By Fernando Berrocal
The financial predictions you forecast for your startup can make or break meeting with potential investors. If your predictions are too low (in contrast to your investor's expectations,) then the opportunity will appear to be modest.
If your forecast looks too unrealistic (too high), then the investor may lose faith in the startup's ability to deliver. It's common knowledge that financial estimates are educated assumptions and should be regarded with precautions. Regarding this situation, ask yourself:
- How much error is acceptable?
- How will you gain the confidence of your potential investor?
- What precisely makes your startup's estimates realistic–or unrealistic?
The word "realistic" is perceived as a deviation from the norm. Ask yourself, “how far off the mark are my organization's projections?” For instance, consider a hypothetical business to business (B2B) startup. The average anticipated revenue for these organizations is around $1.5 million. However, this specific startup claims it will generate $15 million. This is clearly an unrealistic projection. The group predicted a revenue that surpasses the norm by a significant amount. To determine these average amounts, you should look at B2B techs, as well as business to client (B2C) and direct to consumer (D2C) products; as well as marketplace businesses. This data will help startup owners determine where their financial estimates should be depending on their development (and business concept).
In one instance of highly relevant research in this realm, financial predictions for 107 early-stage startups were examined. Some have received financing, while others have not and are currently seeking funds. To maintain confidentiality, all financial data were anonymized before the respective analysis. Many of these businesses only included three years of estimates and omitted the 4th and 5th, the sample size for fourth- and fifth-year projections were less than optimal for this research. With those considerations, we can still notice the differences in growth across different business strategies.
Revenue by Business Model and Year Over Time
The B2B tech marketplace had the greatest average fifth-year predicted sales at $119.5 million and $1.52 million (respectively). On the other hand, D2C products had the lowest average fifth-year projected revenues with $1.2 million. Moreover, the marketplaces have the greatest predicted sales for year two of operations, at $17.8 million dollars, while B2B tech has risen to the second-highest position, with $14.7 million. By the fourth year, the marketplace still had the highest estimate at $99.1 million, with B2B tech placing second at $62.3 million dollars. Finally, B2C technology ranks third with $45 million, while D2C products rank last with $8.1 million dollars. Overall, fifth-year estimates are optimistic; but, due to the small sample size, the data's veracity is skeptical.
Alt text for the image above: Startup Sectors Project and Investors
Average Five-Year Growth Rate by Business Model
We looked at each business model's growth rate over a five-year timeframe. We discovered that some decks didn´t include fourth and fifth-year estimates. B2C tech firms are expected to expand at the fastest pace (7.7x) from their first to the second year. The growth rate of B2B and B2C technology was expected to climb again in the 4th and 5th years. The first-year prediction for D2C goods was the lowest (2.6x). Marketplaces were the only business model whose growth was expected to decline over time, from 5.3x in the first year to 1.5x in the fifth. Categories may have anticipated these variations in growth over time to allow for changes in customer behavior and demands. Now, let's take a look at each business strategy:
- B2B Technology Overview: The first year's income estimates were modest; however, as soon as the second year began, expected finances surged and continued. As the years passed, the disparity between each forecast got wider. In terms of growth, B2B tech businesses expect to expand by 6.4x in their first year. These figures clearly show the disparities in scale possibilities across the various business concepts. When opposed to B2C firms that must spend money on advertising, sales teams at B2B tech firms may generate a lot more income with less expense.
- B2C Tech Overview: In comparison to B2B tech firms, B2C tech businesses had a lower annual average. B2C average annual estimates rose in huge increments over time, similar to B2B. Startups often expand slowly, having the potential to double in size yearly. The ability of B2C tech firms to scale their business models in terms of growth rates has an impact on their forecasts. Since their overall income is based on individual purchases rather than a whole firm bringing on many new clients at once, B2C firms often have lower price points and lower average revenue per user than B2B firms.
- Overview of D2C Products: This business model has the smallest sample size so the results may be inaccurate. Across all types, it´s discovered that D2C revenue estimates showed the most consistent growth over time. D2C startups have a rather slow and stable growth rate. Due to stocking needs, physical items don´t scale exponentially. As a result, as a physical product business grows, more money is required to ensure sufficient inventory is accessible to fulfill orders. Regardless of the influx of digital-only solutions, physical things will always be required.
- Overview of the Market: Of all the business types studied, marketplaces were the most aggressive. Across the board, revenue and growth were the highest. Many of the markets such as “Non-Fungible Tokens” (NFTs), were also Web3-centric. In any case, after a few years of increasing supply and demand in a particular industry, all of the models' creators projected massive growth. We would want to do follow-up research comparing forecasts to actuals to see how close or far off the founders were.
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