• As you survey the cybersecurity market, what’s the current biggest trend?
• You’ve said that “It’s a matter of when, not if, a cyberattack slips past perimeter defenses, so they must have the strategies in place to respond to a successful breach quickly and effectively.” So what is that strategy, in a nutshell?
• How is Veritas addressing the security needs of its clients? What’s the Veritas advantage?
• You’ve also said that “Resilience is a team sport: No one vendor can solve an organization’s entire cyber resilience challenge.” How should companies evaluate complementary IT partners to provide end-to-end cyber resilience?

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An interesting data point from my research is that today, 90% of organizations compete on CX compared to only 27% five years ago. In many cases, a single, bad experience can mean losing a customer.

Customer experience often starts in the contact center, but how companies interact with their customers continues to broaden, and brands must enable customers to communicate with them using the channels of their choice.

DEWA and Avaya Showcase the Metaverse for Customer Happiness

At GITEX Global 2023, currently being held in Dubai, Avaya and the Dubai Electricity and Water Authority (DEWA) partnered to demonstrate an integrated digital interactive hub that enables a range of services and integrates customer services with the DEWAVerse platform, which allows communication in a metaverse environment.

For DEWA, Avaya helped the company complete a digital transformation project in its customer happiness center. At the event, I had a chance to meet with Abeer Eladaway, Deputy Senior Manager of DEWA, and she explained that it was the goal of His Highness Sheikh Mohammad bin Rashid Al Maktoum, the ruler of Dubai, to have all government entities provide best-in-class customer service.

This prompted the name change of DEWA’s customer service centers to customer happiness centers. DEWA actively monitors all customer interactions and has made customer satisfaction a top initiative.

One of the interesting differences regarding the Middle East is that the public sector drives innovation and aims to set an example for private enterprise. This starkly contrasts with the US and Western Europe, where it seems government entities go out of their way to provide bad service.

Also see: Top Digital Transformation Companies

Eladaway expressed that while the older generation will likely prefer face-to-face interactions, many of the younger citizens will prefer to use a virtual one, so the organization designed DEWAVerse as that option.

Based on Avaya technology and delivered through call center firm Moro, the solution includes an integrated digital interactive hub for DEWA customers to access service through an interactive voice system enhanced by AI. This system allows agents to communicate with customers, answer inquiries, and complete transactions in the virtual world.

In the virtual environment, customers have their own private space to see their electricity and water consumption, and carbon footprint. Customers can also interact with live or virtual agents and pay bills through the interface. There is also a feature in which DEWA will recommend different appliances, and customers can measure the power and cost impact.

This implementation, which is hosted and managed by Moro in its data center, enables customers to contact the DEWA using a variety of communication channels, including phone, email, video, and text. Avaya says that multi-channel engagements are fully integrated so that engagements can transition from one medium to another.

Avaya added that an IVR system now offers options for self-service options so that customers can conduct several transactions without any agent involvement. Avaya utilized artificial intelligence in building a dynamic menu that can identify, assign, and prioritize registered callers so they receive the appropriate level of service.

There has been great debate regarding the viability of the metaverse. Once a skeptic, I’ve since changed my mind because it provides an alternate form of communication. People were skeptical of e-mail initially, the web, and social media, but those have proven to be preferred by those “born in” that era.

Motul’s Cloud-Based Solutions for Improved CX and EX

Another customer experience example Avaya had on display at GITEX was with oil and lubricants company Motul. The company has adopted cloud-based solutions from Avaya to improve customer and employee experiences across many different interaction points using a suite of Avaya’s cloud-based solutions.

Avaya said that Motul has deployed the Avaya Experience Platform, which integrates with Avaya Cloud Office (ACO) by RingCentral. The solution connects more than 400 of Motul’s employees around the globe, enabling them to engage more closely with customers and each other, regardless of location.

Avaya’s Experience Platform, a cloud-based contact center solution, helps Motul create and track KPIs to transform its customer service processes. The platform’s cloud-based attributes translate into an implementation without the massive disruption often accompanying customer service upgrades. In addition, Avaya says it requires little employee training.

GITEX Global 2023 has been an action-packed event. Avaya is showing that it is focused on the future and providing companies with real solutions that work today. These announcements show the importance of experiences and underscore how critical it is for vendors to share real case studies. Both DEWA and Motul are using Avaya for novel solutions that show the power of digital transformations that are aimed at improving experiences.

For more information, also see: Digital Transformation Guide

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In this guide, learn about some of the best AI video generator tools on the market today, their pros and cons, pricing, and what you should be looking for if you’re interested in using AI to improve your video workflow.

Table of Contents: Top AI Video Tools

• Top AI Video Generators: Comparison Chart
• Synthesia: Best for AI Avatars
• AI Studios: Best for Text-to-Speech Quality
• InVideo: Best for Social Media and Content Marketing Videos
• Pictory: Best for AI Video Summaries and Highlights
• Lumen5: Best for Ease of Use
• Key Features of AI Video Generation Tools
• How We Evaluated the Best AI Video Generation Tools
• Bottom Line: Top AI Video Generators and Tools

Top AI Video Generators: Comparison Chart

Synthesia: Best for AI Avatars

Synthesia is a leading generative AI startup that helps users transform text scripts and instructions into videos. The solution is particularly well-known for its AI avatars: Users can choose between more than 140 AI avatars — or create their own avatars — and generate audio in more than 120 languages.

Additionally, users have the option to customize backgrounds and branding colors, add soundtrack music and other audio elements, and insert markers to create simple animations.

Users often select Synthesia for its ease of use, full slate of features, natural-sounding AI avatars and extensive artificial intelligence avatar library, and collaborative elements.

For example, once a draft of a video is complete, the creator can easily share that internal link with other users and receive feedback directly on the video platform’s feed. From there, they can embed, download, or otherwise move the video to a new location once it’s ready to be shared more widely.

Pricing

The following two subscription plans are available for Synthesia users:

• Personal: $22.50 per month, billed annually, or $30 billed monthly for one seat and 10 minutes of video per month.
• Enterprise: Pricing is customized based on the number of seats users need. Prospective buyers should contact Synthesia directly for pricing information.

Users also have the option to create one basic demo video for free or to receive a free personalized demo if they are interested in Synthesia for a larger enterprise.

Key Features

• More than 140 stock AI avatars and options for custom and branded avatars.
• AI script assistant and screen recorder.
• More than 65 stock templates as well as branded video template options and a media library.
• Auto-generated closed captions.
• MP4 downloads and video embeds.

Pros

• Live customer support is available to all users.
• More than 120 stock languages and voices are available to users, which is more than nearly any other competitor.
• Customers overwhelmingly consider this an easy-to-use and easy-to-setup tool.

Cons

• Personal plan users are limited to 10 minutes of video per month and one seat.
• Personal plan users cannot access branded templates or AI avatars.
• Some users have had difficulties with speech and audio quality in generated content, especially for less commonly used languages.

