Glen Ford’s Post

I’d like to rewrite history and introduce ChatGPT to the world in November 2017 Using my responsibilities at Black Knight Financial Services (Fintech) in 2018 Exchange Platfrom Manager Product Operations Manager Product Strategy Manager Product Marketing Manager Business Engineer Valuation Insight Product Manager Quality Insight Product Manager Business Integration Specialist Cross-Divisional Business Leader Business Application Owner I’m a human version of ChatGPT and the business unit I was in took full advantage of my capabilities by having me cover business and technical roles simultaneously executing tactical and strategic initiatives. If ChatGPT had been introduced in 2017 Here is an overview of how AI would have replaced my applied biological intelligence (ABI) —Integrating AI into my project planning process would have standardized the outputs and streamlined my delivery of the plans to the project managers —Integrating AI into my CAPEX forecasting process would have enabled me to use customer acquisition and attrition data to determine the profitability of my decisions of where to prioritize investments —AI could assisted with product backlog prioritization, feature parity analysis, and supporting research functions that informed my decision making One of the hallmarks of my career is reducing the technical debt of the division by $500,000+ by recognizing the that new feature sets of the digital version of our platform would retire costly legacy functionality by re-designing workflows of existing implementations to integrate with the new platform. AI would have been helpful in determining If there were opportunities for technical debt reduction across the product portfolio As new features and products were being created I was responsible for ensuring release notes and technical documentation was complete AI could have assisted those teams in creating the documentation in hours instead of weeks to months. While serving on the due diligence teams for multiple mergers and acquisitions, I would recommend integration strategies that would created new products in the market between the two firms. AI would have been able to scan the market to determine the sentiment of the customer base for the recommendations I was proposing. It was my responsibility to create a client and component impact analysis as we began to plan cross-divisional integration and product roadmaps. AI would have helped me analyze the broader market in hours instead of days or weeks. Our client list included JP Morgan Chase Bank of America Wells Fargo Citigroup Fidelity National Title Old Republic Title Stewart Title And 90% of the largest banks and title companies in America. If AI had been introduced in November 2017 I would have been able to implement Lean methodology across all aspects of the business With a $6 million CAPEX budget On average 10% of a capital budget is wasted due to project and process misalignment with business strategy $600,000

Dr. Martha Boeckenfeld, thanks for sharing. ChatGPT is revolutionizing the finance industry by automating report generation, analyzing market sentiments, and enhancing customer service with speed and accuracy. Its capabilities in simplifying financial information and providing interactive data analysis are making financial services more efficient and accessible. This shift towards AI-driven insights and customer interactions marks a significant leap forward in how financial data is processed and understood, paving the way for a more informed and engaged financial future. #Paykio #JitenderSinghDahiya #FinTech #crossborderpayments #startupfunding #angelinvestor #VentureCapital #Innovation #StartupFunding #VCInvestment #BusinessMentorship #StartupChallenges #InnovativeSolutions 

Wry interesting for those wishing to get an easier way to understand finance.

Ever wondered how ChatGPT can redefine your business?🤔 This isn't just tech buzz; it's the future of seamless business communication. In today's rapidly digitalizing world, leveraging tools like ChatGPT can give your business a competitive edge. Discover the prowess of ChatGPT in the recent article from 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀𝗶𝗻𝘀𝗶𝗴𝗵𝘁.𝗻𝗲𝘁. Here are some insights from the article that you must check out:👇🏻 1️⃣ The magic of 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗰𝗵𝗮𝘁𝗯𝗼𝘁𝘀 handling customer interactions with ease. 2️⃣ Gleaning 𝗱𝗲𝗲𝗽 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 with advanced analytics. 3️⃣ 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗳𝗲𝗮𝘁𝘀 with top-tier applications like Salesforce. 4️⃣ 𝗕𝗲𝘀𝘁 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀 to ensure your chatbot conversations are engaging and impactful. Click on the link to read now!👇🏻⬇️ https://lnkd.in/eeayqTUH As you consider implementing these groundbreaking tips in your business, remember that KYP.ai's services provide robust solutions that can seamlessly integrate and bolster the efficacy of technologies like ChatGPT. Ready to optimize and innovate?—Let us be your trusted partner on this journey. 𝗖𝗼𝗻𝘁𝗮𝗰𝘁 𝘂𝘀 𝘁𝗼𝗱𝗮𝘆!📞 #ChatGPT #BusinessTransformation #productivitymining #InnovativeTech #ProcessAutomation #FutureOfBusiness #KYPai

