Two months later, I want to share that Sapiengraph makes for a poor business

I started the Sapiengraph effort by hiring a small sales unit. Historically, I always built the product first then attempt to sell it. The risks are obvious. I might invest months on a product that nobody wants. With sales first, I let the market decide instead. Besides, knowing myself and our team, the technical part of the business is never the problem.

This post intends to share the progress in our effort in market discovery

In the last two months, the sales and marketing team, and I have been hard at work gathering feedback on three fronts:

1. Sales pitches
2. Fund-raise pitches
3. Content marketing

With the feedback, the questions that glare back at me are:

1. What exactly are we selling?
2. Who are our customers?
3. How large is the potential market?

I thought I knew the answers. But our outreach strategy was random at best. We were targeting AI (data analytics) companies, and we were hoping to be AWS for their data needs. But what were AI companies?

We considered Grab an AI company because they have some predictive algorithms that required data to be trained.

We also considered quantitative trading companies to be a part of our target market because they utilized algorithms and big data.

These companies needed data, and we were able to crawl data. Once we got into the nitty-gritty details, questions surfaced.

1. But what data exactly were we offering that was so unique and immediately useful to AI companies?
2. Why do they need us?

The dilemma - infrastructure or solution

I love building infrastructure products like Kloudsec. Infrastructure products are products like Diffbot or Amazon AWS. They allowed other companies to build bigger and cooler things with their product offering.

Solution products solve problems for businesses. Like how Google Analytics is able to solve the problem of  telling me who and how often people come to my website.

To optimize for ease of sales, I went with the solution instead of infrastructure.

Building blocks

What do we have? Our killer advantage is that we have a niche of data that no one else can get. We have

1. A giant database of people's faces and metadata for entire populations
2. A super-accurate facial recognition tech

The mistake was in trying to sell this data directly as a product. But understanding these building blocks, there are a ton of opportunities I can pursue.

The solution

There are multiple opportunities that our capabilities open us up to. Each opportunity comes with its set of answers to:

1. What we are selling
2. How much it will cost
3. Who our addressable market is
4. How it will fit into our company's vision
5. How large our addressable market is

These opportunities include:

• In-store analytics for offline to online retargeting - we can identify who comes into your store and have you retarget them on the interwebs.
• Surveillance - we can augment security with real-time identity verifications
• HR; attendance and registrations - we can automate organisation workflows such as attendance taking through facial recognition and our people database

As we explore these opportunities, it becomes immediately clear how I can pitch better in my sales meetings because now I know exactly what benefit I can offer my customers beyond my capabilities.

Anyways, I strongly believe that business models are iterative. Anyone that tells you that they have a perfect plan on day one is an idiot.