, you need to test the site’s functionality, such as browsing, carrying out product searches, adding items to the cart, and the checkout process.

Conduct user acceptance testing (UAT) to ensure a flawless customer experience

Once you are done with the migration, take time to address customer queries and pay careful attention to their user experience. You need to identify any loopholes or bottlenecks that may be disrupting the customer experience so that they can be fixed in time.

For instance, you need to pay careful attention to cart abandonment. 

  • Maybe your checkout process needs to be further optimized to ensure that there are no lost sales. 
  • Maybe you are not providing the right payment options.
  • Or the right payment options are not working.

Post-Migration Strategies

Implement post-migration monitoring and support

Taking it a step further from user acceptance testing, you need to keep providing support to customers who might be facing any kind of inconvenience at your site. Based on user feedback and analytics, you need to regularly monitor the user experience and incorporate features or updates to enhance it.

Apart from the URLs and site performance, you also need to check the following details in your post-migration review:

  • Check whether the products in your store display on the front end as well as the back end
  • Analyze loading times and check whether the site navigation is smooth
  • Ensure that each product is categorized correctly and appears in the search results
  • Go through all the links that take the user to the header, footer, and menus within the store
  • Run a demo by proceeding to checkout with an order on the BigCommerce site.

How L'azurde Thrived Post Migration from Magento to BigCommerce

Let’s look at the journey of a brand that has been successful after its Magento to BigCommerce migration. L'azurde is a well-known brand with a market presence in KSA, UAE, and Egypt. Their Magento-based store brought forth limitations in terms of integrations and scalability, which got them looking for alternative platforms. 

With the help of shopdev experts and the capabilities of BigCommerce, L’azurde took a step in the right direction to position itself as an omnichannel brand. The strategic move eliminated manual fulfillment operations and connected online and in-store channels seamlessly.

L’azurde now benefits from a compelling OMS (Omnichannel Management System) with a compelling storefront based on Next.js, developed by shopdev. It integrates seamlessly with the BigCommerce backend to connect the brand’s stores in UAE, Egypt, and KSA using the omnichannel model.

The brand now makes the most of a headless architecture provided by shopdev to ensure flexibility, performance, and scalability. As of now, the seamless integration of the BigCommerce front end and back end allows real-time data synchronization. As a result, customers are always able to see up-to-date product information and pricing. 

Key Takeaways

In summary, keeping up with the evolving eCommerce landscape requires both the right platform and the best practices to enhance user experience. The differences between Magento and BigCommerce arise from the simple fact that one is an open-source platform and the other is a SaaS-based platform. 

For your enterprise business, a Magento to BigCommerce migration can bring fruitful results in the form of high SEO ranking, improved customer experience, and better conversion rates. However, it's crucial to follow the right steps before, during, and after the migration. At the end of the day, if business efficiency, performance, and growth are your objectives, BigCommerce is definitely the platform for you.

Artificial Intelligence
1/8/2024
10 Best AI Shopping Assistant Tools for E-commerce in 2024
5 min read

E-commerce businesses have a common goal of enhancing the shopping experience for customers. While some brands find a way to understand what the customer is looking for, others don't. That said, we live in the age of artificial intelligence, which means we don't need to rely on guesswork.

This is where an AI shopping assistant comes in handy. It creates personalized recommendations and enhances search capability for added convenience. Here, we look at best shopping assistant tools for eCommerce in 2024.

How AI Shapes E-commerce Strategies

In a matter of years, AI has reshaped the way eCommerce sellers manage their operations. For instance, they are using generative AI to write compelling product descriptions. Customer support is now completely automated with the use of GPT4. It’s only a matter of time before AI creates paid ad campaigns and launches them on its own.

It's no surprise that the market value of AI in eCommerce retail was USD 6.63 Billion at the end of 2023. The value is projected to grow at a CAGR of 14.60% by 2032.

Here's how AI chatbot shopping assistants can benefit eCommerce businesses:

Personalized User Experience

When your goal is to stay ahead of the competition, personalization is your ticket to success. AI analyzes search patterns, behaviors, and conversations with chatbots to learn customer information. This information is then used to offer personalized product recommendations. Today, AI shopping assistants can help solve customer queries without human input. Not only that, but they also make it easy for customers to find the desired products using visual search.

Streamlined Operations

Apart from content creation, AI is also improving operational efficiency. E-commerce retailers are leveraging AI tools to reduce operational costs and reduce time to market. For instance, AI automates inventory management by analyzing supply and demand. It identifies raw materials and supplies you need and suggests the right vendors. AI can also analyze sales data and customer behavior. 