Also see: Best AI Writing Tools 

AI Studios: Best for Text-to-Speech Quality

AI Studios from DeepBrain AI is a competitor of Synthesia for text-to-video and/or audio-to-video content generation. It has been particularly well received for its speech and audio quality, giving users the ability to easily mix audio and adjust tones and accents for AI avatars that better reflect what sounds natural to their audience.

DeepBrain also does a good job of showcasing how the tool can be used for different enterprise use cases, including education, sales, news and media, entertainment, retail and commerce, and financial services.

In financial services in particular, AI Studios and its avatars have been used by major enterprises to create virtual finance analysts for personalized videos and virtual lobby assistants for bank kiosks in South Korea.

Pricing

AI Studios is available in three subscription options:

• Starter: Between $24 and $144 per month, billed annually, or $30 and $180 billed monthly. Pricing adjusts based on the number of video minutes subscribers select per month. Users can choose either 10, 20, 40, or 60 minutes of video per month.
• Pro: Between $180 and $480 per month, billed annually, or $225 and $600 billed monthly. Pricing adjusts based on the number of video minutes subscribers select per month. Users can choose either 90, 120, 180, or 240 minutes of video per month.
• Enterprise: Custom pricing. The plan includes up to 50 scenes per video, custom AI avatars, and 24/7 priority customer support.

Key Features

• More than 100 AI avatars in more than 55 languages.
• More than 500 prebuilt video templates for marketing, social media, and other business needs.
• Drag-and-drop video editor with closed captioning.
• Compatible with text and audio scripts.
• API access for Pro and Enterprise users.

Pros

• Strong audio editing features for volume, pitch, pronunciation, and audio mixing needs.
• Text-to-video content generation can be completed in five minutes or less for most videos.
• Pricing is incredibly modular and allows users to select how many minutes of video they want to pay for each month.

Cons

• Import maximums, especially for PowerPoint, can be limiting; in general, presentation tools are somewhat lacking.
• Extra video minutes do not roll over at the end of each month.
• Compared to some of its competitors, AI Studios is not as easy to set up and use from the outset.

Also see: AI Detector Tools

InVideo: Best for Social Media and Content Marketing Videos

InVideo is a video-making platform with AI features that support everything from script generation and avatar generation to slideshow design and YouTube video editing. Its template library is one of the most extensive in the market, covering topics and format types for advertising, slideshows, memes, YouTube, Instagram, music videos, breaking news, and logo videos.

With InVideo AI, users can make content that is tailored to specific platforms, such as YouTube, or to specific looks and feels that match a brand’s identity or goal for the video. Additionally, users can input a target audience when generating a video, ensuring the AI picks design elements and other features that fit that buyer persona’s expectations.

Pricing

InVideo is available in three subscription plans:

• Free: $0 per month for unlimited team members and some limited features.
• Business: $15 per month, billed annually, or $30 billed monthly.
• Unlimited: $30 per month, billed annually, or $60 billed monthly.

Key Features

• More than 5,000 project templates; additional premium templates for Business and Unlimited plan users.
• AI script generation.
• Team sharing and shareable links.
• Customizable intros and outros.
• Event and social-media-calendar-driven project templates.

Pros

• All users are given access to branding tools for brand presets, intros, and outros.
• Even InVideo’s free plan supports unlimited team members and users, making it a great tool for affordable collaboration.
• The Social Media Calendar feature is a unique way to make videos based on the most popular social media holidays; in general, this platform offers a range of useful features for social media content creation.

Cons

• Free plan users are not able to export any of their video projects or access the mobile app.
• Some users have commented on difficulties when working with customer support.
• While the template library is extensive, it lacks useful search and save functionalities, making it harder for users to find and save the templates they want to use most.

Also see: Best Artificial Intelligence Software

Lumen5: Best for Ease of Use

Lumen5 is an AI video generation tool that is most commonly used for text-to-video content generation from long-form blogs and news articles. Companies with limited digital marketing prowess frequently select this tool because it is easy to use, offering users a drag-and-drop editing tool, maker templates and tools, and the ability to automatically generate videos from blogs and RSS feeds.

While the platform may not be the best for a larger creative team that wants to make videos collaboratively, it is a strong contender for individuals and solopreneurs who are managing content for multiple brands.

Users have the option to upload multiple brand kits with certain plans; create multiple workspaces; and upload custom colors, fonts, and watermarks. The free Community plan is also a generous option, giving individuals the bandwidth to create up to five videos per month at no cost.

Pricing

Lumen5 is available in five plan options:

• Community: $0 for up to five videos per month.
• Basic: $19 per month, billed annually, or $29 billed monthly.
• Starter: $59 per month, billed annually, or $79 billed monthly.
• Professional: $149 per month, billed annually, or $199 billed monthly.
• Enterprise: Custom pricing.

Key Features

• Smart Summarization feature for blog-to-video content transformations.
• Automatic language detection and matching.
• Built-in photo, video, audio, and AI voiceover media library.
• Automated video generation from RSS feeds.
• Custom branding and brand kits.

Pros

• Although it has limitations, the free Community plan still gives users the opportunity to work on up to five videos per month, which is much more than most free plan and trial options. All paid plans allow users to create unlimited videos per month.
• Lumen5 is generally considered an easy-to-use tool; its video tools and maker tools walk users through the steps for varying drag-and-drop video editing tasks.
• While many similar platforms only support one brand per account, the Professional and Enterprise plans for Lumen5 allow users to work with up to three brand kits.

Cons

• Template options are somewhat limited for Lumen5 users; users also cannot access AI avatars or most speech synthesis tools.
• Only the expensive Lumen5 Enterprise plan supports more than one user per account.
• The Starter, Professional, and Enterprise plans are fairly expensive compared to similar packages from competitors.

Also see: The Benefits of Generative AI 

Pictory: Best for AI Video Summaries and Highlights

Pictory is another AI video generation platform that is best suited for content marketing and social media video projects. It is a particularly effective solution for creating micro-content, or shorter clips and highlight reels from existing long-form content.

The platform is designed to automatically generate these shorter snippets, making it possible for users to get more content, engagement, and reach from a single project.

While the platform is most frequently used by digital creators and marketers, it can also be used by e-learning teams, coaches, and other users who need an accessible video format. Its auto-generated summaries are especially helpful to teams that want to offer more digestible ways to consume video content.

Pricing

Pictory is available in three subscription plan options:

• Standard: $19 per month, billed annually, or $23 billed monthly.
• Premium: $39 per month, billed annually, or $47 billed monthly.
• Teams: $99 per month, billed annually, or $119 billed monthly.

The platform can also be tested through a free trial option, which gives users the opportunity to create up to three video projects, each up to 10 minutes long.

