Tag Archives: future of investing

Where is analytics headed in 2020? An insight gathered from 25 top #startups

The most amazing part of my job is that I get to learn from the smartest entrepreneurs in the world. I cant think of too many people who get a chance to talk to 3 entrepreneurs via video conference in California at 8 am, 2 startup founders from Singapore at 1030, have lunch with 4 amazing big data analytics company promoters in Bangalore and then wrap up the night with a conference call at 830 pm featuring a recently funded analytics company in Boston.

Most VC’s get a local perspective, Silicon Valley, Tel Aviv, Bangalore, or Beijing. I get pitched from all over the world. Most investors in the valley will tell you the best and brightest come to the valley, but I believe there’s a big shift happening. More on that later.

I wanted to share one very insightful thing I learned after 25+ detailed (over 1-2 hour) briefings with entrepreneurs who are all innovating in the analytics space.

The future of analytics is in offerings based on derived insights.

I just gathered this insight, so let me explain.

Historically the analytics space was filled with services companies. In fact ¬†consultants would take loads of data and gather insights to help their clients with their business objectives. The best known analytics companies that dont call themselves analytics companies are Mckinsey, Bain and other management consultants. Then companies like MuSigma and others decided to “offshore” this insights service. The problem with this type of offshore services business is obvious – low margins (net of 20% and since they are people intensive, they dont scale as fast).

The purveyors of the software model of analytics are those that provided a SaaS product – names such as Cognos, Business Objects etc. Companies like Kaggle crowdsourced your analytics and there are hundreds of companies providing SaaS analytics, such as GoodData, Insights Squared, etc. The problem with this type of business is that most of these software products are “generic” hyper cubes and data warehouse / data mart models. Their margins are better than services, but still nowhere near the 80% gross margins that some industries command.

Since we all know that software is eating the world, many companies in industries such insurance, banking, finance, manufacturing are all facing a threat from new age software companies, who are re-imaging the businesses.

The next generation of analytics companies are those that take the insights gathered and create an offering in that specific area so they can benefit from the insights, instead of providing those insights to others in the industry who make more money from it.

Let me take a simple example. Global Analytics just raised $30 Million. They are an analytics company. They used to provide their insights to financial institutions by way of giving them “leads”. These leads were those customers who were worth extending credit to. An average lead in this case cost their client $30 – $100 (depending on quality).

While that in itself was a big and large market, the larger market is to extend the banking facility themselves, which means with their analytics and insights can directly offer short term cash loans to those that their analytics deems are the best. The average customer in this case will make them $500 – $5000 (depending on the size of the loan). They did this via their own offering Zebit.

Now, most founders with a background in software will say “Wait a second. what business are we in? Software or Financial Services”? That’s a good valid question.

But when you get into the “Financial Services” business there’s loads of things you can re-imagine and redo the right way with a “software frame of mind” as opposed to being a “financial services insider”.

Huge difference in revenue and margins.

That’s the future of analytics.

Using the insight gathered from the analytics to offer a product / service direct to customers and not selling the insight or analysis to existing players.

Let me give you some more examples.

Lets say you are foursquare. You have analytics and insights into where people check in, where they go, what their patterns are with respect to travel.

Would you rather sell this treasure trove of data to marketers (and face a bunch of privacy issues) or would you create an offering based on those insights yourself?

The value to a museum of information that a potential customer is near their location is possibly $2.5 ¬†(that’s quite high I imagine if the tickets are $25).

Instead if foursquare offered a virtual museum tour or a personal crowdsourced guide to the museum, then they could sell that for $10 and have 40% margin on that offering.

Imagine if you had driving habits data about car owners – how they drove, what time, how fast, how safe, etc.

Instead of selling the “best driver” data as a lead to the insurance companies, who might pay you $100 – $200 per lead, you could create your own insurance offering based on miles traveled, safety of the drive etc., changing the long standing model of one-size-fits-all car insurance.

There are lots of examples that entrepreneurs are dreaming up these days and the most audacious ones I am talking to want to upend large established industries. It is both exciting and scary at the same time.

That’s exciting. Software will truly eat the world.

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Why more non-technology investors will form the bigger pool of angels by 2020

It is only 7 years to 2020, and I’d like to speculate a bit and make a fool of myself by taking a stab at the future of tech angel investing. To do a good enough job of predicting the future (or a hopeless job of it) you have to know the current state well enough.

In the US there are about 250,000 angel investors across all sectors and about 25% of them are in the technology sector alone. The number of active technology angel investors is claimed to be about 40,000 – active being defined as someone who does at least 1 investment in a calendar year.

Of the 40K angel investors, fewer than 5,000 are classified as “lead investors”. These are folks that will take the pole position in funding a startup and get other investors to rally around them. In India, those corresponding numbers are 500 angel investors in technology and about 25 lead angel investors.

Currently word of mouth networks rule and tend to be the large part of deal flow for investors. Most lead investors get pitched by people they know first or have worked with, then via referrals and finally from random others. This means that typically angel investors tend to put money in things they (mostly) understand or people they know well. That makes logical sense, since they tend to want to add value, learn from and coach entrepreneurs instead of just providing the money and checking in once in a while.

The increasing need for speed to make decisions, means that most angel investors are forming affiliations with others who complement their skills and are beginning to pursue “expertise” in certain areas.

I am noticing another trend that’s starting to make waves in the angel investor ecosystem.

Non-technology angel investors are increasingly becoming due diligence experts in deals.

I spoke with 5 of the top investors in the US a few weeks ago in the technology space and their preferred co-investors were ALL non-tech. That’s amazing and bodes well for startups.

The example I was given is the work being done in agri-tech (intersection of Agriculture and technology). Most of the technology portions are relatively easy to understand for a technology expert, but the non-technology parts of soil testing, crop selection and cold-chain storage were all alien to most technology founders. So they enlisted the help of local (Seattle) farmers and food supply chain experts. In this case it was cheese processing.

In places such as India, where technology founders are a small part of the ultra-rich, this is a dramatic change and a great way to expand the angel investor ecosystem.

I can see how we can enlist more non-technology high-net-worth individual to form teams of investors to help get deals done faster. Since they have good working knowledge of the space and sectors, they are more likely to provide insights and connections that matter.