We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
    7 Min Read
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Self-Service BI Customers Are Not All the Same (Part 1)
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > Market Research > Self-Service BI Customers Are Not All the Same (Part 1)
Business IntelligenceMarket ResearchMarketing

Self-Service BI Customers Are Not All the Same (Part 1)

RickSherman
RickSherman
4 Min Read
Self-Service BI Customers Are Not All the Same (Part 1)
Illustration generated with FLUX.2 [klein 4B] via Cloudflare Workers AI.
SHARE

As I discussed in The Road to Self-Service BI, enterprises need a better understanding of self-service BI so they can avoid the common mistakes often made with it.

Customers come in all shapes and sizes

In almost every industry, marketing groups perform customer segmentation analysis for their companies to sell products or services targeted at specific segments. They target restaurants, hotels/motels, cars/trucks/SUVs, cameras and beer to different customer segments based on needs, perceived value (by customer), income and many other factors.

Customer segmentation is Marketing 101, but for some reason the high tech industry doesn’t seem to get it. In fact, their strategy is often one-size-fits-all.

More Read

Analytics Teams: Own The Business Problem, Not An Infrastructure
Analytics Teams: Own The Business Problem, Not An Infrastructure
Are You Making Use Of Salesforce1 For Your Business
More Marketing Agencies Utilize AI to Embrace Automation
Getting Real Value from BI Investments
What 3 Measures Are Your Business Game Changers?

The problem starts with the industry research analyst firms, who rate “best” products according to the most functionality and, often, the most customers. (Although in BI licenses sold may not equate to active BI users.)

The high tech titans exacerbate the problem when they acquire companies with promising new technology and then assimilate those products into their one-size-fits-all products — the BI suite in our technology segment.

Based on high tech marketing and industry analyst perspectives, everyone would be buying $2,000 digital SLR cameras and $5,000 Tour de France road bikes. But for some strange reason, more people buy point and shoot cameras for one tenth the cost or just use their smartphone for a camera. They buy basic bikes at their local bike shop. This is, of course, not strange behavior at all since the digital SLR cameras and Tour de France bikes are for a specific and very narrow customer segment.

So why does the high tech industry feel that every customer wants or needs the most feature-packed (and likely expensive) product?

What about business value?

IT groups then run BI tool evaluations using the industry research firms’ ratings to select the single, perfect BI tool, which is likely a BI suite. Industry pundits and high tech vendors all proclaim that is cheaper and easier to have one BI tool “to rule them all.” They tout Total Cost of Ownership (TCO) because it sounds more high tech (nerdy) than cheap.

The question that needs to be asked is: who benefits from the one-size-fits-all mentality? Certainly, the vendor selling the BI suite benefits. Also, the IT group supporting BI will likely find it easier to support a one-size-fits-all product. 

TCO is oriented towards product vendors and IT groups, but what about the BI customers? No, I don’t mean IT, but the business people who need BI for their work! Where in the selection process is business value and the business return on investment (ROI)? There is no ROI without business people actually using the BI tool in their work.

BI tool usage (not installed licenses but active users) remains low at most enterprises, even after they select the “best” BI tool.  Add to that the fact that the truly pervasive BI tool is still the spreadsheet.  It seems obvious something is broken. Although one-size-fits-all and TCO should be considerations, without pervasive business usage then there is no business value.

In the next post we will discuss BI customer segmentation.

TAGGED:self service BI
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Flat editorial illustration: The article describes an AI safety incident where an agent bypassed sandbox controls by exploiting D
OpenAI Pauses Advanced AI Work After Agent Bypasses Sandbox Controls
Artificial Intelligence News Security
Flat editorial illustration: The article explains that training robots for physical interaction requires three distinct data cate
Physical AI: What Data Do You Need to Train a Robot?
Artificial Intelligence Exclusive Robotics
What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
Analytics Big Data Exclusive Software
Flat editorial illustration: The article examines AI agents that escalate from legitimate data retrieval to attempted intrusions
OpenAI’s Government Website Incidents Raise a Hard Question for AI Agents: When Should They Stop?
Artificial Intelligence News Security

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

The Road to Self-Service BI
Best PracticesBig DataBusiness IntelligenceData ManagementMarketing

The Road to Self-Service BI

2 Min Read
Big Data and the Wizard of Oz Syndrome
Big DataData Warehousing

Big Data and the Wizard of Oz Syndrome

4 Min Read
Personalization: The Underappreciated Aspect of Self-Service Business Intelligence
AnalyticsBusiness IntelligenceData VisualizationExclusive

Personalization: The Underappreciated Aspect of Self-Service Business Intelligence

8 Min Read
Bidirectional Business Intelligence: What You Need to Know
Business Intelligence

Bidirectional Business Intelligence: What You Need to Know

9 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?