Investor Connect Podcast Hall T Martin

In this episode of Investor Connect, Hall T. Martin explores the challenges and strategies of fundraising in the diagnostics sector. The guest discusses engaging investors from the Middle East, highlighting the need for investor understanding of the diagnostic market dynamics.   The conversation delves into the guest's $6 million fundraising goal to launch their initial product line. Hall advises on structuring funding rounds with a staged valuation approach to attract investor interest gradually. He emphasizes the importance of showcasing concrete milestones and leveraging deadlines to foster investor commitment, particularly within angel investor networks.   Hall provides valuable guidance on refining pitch presentations to resonate with diverse investor audiences, stressing the need for a compelling business case and a clear path to a lucrative exit strategy tailored to the diagnostics industry landscape.   The episode concludes with Hall offering support through Ten Capital, specializing in investor relations and fundraising campaigns. He outlines upcoming hybrid and in-person networking events aimed at connecting startups with potential investors, providing valuable opportunities for the guest's fundraising endeavors.   ________________________________________________________________________ For more episodes from Investor Connect, please visit the site at:    Check out our other podcasts here:   For Investors check out:   For Startups check out:   For eGuides check out:   For upcoming Events, check out    For Feedback please contact info@tencapital.group    Please , share, and leave a review. Music courtesy of .

Five Business Models for Linked Data Hello, this is Hall T. Martin with the Startup Funding Espresso -- your daily shot of startup funding and investing. Linked data is structured data that is linked to other data making it more useful for searches and queries. A wiki site often holds linked data sets. Here’s a list of five business models around the use of linked data. Subscription revenue such as monetizing the data directly. This works well for users who need a continuous feed of new data. Advertising revenue by placing ads around the data. This works well for non-subscription applications such as one-time use data. Authority revenue such as providing validation or compliance on the data. This works well for users that need to verify the validity of the data. Affiliate revenue such as including links in the data. This can be used for ecommerce applications. Value-add data revenue by combining multiple sources of data to create a new data set. An example is adding demographics and purchase history on prospective customers. This gives insight into what product the prospect may be interested in. You can also combine one or more of these models into one application. Consider these five monetization models for your linked data set.   Thank you for joining us for the Startup Funding Espresso where we help startups and investors connect for funding. Let’s go startup something today. _______________________________________________________ For more episodes from Investor Connect, please visit the site at:   Check out our other podcasts here:   For Investors check out:   For Startups check out:   For eGuides check out:   For upcoming Events, check out    For Feedback please contact info@tencapital.group    Please , share, and leave a review. Music courtesy of .

Data-Driven Business Applications Hello, this is Hall T. Martin with the Startup Funding Espresso -- your daily shot of startup funding and investing. Companies are growing their business using data to drive applications. Here’s a list of driven-driven business applications to consider: Streaming services use data to predict what customers want to watch. By using a recommendation engine, they can provide a better quality of service. This works particularly well when the customer needs discovery services before using the product. Recruiting departments are using more data analytic tools to identify the right candidates for the job.   One use case is the use of resume screening which searches for keywords on a candidate's resume and matches the job requirements. Advertising departments continue to gather data to better understand and target their audience. This is often used to find the right media outlet for their product. Financial companies use data to match the right funding tool to the right candidate. By looking at credit scores and other data sources, the financial company can determine how much to loan and at what price. Ridesharing services use data to predict how long a ride will take. By capturing data streams from traffic sources and reviewing historical data for the time of day and day of week, the ridesharing service can better estimate the time of a ride. Consider how data can improve your product, sales, or service.    Thank you for joining us for the Startup Funding Espresso where we help startups and investors connect for funding. Let’s go startup something today. _______________________________________________________ For more episodes from Investor Connect, please visit the site at:   Check out our other podcasts here:   For Investors check out:   For Startups check out:   For eGuides check out:   For upcoming Events, check out    For Feedback please contact info@tencapital.group    Please , share, and leave a review. Music courtesy of .