Key Features

• AI summaries and transcriptions; users can also remove filler words from scripts and spoken audio.
• AI voice narration and voiceovers with support from ElevenLabs.
• Highlight reel and short clip creation.
• Academy for video marketing masterclasses and other learning resources.
• Hootsuite integration for social media projects.

Pros

• Users can easily transform a blog post or other long-form written content into video content that removes filler words and any text that doesn’t make sense in the new format.
• In addition to highlight reels and video summaries, videos can be auto-captioned and auto-transcribed, making this a great tool for greater accessibility.
• The vendor offers video marketing masterclasses, case studies, a blog, and a creator community to give users the resources they need to make more engaging video projects.

Cons

• Pictory does not offer AI avatars to its users.
• No account option allows more than three users per account, which can be incredibly limiting for video team requirements.
• Compared to many other competitors, Pictory is fairly expensive.

Also read: Generative AI for Business: Top 7 Productivity Boosts

Key Features of AI Video Generation Tools

Text-to-Video Content Generation

Many users do not have coding experience and/or the time to learn the finer details of video software.

That’s why many AI video generation tools include text-to-video content generation capabilities, allowing users to easily turn their scripts or other written text into video content that may include human-looking AI avatars, AI voices, and other elements that create a professional-looking and sounding video.

Video Templates

A number of AI tools now give users a baseline video template from which to build their video content. These templates may focus on specific industry use cases, a certain social media or digital platform, or a video format with animation or transitional elements.

Users can often customize these templates and add their own branding, but the video template gives them the creative ideas and basic design to get started.

AI Avatars

Many businesses do not have the budgets to pay actors or employees to act as talking heads for brand videos, but they nonetheless want the personal touch of an onscreen personality. AI avatars can be developed to match different appearances, genders, and other expectations, with personalities, tones, accents, and other unique features added to synthetic voices.

The best AI avatar solutions create natural-looking avatars and give users the ability to custom-create their own avatars. These avatars can be used for personalized sales and marketing videos, e-learning and training videos, and other forms of media that benefit from a friendly face.

Speech and Audio Synthesis

With an AI video tool, AI speech and audio synthesis make it so any number of videos can be made without a human actor or voice. These platforms take text or rough spoken recordings and transform them into video-ready voices that are synthetically generated.

These voices should be available in a variety of languages and, in most cases, users are able to adjust the tone, pitch, accent, and other elements of speech to make the voice sound more believable.

Low-Code/No-Code Usability and Video Editing

Regardless of how much work AI features can do to put together the final product, users typically want some hands-on control over the video creation process.

To make this as simple as possible, most AI video generation tools provide a low-code/no-code user interface, giving customers the ability to move around slides, audio and visual elements, and other pieces of their video with a drag-and-drop editing tool.

On a related topic: What is Generative AI?

How We Evaluated the Best AI Video Generation Tools

Ease of Use – 30%

Most people using an AI video generation tool have little to no experience with traditional video software and its complex features. AI should handle the most difficult aspects of video generation, especially for users looking to create a range of videos at scale; this is why we’ve decided to give “ease of use” a larger weight in our evaluation.

Customer reviews that comment on ease of use, strong customer support, low-code/no-code interfaces, and strong collaboration features all contribute to the ease of use score for each of these tools.

Enterprise Use Case(s) – 30%

The best AI video generation tools give users the extensive capabilities and features necessary to create enterprise-ready marketing, sales, training, and customer service videos.

Although many other AI video generation tools exist for casual mobile users and use cases, we mostly steered away from those tools in favor of platforms that offer enterprise features such as video embeds and exports, useful integrations, business templates, advanced AI avatars and audio synthesis, and other features that support an enterprise video-making workflow.

Video and Audio Quality – 20%

To do enterprise-level projects and create humanoid voices and avatars, it’s important to invest in AI video generators that emphasize high video and audio quality.

While compiling our list, we searched for tools that supported high-resolution video uploads and downloads and audio mixing and synchronization capabilities. We also looked for tools that received favorable customer reviews for AI avatar and sound quality performance and that include basic transition, animation, and intro and outro functionalities.

Cost – 20%

When considering the cost of video generation tools, we looked for both affordability and a range of subscription options. In terms of affordability, we sought out tools that offered free versions and/or useful demos and trial periods.

However, we paid even closer attention to tools that offered a range of subscription options, from free or low-cost to enterprise-level subscriptions and features. We focused heavily on tools that came at a variety of price points, identifying solutions that both small businesses and enterprises could use, as well as tools that smaller businesses could stick with even as their needs scale up.

Also see: Generative AI Companies: Top 12 Leaders

Bottom Line: Top AI Video Generators and Tools

AI video generators simplify a digital marketing and communication practice that has long been considered the realm of expert creatives: video editing and creation.

With the help of an AI video tool, users can now take on many of the most complicated video tasks, ranging from editing footage and audio to creating shorter clips and summaries from long-form content.

Especially with so many affordable AI video generators on the market today, marketing and sales professionals in particular should incorporate this type of software into their digital toolset for accessible video creation and better customer engagement results.

Read next: Top 9 Generative AI Applications and Tools

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Among the topics we discussed:

• Before we dive too deep, let’s define the concept. What does it mean to use artificial intelligence to “contextualize data effectively while aligning with specific business objectives.”
• What are the challenges to this process?
• In essence, what is the guide to achieving this alignment?
• How is Cognizant addressing the AI and data needs of its clients?
• The future of AI in enterprise settings? What are some key milestones we can expect in the years ahead?

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Among the topics we discussed: 

• Let’s talk about integration technology in the enterprise. How does it work in terms of, say, integrating cloud and legacy in-house apps?
• What are the challenges in integration? The typical headaches? How do you recommend companies handle these challenges?
• How is Jitterbit addressing the integration needs of its clients?
• The future of tech integration in the enterprise? Will it ever get easy?

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Read on to learn how generative AI is being used in contact centers now and how it can benefit contact centers that adopt the technology with security, ethics, and other best practices in mind.

Table of Contents: Contact Centers and Generative AI

• How Is Generative AI Being Used in Contact Centers Today?
• Benefits of Using Generative AI in the Contact Center
• Generative AI in the Contact Center: Tips and Best Practices
• Bottom Line: Contact Centers Supported by Generative AI Technology

How Is Generative AI Being Used in Contact Centers Today?

Voice Generation for Customer Service and Client Calls

Though most people think of generative AI in the context of text or image generation, the technology has also come a long way in the areas of audio generation and voice synthesis.

With the right tools, contact centers can use artificial voices that are trained to sound human-like and take calls, answering complex questions and/or triaging calls to more experienced reps just as a human would. For contact centers where video calls are more common, artificial intelligence avatars can also be generated that both look and sound like a human employee.

Off-hours Customer Service Support

AI agents are particularly effective for international businesses, healthcare organizations, and contact centers that have trouble staffing their centers after regular business hours.

