Business Ideas V: BestUse

Idea: BestUse – analyze real estate through the lens of local zoning and code to determine best use, and identify underused properties

MVP: The process of identifying promising opportunities in real estate is largely a manual one today. Real estate investors and agents scour listings and property records to determine where opportunities to convert an old office into multifamily housing might exist, for example. BestUse would automate this process by using machine learning to compare zoning laws and potential uses to identify underutilized properties. A minimum viable product would involve targeting a particular metro area to analyze local zoning and building rules there in detail.

Market: BestUse has a likely path to market very similar to HiddenLevers (my current concern). The advantage of selling high value software in a niche market is that initial clients can be acquired very quickly after alpha release – the moment HiddenLevers portfolio stress testing worked in a minimal way for a professional audience, client acquisition amongst investment advisors began. With BestUse, real estate investors might quickly embrace a technology that enables them to identify “diamonds-in-the-rough”, properties currently languishing in a sub-optimal use.

The downside with this approach – the total addressable market tends to be limited: if real estate investors are willing to spend four to five figures per year for this capability, the total addressable market might be in the billion dollar range – enough to build a viable business, but not enough for a highly scalable growth path.

Idea Score (0-10 scale, up to 2 points per question): 6 points

Feasibility of MVP / Market Entry: 2

An MVP for BestUse would require a non-trivial initial effort to acquire needed real estate data and to plug in the appropriate analytics on local real estate codes. Actual market entry would likely follow a pattern similar to that for other niche analytics products – get in the hands of paying beta customers and iterate. This is a proven model with much lower risk than launching b2c oriented products.

Revenue Market Size or Eyeballs: 1

If the market is confined to analytics tools used by the commercial real estate industry, then the total addressable market is likely to be subscale (no unicorns here). A high margin $10M revenue business is possible, but getting past this to the next level is a key concern. Since the same sort of analytics is used in commercial real estate appraisal (an $8 billion market), adding this and related capabilities might push the scale a bit – but it’s not clear how to get to a $10B addressable market.

In a Growing Market? 0.5

The real industry is very mature, with growth rates unlikely to exceed the overall economy.

Difficulty, Barriers to Entry, and Competition 1.5

BestUse requires a combination of knowledge of real estate investing with technical modeling capabilities, providing a modest barrier to entry. The need to analyze zoning rules further raises the bar here.

Startups have started to appear in this space – Skyline is using similar analytics to partner invest in properties, an approach which might lead to greater overall market potential. Bowery Valuation is focused on automating real estate appraisals, a naturally related market.

Riding Hype or a Trend? 1

Applying advanced analytics and machine learning to any niche generates interest at the moment – but this is not a particularly innovative or new use case.

Business Ideas III: HalfTimer

Idea: HalfTimer – Link employed developers with spare capacity to half-time positions

The economy is going full steam. The number of job openings is at an all time high [1]. Technology positions are particularly in demand, with hundreds of thousands of developer positions unfilled nationwide.

MVP: Halftimer.com places developers interested in long-term part time employment with companies looking for experienced development talent. We have found that experienced developers are willing to lower their hourly rates by up to 40% in order to secure a long term contract that is in addition to their full time job. This differential enables savings for companies that work with HalfTimer – a substantial competitive advantage in the staffing business. The initial MVP need not involve more than outreach to employers and developers via LinkedIn, to staff the first several candidates and prove the model.

Market: 5M full time technology professionals

Halftimer.com builds on a concept successfully used by my other ventures to tap an underutilized resource: experienced, full-time employed developers. Many developers, particularly at large corporations, are not fully utilized whether in terms of mental capacity or even time (this documentary details the situation at length). There are almost 5m individuals employed in development-related positions in the US today – if even 10% have excess capacity, this represents a pool of 500,000 potential resources.

Scoring (0-10 scale, up to 2 points per question): 6 points

1. Feasibility of MVP / Market Entry: 1.5 points

The HalfTimer concept exploits an inefficiency: most employers historically won’t buy limited hours for professional work. On the developer side, developers looking for additional freelance work find it difficult to consistently find small projects that fit around their day jobs. HalfTimer attempts to solve this problem, and market entry is straightforward as this is just a new spin on existing staffing concepts.

2. Revenue Market Size or Eyeballs: 1.5 points

500,000 potential HalfTimers, with net revenue per resource at $15,000 = $7.5B/yr total addressable market. Put another way, staffing ~100 HalfTimers would generate 1.5M in net revenue (against roughly $6.5M in gross revenue), enough to run a profitable small startup. The crucial question: cost of acquisition of both employers and employees.

