I have seen many entrepreneurs building their startups solely based on the vision they have. Having a vision is a good start, but it’s only a tiny piece of the puzzle. So many other things live above a good vision, especially when it comes to growing a company.
As a professional investor, I’m going to walk you through the process I have been implementing at my portfolio companies. It’s how I recommend building a growth engine, or a strategy your startup can use to achieve sustainable growth. My process can be applied to different parts of the engine, such as marketing, human resources, product development, etc. Here’s how you can get started:
Identify a problem.
Successful entrepreneurs come in many shapes and backgrounds, but they all have a common skill: discovering pain points in their fields. By understanding the questions your customers have, you can create value for them instead of just pushing products and collecting user counts. I’ve found that understanding your customers also results in an incredibly higher retention rate for your business. The way you know that you’re solving the real issues is to have customers willing to pay you anything to have you take over their problems.
You might ask, “Where do I look for problems?” There’s no absolute way how you should start. However, I’ve seen that the founders I work with who successfully spotted the opportunities and carried out the executions were inspired by what they were familiar with or loved.
Form a hypothesis.
Building a startup is like practicing a scientific experiment. Once you recognize a problem, you then have to hypothesize different potential causes and ways to fix it. It is also the most crucial and difficult step in building a growth engine for your company.
A hypothesis can be anything. Without it, you can’t design a product that connects with people and provide maximum value to the customers. This is the time that you demonstrate your superpower as an entrepreneur: imagination and creativity. Without imagination and creativity, you cannot build a moat around your business, and you’re just simply doing what your competitors are doing.
Once you have the hypothesis, it’s time to design the test. Just like a scientific experiment, there are two main types of testing: quantitative and qualitative approaches. And, these tests are usually carried out under a controlled environment, which means the things that can go wrong are limited. Under a controlled environment, you limit the variables or the items you want to test, such as conversion path, website layout or modification on a product, to get accurate correlations between your hypothesis and results.
The qualitative approach concentrates on a small portion of data and understanding deep-down elements of this data. A qualitative approach is a good way for early startups to start gathering feedback from users while the team is building up the product. The traditional method of building a product is to perfect every detail of the product before the launch. Once it’s launched, no more modifications or upgrades have to be implemented.
On the other hand, the quantitative approach is well-suited for companies that have a large number of existing users or traffic. It focuses on cumulating numerical data and generalizing it across segments of test results to explain a particular phenomenon. An example of a quantitative approach would be testing how users react to a specific Facebook ad based on their demographics.
Under the quantitative approach, results are sorted into different buckets, and from there, you can make strategic decisions with the data. With the right margin of error and confidence level, the data from the quantitative approach is just as high quality as the qualitative approach.
With our qualitative and quantitative approaches, building a product is like building a house. After setting up the foundation, you start with one room at a time. Once a room is finished and inspected, you then move on to the next one. It’s very important that you don’t waste all the resources building a product that nobody wants.
Collect and analyze.
While the test is running, it’s time to collect data. Data is the fuel for your growth engine. The more you can learn from the data you have collected, the more you can learn about your customers and how they interact with your products. That knowledge can then transform into the next product upgrade or modification. So, how do we translate the raw data into meaningful intelligence?
Before the test is live, you first need to finalize with your team on the key performance indicators you want to obtain. KPIs are the way to present raw data into meaningful pieces of information. For example, your marketing expense is not very useful when comparing with competitors simply because companies at different sizes have different marketing budgets. However, when you divide marketing expenses by how many new customers you have acquired, you get a brand new data point called customer acquisition cost. With a CAC, you can compare the efficiency of your marketing spend with your competitors.
You can create any KPI that’s relevant to your business. There are a couple of common KPIs to sort raw data into, such as conversion rate or lifetime value. To track the result of the tests, you have to make sure these KPIs are easily comparable with others.
Building a successful and long-lasting business is not easy. Many things can go wrong, and any misstep can burn all your hard work into flames. By following the steps laid out above, you can ensure that constant improvement and testing are running parallel with your growing operation. The way to build the most significant moat in town is to innovate while having everything under control.