AI chatbots and agents can be on the clock 24/7 and never experience the fatigue or frustration that a human employee might feel if they worked these extended hours. As generative AI capabilities for these AI assistants and service reps continue to advance, they are becoming increasingly capable of handling complex tasks and customer requests without human intervention.

Also see: Top Generative AI Apps and Tools

Service Representative Coaching and Live Assistance

Generative AI contact center tools are frequently used to monitor human rep calls and give them feedback on how their tone is coming across, how customers are receiving that information, and other factors that may positively or negatively impact call outcomes.

Additionally, these tools are designed with administrators’ and managers’ needs in mind: although artificial intelligence can now handle most coaching tasks on their own, they also transparently share information about:

• Contact center rep evaluations.
• Previous coaching sessions.
• The number of evaluations each employee has received.
• Other data in a digestible dashboard format so managers can intervene and provide further coaching or disciplinary action if necessary.

Call Recording and Summarization

Generative artificial intelligence platforms go beyond simply recording contact center calls and use their algorithmic training to help contact centers extract deeper intelligence and insights from call transcripts.

For example, if a customer service rep has a 30-minute call with a customer that touches on several issues and shifts tone throughout the conversation. In this case, certain generative AI solutions can quickly summarize this conversation in key bullet points, assess buyer sentiment at different points in the conversation, and make recommendations for how or if a rep from the contact center should follow up with this individual.

In many cases, these tools are also able to supplement information from the current conversation with past conversations, buying or patient history, and other data that informs employees about who this individual is and what they expect from the brand.

Omnichannel Content and Communication Enrichment

The modern contact center rarely sticks to traditional phone calls, often giving users the option to communicate with their reps via email, chatbot threads, and social media messages. When contact centers opt to use generative AI-driven chatbots and analytics tools, they can more easily embed intelligent assistance into all of the channels where customers choose to interact with them.

Because of this omnichannel approach enabled by modern AI, chatbots and AI assistants are frequently able to use their natural language skills and advanced search capabilities to extend useful learning resources and knowledge base materials to customers, helping to avoid the need for further contact center or customer service escalation.

Also see: Best Artificial Intelligence Software

Sentiment Analysis and Real-time Analytics

Live call monitoring used for real-time analytics across a variety of demographic and customer data points. Can determine how customers are feeling and make recommendations for how to interact with individuals and customers as a whole better in the future.

Automated Follow Ups and Touchpoints

Contact centers have traditionally required reps to manually handle repetitive tasks, like accepting customer calls and messages, recording and reviewing transcripts, and following up with customers at regular intervals.

With the help of generative AI tools, many of these tasks, including reminders for these tasks, can be automated so employees are able to focus on more complex customer experience tasks. In the meantime, AI tools set up calls, emails, and other types of follow ups to ensure customers feel taken care of and are reached at key points in the customer lifecycle.

Also see: 100+ Top AI Companies

Benefits Generative AI in the Contact Center

Generative AI in the contact center helps businesses to better organize, automate, and respond to customer service needs. Some of the most important benefits that come from using generative AI in contact center settings include the following:

• Fill in the Gaps for Employee Shortages: Artificial intelligence can take on open roles for certain contact center tasks, like answering phones and preparing and analyzing call transcripts; generative AI agents are especially useful for 24/7 phone coverage and international availability.
• Real-Time Detailed Data Insights: Live coaching and performance tweaking opportunities are made more feasible with the help of generative AI data analytics. Both predictive and prescriptive analytics, with AI-driven recommendations, can be used to improve future call cadences and behaviors.
• Employee Training and Guidance: Employees can be trained during their calls to make better decisions and improve their conversational skills immediately with the help of AI coaches. Taking this approach doesn’t require human managers to listen to recordings and give feedback at a later time, when that feedback may be more difficult to apply.
• Learn and Improve After Each Customer Interaction: Generative AI tools themselves are trained to take customer queries and other data inputs and give customers the best possible answer. Beyond simply answering customer questions, these generative AI agents are trained to use this conversational data to improve how they interact with customers in the future.

Generative AI in the Contact Center: Best Practices

Using generative AI in the contact center can improve workflows for employees and outcomes for callers. But because of the nature of these tools and how they are trained, there are many AI-related cybersecurity and ethical considerations about AI that should be weighed when implementing contact center AI tools.

To ensure your team follows best practices that consider the wants and needs of the client, follow these tips:

• Adhere to Relevant Data Privacy and Usage Laws: This is especially important if you’re working in a highly regulated industry’s contact center, like a healthcare facility. For a better customer experience and to prevent legal action, go beyond the basics of data compliance and privacy laws and follow AI privacy best practices that put the customer first.
• Integrate and Embed Generative AI into Existing Tool Stacks: Contact centers should run like well-oiled machines, so it’s a good idea to invest in contact center tools that natively include generative AI capabilities or that integrate smoothly with generative AI tools like ChatGPT and GPT-4.
• Use Proven and Purpose-Built Contact Center Tools: Look for leading solutions from proven AI leaders and well-funded, innovative AI startups. Examples of leading generative AI contact center and e-commerce solutions include the following: Gridspace, Salesforce Einstein, Microsoft Copilot, Cresta, and Observe.ai.
• Monitor Customer Feedback Pre- and Post-AI Implementation: Generative AI agents, chatbots, and coaches may slip up occasionally, especially as they are learning how your customer base works. To catch their mistakes and train them for better outcomes in the future, continue to monitor their performance and how customers feel about AI-powered interactions.

Bottom Line: Contact Centers Supported by Generative AI Technology

Regardless of what tools you choose to use in your contact center, customers should not feel like they’ve been “left to the robots.”

For more complex call center scenarios or high value customers who are dissatisfied, humans should always be available to give them the personal touch they require. It’s also a good idea to ensure that human employees are continually vetting and updating pretrained AI responses to fit the times, buyer and/or patient trends, and other changing customer expectations.

Ultimately, generative AI offers exciting new opportunities for customer engagement and automation for contact centers, but this technology must be used responsibly and thoughtfully. It’s most important that customers and employees feel that the contact center is being supported by AI rather than taken over by AI.

Read next: Generative AI Companies: Top 12 Leaders

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Why is synthetic data important? Approximately 328.77 million terabytes of data are created each day. There are limits to what and how you can use this vast amount of data without breaking compliance laws or compromising privacy.

By using synthetic data, organizations can overcome the challenges of data access, data sharing, and data privacy and can still perform critical tasks that depend on real-world data. Moreover, synthetic data helps organizations overcome data scarcity issues, especially when there is a limited amount of actual data available for analysis or AI model training.

Read on to learn more about the best synthetic data software, including their pricing, features, pros and cons, integration and more.

