Failed Retail Video Analytics Startup Analyzed

By: Brian Karas, Published on Dec 19, 2017

Most manufacturers in this industry try hard to cover up failure.

But an industry startup backed by Silicon Valley's most prestigious accelerator has provided an in-depth account of the causes of their demise. Inside this note, we review and analyze them, pointing out other important causes, and companies struggling in retail video analytics.

**** ************* ** **** industry *** **** ** cover ** *******.

*** ** ******** ******* backed ** ******* ******'* **** prestigious accelerator *** ******** ** in-depth ******* ** *** causes ** ***** ******. Inside **** ****, ** review *** ******* ****, pointing *** ***** ********* causes, *** ********* ********** in ****** ***** *********.

[***************]

Prayas *********

****** *********, *** ****** *******, was ******** ** ***** a ****** ********* ********. The ******* *** **** of ************** ****** **** ******* batch. ****** ***** ******* is ***** ******, *** company ******* ** * different *********** *** ****** their ****** ********* ******** in June ****.

**-******* ******* ********** [**** ** longer *********] ********* *** ******* *** the ******* ******, ** * **** detailed *** *********** **** post.

Lessons *******

******* ****** **** ** the **** **** *** particularly ******** ** ******* challenges ** ****** *********:

** *** ****, ***** looking ** *** ****, someone *** ** ****** out **** ** ** and **** ********* *** solution. **** **** *** analytics ******* **** ******, and ********* ******** ** adoption. 

**** ** ******* *** of *** ******* ********** for ****** ********* ********. While **** *** ******* metrics ** ******** ****** the *****, ** ***/****** profile ** ********, *** retailer ***** ***** ** decide **** ** ** with **** ****, ***** is *** ****** *******. Further, ** *** ** difficult *** *** ********* products ** ***** ***********, as ********* ***** ** retailers **** ****** ********* target ******* *** ***** layouts. *** ******-**** ***** browsing ** ****** *** 10 ******* * **** sign ** * *** one? ** **, **** do *** ** ** encourage ** ********** ****?

**** ******* **** ********* protection-style *********, ***** *** action **** *** ********* is ******* **** *****-***: determine ** *** ****** is *** ********** ** be ** *** ********, and ** **, ******* to *** **** ** leave *** ******** *** guards, ******, ***.

******* **** *** ******** model *** **** ****** didn’t ****** *** **** like **** *******, *** so ***** *** ** imperfect **********. ***** ********* weren’t **** ** ***** this ****, ** **** them * *** ** figure *** *** ** use **. ** **** couldn’t ****** ** ***, the **** *** *******.

****** ********* ********* *** often ********* **** **** customers *** *** ********** have, ***** *** ******** early ********, *** ** the **** **** ****** the ******* **** *** first ***** *****: ********* do *** **** ********* and ******* ** ***** to *** ** **** data. ** *** **** can *** ** **** in **** *** **** increases *******, ** ***** value.

*** ********, *** ** the ***** ****** ** should’ve **** ***** **** been ** **** ** an ****** ** *** field ** ******** ******* and *** ****** ************. We *****’** ****** ** this ****** ***** *** plans ** *** *** the ***** **** ***** cameras, *** *********** ** they **** ********* ** not. ******* ** **** panicked *** ******* *** a **** ****, *********** between ******* ******* **** it ***** **** *** hopeless **** ** ******’*.

*** ******** ** ****** lacked ******** ******** *********, or **** *********** **** the ******** ********. ***** model *** ***** ** pulling ***** **** ******** surveillance *******, *** **** doing *****-***** ******** ** the ***** ** ******** their ****/*******. *******, **** were *** **** ********* it *** ******** ** retrieve *** ***** **** required, *** **** ********* unaware **** ***** *** a **** ****** ** systems ********, ***** **** unique ***'* *** **********, which **** ** *********** costs.

******* ********* ******** **** infrastructure ******. ** *** case, ** *** ******* with *** ****** ******* and ****** ****** **** typically **** *** * 1 **** ********** ** power ***** *** ******.

******** ********* *** **** a ******** ****** *** many *****-***** ***** ******** in *** ********** *****. Though **** ** ********* bandwidth *** ** ******** better ** **** **** when **** ***** ******** in ****, ** ***** remains * ******** ****** for ***** ********* ** scale *******, ** ******* customers **** **** **** a *** ******* *** location.

** **** ********** ****** by ***** ***** ** progress. ** ****** ******* that ** **** **** close ** ******* *** deal... Three **** ***** * was ******* ******* ****** that **’** **** ***** to * ******* ****** contract **** ****. ***** years ***** — ***** no ********!

**** ** * ******* often **** ** ******** in *** ******, ********* customers *** ** ********* say "***", *** ****** to ***** ********, *** they **** *** ***** not ******* ** **** a **** "**" ******. This ******* ** ********* anticipating ******** **** **** never *****, *** ******** resources ** ******** **** opportunities, **** ****** *** would-be ******** ***** ******* and ************. *******, ****** customers ** ********** **** a ********** *** ***** extremely ****-*********, ********* ** spend ***** ** ********** that **** *** ******** improve *****, ****** ******, or ********* **** * direct ******-**** ******.