3. In a Growing Market? 2 points

The technology employment market continues rapid growth, and the core constraint remains supply – which is precisely the problem HalfTimer seems to resolve.

4. Difficulty, Barriers to Entry, and Competition: 1 point

Many existing players in the staffing space could potentially attack this idea, and technically there are no real barriers to entry. Gigster, Gun.io, TopTal, and FlexTeam are startups attempting to ease companies’ ability to find freelance talent – these are similar but not identical to the HalfTimer concept (startup competition bolsters the strength of the idea, as it confirms an idea is worth exploring).

5. Riding Hype or a Trend? 0 points

The gig economy has grown substantially, and HalfTimer represents an evolution halfway between freelance and traditional full time employment. But it’s not clear that concepts in this space have much mind-share at the moment.

[1] The JOLTS survey shows the number of openings to be at an all time high, even when compared to 2000 and 2007 on a relative basis.

Note: I changed the first scoring question to address feasibility rather than whether the idea is “transformative”, which seems to be an imprecise concept at best.

Business Ideas I: Juggler, Never Let A Message Drop

Over the years I have kept a running spreadsheet of business ideas – my current business, HiddenLevers, was once a denizen of the same spreadsheet. But ideas have expiration dates [1], and my idea list has grown while my available time has shrunk. Over the next few months I will be sharing my ideas – I’d love to hear feedback and to inspire others to take the next step or gain inspiration. To provide structure, for each idea I’ll share my thoughts on what I thought the MVP might be, and a scoring of the idea using my own 10 point scale. Here goes!

Idea: Juggler – Never Let a Message Drop

Juggler would watch your firm’s emails, LinkedIn, and other messaging platforms to ensure that every inbound request is tracked and gets a response. The challenge today is that inbound business communication arrives across channels, and often comes in to many different personnel at your firm. Using AI, Juggler would determine which messages actually require response, and monitor these across all firm users, alerting managing when prospects and clients are awaiting response.

There are a ton of AI-based email solutions and also support email solutions from firms like Zendesk – but none of these seem to focus on this specific use case – firm-wide monitoring and taking a global look at all communications to a particular client.

MVP:

The MVP is simple – do the machine learning work to simply determine whether a particular email requires response. Emails asking questions clearly come to mind – but taking a true machine-learning approach, can we approach 99% accuracy here? This can then be married to a simple UI showing individuals (not messages) requiring attention – this sort of dashboard data could ideally then be integrated into Salesforce or other CRM platforms.

Scoring (0-10 scale): 6 points

1. Is it Transformative? 1 point

This is a fairly standard use of machine learning in 2018 – but the accuracy level required to make this viable is not. Also, many businesses still don’t take real advantage of CRM systems, and this idea automates some of the key value concepts from CRM for a small business (ie don’t let any leads slip through the cracks – I’m looking at you, contractors).

2. Revenue Market Size or Eyeballs: 1 point

This is a broad market – virtually every business could use this capability, so volume pricing of even a few dollars a month in a SaaS solution could scale quickly. Presuming that this capability is worth $5/user/month – the US market alone is greater than a billion per year.

3. In a Growing Market? 1 point

While email utilization is stable, multi-channel communication is growing – think chat, social media, VOIP (phone) – in theory the same approach could be applied to all of these.

4. Difficulty, Barriers to Entry, and Competition: 1 point

It may prove difficult to achieve the level of accuracy with machine-learning to inspire user confidence. If businesses suspect that even a few important messages might be slipping through, they will lose confidence and not use the product. Ideally the system ought to learn based on each user and firm’s data – posing a bit more complexity.

5. Riding Hype or a Trend? 2 points

AI and machine-learning are arguably THE trend of the moment, and while arguable overhyped – the Juggler idea definitely is riding this trend.

 

[1] James Watt’s steam engine was an excellent invention, and applying it to pumping water out of mines an excellent business idea – for the 1770s. The concept of hailing a car via smartphone was likewise a great idea – in 2009. It’s also possible to be too early – Yahoo Briefcase shutdown the same year DropBox was founded (although the latter was also a vastly superior implementation).

 

P.S. Investors out there, feel free to reach out if any ideas in this series are of interest – while my core business continues to grow rapidly, I’m open to discussions on how to seed fund and launch against many of these ideas.