Jump to:

• Top synthetic data software: Comparison chart
• Best synthetic data software
• Key features of synthetic data software
• How to choose the best synthetic data software for your business
• How we evaluated the best synthetic data software
• Bottom line: Top synthetic data software

Top Synthetic Data Software: Comparison Chart

Top 9 Synthetic Data Software

MOSTLY AI Synthetic Data Platform: Best for ease of use

Overall rating: 4.55

• Cost: 5
• Feature Set: 5
• Ease of Use: 5
• Tools: 5
• Support: 2

We included MOSTLY AI for its versatility and comprehensive features. This versatility allowed us to generate realistic and diverse datasets for a variety of use cases.

The MOSTLY AI synthetic data platform allows enterprises across industries to generate high-quality, privacy-preserving synthetic data. Those in the banking, telecommunication, healthcare and insurance can use MOSTLY AI to generate synthetic data for various use cases such as data anonymization, artificial intelligence and machine learning development, testing and product development, and cross-border and enterprise data sharing.

To learn about the tool, I created a free account, which took me less than two minutes to sign up. After signing up, I didn’t have data to upload so I selected one of the three sample data available (Bank Marketing) and proceeded to generate synthetic data based on that sample.

Pricing

• Free forever plan: Allows you to generate up to 100K rows per day.
• Team: $3 per credit.
• Enterprise: $5 per credit.

The actual price you will pay per month depends on the number of data subjects (rows), data points per subject (columns) and creators (users). For instance, a “team plan” user with 1 creator, 100 data points per subject, and 100,000 data subjects will pay $1,860 per month or $22,320 per year, while an “enterprise plan” user with the 1same feature will pay $3,100 per month or $37,200 per year.

Key features

• Time-series support.
• Support for different data types – MOSTLY AI works with various structured data: numerical, categorical, and date-time variables.
• Data rebalancing for data exploration.
• Deployment via Kubernetes or OpenShift.

Pros

• Users say the free plan is feature-rich.
• The platform is easy to learn and use.

Cons

• Dedicated support is limited to enterprise plan users.
• Users says the UI elements can be improved.

MOSTLY AI integrations

You can connect MOSTLY AI with various third-party tools, including:

• Amazon Web Services (AWS)
• Microsoft Azure
• Google Cloud Platform
• Oracle Cloud Infrastructure
• PostgreSQL
• SQL Server
• Snowflake
• Databricks
• Maria DB

Also see: Best Artificial Intelligence Software

Syntho: Best for small and medium businesses

Overall rating: 3.28

• Cost: 0
• Feature Set: 5
• Ease of Use: 4.5
• Tools: 5
• Support: 1

Our research found that Syntho’s synthetic data can be used for data analysis as though it is real data, and the outcomes will be nearly identical to analysis results on the original data.

Syntho is an Amsterdam based startup founded in 2020 that AI-Generated Synthetic data for public organizations, healthcare and finance industries. This synthetic data can be used by organizations for training machine learning models, testing applications, and conducting data analysis without compromising privacy or security.

You can deploy Syntho on-premise, any (private) cloud and Syntho cloud. You can also run the Syntho Engine as a Docker container or python package in your secure IT environment. To do this there are some minimum hardware and software requirements that you must meet.

Minimum hardware requirements

• 32 GB of RAM
• 8 virtual CPUs
• ‘Sufficient’ storage for the data

Minimum software requirements

• Docker Compose Deployment
  • Docker: 1.13.0+
  • Docker-compose: V3 and higher
• Kubernetes Deployment (alternative)
  • Kubernetes: 1.20 and higher
  • helm: v3 and higher

Pricing

Syntho offers three pricing plans: Basic, standard and ultimate. However, the vendor requires interested buyers to contact them for quotes. Pricing depends on the size of your database and your preferred plan.

Key features

• Support time series data and longitudinal data.
• On-premise and private cloud integration.
• PII discovery and generation.
• Auto-scaling via Ray & Kubernetes.

Pros

• Advanced subsetting capability.
• Its self-service capability and easy-to-use interface make it accessible to users of all skill levels.
• Role-based access control (RBAC).

Cons

• Lacks free plan and pricing transparency.
• Some users reported that it does not infer the relationship between databases.

Syntho integrations

Syntho integrates with various databases and filesystems.

• Postgre SQL
• MySQL
• Microsoft SQL Server
• Oracle
• Databricks
• Amazon S3
• Sybase
• MariaDB
• Hive
• IBM DB2

GenRocket: Best for test data management (testers)

Overall rating: 2.43

• Cost: 0.65
• Feature Set: 3.75
• Ease of Use: 1.5
• Tools: 2
• Support: 2

We selected GenRocket because it allows developers and testers to generate data sets with specific characteristics, formats, and structures required for testing different scenarios. This accelerates the testing process and improves the overall quality of software applications.

GenRocket is a software company that specializes in test data generation. It provides a platform that allows users to create and manage realistic and customizable test data for software testing and development purposes. The generated data can be used for various types of testing, including functional, performance, and security testing. GenRocket also offers additional features, such as data masking and subsetting, to ensure data privacy and compliance.

GenRocket has a four-step methodology that enables testers to work independently to provision their own data on demand.

• Model – the data to be generated during testing.
• Design – the variety and volume of data for testing.
• Deploy – test data cases into a test environment.
• Manage – test data projects in a shared repository.

Pricing

GenRocket offer three pricing plans.

• Growth: $55,000 per year. Includes 20 test data projects.
• Business: Quotes available on request. Includes 40 test data projects.
• Advanced: Quotes available on request. Includes 80 test data projects.

Key features

• Offers a library of 730+ data generators.
• Has a library of 101+ data formats.
• Data subsetting and masking.
• Support various test use cases, including realistic data, negative data, data for complex workflows, machine learning data and X12 EDI transaction data.

Pros

• Self-service test data portal.
• Can be integrated into your CI/CD release pipeline.
• User applauds GenRocket technical support.

Cons

• Add-on cost extra fee.
• Steep learning curve.

GenRocket integrations

Some of the top tools GenRocket integrates with include:

• Jenkins
• Azure DevOps
• Selenium
• UiPath
• Katalon
• Tosca

Also see: 100+ Top AI Companies

Tonic.ai: Best for developers

Overall rating: 3.93

• Cost: 1
• Feature Set: 5
• Ease of Use: 4.5
• Tools: 5
• Support: 4

We selected Tonic.ai for its advanced capabilities in generating privacy-conscious synthetic data. Although it requires you to invest time to learn and implement the platform, we found Tonic.ai’s ability to preserve relationships, consistency and complex structures in the data is particularly valuable.

Tonic.ai’s synthetic data platform equips developers with the tools they need to generate “fake data” that closely resemble real data. The platform allows developers to create realistic test data based on your organization’s data, preserving critical relationships and maintaining input-to-output consistency across tables and databases. Tonic.ai is suited for developers and data scientists in finance, ed-tech, insurance, retail and healthcare.

