Key Struggles with Analytics, Decision Intelligence, and Machine Learning Micro-Business Communities

A Big Market has a ton of Untapped Potential:

Conaxon has spent a lot of time interviewing small business owners, representatives from economic development organizations, chamber of commerce’s, and small-business development centers. Out of these conversations, a burgeoning passion for finding a way to make machine learning (ml), artificial intelligence (ai), analytics, and decision intelligence (DI) more plausible for the micro-businesses out there. By focusing on how to apply these technologies, Conaxon can help take the fear and risk out of key decision making for the small companies that could use the help.

Our mission is to optimize decision making processes for small and micro businesses using a platform that aggregates shared data from contributors and recommends data to users that might help answer key business questions.

Nearly 99% of businesses in America are considered small—topping out at about 30 million. A further subset of the small businesses are called micro-businesses and they make up nearly 75% of the small businesses. We think a vast majority of those micro businesses are underserved due to a focus on firms that can deliver huge contracts.

What we’ve Found in our Research so far:

Here are the key struggles and how our (pre-launch) product Collective Vantage attempts to address some of those:

Cost

For most micro-businesses, budgets are tight! Return on investment is of huge importance when making purchases—especially when it comes to technology. Given how hard conveying the value of analytics is in terms of financial return for a large organization, the uphill climb is even steeper for a small business. The constituent components for a production-level analytics, ai, and ml application are still quite expensive to build, maintain and grow. A data engineer in most areas commands northward of $70,000. Many Data Scientists make northward of $80,000 to $90,000. Business intelligence professionals and analysts can make between $65,000 and $80,000. If a consultant is being considered, they can charge several hundred per hour. Marketing databases that aid in customer segmentation can also cost many thousands of dollars—and are often out of date quickly. It doesn’t take long to realize your typical small business will struggle to afford tools, human capital, and data.

All these costs in mind, Conaxon realized if the decision making process could be optimized, then a lot of good can be done for a many businesses. Essentially, automating the process of research, aggregating data, cleaning, enrichment, and basic presentation would save considerable time and create economies of scale required to quash the cost. Conaxon believes Collective Vantage has the technology to achieve these efficiencies and can deliver an extremely competitive product relative to other players in the space.

There Just Isn’t Enough Data

In all of our interviews, it was very obvious that small & micro businesses struggle to collect and store enough structured data to derive insights. Most companies, logically, are focused on the operations and delighting customers. Data isn’t really at the top of most small businesses to-do list.

This feedback prompted a thought! Why not aggregate data across a network of similar businesses to create a large dataset that can be anonymized, cleaned, enriched and more useful? This type of model provides some unique advantages:

• Users / contributors get a truer sense of the larger context of a market, customer segment, or any other subject matter that gets aggregated. The whole is greater than the sum of its’ constituent parts

• Since the goal is to aggregate completely across a network, a user / contributor can ‘look across’ to other products and services being offered to find opportunities for innovation within their own local markets. Diversity in analytics is a key advantage we want to provide to contributors and users

• Data quality is more likely to be less of a concern because there is an incentive to not poison the well everyone is drinking from in terms of what gets contributed

• Contributors do not need a ton of data to get started. In fact, we want to encourage large networks of businesses to start small continue to grow their capabilities while still being able to adopt analytics, ai, ml, and DI in the short-term. Costs can remain low with this approach as well.

Data can take Awhile to Collect

Interviews with our target customers seem to indicate that, in most cases, there would be a pretty long lead time to be able to have a sizeable enough dataset for analytics. If a retail establishment wanted to do any sort of sophisticated forecasting, it would take years to collect sufficient number of observations. Consider a small antique shop that wants to do customer segmentation. Unless an antique shop brings in hundreds of customers in a short amount of time, the database will become outdated quickly and it will be impossible to detect drift.

Collective Vantage addresses the timeliness issue by taking small sets from many sources and continually supporting contributors in expanding their collection capabilities.

Complexity

We have been learning that many small and micro businesses simply can’t yet tackle these complex topics on their own. Many micro businesses are an owner-operator with a few employees that do not specialize in analytics, let alone ai or ml.

Our solution is focused on being able to quickly tackle the decision making process by being the analyst for the customer—but much faster and more cheaply than hiring someone or performing the work themselves. The simplicity comes from the customer/user inputting a question they want an answer to so to make a decision. Once the question has been asked, Collective Vantage handles the rest. The platform returns a set of recommended data and analysis that can help answer the query in an informed way.

When cash is tight, ROI is king

Many businesses we talked to expressed how tough it is to just pay the bills. Insufficient cashflow is the third leading reason entrepreneurs close their doors. For those contributing data to Collective Vantage, we want to show that data truly is an asset, each entity owns their data, and each entity can derive monetary value from their data assets. To address the concern over ROI, Collective Vantage will provide the opportunity to earn crypto or cash when a contributors data is sold (with permission of course). Because we believe that each contributor owns their data and is contributing to a valuable dataset that outside entities that will want access, it makes sense to redistribute those revenues back to contributors.

Join the Team

Conaxon is looking to find 100 businesses to partner with on our launch. Please visit: https://collective-vantage.crd.co to sign up and learn more about Collective Vantage.