From 0 to 10X: Harnessing AI to Turbocharge GTM Teams with Subskribe and Okta
•Download as PPTX, PDF•
0 likes•9 views
The document promotes a booth at an event where attendees can stop by booth number 230 for a sweet treat. It provides only a brief invitation to visit the booth without any other context or details about the event or what type of sweet treat will be available. The document is only a short advertisement encouraging people to visit a specific booth for food.
Recommended
More Related Content
More from saastr
More from saastr (20)
Recently uploaded
Recently uploaded (20)
From 0 to 10X: Harnessing AI to Turbocharge GTM Teams with Subskribe and Okta
- 10. ○ ○ ○ ○ ○
- 12. And stop by booth #230 for a sweet treat!
Editor's Notes
- The history of AI parallels the history of computing. With quiet beginnings in the seminal paper by Alan Turing where he posed the question: can computers think? AI has come a long way. 1997 was a landmark year where a computer defeated the world champion in a chess match. Fast forward to 2023, and ChapGPT seems to have taken over the world. So how will AI change the GTM world? Will it be really disruptive? Will companies like Salesforce even exist? 1950: Alan Turing publishes Computing Machinery and Intelligence, arguing "Can machines think?" 1956: The event that kickstarts the field: McCarthy and Minsky organize the Dartmouth Summer Research Project on Artificial Intelligence (DSRPAI). 1964-1966: Joseph Weizenbaum develops the first chatbot, ELIZA, at the MIT Artificial Intelligence Laboratory. 1986: NavLab - the first autonomous car, is built by CMU. 1997: Deep Blue beats Gary Kasparov in chess. 2011: Apple brings AI assistants to the masses by releasing its first iPhone with Siri. 2017: A team of Google researchers propose a new architecture, the Transformer, 2022: OpenAI releases ChatGPT, which reaches one million users within five days.
- There are some general patterns of utility we can expect to see with AI. Here are 4 that look like clear strong winners. Having said that, there might be a 5th that becomes big, or there might be minor but important ones that show up. This area is still developing. Workflow automation: AI doing something that’s complex and tedious with a quick short command Detect opportunities and anomalies: AI identifying opporrunities to boost revenue, or automatically detecting potential issues that aren’t obvious. Quickly fetch data: think Siri for GTM data that works. Ask a question, get the answer in a second. Your personal chief data scientist. Copilots: we are already seeing this happen with software development and other areas. AI will be a huge in assistive roles, whether that’s actively helping build and correct content, or in smaller roles like what autocomplete and auto fill do today on the web.
- Each stage in lead to revenue pipeline has potential to be disrupted by AI. Let’s look into some potential ideas in each one. GTM will move to an AI-First mindset
- Predicting and assisting with opportunity, creation is a huge opportunity. Think of a waterfall where you can predict which segments of the market are going to be good prospects for you, what the closing rate on an individual opportunity might be with a high degree of confidence, intelligent territory planning. etc.
- AI smarts helping close sales deals. Whether its predicting the likelihood, or suggesting actions that’d improve the odds, or benchmarking against similar companies, there will be a huge wave of innovation in this space that’ll help companies compete more effectively.
- application of artificial intelligence (AI) to optimize and streamline the accounts receivable process. It involves using AI technologies to enhance various aspects of managing invoices, payments, and collections. Here's how you can achieve SmartAR using AI: Usage Pattern Analysis: AI can analyze customer usage patterns to predict future consumption. By understanding usage trends, you can offer tailored pricing plans and discounts that align with the customer's needs, optimizing their billing experience. Fraud/Anamoly Detection: Implement AI algorithms to detect billing fraud and unusual activities. AI can analyze transaction patterns and flag suspicious behavior, helping to prevent fraudulent activities and ensuring a secure billing experience. Credit Risk Assessment: AI can analyze credit scores, financial data, and external factors to assess the creditworthiness of new and existing customers. This helps you make informed decisions about extending credit terms. Collections Prioritization: AI can help prioritize collections efforts by identifying high-risk accounts or those with the potential for disputes. Focus resources on these accounts to resolve issues and secure payments.
- Using AI to enhance upsell and renewal processes in your Go-To-Market (GTM) strategy can lead to more effective customer engagement and increased revenue. Here's how you can leverage AI for these processes: 1. Predictive Analytics: Implement AI algorithms to analyze customer data, behavior, and historical purchase patterns. Predict which customers are more likely to be interested in upsell offers or contract renewals based on their past interactions. 2. Customer Segmentation: Use AI to segment customers based on their preferences, needs, and buying behavior. Tailor upsell and renewal strategies for each segment to provide personalized offers. 3.Behavioral Analysis: Analyze customer behavior in real-time to identify signals indicating potential interest in an upsell or renewal. For example, an increase in product usage might trigger an automated offer. 4. Automated Communication: Implement AI-driven communication channels, such as personalized emails or chatbots, to deliver timely upsell and renewal offers. These automated communications can engage customers at the right moment.