Data-Driven Business Models Hello, this is Hall T. Martin with the Startup Funding Espresso -- your daily shot of startup funding and investing. A data-driven business uses data to drive business decisions and processes. A data-driven business model is one in which the business is structured around data and changes price, costs, and responsibilities according to the incoming data. Many companies already use some data to drive decision making but a data-driven business takes it to the next level and uses it for strategic decisions. The benefits of a data-driven business model is that it brings greater productivity. It can decrease costs. It can speed up decision making.  It can create better products and services. It can increase revenue through new sources of income. To implement a data-driven business start with a strategy about how data can drive the business. Identify the key data sets needed. Implement an analysis of the data to make the incoming data useful for decision making. Install a process for using the data in the actual decision making program. There are limits to data-driven decision making as the complexity of business often requires more than just a data set to determine the next steps.   Thank you for joining us for the Startup Funding Espresso where we help startups and investors connect for funding. Let’s go startup something today. _______________________________________________________ For more episodes from Investor Connect, please visit the site at:   Check out our other podcasts here:   For Investors check out:   For Startups check out:   For eGuides check out:   For upcoming Events, check out    For Feedback please contact info@tencapital.group    Please , share, and leave a review. Music courtesy of .

Business Model Examples for Data Hello, this is Hall T. Martin with the Startup Funding Espresso -- your daily shot of startup funding and investing. There are several business models used for monetizing data. Here are some of the more commonly used ones: Brokerage -- this model matches data providers for data users for a fee. There are thousands of data sets available and many of them are not easily found. Bundling -- this model combines several data sets together to provide a new data set. By combining multiple data sets from different sources, new value can be created. Data as an asset -- this model sells data that is valuable by itself. An example of this is a customer list of a specific product.  Companies selling similar products purchase it to promote their product. Subscription -- this model provides a continuous stream of data. An example of this is a weather data feed which is required by those providing weather apps. Aggregation -- this model provides a list of sources for a product or service. Sites providing home contractor services require a list of contractors as one example. This is often used for advertising and promotion.  Pay-per-use -- this model provides data as needed and charges for each unit. An example is email generation which generates an email for each contact or verification of an email. Consider these business models for your data set.   Thank you for joining us for the Startup Funding Espresso where we help startups and investors connect for funding. Let’s go startup something today. _______________________________________________________ For more episodes from Investor Connect, please visit the site at:   Check out our other podcasts here:   For Investors check out:   For Startups check out:   For eGuides check out:   For upcoming Events, check out    For Feedback please contact info@tencapital.group    Please , share, and leave a review. Music courtesy of .

Building a Data-Driven Business Model Hello, this is Hall T. Martin with the Startup Funding Espresso -- your daily shot of startup funding and investing. A data-driven business model can accomplish a number of goals such as increasing brand awareness, understanding the customer better, and improving products and services. Here are the key steps in building a data-driven business model: First, determine the outcome of the business model. Find clarity on the goal of it. Second, what is the deliverable from the effort? Is it a data set that shows how to improve customer satisfaction, increase awareness, or understand customers' perception of the product. Third, what data is needed? The data can come from the customer, partners, or generally available data sources. Fourth, how do you analyze the data? This could be applying prescriptive, descriptive, or predictive types of analysis. Fifth, determine how to monetize the data. This could be selling the data directly, using it to improve internal processes or providing the data to partners or customers to enhance the selling process. Sixth, identify the challenge in capturing and analyzing the data. This could be regulatory requirements, data quality issues, data quantity issues, or data analysis capabilities. Start with your business goals. Consider these steps in implementing a data driven business model in your organization.   Thank you for joining us for the Startup Funding Espresso where we help startups and investors connect for funding. Let’s go startup something today. _______________________________________________________ For more episodes from Investor Connect, please visit the site at:   Check out our other podcasts here:   For Investors check out:   For Startups check out:   For eGuides check out:   For upcoming Events, check out    For Feedback please contact info@tencapital.group    Please , share, and leave a review. Music courtesy of .