Improved Sales

AI can also improve sales by providing eCommerce businesses with valuable insights. It analyzes competitor pricing strategies to help you optimize yours. Moreover, enhancing search capabilities using AI shopping assistants can also help boost sales. It can identify cross-selling and upselling opportunities to extract higher revenue. 

What to Look for in AI Tools for E-commerce

With more and more AI solutions being introduced to the e-commerce market, how can you select the right one for your business?

Let’s start with the basics:

  • Identify the problem you want to solve using the tool. Your eCommerce business can use AI to improve data analysis and enhance customer service. 
  • Learn whether the tool can improve efficiency or reduce operational costs. 
  • Evaluate the best AI-powered personal shopping assistant tools available in the market. Look for the capabilities that will enhance your operations. 
  • Check for accuracy, integration, and scalability. Determine whether the AI solution can integrate with your eCommerce infrastructure.
  • Ideally, the AI tool must be able to work even when your business grows in terms of size, channels, or locations. 
  • Consider the appearance, customizability, and user-friendliness of the AI solution. Your teams should not find it difficult to get their heads around the tool’s functionality.
  • Another important aspect of AI tools is that they learn from the data they process. Does the tool require large datasets or specific formats?

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10 Best AI Shopping Assistant Tools for 2024    

While every AI shopping assistant tool is built with the same motive in mind, they all have their pros and cons. At the end of the day, the right tool for your business is the one that fulfills your unique requirements.

1. shopdev Shopping Assistant 

shopdev's AI-powered Shopping Assistant transforms e-commerce. It provides personalized product recommendations, enhancing discoverability, satisfaction, and conversions. Empower your customers with our advanced AI-powered chatbot.

Conversational shopping assistant assists customers through their online shopping journeys. Its algorithms detect keywords entered by customers to find the right products.

AI-powered shopping recommendations are provided to customers based on the search query.

Multimodal AI combines information from different sources of a product page to deliver accurate results.

Features 

  • Personalized recommendations based on search history and preferences
  • Object detection to differentiate between products
  • Product discovery to find the right product for the customer
  • Customizable UI for your brand’s design language
  • Natural language processing to interpret search queries
  • Computer vision to extract data from images
  • Omnichannel support for connecting physical and online channels
  • Multilingual support to serve a wide range of customers in different regions

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2. Manifest                       

Manifest AI promises to improve sales by creating long-lasting relationships and is said to cut down the customer drop-off rate by 40%.

Natural language processing provides the capability to interpret any kind of customer query and help customers make purchase decisions. This means that the tool will find the right product even if the customer enters a vague description. 

Image classification makes product search significantly easier and faster. To be on the safe side, Manifest AI provides 5 product recommendations as a result of the customer query. 

Customizable UI allows eCommerce businesses to follow their brand guidelines. 

Features

  • Product discovery
  • Natural language processing
  • Image classification
  • Customizable UI
  • Multilingual support

3. Shopping Bot       

ShoppingBot is a personalized chatbot that is trained on your website data to assist visitors in the best ways possible. It works around the clock to help eCommerce retailers enhance customer satisfaction and make them brand advocates.

Easy to set up with email support for all users. 

Ability to respond to customer queries within 48 business hours.

Strong security mechanisms with firewalls and encryptions to keep all of your data confidential.

Multilingual support is beneficial for eCommerce businesses operating out of multiple countries. 

Features

  • Personalized recommendations
  • Secure conversations
  • Product discovery
  • Natural language processing
  • Image classification
  • Multilingual support

4. Shopmate

Shopmate is an AI chatbot that boasts 24/7 customer support, but it only needs 3 minutes to know your products and store information.

It analyzes your customers’ shopping history and preferences to intelligently recommend the right products. 

Support handling feature allows you to answer customer queries instantly and efficiently. 

Automatically analyze information from blogs, internal documentation, and FAQs on your site. This allows the AI shopping assistant to provide customers with accurate information.

Features

  • Fast processing speeds
  • 24/7 availability
  • Personalized recommendations
  • Secure conversations
  • Product discovery

5. Intercom AI Chatbot    

Intercom AI chatbot is focused on improving team efficiency and resolving customers’ concerns. The chatbot resolves 50% of support questions on its own, within an instant.

