While interest in Siggraph as an event has declined over the years, the advent of generative AI and the near-term potential arrival of AGI (Artificial General Intelligence) should cause a significant resurgence. This is because AI dramatically changes how people […]
The post Siggraph 2024: Learning About the Present and Future of Generative AI and the Coming of AGI appeared first on TechSpective.
ChaGPT Chat Generative Pre-trained Transformer) a boom in the technology industry introduced by OpenAI in 2022. It’s a profound innovation of cutting-edge Artificial Intelligence (AI) technology. OpenAI’s Large Language Model (LLM) powered ChatGPT has created waves in the modern tech industry.
ChatGPT is trained with a diverse set of databases which allows the application to generate creative, detailed, structured, and tweaked content responses. Delivering human-like text responses to user prompts, this modern generative AI application is gaining momentum across the industry. Moreover, with its Natural Language Processing capabilities, ChatGPT can better understand and engage customers users through a qualitative conversation.
Generating content as a core application, ChatGPT is also witnessing breakneck growth in various aspects. Using ChatGPT a software development team can write code and test code and a marketing and sales team can create compelling email content and sales campaign content faster. Further, integration of ChatGPT’s APIs into your CRM-like applications could help you instantly respond to customer queries and ensure personalized experience through reliable communication all the time. Hence, companies can achieve customer satisfaction and improve retention rates.
Like these, the applications of ChatGPT or the uses of ChatGPT are incredible. The HR department, development team, operational team, marketing, and sales department can avail the benefits of ChatGPT. Especially, the use of ChatGPT for sales and marketing increasing nowadays to streamline various aspects of the sales processes.
Today, in this article, we would like to give you a little information on how can ChatGPT be useful for sales and what are the benefits of customizing ChatGPT for your sales operations.
The generative AI powered ChatGPT using Natural Language Processing potentialities would help sales and marketing teams to automate responses to customer queries. Hence, integrating a well-trained GPT model into CRM applications will help can automate the process of receiving customer queries and sending accurate responses faster than a human workforce does. IT will improve the customer loyalty and at the same time boost productivity.
Leveraging the innovative advanced ChatGPT platform, sales and marketing professionals can generate content required for digital campaigns. ChatGPT is been trained with vast versatile databases related to market trends that help sales professionals get content ideas and relevant snippets and other marketing materials for boosting their campaign activities.
ChatGPT is the most useful asset for translating languages. Using ChatGPT like large language learning model, it will be easy to sales professionals to give prompts in one language and getting responses in required language. Hence it can be used as a language translator and supports multilingual interactions.
Giving necessary customer data input as a prompt to this advanced and AI-powered GenAI-based ChatGPT, sales professionals can segregate customers’ data based on their requirements, order types, order quantity, payment status, etc. It will reduce manual efforts and help in maintaining clear and structured sales data with zero errors.
In this digital world, getting noticed by prospects is a key step for ensuring a strong lead pipeline and improving conversions. Giving introductions to the brand’s services and products and doing continuous follow-ups are two mandatory tasks of a sales professional. ChatGPT will play a significant role in email generation in just a matter of seconds.
Providing your requirements such as targeted audience group, email intention, and email type (a service introductory draft or a follow-up), sales professionals can get creative email content. Later, it can be customized as per business requirements. Hence, time-consuming email writeups would be automated and help resources focus more on lead generation and nurturing.
It is one of the top benefits of ChatGPT in sales. ChatGPT helps the sales team or operations team to better manage sales processes and derive insights from historic sales data. These insights or summarized data would help the sales team to predict the market growth opportunities and create results-driven sales strategies.
Integrating ChatGPT into your existing sales applications and processes, identification of quality leads, gathering associated customer data, and creating lead generation striation would become seamless. By defining your prospects, ChatGPT assists in picking the best quality leads seamlessly and contributes to optimized ROI.
ChatGPT guides communication strategies to sales representatives. You can also train ChatGPT to automate onboarding processes, pushing automated recommendations to leads based on their previous search history feedback collection and analysis, and many more can be done by customizing ChatGPT APIs and integrating them into your sales applications.
These are a few significant applications of ChatGPT in sales. This powerful Generative AI application helps the sales team generate content that meets their needs. Like these, ChatGPT offers multiple benefits to sales teams.
Whether conversational AI or generative AI apps will have a bright scope in the years ahead with their smart, intelligent, and automation capabilities. Marketing, sales, development, and almost every department can gain from ChatGPT content generation potentialities and improve their focus on core activities.
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In a fast-growing environment, how does our small data science team continuously solve our company’s and customers’ greatest challenges?
At Razorpay, our mission is to be a one-stop fintech solution for all business needs. We power online payments and provide other financial solutions for millions of businesses across India and Southeast Asia.
Since I joined in 2021, we have acquired six companies and expanded our product offerings.
Though we’re growing quickly, Razorpay competes against much larger organizations with significantly more resources to build data science teams from scratch. We needed an approach that harnessed the expertise of our 1,000+ engineers to create the models they need to make faster, better decisions. Our AI vision was fundamentally grounded in empowering our entire organization with AI.
Given our goal of putting AI into the hands of engineers, ease-of-use was at the top of our wish list when evaluating AI solutions. They needed the ability to ramp up quickly and explore without a lot of tedious hand-holding.
No matter someone’s background, we want them to be able to quickly get answers out of the box.
AI experimentation like this used to take an entire week. Now we’ve cut that time by 90%, meaning we’re getting results in just a few hours. If somebody wants to jump in and get an AI idea moving, it’s possible. Imagine those time savings multiplied across our entire engineering team – that’s a huge boost to our productivity.
That speed allowed us to solve one of our toughest business challenges for customers: fraudulent orders. In data science, timelines are usually measured in weeks and months, but we achieved it in 12 hours. The next day we went live and blocked all malicious orders without affecting a single real order. It’s pretty magical when your ideas become reality that fast and have a positive impact on your customers.
When team members load data into DataRobot, we encourage them to explore the data to the fullest – rather than rushing to train models. Thanks to the time savings we see with DataRobot, they can take a step back to understand the data relative to what they’re building.
That layer helps people learn how to operate the DataRobot Platform and uncover meaningful insights.
At the same time, there’s less worry about whether something is coded correctly. When the experts can execute on their ideas, they have confidence in what they’ve created on the platform.
For cloud computing, we’re a pure Amazon Web Services shop. By acquiring DataRobot via the AWS marketplace, we were able to start working with the platform within a day or two. If this had taken a week, as it often does with new services, we would have experienced a service outage.
The integration between the DataRobot AI Platform and that broader technology ecosystem ensures we have the infrastructure to tackle our predictive and generative AI initiatives effectively.
In the highly regulated fintech industry, we have to abide by quite a few compliance, security, and auditing requirements.
DataRobot fits our demands with transparency, bias mitigation, and fairness behind all our modeling. That helps ensure we’re accountable in everything we do.
For smoother adoption, creating standard operating procedures has been critical. As I experimented with DataRobot, I documented the steps to help my team and others with onboarding.
What’s next for us? Data science has changed dramatically in the past few years. We’re making decisions better and quicker as AI moves closer to how humans behave.
What excites me most about AI is it’s now fundamentally an extension of what we’re trying to achieve – like a co-pilot.
Our competitors are probably 10 times bigger than us in terms of team size. With the time we save with DataRobot, we now have the opportunity to get ahead. The platform is an extreme developer productivity multiplier that allows our existing experts to prepare for the next generation of engineering and quickly deliver value to our customers.
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