Time to go to market. Who will do the selling?
There comes a time in the evolution of every startup where it is time to put a freeze on the design process and hit the streets with the product as is. It can be all too easy to spend valuable time and resources unnecessarily trying to perfect a product. A basic rule of thumb is if the design meets the determined criteria, then go to market as is. As with most business parameters faced by startups, this is often much easier said than done.
There are generally a few options available to rolling out and scaling up a product offering. Just a few of the most common models used are a direct sales force, a distributor model or independent contractors. In this article, we will review the factors that must be first measured to determine the best sales model for a given product line. We’ll review the particular sales models in greater detail in the next article in this series.
The particular product involved will have a great bearing on determining which model is best, but fortunately there are a few common characteristics of each that will be helpful in deciding which model is most ideal for your product. Each have their respective strengths and weaknesses, and selecting the most appropriate model for your line of business will be key to your success.
Having reasonable and realistic sales projections based on some level of fact is critical in determining which model to use. PROCEED WITH CAUTON! One of the biggest pitfalls companies make in the early stages is that they base their projections and forecasts off of external data. They take market information on things such as total market size, number of sales people, number of calls made, hit rates, etc. and then make assumptions. While this is a common process, there is a HUGE flaw with this line of thinking. Until you actually sell something and can retroactively look at the actual experience, the projections made from external data points alone amount to nothing more than a college term paper. It is critical to have at least tested the waters to determine the most effective and efficient manner in which to proceed before committing to an alternative.
Cash flow is a vital metric when determining which model to ultimately adopt. Some models are much more expensive than others. A key determinant in deciding which sales model to deploy is to understand how sophisticated the sales process is. As a general rule of thumb, the more technical and sophisticated the product is, the more control you will need over the process. A need for more control leans more toward a direct sales force. Products that don’t require a high level of expertise or control of the sales process lean more toward a distributor model.
With most startups, it is often best to have a more senior partner very involved the sales process in the early going. As prototypes become available, working directly with end users in completing trials and evaluations will tell much as to how difficult and time consuming an average sale will be. This in turn will be very useful in developing the most appropriate sales model. Look closely at how many people were contacted, how many sales presentations were made and how long it took from the first customer contact to receiving an actual purchase order. These genuine limitations learned from your actual experiences in the market plae are the most valuable data points when making sales projections. These projections, based on what has happened in the past, will help to determine how many sales people you will need and what your cash flow and return on investment are likely to be.
There are the two main points to glean from this discussion: 1.) Make sure that you have validated in some manner the sale process by actually making some sales before crafting wholesale projections based solely on external data. 2.) Do not make significant outlays of cash to fund the sales process until you have at least some semblance of what the return will be and how long it will take. The corporate graveyards are littered with startups that have died a painful death even though they had a really good product, but they spent all of their resources before having a sustainable sales process figured out.
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