The chatbot named Fin is the result of a big breakthrough by Intercom in the field of sophisticated AI language models. 

It provides accurate answers and maintains a conversational tone to make your customers feel at home.

Built-in safeguard to ensure that Fin only answers customer queries based on your brand’s guidelines. 

It’s an AI tool you can trust with your brand’s secrets as your team can also monitor all of the bot’s responses.

Features

  • Natural language processing
  • Accurate product discovery
  • Personalized recommendations
  • Secure conversations

6. Infichat            

Infichat is an AI-powered shopping chatbot that assists your customers in product searches. Customers can ask questions based on the descriptions, sizes, and colors of the product.

Personalized recommendations based on their shopping history. 

24/7 availability makes it one of the best tools to enhance customer satisfaction and boost sales.

Minimal setup required. The AI tool is easy to use for any of your team members. 

Features

  • Seamless customer support
  • Instant product discovery
  • Personalized recommendations
  • 24/7 availability

7. Tidio AI       

Tidio AI, a user-friendly and functional live chat app comes with the best customer support out there. The chatbot and ticketing solution is purpose-built to serve mid-sized eCommerce businesses that wish to solve customer problems and improve sales.

Customization based on your brand requirements.

Easy setup with extensive chatbot template library. These templates cover both sales and support scenarios, meaning your eCommerce brand doesn’t have to worry about responding to longer conversations. 

The advanced AI behind Tidio is capable of holding long conversations with customers in case of highly-priced items.

Features

  • Customization
  • Built-in templates
  • Seamless customer support
  • Instant product discovery

8. Chatfuel     

Chatfuel takes the convenience of setting up an AI chatbot to the next level. You don’t need any special skills in coding or programming languages. All you need to do is click a few buttons to select what you like the most. 

Drag-and-drop builder for creating your customized chatbots.

Ready-to-use templates and free catalog for popular eCommerce platforms.

Easy to use with an organized UI which makes the work all the more productive. 

Integrates with external systems to enhance automation and performance. 

Features

  • Drag-and-drop functionality
  • Easy to use
  • Customization
  • Ready-to-use templates
  • Free catalog

9. Verloop                

Verloop enhances your customer support by responding to customers in the way they like. This includes voice conversations, WhatsApp, Instagram, and web applications just to name a few. 

It is user-friendly and allows you to carry on conversations with up to 3 customers at the same time. 

Your team can address more customer queries in less time

You need fewer customer support executives to pay salaries to. 

Features

  • Customized bot solutions
  • Personalized conversations
  • One-to-many conversations
  • Instant product discovery
  • 24/7 availability

10. Giosg 

Giosg is a sales acceleration solution that automates live chat using AI chatbots. Its interactive content helps build engaging online experiences for your shoppers and turns them into loyal customers.

Easy navigation and built-in tools for marketing, communication, and handling support tickets.

Interaction builder allows you to create elements and interactions with customers on your website when required.

Features

  • Seamless customer support
  • Easy navigation
  • Interaction builder
  • 24/7 availability

Key Takeaways

As technology evolves, eCommerce businesses are looking to speed up their operations. AI shopping assistants are quickly gaining popularity in the industry. Both businesses and customers benefit from personalized product suggestions and accurate search results.

If you’re looking to build brand loyalty through AI-based personalized recommendations, look no further. shopdev’s AI shopping assistant has everything you need to take your brand’s customer experience to the next level. 

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Artificial Intelligence
11/14/2023
15 Generative AI Use Cases for Enterprise Businesses
5 min read

In today’s tech-driven era, enterprise leaders find themselves at a crossroads where they have to deal with high-interest rates, inflation, and geopolitical concerns. They look for ways to accelerate product development and enhance service quality. One such ‘way’ is through a technological revelation you have already heard of -  Generative AI.

Generative AI isn’t just the most buzz-worthy tech trend of 2023. Between 50% to 60% of all organizations have already adopted the disruptive technology.

Whether you consider customer relationship management (CRM), enterprise resource planning (ERP), product engineering, or service delivery, the applications of generative AI for enterprises just keep growing.

Generative AI Enterprise Use Cases   

Generative AI is a subset of AI that goes beyond data analysis to create new and unique content. Based on patterns learned from the data they are trained with, generative AI tools like ChatGPT, DALL-E, and StyleGAN have demonstrated groundbreaking results.

In general, the enterprise use cases for generative AI revolve around automating, simplifying, and enhancing the quality of operational workflows.

