Data Strategy and Quantitative Forecasting Can Help Early-Stage Startups – CXO Matters
Business

Data Strategy and Quantitative Forecasting Can Help Early-Stage Startups

Data Strategy and Quantitative Forecasting Can Help Early-Stage Startups
Data Strategy and Quantitative Forecasting Can Help Early-Stage Startups
Image Courtesy: Pixabay
Written by Melwin Joy

Fresh startups are facing a financial crisis that has worsened as the venture capital raising market has tightened significantly. To appeal to potential investors, especially recession-conscious investors, startup founders must provide compelling evidence of a strong track record. One way to do this is through data strategy and quantitative forecasting, but when there is little or no economic history, there are few metrics available to support such a forecast.

But all is not bad news. There are tactics to overcome this challenge and build a compelling case. Done right, these steps can not only provide compelling, data-driven financial projections but also lay the foundation for a data-driven strategy that helps founders scale their businesses. While venture capitalists love big, bold business ideas and have recently emphasized metrics like cash burn and profitability, strong annual revenue projections are still extremely important.

Data Strategy and Quantitative Forecasting

Generally, the higher the earnings growth rate, the higher the potential valuation and the more likely investors will receive interest. Startups must be agile in order to grow quickly and achieve the annual recurring revenue they need. To do this, they need to be data savvy, which means they need to make operational information accessible and easy to interpret.

By utilizing metrics to create benchmarks to guide business actions, and then incorporate them into business plans, financial models, and sales presentations as they move through the different stages of fundraising. However, no company has unlimited resources to research and compile these statistics, so every startup must build a foundation for a simple data collection and analysis function that focuses on the most needed metrics.

As we understand, quantitative forecasting needs a great amount of data to work. To collect data, startups can focus on the following three points.

  1. Market research
  2. Pricing
  3. Sales pipeline

Let us explore them and learn what they stand for in the business.

Market Research

A deep understanding of the target market help startups create a fact-based framework for forecasting sales and profitability with valuable benchmarks. The data you collect helps define the broadest target market and develop the basis for pricing and other key financial metrics. Even the most basic market research can yield strong data strategy results for a business trying to define its customer base. Prospective customer surveys are excellent sources of both qualitative and quantitative information. In-depth interviews with a company’s current employees, vendors, and customers can provide qualitative insights that you can use to strategize your business to maximize business value.

Pricing

A startup’s metrics strategy is to implement profitable and sustainable pricing mechanisms, maximizing sales revenue. However, I have found that few traders fully explore the pricing strategies available to them. Pricing can seem like a dark art. You pay too much and lose customers. Pay too little and you’re leaving money on the table and undermining your fundraising goals. The balance is delicate, but you can achieve it.

You need to understand the pricing fundamentals like cost-plus, competitive, penetration, and value-based pricing. Each type of pricing has its advantages and disadvantages. By deducing the right balance and usage among them will enable you to determine the right pricing for your products and services.

Sales pipeline

Startups can maximize revenue projections by developing and refining metrics for customer acquisition and sales. This means creating the most efficient sales pipeline possible. With Sales Pipeline, founders, managers, sales professionals, and investors can visualize the flow of customers through the various stages of the company’s sales cycle. By estimating the likelihood that prospects will convert to customers based on these steps, you can create revenue projections.

Conversion data is particularly effective for operations and tactics. With this information, you can predict how many new leads you will need to generate in a given period of time to reach your annual revenue forecast.