Pricing

Tonic is available in two editions: Tonic cloud and enterprise. To get quotes for these plans, you must contact an in-house expert for custom quote. Tonic offers a 2-week free trial which allows you to try the tool before making a purchase decision.

Key features

• It supports several flat files including .txt, JSON, CSV and XML.
• Schema change alerts capability helps to prevent sensitive data leakage.
• Connects with several CI/CD applications.
• De-identification and AI synthesis capabilities.

Pros

• Ranks high for ease of use and feature set.
• Offers quality customer support.
• Offers subsetting functionality.

Cons

• Some users reported that the tool is somewhat expensive.
• Steep learning curve.

Tonic.ai integrations

This platform integrates with several third-party services including

• PostgreSQL
• MySQL/MariaDB
• SQL Server
• MongoDB
• Vertica
• DocumentDB
• Oracle
• Snowflake
• Redshift
• BigQuery
• Databricks
• Amazon EMR w/ Glue
• Spark

Hazy: Best for financial services

Overall rating: 3.18

• Cost: 0
• Feature Set: 5
• Ease of Use: 4.5
• Tools: 2.5
• Support: 2

Hazy enables businesses to create realistic but entirely fictional datasets that mimic the statistical properties of accurate data without exposing actual customer information. Hazy is used in the financial services industry for fraud modeling, asset management and customer engagement, financial crime, credit risk,  AML, and operational risk.

Hazy’s synthetic data engine is built to handle complex data from large enterprise. Hazy can connect with complex network and security setups, working alongside your original data to provide the highest level of protection, whether it’s stored on your premises or in your private cloud. With Hazy, complex data can be generated for financial service applications and securely stored within the company’s silos.

Pricing

The company doesn’t advertise its rate on its website but encourages interested buyers to get in touch with an in-house expert by completing a short form on their website.

Key features

• Advanced memory optimization and subsetting techniques lower energy usage.
• Deploy on-premises or in the cloud.
• It can create diverse datasets that encompass various scenarios, enabling thorough testing and analysis.

Pros

• Support complex data needs.
• Users applaud Hazy’s built-in privacy tools.

Cons

• May not be suitable for small companies.
• Lacks transparent pricing.

Hazy integrations

Top Hazy integrations:

• Snowflake
• AWS
• Azure

On a related topic: What is Generative AI?

K2View: Best for ML training

Overall rating: 3.60

• Cost: 3.25
• Feature Set: 5
• Ease of Use: 2
• Tools: 5
• Support: 1

K2View offers four synthetic data generation methods, making it easy for teams to generate and integrate synthetic data into CI/CD (Continuous Integration/Continuous Deployment) and ML (Machine Learning) pipelines.

K2View synthetic data generation tool combines four data generation methods: Generative AI, rules engine, entity cloning, and data masking.

• Generative AI: The Generative AI model involves subsetting the required source data to train generative AI models. This data is then masked to ensure privacy and protection. The masked training data is used to train the GPT (Generative Pre-trained Transformer) model, which enables synthetic data generation.
• Rule engine: Rule-based data generation allows you to generate data creation functions based on data classification, and then you can proceed to customize, test, and debug the functions code-free. The rules engine data generation allows users to assign business parameters for the functions and generate data on demand or via API.
• Entity cloning and data masking: Entity cloning allows you to extract, mask, and clone a single business entity and all its data and then create unique identifiers for each cloned entity. The data masking data generation method auto-discovers sensitive and personally identifiable information (PII) and then applies prebuilt, customizable data masking functions. K2View allows you to mask data inflight, as it’s extracted from the sources.

Pricing

K2View pricing is available on demand.

Key features

• Connectors to structured and unstructured data sources.
• Low code/no-code platform.
• Version and roll back datasets on demand.

Pros

• Preserves data relationships.
• Data masking capabilities.
• Enhance data privacy and compliance.

Cons

• Steep learning curve for beginners.
• Users say it’s expensive.

K2View integration

You can connect K2View with the following tools:

• IBM DB2
• Salesforce
• Oracle
• Couchbase

Datomize: Best for data analysts and machine learning engineers

Overall rating: 3.96

• Cost: 4.4
• Feature Set: 3.4
• Ease of Use: 4.5
• Tools: 5
• Support: 3

Our research found that Datomize excels in analytical data sets with its AI-powered data generation capabilities. By leveraging behavior extracted from current data, Datomize allows data analysts and machine learning experts to generate precise and relevant analytical data sets.

The Datomize AI-powered data generation platform allows data analysts and machine learning experts to get the most out of their analytical data sets. It enables you to generate the exact analytical data sets required using the behavior extracted from current data, and creates synthetic data that is similar in properties to the original data but without containing any sensitive or personal information.

Pricing

• Community: Free forever plan with 40 credits per month and up to 20MB input size.
• Starter: $720 per month, billed annually or $800 per month billed monthly. It includes 160 credits per month plus up to 500MB input size.
• Enterprise: Quote available upon request. Unlimited usage and input size.

Key features

• Advanced augmentation capabilities.
• Datomize’s rules-based engine enables users to generate the exact analytical data set needed for any desired scenario.
• Support time-series data.

Pros

• Offers a free forever plan.
• Predict outcomes for any scenario.

Cons

• Limited resources about the product.
• Lacks live chat support.

Datomize integrations

• Python SDKs
• PostgreSQL
• MySQL
• Oracle

Sogeti Artificial Data Amplifier (ADA): Best for testing and development use cases

Overall rating: 2.55

• Cost: 0
• Feature Set: 5
• Ease of Use: 1
• Tools: 5
• Support: 2

Sogeti received high marks for its feature set, which includes the maturity of the product, its ability to serve large enterprises and output fine tune capability. Sogeti also scored 5 out of 5 for “Tools” due to its quality of generated data and scalability.

Part of the Capgemini Group, Sogeti is a Managed Service Provider (MSP) with operational presence in over 100 locations globally. Sogeti ADA generates realistic, usable data based on real data sets. it leverages advanced deep learning based on a combination of artificial neural networks to analyze existing data and create similar but new data points. It can generate large volumes of data, helping organizations tackle the data scarcity challenge.

Pricing

Quotes are available upon request.

Key features

• Realistic and diverse data generation.
• Support for different data types.
• Bias and overfitting reduction.

Pros

• Sogeti’s generated data preserves all the characteristics, correlations and properties of the original data.
• It can be customized to suit your specific needs and use cases.

Cons

• Lacks transparent pricing.
• Usability requires training and expertise.

Sogeti Integrations

Sogeti top integrations include:

• SAP S/4HANA
• Azure
• AWS

Also see: Generative AI Companies: Top 12 Leaders

CA Test Data Manager: Best for complex data generation

Overall rating: 2.78

• Cost: 0
• Feature Set: 3.25
• Ease of Use: 4
• Tools: 5
• Support: 2

Significantly CA Test Data Manager focuses on protecting sensitive information – it offers features such as data masking, which helps to protect sensitive and personal information in test environments by replacing real data with realistic but fake data.