Quick Automation of Project Workflows    

When it comes to workflow automation, generative AI helps enterprises, especially marketing and sales-driven organizations with content creation. With automated content generation, businesses can speed up their entire digital marketing workflow. Generative AI can create a variety of engaging blog posts and ad copies, as well as personalized social media posts and product descriptions to target the right audience.

Simplify Repetitive Tasks for Employees

Regardless of the industry you pick, there are always going to be repetitive tasks that become a hurdle for innovation in enterprises. In this scenario, generative AI not only streamlines repetitive tasks for employees but also provides consistent and high-quality outputs. This means you have better customer engagement and a higher number of satisfied customers across the board.

Maintain High-Volume Production Standards

As generative AI continuously learns from the data it processes, it can interpret complex data to refine production standards. Whether you are on the factory floor or in any other part of the organization, generative AI equips you with the right tools to address quality standards in production. 

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How Enterprises Are Using Generative AI Today

Although the technology itself is the same for all, not all enterprises are able to use generative AI to its full potential. In some enterprises, it may be used as part of a conventional subscription-based tool to improve operations to a certain extent. In other cases, organizations are even building their own AI models to add to their tech stack.

Industries Embracing Generative AI

Let’s look at the ways different industries are utilizing the power of generative AI:

E-commerce and Retail

To understand the use of generative AI in retail, we take the example of Shopify. The eCommerce platform has now introduced a feature called Shopify Magic, which allows retailers to generate product descriptions using generative AI. 

Users can input their desired tone and keyphrases for the product-related content they want to generate. Then, Shopify’s magic tool automatically generates a description based on the given parameters. In the background, of course, its generative AI working its magic. 

Shopify makes the list of a handful of retail enterprises that have adopted generative AI, and even though Shopify Magic is still in its infancy, it is being well-received.

Software Development and FinTech

Where there is online shopping, there ought to be transactions. That brings us to two of the notable industries that have a high AI adoption rate - FinTech and software development.

Stripe is a renowned financial services SaaS provider that uses OpenAI’s GPT-4 to enhance its operations. 

The generative AI tool allows Stripe to improve query management, summarization, documentation, and more. An internal feature called Stripe Docs is also available for users to enter their natural language queries related to documentation. 

Upon submitting their query, users receive a response where Stripe’s AI summarizes and extracts important information in a human-like format. Moreover, the SaaS provider is also working with OpenAI and other generative AI companies to create smoother subscription and checkout processes for customers. 

Travel and Hospitality

Here’s yet another industry that is using generative AI to improve customer experience. The travel and hospitality sector is all about ‘looking after’ the customers, and Expedia understands that. 

Expedia uses the beta version of the popular generative AI tool ChatGPT for its travel planner. The AI integration allows Expedia users to ask questions and receive recommendations for travel, lodging, and other recreational activities. Not only that, but it also saves the suggested hotels and destinations using an AI-based feature. This means that customers can see what was recommended earlier and easily book their next destination.

In the context of enterprises, Expedia’s AI use case comes in handy for frequently-travelling employees. The solution streamlines the travel process and gives the employees more time for their high-priority tasks.

how generative ai will affect industries in coming years

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Generative AI Use Cases: Ethics and Compliance

Before we get into generative AI use cases, here’s a quick heads-up. With all the applications and developments in the field of generative AI, we often ignore the fact that the technology is still in its infancy. This means that there are still many unknown factors. For instance, the end-users are not aware of the way the AI models are trained, or what data is used to train them. 

The fact is that generative AI models have a wide range of capabilities that can be very useful, but also very harmful when it comes to cybersecurity. Not to mention, the quickly growing skillset of generative AI models may result in them replacing skilled professionals.

Considerations for Ethical Use of Generative AI

With that said, what should enterprises do to ensure that they are ethically using generative AI? Here are a few tips to get started:

  • Do not use sensitive data to train an AI model. The inputs must be depersonalized and non-sensitive
  • Stay updated with current generative AI trends so that you know which tools are credible
  • Set up an ethics policy for AI usage in your enterprise. It should guide internal users to use the right AI tools
  • Provide training to all employees so that they stay one step ahead of AI and use it to advance in their careers.

15 Implementable Generative AI Use Cases 

Code Generation, Documentation, and QA

Generative AI assists software developers and programmers by writing and completing code faster than ever before. Software teams use AI tools to write code in multiple languages and speed up their development process, hence increasing their productivity and efficiency. 