The largest factor in determining the quality of a ChatGPT response is the input that generated it. In other words, you can’t complain about the output if you’re the one providing the input. Here are a number of strategies to help you consistently generate accurate, creative, and insightful responses — and reduce your temptation to grumble: 1. Define the Role: Clearly specify the role ChatGPT should adopt. For example, "Act as a data analysis expert..." will channel the AI's responses within the desired expertise — data analysis — ensuring the relevance and depth you require. 2. Clarity is King: Ambiguity is the adversary of precision in AI interactions. Ensure your instructions are unambiguous and detailed. For example, "Summarize the following article in three sentences focusing on its implications for renewable energy" is a far superior prompt to “Summarize this.” 3. Use Delimiters: Employing delimiters like ****, ----, or //// to separate instructions or different parts of a prompt helps organize complex requests and ensures each part of multi-step instructions is understood and addressed correctly. 4. Patience Pays: Complex prompts may require a moment for the AI to 'think' and synthesize information, especially when processing chained prompts or intricate instructions. 5. Example-Driven Guidance: Providing examples of desired outputs can significantly steer the AI's responses to give you what you want. Provide an example of a well-crafted executive summary to guide the AI in generating a similar one. 6. Iterative Approach: Engage in an iterative process where the AI's responses are refined through subsequent prompts based on the initial output. This method is particularly effective for complex tasks requiring layered thinking. 7. Format Matters: Specify the desired format of the response, whether it's a list, essay, code, or bullet points. This ensures the information is presented in a way that suits your needs. 8. Dynamic Variables: Incorporate dynamic variables for customizable and scalable prompts. This technique is invaluable for templates used in different contexts like email marketing campaigns or chatbots. ChatGPT is a great example of “You get what you give.” If you want AI to deliver consistent, high-quality outputs, you have to provide it with consistent, high-quality directions. The sophistication and precision of ChatGPT’s outputs correlate directly to the inputs you provide.

I’ve tested and used hundreds of tools in the past decade. Most of them had no impact on my productivity, but some did. These are four must-have tools for Product Managers. 👇 1. Pen and paper I’m old-fashioned when it comes to this, but hear me out… Pen and paper scribbles allow you to test a thought early on and map it out when inspiration hits you. Despite testing several tools for this purpose, I still find I’m faster with an analog pen than with a digital tool. 2. Atlassian products I know, I know. They’re the ones we love to have and hate to love. 😅 Confluence and Jira help set a daily agenda and coordinate tasks with my team. They also help tremendously with internal communication. 3. ChatGPT I won’t give you a list of 10 prompts you must use, but I will say that AI changes the game. I’m still testing out ways to use ChatGPT to reduce time on mundane tasks, but I have to say the results are promising. I firmly believe that AI won’t replace Product Managers, but someone who knows how to use it will. 4. Analytics to monitor platform usage I use three tools to measure performance and engagement: Tableau, Snowflake, and Metabase. Though I still use Google Analytics, it’s more complex post-GA4. Instead, I’ve relied on Google Data Studio, which has more capabilities. What tool did I miss? 🤔

During a research project we're conducting on the relationship between product and analytics teams, I asked #ChatGPT to illustrate a day in the life of these two groups. What I initially received amused me, but this quickly turned into bitterness. As evident from the attached screenshot, a day in the life of product and analytics teams, at least through the lens of an artificial intelligence platform, appears quite fruitful. There's evident collaboration; the analyst is “discussing strategies and product roadmaps,” and “They are both engaged in a constructive conversation… indicating a collaborative and dynamic working environment.” Unfortunately, this is not a true reflection of reality; it's as artificial as the AI that created it. The only accurate aspect of this illustration is probably the “multiple screens displaying data visualizations and analytics tools.” I wonder why ChatGPT illustrated it this way, considering we all know this isn't the typical reality. In many instances, data analysts are merely dashboard builders, called upon when a product manager struggles to understand why a KPI is dropping. Often, there is little to no deep collaboration and certainly no “discussing strategies.” Worse, data analysts frequently attempt to derive insights without knowing if they're aligned with the product and company strategy. As we work closely with product and analytics teams, we recognize this idealized image can be achieved. But it can only happen when the analytics teams are genuinely appreciated and given the responsibility and trust to do what they’re hired for: bring actionable insights to drive meaningful product and business change. P.S. Data analysts, don't wait for this change to happen magically. Assert your place at the product strategy discussion table and demonstrate to the product team how you can guide them in the right direction. And if you're unsure how, feel free to reach out. #dataanalytics #loops #DecisionDrivers

What AI tools I use to decrease workload while increasing results. Not many, honestly. I'm just using the keyword as bait 🤪 BUT, what I do use a lot of is automation, AI's older brother that I think not enough people are talking about. I use tools like Zapier, GoHighLevel, Manychat and Meta Business Suite to automate things such as CRMs, email workflows, comment responding, lead nurturing and reporting. But, some of the AI tools that I DO use are: AI Live Chats → I've used GoHighLevel's own AI live chat or Intercom's 'Fin' to create Live Chat features that answer customers' queries without having to deal with them myself. Brainstorming → I've used ChatGPT or Gemini to come up with content ideas, hashtags, or to tidy up scripts or copywriting I've written. Branding → Again, I've used ChatGPT or Gemini as tools to help come up with taglines or even names for brands I have worked with. Research → I've used AI to do competitor or market research to help in content creation or product development. Lead Generation → I've used AI tools like Clay to help with lead scraping and then creating personal messaging for individual leads. Are there any AI tools I'm missing out on that I need to try? PS. I talk about automating your customer acquisition in my new 'Automated Acquisition' Blueprint. You can check it out here: https://lnkd.in/egZyYPm2