Developed by CA Technologies, CA Test Data Manager is a tool allows you to create, generate, mask, and refresh test data for application testing. CA Test Data Manager automates the process of creating test data by integrating with various data sources and providing data management features like data subsetting, data masking, and synthetic data generation. CA Test Data Manager supports 32-bit and 64-bit physical and virtual Windows machines.

Pricing

Quote available upon request.

Key features

• It has a discovery and profiling feature that allows you to identify personally identifiable information (PII) across multiple data sources.
• It allows you to create future scenarios and unexpected results to test boundary conditions.
• CA’s virtual test data manager capability enables you to generate multiple copies of test data in seconds through cloning.

Pros

• Self-service test data provisioning.
• Integration with governance and risk management.
• Data masking.

Cons

• Limited support.
• Limited resource and product information.

CA Test Data Manager integrations

• Oracle RAC 11g
• Oracle RAC 12c
• IBM DB2 11 for z/OS
• IBM DB2 UDB 11.1
• CA IDMS 19.0
• MySQL 5.6

How to choose the best synthetic data software for your business

When shopping for the best synthetic data software, your organization’s unique needs for synthetic data should be your topmost priority – are you most concerned with compliance, with speed? You need to identify the types of data you need to generate and determine the pain point such data will solve for your business.

After identifying your data needs, it’s time to conduct extensive research – look for solutions that align with your requirements and provide the necessary functionalities. Our evaluation has lessened the research burden for you; there’s quite likely a choice that fits your needs in the list above. Next up is to evaluate the tool’s data generation techniques, customizable capabilities and scalability. And be sure to take the software for a test drive – make sure it actually works for your needs.

How we evaluated the best synthetic data software

We weighed the best synthetic data tools across five categories –each category has sub-categories that helped us evaluate and compare the AI writing tools.

Cost – 20%

We examined the different pricing plans offered by each synthetic data software. This included evaluating the cost of the tool on a monthly or annual basis. We also check to see if the tools offer value for money.

Features set – 30%

We assessed the core data generation capabilities of each tool and its functionalities, including the maturity of the product’s ability to finetune the output and we also confirmed if the tool is geared for large enterprises.

Ease of use – 25%

We looked for intuitive and user-friendly tools, allowing users to navigate and utilize the tool’s features easily.

Tools – 10%

We evaluated each tool’s output quality and scalability level.

Support – 15%

We assessed the availability and responsiveness of customer support channels, such as email, live chat, or phone support. We also considered the availability of resources and documentation, such as user guides, tutorials, or knowledge bases.

Bottom line: Top synthetic data software

There is no one-size-fits-all when selecting the best synthetic data software. For instance, data analysts and machine learning engineers may find Datomize beneficial, while Hazy may be the best option for financial service companies.

The best synthetic data software for you will depend on various factors, including your organization’s specific needs, the use case, the industry, and data compliance requirements. Clearly, given the complexity of this category, you’ll need to do your homework to select the best synthetic data software.

Read next: Generative AI Examples

The post 9 Best Synthetic Data Software 2023 appeared first on eWEEK.

Among the topics we discussed:

• What’s a major challenge that companies face with their data analytics practice? For all the effort and expense, what’s still holding companies back?
• How can companies solve this issue? Is there industry momentum toward any solutions?
• How does Pure Storage support the analytics practices of its clients?
• What about ESG and the issue of data storage, with the shift from hard disc to flash? What are the implications for issues like power use and sustainability?

Listen to the podcast:

Also available on Apple Podcasts

Watch the video:

The post Pure Storage’s Justin Emerson on Analytics Performance and Flash Storage appeared first on eWEEK.

In this guide, we’ll cover some of the most common use cases of generative AI in e-commerce today and we’ll touch on how today’s benefits may lead to further AI growth in this industry.

Table of Contents: Generative AI and E-Commerce

• Generative AI Use Cases in E-Commerce
• Leading Generative AI Solutions in the E-Commerce Space
• Bottom Line: The Benefits of Generative AI in E-Commerce

Generative AI Use Cases in E-Commerce

Generative AI can be used to supplement or even supplant various components of a company’s e-commerce workflow.

Across the e-commerce sector, artificial intelligence benefits both the vendor and its employees as well as customers and prospective buyers. Learn more about generative AI’s use cases in e-commerce below:

AI-Driven Analytics

E-commerce of course involves less face-to-face interaction with customers than traditional commerce, so it can be particularly challenging to gauge customer satisfaction across different parameters and data points.

Online businesses have used data analytics tools for many years now to better understand how customers engage with their brands. But these tools have been limited in the quantity and quality of data they collect as well as the speed with which data is updated.

In contrast, generative-AI-driven data analytics tools give business leaders and data scientists more contextual customer data, updated in real time and across different shopping, channel, and demographic data points.

These generative AI tools can collect data in various unstructured formats, including customer service queries, social media posts and comments, ad clicks and engagements, and other data that has historically been difficult to capture.

Additionally, these tools often go beyond predictive analytics, offering insights into what’s happening now and making prescriptive recommendations for what vendors can do to achieve better results, products, and services in the future.

Other ways users can combine generative AI and data analytics for better e-commerce outcomes include the following:

• Quickly assess products, websites, and other customer-facing assets to determine if they are meeting quality requirements.
• Make more accurate and timely supply chain predictions.
• More effectively manage inventory and demand forecasting needs.

Customer Service Chatbots, Agents, and Coaches

With generative AI chatbots and virtual agents, businesses can handle chat conversations 24 hours a day that are designed to feel like a real human is engaging with the customer.

Many brands have had 24/7 operational chatbots in the past. But without the content generation and predictive capabilities of generative AI, these previous chatbots have relied heavily on human-built workflows and prebuilt responses that don’t always meet customer needs. Their limited training on limited amounts of data severely impacted their ability to interact with customers. They can’t solve problems in the face of unique customer experience scenarios.

When a customer service problem needs to be escalated, generative AI agents can also be used to triage more complex communications to human customer service reps, giving them all of the contextual information they need to follow up with the customer effectively.

Additionally, these AIs can be used to coach human customer service reps on how to have better customer interactions that match the tone and needs of that individual.

AI Search for Customers

Generative AI tools have made it possible for businesses to quickly scale up their online knowledge bases in a way that answers a variety of customer questions that may not have previously been considered or adequately covered in early versions of online resources.

This database of knowledge can then be embedded in brand websites and apps, and in some cases, may also be connected to the internet for real-time search capabilities and more targeted ads.

AI-driven search not only gives customers the best search results for their queries but also frequently offers contextual information, suggested next searches, and other information that may assist them in their buying experience.

Product Descriptions and Content Writing

Businesses of all backgrounds are experimenting with generative AI for content creation, and the e-commerce world is filled with opportunities where AI can fill the gaps. For example, generative AI tools can be used to quickly write product descriptions, product guides and white papers, marketing and sales blogs, emails and marketing campaigns, chatbot responses, and targeted ad content.