Deserve ******* *** ********* *** *********

****** ********* *******, *** knowing **** ** **** onto ********* **** ** uncommon, *** **** ** the ******** ********, *** in **** ****** ** well. ******* ********** ******** respect *** *********** *** knowing **** ** **** on *** ****** ********* else. ****** ********* ******* into "*********", ***** **** pivoted **** *********** [**** ** longer *********] ** ****** ****, which ** ***** ********* active (****** *** ******* to ** **** ******** or ****** *********).

Retail ********* *********** ******

****** ** ********* *** the **** ******* ** find ****** ********* ** be * *********** ******. ***** ******* ******** ** **** ** a ****** ********* ******** to ***** ******* ** Silicon ******, *** *** ***** quietly ******* ** * broader-scale ******** ********* *******, marketing ** ***** *********, such ** **********, *** offering ******** **** *********** search, ** **** ** various ***** ** ********* for ******* ******** ******* purposes. ***********, * ****** analytics ********** *** **** years, *** **** ~$* million ** *********** ******** ** ****, *** ** *** extent **** ***** ******** will ******* ***, **** depend ******* ** **** strong ****** ******** ** retail ** *******. ** 2015, ****** ********* *********** ********* sold ** ******** [**** no ****** *********], * ********** small ***** ********.

**** ****** ********* ********* have ******* ****** ********* applications **********, ******* ********** that ******** ******, *** willingness ** *** *** solutions, ** *** ******** to ******* **** ** perimeter ********** ** *********-******** search ***********.

Comments (9)

Undisclosed #1

12/19/17 11:39pm

"However, retail customers in particular have a reputation for being extremely cost-conscious, unwilling to spend money on technology that does not directly improve sales, reduce losses, or otherwise have a direct bottom-line impact."

Being 'extremely cost-conscious' (because of the thin margins/high competition in retail) tends to also make these customers 'extremely vaporware-conscious' as well.

I love how the dude insinuates that retail customers are apparently just too dumb to figure out the benefit/value of the data produced by his product:

"problem with our business model was that people didn’t really use data like this already, and so there was no imperfect substitute. Since customers weren’t used to using this data, it took them a lot to figure out how to use it. If they couldn’t figure it out, the data was useless."

Say what?  Whose fault is it that the customer doesn't understand the value of your product again?  The customers?

yeah... sure.

 

Avatar

John Bredehoft

Idemia | In reply to Undisclosed #1 | 12/21/17 06:53pm

I didn't interpret that statement as implying that the customers are dumb. I took it to mean that the vendor realized that he didn't educate the customer on how to convert the data into something actionable. 

Undisclosed #1

In reply to John Bredehoft | 12/21/17 09:28pm

My perception (and position) is that the data produced is not 'actionable' to begin with.  i.e. retail analytics are of limited actual value - and the market has spoken.

Hence, my interpretation concludes that Mr. Maheshwari also knows this and is left with nothing other than casting doubt on the customers ability to understand the benefits of the data his product produces in order to avoid the cognitive dissonance of the fact that his product adds no actual value to retail customers.

Undisclosed #2

IPVMU Certified | 12/20/17 12:36am

The founders of Prayas lacked security industry expertise, or even familiarity with the products involved. Their model was based on pulling video from existing surveillance cameras, and then doing cloud-based analysis of the video to generate their data/reports.

Putting the “cart” before the horse...

Marty Calhoun

IPVMU Certified | 12/20/17 11:30am

Openly admitting failure, and knowing when to move onto something else is uncommon, not just in the security industry, but in most others as well. Pranshu Maheshwari deserves respect and recognition for knowing when to move on and pursue something else

Very well said....

Undisclosed #3

12/20/17 01:49pm

Many analytics companies fail to realize they are data rich and information poor.  Video content analytics is not about video, it is about the content.

Undisclosed #1

In reply to Undisclosed #3 | 12/20/17 02:07pm

"Video content analytics is not about video, it is about the content."

that is exactly right.

Retail analytics may provide data (content).... but if capturing this data provides no additional value to the customer, then why would they buy the product that produces this (useless to them) data?

Personally, I have long believed that the data that retail analytics produce is (primarily) data that is already known by retail establishments.  hence the struggle that providers of this data have historically experienced - and is probably the main reason that these providers have largely been unable to convince retail to buy their 'solutions'. 

 

Undisclosed Manufacturer #4

12/21/17 03:28am

I could write a book about this subject, (and maybe I will when I retire), but the single line from the blog that should be etched in stone was:

When we started working on the retail analytics idea, we didn’t even really have conversations with customers —

The "if we build it they will come" mantra may play well in Silicon Valley but it doesn't in Wisconsin. If you've asked no questions, then how could you expect to deliver relevant answers?

