Business Ideas VII: GuideMe

Idea: GuideMe – an automated guidance counselor that helps students make better college and career choices

MVP: Too many students in the US leave college with too much debt and no realistic career path – in part because guidance counseling is a luxury at many American high schools. GuideMe will help fill this void, using students’ interests and strengths to show each student the college or vocational programs that will help them achieve their goals. GuideMe will also help students evaluate admissions offers to determine the best choice in terms of career ROI, taking into account both costs and future income.

Market: US high schools average one guidance counselor per 500 students, leaving most students with no career guidance except what’s available via friends, family, and the internet. In this vacuum there’s a tremendous opportunity to help students and families make better choices, with better careers and less debt the end results.

From a business model perspective, students and high schools have limited resources, but employers have a substantial recruiting need, and a successful app could funnel qualified candidates into positions at a far lower cost than traditional means of recruiting. There are over 150M working Americans, 100M of whom lack a college degree. The vast majority of that 100M employees might benefit from vocational training and placement services – almost 50% of employees change jobs annually. If the value of placing an employee is conservatively estimated at $1000 (versus the 20-25% of salary typically paid in white-collar recruitment), this leads to a total addressable market as large as $50B. [1]

Idea Score (0-10 scale): 8 points

Feasibility of MVP / Market Entry (out of 2): 2

The GuideMe MVP would leverage data on salaries and tuition published by college programs in order to determine career ROI, adjusting each career path for projected future changes. Much of this data is either publicly available or can be licensed, but it may need to be refined newer or non-traditional careers.

GuideMe would then determine the highest ROI programs for a student, based on their GPA, test scores, and interests. Virtually all of the data needed for the MVP is publicly available, though career ROI estimation algorithms vary – given my experience building HiddenLevers, this should be a competitive advantage.

Revenue Market Size (out of 4): 4

As noted above, the total market opportunity in the HR recruitment space, taking into account only the under-served vocational market, is conservatively estimated at $50B  per year.

GuideMe’s principal issue is that the initial platform rollout is devoid of any revenue generation plan – users in the cost-conscious student market are unlikely to adopt a paid guidance product. GuideMe instead intends to roll out a full-featured free product, while developing a placement product for employers requiring specific skillsets. GuideMe will be well positioned to match capable students with employers, enabling higher volume placement at a lower cost to businesses.

The challenge in building a two-sided marketplace style product is well known, but the returns to success can also be extraordinary.

Difficulty, Barriers to Entry, and Competition  (out of 2): 1

Many sites and apps exist to provide guidance in aspects of the college decision process, but none  provide comprehensive career guidance, and none utilize the concept of career ROI.

Existing competitors like MyKlovr are attempting to solve aspects of this problem, but appear to be focused on paid software approaches, which will limit growth potential. There is substantial risk involved in building  a free guidance product, and then working to link it to employment placement, but this approach is likely to capture the largest number of users in a space where massive scale is possible.

Riding Hype or a Trend (out of 2): 1

At present there seems to be little focus on this market – but if scale can be achieved among the 20M students in US high schools, then building a funnel to employers should become relatively straightforward. Very little has been done to improve the functioning of the middle of the US job market in particular – the rewards are too small for traditional HR firms to work hard at placing a plumber. Automation is the key to unlocking the scale potential in this market – and early career guidance is the key to bringing large numbers of candidates to market.

 

[1] Public companies like Randstad, Adecco, Robert Half, and Manpower show that valuations in the $5-10B range are possible in this sector.

Business Ideas VI: Run My House

Idea: Run My House – manage all your household services from a single app

MVP: Running your own house sucks – even if you outsource tasks like yard service, gutter cleaning, pest control, and cleaning, it’s still a challenge to deal with numerous service providers by inefficient means like phone calls. What if you had an app that enabled you to simply check off the service subscriptions you desire, and to take pictures to show problems needing resolution? Even when homeowners work with their existing service providers, there are major communication inefficiencies – not to mention the difficulty in acquiring good providers in the first place!

The difficulty with an MVP in the home services market is chiefly a business problem – a substantial percentage of home service work is performed in the informal economy, and as a result it’s highly fragmented. As a result this business is best attacked in a single test market to start, as providers need to be secured across all major services in order for homeowners to realize value in the service.

Market: The combined household market for home cleaning, yard service, pest control, gutter cleaning, and related scheduled services exceeds $100 billion per year, and including non-scheduled maintenance the total market may exceed $500 Billion annually. This market is currently incredibly fragmented, in no small part because there are limited economies of scale in providing most of these services.