Once the code is written, the most useful and quickly emerging use case of generative AI comes into play. Quality assurance is one of the most crucial phases in software development. With generative AI, it becomes as easy as implementing the right tools and entering the right prompts. AI models are capable of fixing bugs, analyze test cases, and also create various types of documentation.

Furthermore, generative AI-based coding tools are now advancing beyond the basics to help non-developers write code by using simple queries. By entering scenario-based queries in natural language, they can leverage generative AI to write code that works. This is a giant leap in the world of enterprises that are aiming at tech democratization.

Product and App Development

While writing code speeds up the process for software developers, generative AI is also being used to develop entire apps and products. From analyzing material options to proposing new designs, it has given a futuristic angle to product development. With generative AI, iterative product development teams can make design refinements in real and perform more efficiently.

Apart from assisting the development of digital products and apps, generative AI also finds use cases in semiconductor chip manufacturing and design. Not to mention, it has significantly improved customer support services by allowing companies to build chatbots based on OpenAI foundation models. Examples of such solutions include GPT-4, A121 Labs, Stability AI, and MOSTLY AI.

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Blog and Social Media Content Writing

As we have seen earlier in this blog, generative AI is empowering marketing enterprises with automated content creation. Every marketing team aims to save time and resources and have a favorable time-to-market. 

Generative AI is good news for marketers, as its large language models (LLMs) allow you to create unique content for blog posts and social media platforms. It also helps create engaging content for business websites and prevents you from missing out on details when writing product descriptions.

Most of these AI models allow users to provide instructions and specify the tone, voice, and other aspects of the content they want to generate. Enterprise users can even input past content written by their company and prompt the AI tool to follow the same tone. Examples of these AI tools include HubSpot Content Assistant, Phrasee, Notion AI, and Jasper.

Inbound and Outbound Marketing Communication

Apart from blog and social posts, marketing teams also need to enhance their inbound and outbound marketing campaigns. The traditional process requires employees to manually create contextualized emails and chats. These are then sent to current and prospective customers. Generative AI solutions are now automating this process by creating and sending emails. 

Not only that, but generative AI can also qualify certain contacts for the next step in the enterprise’s customer relationship management (CRM) platform. Examples of AI solutions enhancing project management capabilities in enterprises include Salesforce Einstein GPT and Twain.

Graphic Design and Video Marketing

Graphic designing and video creation are also crucial to a successful digital marketing team. Generative AI helps creative designers by generating realistic animations, images, and audio that can improve graphic designing and video marketing projects. 

In addition to videos and images, some generative AI service providers also offer avatars and voice synthesis features. These allow marketers to complete their video production without the need for actors, expertise, or equipment.

While the avatars and voices being offered today still require some manual input to replace real human speakers, it is still a step ahead in the right direction. Rephrase.ai, Diagram, Synthesia, and Lightricks are examples of AI solutions offering graphic design and video marketing services. 

Entertainment Media Generation

Moving on, the entertainment media industry is probably the one to benefit most from high-quality and realistic AI-generated images. Generative AI finds applications in movie making, video games, virtual storytelling, VR experiences, and podcast generation

The entertainment industry finds it convenient to use these AI tools instead of setting up cameras, editing footage, and recording audio. According to tech experts, generative AI is all set to revolutionize film content creation, script writing, and video production. As we speak, AI tools like Latitude Voyage, Plask, Charisma, and Stability AI’s Stable Diffusion are being used to create interactive non-player characters (NPCs).

Performance Management and Employee Training

Apart from enhancing operational efficiency and accelerating processes, generative AI is also being used to analyze business performance and train employees. For instance, generative AI can be used in contact centers of an enterprise to analyze call documentation. 

By using sentiment analysis, generative AI can provide business owners with valuable insights. With this information, you can assess customer service quality and set up training sessions for employees. Conversational AI tools like Gong, CoachHub AIMY, and Anthropic Claude allow your employees to get performance feedback and understand areas for improvement. 

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Reporting and Data Analytics

One of the reasons why generative AI has quickly become a part of enterprise reporting is its ability to process massive amounts of data. When it comes to analysis of unstructured and qualitative data, nothing can match the power of generative AI. It is improving business reporting and intelligence by providing real-time data-driven insights.

Of the areas where generative AI is being used, data narratives are probably the most interesting. There are highly contextualized explanations of datasets provided by AI that are far more advanced than typical visualizations and data dashboards. Examples of such AI solutions include Narrative BI, Dremio, and SparkBeyond Discovery.