Undisclosed #3

In reply to Undisclosed Manufacturer #4 | 12/21/17 01:39pm

Hope is not a strategy. I find that engineering led start-ups to have this mindset more so than sales led start-ups.  Tools don't build houses, carpenters do and salespeople sell them.

Login to read this IPVM report.

Related Reports

Deep Sentinel Presents Crime Response For Business on Jun 11, 2020
Deep Sentinel presented its anti-intrusion and live response for home and...
Wyze Fails To Deliver Own On-Board Analytics, Launches Novel Name Your Own Price Service on Jul 24, 2020
While Wyze failed to deliver their own onboard analytics to replace the...
Startup Videoloft Presents Cloud Storage on May 27, 2020
Videoloft presented offsite cloud storage at the May 2020 IPVM Startups...
Disruptive Free Lead Generation Added To IPVM on May 15, 2020
IPVM has added lead generation for sellers, for free, disrupting the...
Wrong Dahua Australia Medical Device Approved on Jul 20, 2020
Dahua's body temperature system is now in Australia's medical device...
Terrible Convergint Coronavirus Thermal Camera Recommendation on Apr 01, 2020
A week after Convergint disclosed falling revenue, pay and job cuts,...
Pivot3 Mass Layoffs on Mar 27, 2020
Pivot3 has conducted mass layoffs, the culmination of grand hopes, a quarter...
Don't Deceive. Lessons From Scott Schafer on Mar 20, 2020
Deception is bad. We can learn some important lessons from Scott Schafer, a...
Anyvision Layoffs on Mar 19, 2020
Anyvision has conducted a layoff, citing the impact of coronavirus, joining a...
IPVM For PR / Marketing People on Apr 29, 2020
Since IPVM does not accept advertising nor sponsorships, etc., PR / marketing...
ROG Security - Cloud AI For Remote Monitoring on Jan 28, 2020
ROG Security is offering cloud-based AI analytics to remote guard companies,...
Anyvision Presents AI Facial Recognition and Mask Detection on Jun 08, 2020
AnyVision presented its AI facial recognition and mask detection at the May...
VergeSense Presents People Tracking Sensor on Jun 04, 2020
VergeSense presented its people tracking sensor and social distancing...
Amazon, Microsoft and IBM Abandoning Face Recognition Is An "Irresponsible PR Stunt" Says AnyVision on Jul 17, 2020
In the wake of national protests against US police abuses, big tech firms...
Camio Presents Coronavirus Social Distancing Analytics on Apr 20, 2020
Camio presented its social distancing analytics for responding to coronavirus...

Recent Reports

SIA Coaches Sellers on NDAA 889B Blacklist Workarounds on Aug 05, 2020
Last month SIA demanded that NDAA 899B "must be delayed". Now that they have...
ADI Returns To Growth, Back To 'Pre-COVID Levels' on Aug 05, 2020
While ADI was hit hard in April, with revenue declining 21%, the company's...
Exposing Fever Tablet Suppliers and 40+ Relabelers on Aug 05, 2020
IPVM has found 40+ USA and EU companies relabeling fever tablets designed,...
Indian Government Restricts PRC Manufacturers From Public Projects on Aug 04, 2020
In a move that mirrors the U.S. government’s ban on Dahua and Hikvision...
Directory of 200 "Fever" Camera Suppliers on Aug 04, 2020
This directory provides a list of "Fever" scanning thermal camera providers...
Face Masks Increase Face Recognition Errors Says NIST on Aug 04, 2020
COVID-19 has led to widespread facemask use, which as IPVM testing has shown...
Dahua Loses Australian Medical Device Approval on Aug 04, 2020
Dahua has cancelled its medical device registration after "discussions" with...
Google Invests in ADT, ADT Stock Soars on Aug 03, 2020
Google has announced a $450 million investment in the Florida-based security...
US Startup Fever Inspect Examined on Aug 03, 2020
Undoubtedly late to fever cameras, this US company, Fever Inspect, led by a...
Motorola Solutions Acquires Pelco on Aug 03, 2020
Motorola Solutions has acquired Pelco, pledging to bring blue back and make...
False: Verkada: "If You Want To Remote View Your Cameras You Need To Punch Holes In Your Firewall" on Jul 31, 2020
Verkada falsely declared to “3,000+ customers”, “300 school districts”, and...
US GSA Explains NDAA 889 Part B Blacklisting on Jul 31, 2020
With the 'Blacklist Clause' going into effect August 13 that bans the US...
Access Control Online Show July 2020 - On-Demand Recording of 45+ Manufacturers Presentations on Jul 30, 2020
The show featured 48 Access Control presentations, all now recorded and...
Face Detection Shootout - Dahua, Hanwha, Hikvision, Uniview, Vivotek on Jul 30, 2020
Face detection analytics are available from a number of manufactures...
Sunell is The First China Manufacturer to Market NDAA Compliance on Jul 30, 2020
Most China manufacturers are going to be impacted by the NDAA 'Blacklist...