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Posted on by Mike

Big Data, Small Data

Big Data

“Big Data” has been a “hot” business topic for the last several years.  It refers to high volumes of information that may span multiple content types (words, numbers, graphics, sound, etc.).

The idea is to use big data to spot trends that help a business decide on or confirm a market facing strategy.  Data Analytics is the process of manipulating big data to create views and insights from actual real time and past performance.  Read about the difference between “big and small” data.

On December 28, 2016 Bloomberg Radio aired a piece about data analytics yielding very positive results for those businesses who took the time to analyze their company data.  In fact, for large and medium size business, data analytics is no longer exceptional.  The interviewee claimed, “data analytics are now table stakes.”

Small Data

Small business does not usually generate “big data”.  However, the process of analyzing small business data can prove very beneficial.  The volume of data is usually too small to create the same trending inferences that are possible from big data sets, but helpful nonetheless.  A strategic use of your small data will help tease out customer and inventory profiles.  These profiles can then be used to improve targeted marketing and lead to increased sales.

A practical data mining process will work for many small businesses.

Some “Small Data” Business Ideas

Think of your business data as two separate kinds of data: “Indicative Data” and “Transactional Data”.  Examples of “Indicative Data” are: Customer Information, Inventory Information, Vendor Information, etc.  Examples of “Transactional Data” are: Orders, Sales Invoices, Purchase Orders, Customer Inquiries, etc..

Easy as “A,B,C”

What should you do with indicative data?  Create customer and inventory profiles.


 Take all of your customers and rank them as A’s B’s or C’s with:

  • A’s being your very best customers (High Sales volume, High Ticket Orders, Recurring Orders, Loyalty)
  • B’s being your average customers (Average Sales Order Volume, Average Ticket Order Sizes, Random reorders)
  • C’s being your marginal customers (Low Sales Volume, Below Average Ticket Orders, Infrequent Orders)

Create a profile of each group (A,B,C) by recording the following information for each member of the group:

  • Their Industry
  • Their Annual Gross Sales
  • Your Annual Gross Sales to Them
  • Their Annual Number of Orders To You
  • Number of Employees
  • Their Location
  • Their Web Presence
  • Their Social Media Presence
  • Their Credit Rating
  • Seasonal Business or Not
  • Private/Public Company
  • Local/National Market

By summarizing the details above, one can get an accurate definition of an A,B or C.  Before creating a strategy to maintain A’s, convert B’s to A’s and convert C’s to B’s you will want to know about what you are selling to whom.  So work your inventory into A’s, B’s and C’s.


Take all of your Inventory items and rank them as A’s B’s or C’s with:

  • A’s being your best sellers
  • B’s being your average sellers
  • C’s being your slow or no movers

Create a profile of each group (A,B,C) by recording the following information for each member of the group:

  • Item Category
  • Average Item Landed Cost to You
  • Average Item Selling Price
  • Average Days in Inventory
  • Annual Quantity Sold

By summarizing the details above, one can get an accurate definition of an A,B or C inventory item.  For A’s and B’s, measure the actual item demand, forecasted demand and time to replenish each item, then calculate reorder levels to assure availability.  For C’s, consider dropping them or creating a marketing campaign to get them to a “B” status.  The only exception might be if the “C” item is crucial to filling an “A” Customer’s” order or if the “C” item is an intentional loss leader.

Transactional Data Provides the “Payoff”

Transactional data is the “voice of your existing market”.  While indicative data (Customers and Inventory) ranks your customers and inventory items, transactional data tells you who’s buying what at the lowest level, but more importantly tells you which customer profile buys which inventory profile.

The best transactional data to analyze are the detail line items on the sales order (not the sales invoice).  The sales order tells you what your customers wanted and is not contaminated by what you actually sold (The order’s Invoice).  By mapping what you’re A, B and C customers WANT THE MOST will help you prioritize your internal supply chain from Marketing to Sales to Order Fulfillment to Delivery to Customer satisfaction.

You are now in a position to sow the seeds of growth by pitching “A” profile values to “B’s” and “A” and “B” profile values to “C’s”.  This new found information is highly valuable because it came from actual purchases, not “best guesses” from marketing and sales intuitive processes or from customer satisfaction surveys.  The information came from your market voting with their dollars!

Taking the time to process your own data, data right under your nose, can have big and unbiased payoffs.

Caution, Knowledge is Not Virtue

Notwithstanding the strong case made for analyzing your small data, simply knowing the facts is not enough.  These “facts” need to be used by your marketing department or organization to communicate and persuade the targeted A’s, B’s and C’s to place orders with your sales force.  The messaging used by your sales force needs to align with your marketing messages.  These final step are essential in converting our analytical results into cash that will grow your company.


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