Customer Support and Customer Experience

Generative AI chatbots aren’t really a new thing. They handle customer service queries along with virtual assistants all day long. That being said, the chatbots that have been used for straightforward customer service engagements are not as advanced as generative AI. 

Now, with advanced AI models, you get additional resources to provide comprehensive human-like answers without manual inputs. Enterprises that have adopted this technology in its early days are building their own customer service solutions using OpenAI’s ChatGPT and API. Forethought SupportGPT, Gridspace, and IBM Watson Assistant are some of the examples of chatbots that are enhancing customer experience in enterprises.

Pharmaceutical Drug Discovery

Generative AI isn’t just the future of the pharmaceutical industry. It is already being used to enhance the efficiency of drug discovery and design operations. Using the valuable insights provided by generative AI, scientists are creating novel molecules and discovering disordered proteins. They are also designing better drugs and predicting clinical trial results using the groundbreaking technology.

This particular enterprise use case of generative AI is expected to grow by a significant margin in the years to come. Entos, Aqemia, New Equilibrium Biosciences, and Insilico Medicine are a few examples of AI tools being used in the pharmaceutical industry.

Medical Diagnostics and Imaging

When you consider the field of medical diagnosis and imaging, generative AI is still a relatively new concept. However, its potential is growing exponentially. As AI-based image processing and generation tools become more capable of zooming into medical images, professionals can now get a better understanding of areas they haven’t seen so clearly before.

Even in its infancy, generative AI is performing medical image analysis and offering basic diagnostics. Well-known tools like ChatGPT and GPT-4 are being tested in the pathology space, with ChatGPT even passing the U.S. Medical Licensing Exam. That said, the results still need to be cross checked with medical professionals and analyzed for anomalies. Other examples of AI solutions in medical are Paige.ai and Google Med-PaLM 2.

Consumer-Friendly Synthetic Data Generation

Considering the potential security concerns that can be caused by generative AI, you may assume that this is just one of its negative aspects. But hold on - what if we could use the same factor to improve the data being generated and make it more consumer-friendly?

When you get your prompts right, generative AI will provide you exactly what you’re looking for. It can be used to create synthetic copies of data that is actually sensitive, hence allowing analysts to get what they need without being non-compliant. With these copies, data analysts and other enterprise members can create their own AI models. Examples of synthetic data generation tools include Infinity AI, Syntho Engine, Synthesis AI, and MOSTLY AI.

Smart Manufacturing and Predictive Maintenance

The manufacturing industry sees another use case of generative AI for enterprises. As it continues to transform modern manufacturing, generative AI is helping workers innovate and achieve their production goals. With predictive maintenance, generative AI models can create to-do lists and timelines to assists enterprises in improving their workflow. These models also suggest areas for improvement and simplify your process of collecting data from different parts of your production line.

Moreover, another process called inverse design also uses generative AI to analyze what’s missing in a process. Tools like Clarifai, C3 Generative AI Product Suite, and Biomatter can identify missing materials from a process and generate their replacement to suit the requirements. 

Fraud Detection and Risk Management

Another area of enterprises that must not be missed is fraud detection and risk management. Although your business might get lucky without such measures, it’s always better to have AI by your side. In this use case, generative AI analyzes transaction data and identifies anomalies in the patterns. It helps in fraud detection to ensure smooth operations in finance and insurance sectors.

As of now, enterprises must invest in anomaly and fraud detection solutions that use generative AI to catch even the slightest deviation in transactional patterns. Simplifai InsuranceGPT and Docugami are the best known examples of such solutions.

Optimized Enterprise Search and Knowledge Base

Where there are enterprise tools, there needs to be documentation and a knowledge base. Generative AI is helping enterprises enhance both internal and external search capabilities. AI tools like Elasticsearch Relevance Engine, Glean, and Coveo Relevance Generative Answering not only identify enterprise resources for users but also company applications, web properties, and messaging tools.

Visitors can get a self-service by using generative AI tools incorporated into business websites and customer-facing displays. They can get answers to their brand-related questions and also get the right resources using AI chatbots.

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Key Takeaways

Considering the rapid evolution of AI, it's not hard to guess that there will be even more enterprise use cases for generative AI in the days to come. As AI technology develops new capabilities, enterprises will have more opportunities to improve their operations. If you are an enterprise looking to adopt generative AI, you need to find the right model that works in your specific use case and aligns with your objectives as well as your customers.

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