An Overview of Market Research For Entrepreneurs

Validating a product idea through market research is a critical step in launching new products.  But what exactly is market research, and how does an entrepreneur or established small business owner conduct such research?  In my attempt to answer these questions I turned to Wikipedia and then Google.   Interestingly enough, the most comprehensive definition I encountered came not from the web, but from Edward F. McQuarrie’s book, “The Market Research Toolbox: A Concise Guide for Beginners.”

McQuarrie defines market research as any effort to gather information about markets or customers.   These efforts include utilizing secondary research, visiting potential and existing customers, conducting focus groups, running surveys, and conducting conjoint analysis.

Translating Raw Sales Data Into A Cash Flow Statement

In my previous post, Managing Your Small Business’s Cash Flows, I alluded to writing posts on using Markov Models to forecast cash flows and cash collection rates.  I started writing the post and realized that it requires a good bit of background knowledge.  This is the first post in a series of posts aimed at providing that knowledge so we can get to Markov Models. The series will be loosely structured along the following lines.

1. Translating Raw Sales Data Into a Cash Flow Model (this post!)
2. An Overview of Sales Data and Markov Models: Finding Transition Probabilities
3. Using Markov Models To Estimate Accounts Receivable and Cash Collections

Hypothetical Raw Sales Data

I created the data set below in Excel.  There are four columns: Invoice #, Sale Month, Sale Amount, Month Collected, Months Since Sale.  The Month Collected field tells us the month in which the cash from the sale was actually received.  The Months Since Sale tells us how many months it took to collect the cash.  This sales data covers a period of 4 months and has 4 sales per month.  Let’s pretend we took the data from XYZ Company, Inc.

Managing Your Small Business’s Cash Flow

Late last year, Sequoia Capital gave the CEO’s of their funded company’s a gloomy outlook on the economy.  The firm recommended start-up companies reassess growth assumptions, financial forecasts, and focus intensely on cash management.  Their suggestions to cut expenditures and conserve cash are equally important for small businesses.  Maintaining and creating positive cash flow is vital to keeping a company afloat.

A business owner can immediately boost cash flows by decreasing the gap between total sales and total cash collected.  While Tom and I don’t have this problem at smbZen (we collect 100% of our sales sans fees through credit card purchases), many of our readers in the small business community do.  Here’s an overly simplistic model to illustrate the gap.

Forecasting Sales Without Historical Data (Part IV)

This post is a continuation of

• An Overview of Business Forecasting
• Forecasting Sales Without Historical Data (Part I)
• Forecasting Sales Without Historical Data (Part II)
• Forecasting Sales Without Historical Data (Part III)

A Comparison of the Linear, Exponential, and Modified Exponential Models

In the previous posts, we provided examples of the Linear, Exponential, and Modified Exponential Models.  For the purposes of this post, lets assume we are a new small business looking to sell our new product named MyCoolProduct.   Our market research suggests that the market saturation point for MyCoolProduct is 250,000.  Let us further assume that we estimated sales in time period 1 to equal 1,000 units and would like to reach 25,000 in 24 months.

Forecasting Sales Without Historical Data (Part III)

This post is a continuation of

• An Overview of Business Forecasting
• Forecasting Sales Without Historical Data (Part I)
• Forecasting Sales Without Historical Data (Part II)

The Modified Exponential Model

Although the Linear and Exponential Model are excellent for short-term forecasting, they are not appropriate for long-term forecasting.  Neither methodology accounts for market saturation.  The Modified Exponential Model and the Bass Model address this limitation.

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