Okay that was a cheap attempt to draw attention to our too-often neglected blog. But the most common request for our custom market research services is “How big is our market?” Oftentimes, my initial reaction will be to ask, “If I told you that I knew for a fact it was $ x million dollars and you had 35% share, what would you do differently?” If the honest answer is “nothing” then I try to steer them toward objectives that will be more immediately useful to them… for example, a price sensitivity analysis to see if there’s room to raise prices, or a customer switching study to see what it will take to get a competitor’s customers to defect. Commissioning a market research assignment should be based on idle curiosity.
On the other hand, if the client is considering acquiring a competitor, or wants to know whether to increase production capacity, or is contemplating the ROI on an expanded sales force, then determining a market’s actual size and growth is an important but difficult undertaking.
A market estimation model from BioInformatics provides your company with the current landscape, forecasted changes in the market, and the positioning of each major competitor. The information generated can give you insight into the following:
What is the estimated size of the market? Is it growing or declining?
At what rate is the market growing or declining?
How many competitors are in the market? Where does my company stand compared to competitors?
What purchasing trends/patterns exist?
What customer segment is spending the most on my product?
What are the potential sales of my product?
Are we currently reaching a specific segment with current marketing efforts?
Not too long ago, a leading life science supplier asked us to estimate the market size and share of the market for a specific kind of instrumentation and related consumables. Our client needed to understand their competitive position, recent purchasing activity, future growth, and any threats/opportunities posed by other suppliers. We created a market estimation model using end-user and secondary market data, and developed a statistical model designed to relate and analyze specific variables to forecast the market. This approach is based on the premise that the market is a set of objects (products, prices, discounts, usage, etc.) that interact, and by using equations we can display the interrelationships of these objects. Some of the variables that were used to build the statistical model are:
Average number of scientists/technicians per lab/group and the number who perform a specified technique
Number of scientists who plan to begin using the technique in the next 12 months
Number of experiments/reactions run per week and the average volume per experiment/reaction
Expected change in the number of experiments/reactions over the next 12 months
Number of instruments per lab per brand
Number of scientists who intend to purchase a new product in the next 12 months
Number of scientists who intend to switch brands in the next 12 months
Competitor instrument and consumable prices
Average discounts off list price
The statistical model output was presented to our client in easily understandable tables that presented the overall market size, share and segment, with in-depth analysis by market segment, downstream application and region. We also provided an interface to an Excel spreadsheet so that various assumptions (e.g., the total population of end-users, prices, average discounts, etc.) could be adjusted to “war game” various scenarios to guide future marketing efforts, project future demand and forecast sales under various scenarios.
Still, estimating market size/share/growth is a little like making sausage — ou don’t really want to see how it’s done! Except in areas like the US federal government, or those markets closely monitored by the SEC/FTC etc., most market data is buried deeply in the divisions and operating units of companies. The only way to achieve a fair degree of accuracy is to extrapolate information on the purchasing practices of end-users, and correlate this with sales data reported by distributors and the active competitors themselves. And where this distributor and competitor data is not available, then assumptions have to be made based on industry knowledge and “gut instinct.”
Estimating market size is not impossible, but it is almost always still an estimate. It is extremely difficult and time consuming, and this drives up the cost of obtaining the data. When time and budget are constrained in any way (and they always are!) the accuracy of the data will decline proportionally. It is up to your corporate decision-makers to decide upon the level of inaccuracy that they are willing to accept. As an analyst, you must work with these “information consumers” to determine how much certainty is required, and how they wish to define the “market”.