New M&A Market Sizing and Strategy

BACKGROUND Basis State's core business is making the connection between 2 types of companies: small startups (<$2M USD annual revenue) and later enterprises (>$50M USD annual revenue). Our services involve understanding the technical needs of the larger enterprises, and how the technical assets of small startups can fill those needs. We use that understanding to facilitate acquisitions. We mainly offer this service in support of startups that are looking for an acquirer ("sell-side"), but are in the process of offering new services for larger enterprises that are looking for acquisition targets ("buy side"). In addition to startups and larger enterprises, there's a wing of our ecosystem that buys and sells startups, but that we do not clearly understand: investor-operators. Having a strategy for this segment, and a lead list of its entities, is a growth opportunity for us. THE PROJECT This project involves helping Basis State incorporate the investor-operator market into our exiting offerings. In order to do this, we need to: Know the size of the investor-operator segment and its potential impact to our business Understand the subsegments within the investor-operator segments, and how their needs for our services might differ Understand the relative importance of the various use cases for our service. For example, investor-operators might be looking for startups to "bolt on" to their larger portfolio companies. Or, they might want to use our service to divest portfolio companies that are not growing. Identify any channels for this market. Online communities, open lists/databases, complementary product or service providers that might be strategic partners as we enter the market. Have clear criteria for targeting individual entities within the segment, i.e. what signals can we look for to know an entity might be interested in our service. Have a list of target entities to jump start our outreach WHAT WE KNOW SO FAR In order to have any interest in our service, the investor-operator must be interested in making or finding acquisitions of very small software companies (<$2M annual revenue). Further, they must operate their companies. The challenge of the operator-investor market is that it is fragmented and goes by different names. Further, each entity has its own specialization, a.k.a. "thesis," which will determine whether or not they are interested in small software acquisitions. Here are some of the known facets of the market. Boutique Private Equity - small private equity funds. Most are not interested in small acquisitions, although a subset might have the "bolt-on" use case. Operating VCs (or Angels) - this is an emerging segment and a very small portion of VC funds. Most do not operate companies. Venture Studios - most build their companies from the ground-up, but some might have an interest in growing their companies through small acquisitions Serial Entrepreneurs WHAT THIS PROJECT PROVIDES We are a small company. Your work could have a major positive impact on our business. We will share that impact (quantified) so you can claim the success. Anyone with an interest in M&A, venture capital, private equity, or startups will get first-hand experience with how these industries operate.

Create a Semi-Automated Workflow for Identifying Potential Acquirers

BACKGROUND Basis State uses several steps in its identification of potential acquirers. Most steps are manual, using a set of both purchased tools (e.g. CRM) and proprietary tools (website keyword extractor). Our selection of potential acquirers is a mix of heuristics that come from experience, as well as the output of more automated methods. The current process has too many manual steps and takes too much time. There is ample opportunity to streamline the process, turn some of our assessments into defined rules, and automate more of the steps. THE PROJECT Involves: Documenting the current process, along with time/resources for each step Finding areas with the most leverage for efficiency Redesigning the process to take advantage of your findings. We have a modest budget for software development if you find opportunities to automate or connect pieces using APIs. A successful project will include the following: A significant (>20%) gain in efficiency over the current process An algorithm that scores acquirers for their fit and propensity to make acquisitions. We can guide you through the data points we use as well as how we factor them. Build a matrix for title and type of acquirer to respond to outreach based on response rates An overall reduction in hand-off points, or other junctures that are prone to error or delays You will use: Your analytical skills as you use our current data to determine which is the most valuable to selecting acquirers. Regression might be helpful. Your understanding of business process design Your knowledge of engineering as you assess our current “stack” for opportunities to streamline by using new or alternative tools WHAT THIS PROJECT PROVIDES Hand on experience in an entrepreneurial environment and the work required to create a scalable business Better understanding of what creates success in a tech start-up and where some businesses will struggle to achieve success Better understanding of how acquisitions close and are valued in a market with few transactions and a lack of common metrics

Industry Classification Algorithm

Description We need an algorithm to classify businesses into industries. Based on previous endeavors, we anticipate this involves scoring the businesses with a probability of belonging to a given category, using correlations between the various inputs we have in our database. We will provide all of the data necessary to complete the project. The classification involves 3 inputs: A list of terms that appear on the business' website A 3rd party description of the business A 3rd party list of industries with which the business is associated The output is a probability that this business belongs in any of our list of ~100 industry classifications. We have a training set of several hundred businesses that have been manually assigned. We have a universe of roughly 50,000 businesses that need assignment, so we will program your algorithm into some sort of automated workflow (you get bonus points for providing a methodology for automation). Qualifications Data science background including comfort with statistical methods. Background with programmatic execution of algorithms also helpful, but not required.