Unfortunately for the consumer, this leads to a terrible experience. If Run My House can capture a 10% fee for delivering volume to providers, while keeping the cost to consumers static, it should be possible to capture meaningful market share. With a total addressable market greater than $10B, there is true unicorn scale possible in this market.

Idea Score (0-10 scale): 7.5 points

Feasibility of MVP / Market Entry: 0.5

Building an MVP for RunMyHouse could be daunting, given the number of service providers that must be secured before the service becomes compelling. This sort of “full-stack” startup, providing a complete service rather than just software, has larger potential but also substantially greater risk and capital requirements. Typically it makes sense to attack individual metro areas individually, starting with a beta market and working through challenges there first.

A simpler alternate MVP might simply help homeowners organize communication with existing vendors – perhaps by providing the software for free, with vendors selling their services via the app. This Zenefits-style approach (the give-away-the-software part, not the HR disaster) could enable rapid expansion at lower cost.

Revenue Market Size: 4 (out of 4)

As noted above, the total market opportunity in the residential space is several hundred billion per year – a 10% take rate implies a true addressable market size of 20B+. Numerous public players in the home services and home sales space (ANGI, Z) point to the possibility of a unicorn valuation for a successful player.

Difficulty, Barriers to Entry, and Competition  (out of 2): 1

A large scale b2c rollout of this sort would likely require substantial funding. HomeJoy was a substantial failure in this space, showing that giving away services at negative margins can take even well funded startups down. Handy, its largest competitor, has since worked hard to get to profitability, underscoring the risks of the home services market.

Taking a software-only approach could lower the risk of rollout, but substantial marketing spending would still be required to get customers and providers onboard.

Riding Hype or a Trend? 2

Bringing fragmented, illiquid, hundred-billion dollar markets online has been one of the key success stories of the last 20 years of the internet. Home services has been among the final frontiers because of its deep fragmentation, but Uber and ride-sharing proved that change will come to even the most glacial industries.

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 IV: Follow My Diet

Idea: Follow My Diet – Help users follow their diet’s guidelines when eating out

MVP: Eating within a diet’s guidelines is challenging for most, and is further complicated when eating out at restaurants. FMD solves this problem by detecting when a user is in a recognized restaurant, and showing only those menu options that meet their diet’s rules (the app would also show how to custom order at restaurants to stay within the diet). At launch the top 100 restaurant chains in America would be supported, representing the majority of all American restaurants – crowdsourcing additional restaurants and menu items should enable coverage to expand quickly from there. FMD will also enable the tracking and optimization of a user’s diet over the course of time – fall off track and the app will let you know what sorts of food choices would put you back on track for the rest of the day or week.

Market:

Roughly 15% of all Americans (45m people) are trying to follow a particular diet at any given time, with total spending in the diet and weight-loss industry exceeding
$33B last year. FMD could market the app toward existing diet providers in the space, as a management tool for their clients. FMD could also find a market in the management
of diabetes and other diseases where diet is an integral part of managing a long-term chronic disease.

With a large potential user b2c user base, freemium or advertising-based business models might make the most sense for FMD – but the possibility of a disease-management oriented approach remains open as well.

 

Idea Score (0-10 scale, up to 2 points per question): 4.5 points

(Overall this idea scored relatively poorly – I think pivoting it toward the health management space, perhaps diabetes or other food-related disease management, could strengthen the business case substantially)

Feasibility of MVP / Market Entry: 1

A substantial amount of restaurant menu data needs to be gathered and maintained in order to enable the app to function – but most of this is readily available and can be parsed online. With major restaurant chains commanding a huge market share in the restaurant industry, it should be possible to gather this data pre-launch in order to enable a functional product at launch.

Revenue Market Size or Eyeballs: 1

While the market size is large (as discussed above), advertising-supported products need to gain substantial scale in order to support a meaningful revenue stream. Since FMD is initially focused on helping dieters eat out, restaurants may be interested in sponsoring the app in order to drive traffic.

In a Growing Market? 1

The market for weight-loss and diet solutions is well established, and on the whole can no longer grow faster than single-digit growth rates. But the market for apps
that help manage diet-related diseases continues to grow rapidly, providing a strong potential growth niche.

Difficult, Barriers to Entry, and Competition 0.5

Numerous competitors exist in the diet app space, and apps even exist to find healthy restaurant options – but none attempt to analyze the mass market restaurant space. This is the opportunity for FMD – fast casual and similar restaurants can be hard to navigate for dieters, but it seems that there are no apps that attempt to solve this menu navigation process in a comprehensive way.

Riding Hype or a Trend? 1

Digital health apps, fitness trackers, and similar are a fast growing space. While diet-related apps operate at the edge of this space, the relationship may provide some halo for a business like FMD.

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.