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Whether You Are an SMB or SME, Usable Analytics are SOP

Updated: Jun 24

Retail Analytics Series Part III: The Midsize Business



Whether your retail business is classified as small or midsize, SMB or SME, usable analytics are SOP.


Gartner defines a midsize business as one with 100–999 employees, or more than $50 million but less than $1 billion in annual revenue. Classifications differ, but suffice to say a midsize business isn’t McDonald's, nor is it Mac’s Diner. 


Forbes published a list of 25 Companies That Believe Smaller Is Better. While not household names, they are representative of small or midsize businesses that you do business with daily. Marketing and tech firms, online retailers, regional auto dealerships and beverage distributors hit Gartner’s revenue qualifications and thrive on anonymity.


Usable Analytics are SOP

SMB or SME, Usable Analytics are SOP


Small and midsize companies make up 99.9 percent of all U.S. businesses. For added confusion, there are SMBs (small and medium-sized businesses) and SMEs (small and medium-sized enterprise).


Rekha Srivatsan, Vice President of Product Marketing at Salesforce, was quoted on Sharebird breaking down the two:


“SME refers to small and medium-sized enterprises, which are businesses that have a specific range of employees, revenues, or assets. In contrast, SMB stands for small and medium-sized Businesses, and the term is more focused on the size and scale of the business, rather than specific financial or operational criteria.”


I’ll spare you the extra words to further clarify. That’s a job for an SME (subject-matter expert).


SMB or SME, Usable Analytics are SOP

Analytics Without the Analytics Department


Pivot Analytics points to natural language search tools benefitting small to midsize businesses. ThoughtSpot — a midsize company with $150 million in annual revenue — recently released a new BI (Business Intelligence) analytics search software.


ThoughtSpot’s AI-powered GPT3 gives businesses with smaller budgets the power to analyze data more efficiently, including the ability to comprehend context in search queries. The GPT3 tool has proven effective in illuminating patterns and trends usable with various cloud services. The Company’s clients include small, mid and enterprise levels.


Who’s In the Midsize Corner?

Who’s In the Midsize Corner?


CogniSure AI, headquartered in Illinois, is a young business with fewer than 100 employees and under $5 million in annual revenue. Its niche is rectifying unstructured data within in the insurance industry. Virginia-based Yurbi provides similar services on a broader scale. Both approach the BI platform with affordable options for white label software and non-technical users, particularly medium-sized businesses.


MIT’s Analytics Capstone project cites CogniSure’s model for data extraction.


“The issue of unstructured documents is the biggest barrier [to] digitization of the underwriting process for a $250+ billion industry. Over 90 percent of submissions are unstructured. CogniSure has a large set of proprietary extraction algorithms that produce accurate results (95 percent+ accuracy) and are trained on thousands of document types.”


Cognisure continues to invest significant research and capital to improve its products, but, as with Yurbi, both envision groundbreaking integrations of usable data and analytics for their clients.


Usable Analytics are SOP

Just Order It From Amazon


Iconic names offering analytics for the small or midsize business include Amazon (QuickSight), Microsoft (Power BI), Oracle (Analytics Cloud) and Salesforce (CRM Analytics). Software marketplace G2’s Matthew Miller compiled an extensive synopsis of Best Analytics Platforms for Medium-Sized Businesses


In addition to the behemoths, sources that have increased market awareness for SMBs and SMEs include Alteryx, Qlik Sense, Teradata, and Sigma.


Other leading options for retail analytic software include:



Usable Analytics are SOP

Define Your Analytics Goals


Software developer 3Pillar Global reminds us that midsize organizations don’t always have the means to implement usable analytics nor the time for trial and error like large businesses do. It advises the following best practices to develop a big data strategy:


  • Define your goals

  • Make a list of must-have capabilities

  • Research what similar companies are doing

  • Consult with experts

  • Comply with CCPA and GDPR requirements

  • Realize your storage capabilities


Finally, ask yourself what data you need to analyze, where it's coming from, and what you will do with the insight gained.


Big data is not for every organization, but it’s more accessible than ever. Customers in all sectors now demand that you possess the insight to provide a better shopping experience. Usable analytics are no longer a luxury for midsize businesses, but standard operation procedure.

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In Part IV I examine analytics strategies taken by the iconic retail enterprises that are able to do whatever they want to produce usable analytics.


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