Because of the speed and scale at which generative AI content writing tools can work, businesses can quickly create and rework content while also using these tools to detect customer sentiment in queries and respond accordingly.

Especially in marketing and communications campaigns, many of these content generation tools can also be trained and set up to automatically reply and follow up with customers when appropriate.

Back-Office Operational Support

A growing number of AI tools focus on creating a one-stop shop for e-commerce back-office operational tasks, including content generation, task management, storefront management, and ad management needs.

An example is Shopify Magic, a set of generative AI capabilities that is built directly into the Shopify commerce platform. Its latest feature is Sidekick, a Shopify assistant that helps vendors manage their task lists while answering specific questions about everything from customer interactions to what’s needed to prepare for an upcoming sale.

Virtual Customer Experiences

Though this area is still fairly early in its development, virtual customer experiences like virtual try-on for clothing e-tailers are quickly growing and gaining a loyal customer base.

Clothing retailers are primarily benefiting from this new innovation, but other VR/AR experiences are also in the works that allow users to have remote shopping experiences that “feel” real. Additionally, a growing number of customer-facing apps now exist that combine different generative AI elements, such as AI assistants, chatbots, guided search, and catered product recommendations, to create a smoother shopping experience for users.

For more on a similar topic, read AI in Retail: What You Need to Know.

Leading Generative AI Solutions in the E-Commerce Space

A number of generative AI solutions have popped up to solve for different e-commerce use cases, including ad and product content creation, communication and customer service, and more.

Below, we’ve gathered information about some of today’s leading e-commerce-focused generative AI solutions:

• OpenAI’s ChatGPT and GPT-4: OpenAI’s ChatGPT and GPT-4 are being used by many other generative AI vendors as a foundation for embeddable chatbots, virtual assistants, and other tools that improve the customer experience on e-commerce websites and virtual storefronts.
• Jasper: Jasper’s library of tools covers a range of e-commerce needs, including generative AI chatbots, image generation, brand-driven content generation, and automated marketing campaigns.
• Gridspace: A contact center tool that supports e-commerce needs like virtual agents to take calls and detailed conversational analytics to coach and improve future conversation outcomes.
• Veesual: VR/AR-driven customer experiences for clothing shopping and virtual try-ons.
• Shopify Magic: A back-office assistant that can help vendors with task management and content generation types of tasks.
• SolidGrids: Product image and content generation, including banner generation and SEO optimization features.
• Describely: Product descriptions, catalog content, and other types of product-driven content generation.
• Cresta: A contact center solution for virtual contact automation, rep coaching, and real-time call analytics.
• AdCreative.ai: Creative ad content generation platform.
• Shulex VOC: A ChatGPT-driven AI assistant that makes suggestions, answers questions, and automates various e-commerce tasks.
• Phrasee: A content generation platform that works across email, SMS, web, app, and social channels and focuses on customer loyalty outcomes.
• Kore.ai: A platform with both employee experience and customer experience tools for conversational AI, AI-driven assistance, and smart search.

For more information on these solutions and others from emerging generative AI startups, read about the 50 Generative AI Startups to Watch in 2023.

Bottom Line: The Benefits of Generative AI in E-Commerce

The generative AI and e-commerce market is ripe with new tools and features emerging on a near-daily basis to address the different wants and needs of e-commerce vendors, business stakeholders, employees, and customers.

While certainly not everyone is open to artificial intelligence taking over tasks that have traditionally involved human-driven customer service, more and more people are growing comfortable with this development. It provides new conveniences, particularly to retailers that are struggling with worker shortages.

With generative AI in a supporting role, e-commerce companies can confidently move forward and grow their businesses in a way that feels sustainable and innovative.

Read next: Top 9 Generative AI Applications and Tools

The post Generative AI’s Impact on E-Commerce appeared first on eWEEK.

The critical elements of digital transformation to keep in mind are customer experience, operational excellence, and innovation. Specifically:

• Delight your customers: You need to optimize customer experiences, ensuring a smooth, automated journey that is connected and personalized across all channels.
• Stay flexible, productive, and efficient: Hybrid workforces demand a lot. Build an ethic of operations excellence that can handle all the needs of your company while staying secure and accountable is critical.
• Look to the future: Innovation is about optimizing day-to-day operations so you can focus on new products and opportunities.

A “Do It Yourself” Approach is Hard to Execute

Executing digital transformation by yourself is a daunting prospect. And, even with some of the common platforms available, the heavy lifting can be overwhelming.

Getting the coders you need to get everything done is a thankless task—something that might be impossible in today’s labor market. But rather than putting this on next year’s to-do list, there are ways to do everything you need now using a different approach: No code.

We’ve all heard the soothing terms low code and no code. But how viable are they? ZK Research has evaluated several solutions in the past few years, and we see them as a shortcut around development cycles that used to take months or years.

One such platform—from Newgen, an India-based company whose platform can automate all aspects of a business for efficient operations and end-to-end customer journeys—can deliver the business outcomes we described above. The company’s NewgenONE platform enables the following:

• Automate manual processes and applications.
• Speed up transformations with low/no code.
• Create insights from documents, images, videos, and audio files.
• Extract more from existing systems without a complete rebuild.
• Build a culture of innovation across a company’s ecosystem, including internal groups, customers, and partners.
• Scale and secure the cloud.

Also see: Top Digital Transformation Companies

The Platform

The NewgenONE platform automates key parts of a business to make operations more efficient and ensure customer journeys are seamless.

One Newgen customer, Bank Midwest, a leading community bank in the Midwest region with assets totaling $1.3 billion, chose NewgenONE to transform its processes and customer experience with a tailored solution that eliminated the need for multiple-point solutions. The bank efficiently integrated these features into their projects, paving the way for enhanced efficiency and scalability to meet future business demands.

Another financial organization—Georgia’s Own Credit Union, one of the largest credit unions in Georgia—partnered with Newgen to transition 65% of its new applications online, reducing the application journey time to just five minutes. In addition, NewgenONE reduced back-office processing time by 35%.

Bottom Line: Low Code/No Code Delivers

Low code/no code platforms can often be all talk and no reality. But, after speaking to some of their customers, ZK Research believes NewgenONE platform can deliver on the promise.

Also, Newgen has been recognized by other research firms, most notably Forrester and Gartner, as having a complete and easy-to-use platform. The company says, on average, customers have achieved an ROI of 371% over three years, which is in-line with the case studies I cited above.

Executing on digital transformation using old-school tools will not scale and can often lead to unsuccessful projects. Low code / no code masks much of the complexity that developers will face and simplifies digital projects.

Read next: Digital Transformation Guide

The post Newgen’s Low-Code Platform Geared for Digital Transformation appeared first on eWEEK.