COmpany Profile for Penser Analytics Pvt Ltd

2. Meet Sherlock
2
Sherlock is an instantaneous integrated
decision support system that addresses the
basic need of rapid access to relevant data
with advanced analytics backed insights to
take business decisions

3. Our Value Proposition
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Question Based Analysis
Get your toughest business questions answered
Effortless Advanced Analytics
Machine learning algorithms; Random forest, Neural networks, Regression etc.
Rapid Hypothesis Testing
Test various scenarios before taking decisions
Sherlock from Penser Analytics, real time decision support system with all advanced Machine leaning Algorithms
• An analytics platform that meets the needs of
business (analytics and BI) and IT.
• Ensureone version of the truth (1VOT)
• Enable Everyone in your organization with relevant
advanced analytics
• All Analytics delivered within a minute
Our USP:

4. Pre-built Questions & Scenarios for all operations
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We understand the KEY QUESTIONS in a retail environment
1
2
3
50+ Relevant business questions
aligned to various retail
operations
Advanced Search for power users
opens various parameters and
behaviors captured
All reports and business questions
along with statistical analysis are
available within seconds

5. Address all Strategic Needs
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ALIGN every business operation, EMPOWER them with the right data to OUTPERFORM
Masterdata management for
centralized data management
Optimize every operation from
procurement to marketing
Integrate every business
process from procurement to POS
to campaign management
Align everyone in the
organization to one goal
Empower everyone with relevant
analyses and reports
Monitorevery process and
operation
Reach your targets and
outperform

6. 1 Product Diverse Solutions
What products drive
Omni-channel behavior?
Predict student
success & content
effectiveness
Predict purchase behavior based
on emotions
Frauds Model &
Scorecard
Move Inventory
to complete set
Prospects for today for every
stylist in every store
Inventory Aging Analysis
to save 90 Lac INR

7. Our Data Integration Module
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Our solution is system agonistic, that can be deployed on top of any IT solution.
DATA EXTRACTOR
• DI through inbuilt or customized
connectors.
• Real-time extraction of data
EMB (Enterprise mapping BUS)
• Pattern based mapping of information
from various data sources
INVENTORY & CUSTOMER
STITCHING, CURRENCY
NORMALISATION
• Stitching of SKUs or Customers from
different platforms to an unique
identifier
DATA CLEANSING
• Missing value imputations, removing
unwanted characters and observations.

8. Our Architecture
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Our solution is cloud agonistic, that can be deployed on any cloud provider as well as on premise
Analytical Dataset
Multi Dimensional Cube

9. Team Behind Sherlock
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Co-Founder & CEO Co-Founder & CTO
A thorough professional from
the Big Data & Analytics field
with over 12 years experience.
Worked in various early stage
companies with a passion to
turn ideas into products.
An ex-IITian and a proven
thought leader who
consulted for over two years
in the field of analytics for
companies like General
Motors, Payback.
• The team behind Penser Analytics is from
leading universities like IIT KGP, IIT
MUMBAI, NIT etc.
• Our team comes with over 16 years of
analytics experience, 20+ years experience
of working on various backend systems, 9+
years of UI experience combined with over
a decade of experience in sales.
• We have over 15 years of experience in
leading analytics operations for retail CRM
• Our team has equal parts of sophisticated
experience combined with the ‘frugal
innovation’ to fuel Sherlock
Penser Analytics was founded to help
clients take decisions faster without
waiting for analysts to come up with
advanced analytics or reports
“
“

10. Our Clients Speak
“Using Sherlock, our CRM team is able to access
predictive analytics based target groups under 60
seconds saving precious time for me and my team.
Sherlock has the potential to become a key corner
stone in our Omni-channel strategy by seamlessly
integrating both the online and offline businesses.
Also, we find that the predictions from Sherlock are
above 80% accurate”
- Abhishek Pillendla, Head – CRM
BabyOye by Mahindra
“I have been in analytics and marketing research for
30 years. Early in my career, at the Kellogg
Company, …. I have recently been introducedto a
tool called “Sherlock”. Sherlock is a complete DSS
system. This system is truly amazing and offers
automated analytics modules (“analytics in a box”)
and the most advanced “data visualization” that I
have seen. In addition, the system is fast,
comprehensive and is seamless and elegant in
handling different & disparate forms of data. Overall,
I see Sherlock as a potential “game changer.”
- Michael Wolfe, CEO & Founder Bottom Analytics
(Past: Coca Cola, Kraft Foods, Kellogg etc.)

11. Investors Behind Sherlock
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Brahma Vella Srinivas Sreeramaneni
Founded various IT companies
got it acquired by Adobe.
Recently had their company
Uurmi Systems by Mathworks.
Co-Owner of Telugu Titans.
Started an agriculture based
sugar manufacturing industry
Founded Rofus Software
and got it acquired by
GlobalLogic. Invested in a
multitude of companies
from education, Product
companies. Started Unify
Technologies
Penser Analytics was backed by
seasoned and proven entrepreneurs.
“ “

12. Sherlock among Competition
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How do we rank among everyone else in the market
BI/
Visualization
Tools
SERVICE FEATURES
Analytics as
a Service
HYPOTHESIS TESTING
ADVANCED ANALYTICS
QUESTION BASED ANALYSIS
QUICK TURN AROUND
INDUSTRY SPECIFIC SOLUTIONS
IBM Watson
REPORTS
UNSTRUCTURED TEXT/ PARAGRAPGH

13. Product Roadmap
• Create & Save Reports
• Configure Analysis
• Share & Comment
Partner & Self Serve
V2
V3• Total Integration into Business Process
• Platform for Analytics Teams
• Bots
Analytics Teams

14. THANK YOU
+91-9632705666
cs@penseranalytics.com
www.penseranalytics.com

15. Retail Solutions

16. Customizable & Pre-defined Industry-Standard Analyses
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Contextual Reporting Suite/ Configured Reports/ Management Information System (MIS)
Occupation : Merchandiser
Responsibilities: Ensure right
products in the right store in the correct
quantities.
Analysis/ Reports provided:
• Store Product wise performance
• Forecast for each Product in every
store
• Key drivers forsale of a product
• Product Affinity Analysis
Occupation : Buyer
Responsibilities: Decide what tobuy
from suppliers and stock
Analysis/ Reports provided:
• VendorPerformance
• Accurate demand forecast toavoid
stock-outs and dead stock
• Buying Efficiency
• Track performance of new products/
offerings
Occupation : Marketing
Responsibilities: Increase Campaign
Performance. Optimize price
markdown
Analysis/ Reports provided:
• MartetMix model: Individual ROI of
all campaigns
• Suggested ‘ComboOffers’to
promote slow moving products
• Forecasted Impact of a campaign
Occupation : Store Manager
Responsibilities: Responsible for
day-to-day operations of store
Analysis/ Reports provided:
• Store Performance/ Potential
• Employee productivity
• Space productivity
• Impact of in-store campaigns
• Optimal Store Layout
• Sales forecast

17. Omni Channel Operations
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How to UTILISE information from different channels, ONLINE, MOBILE and PHYSICAL STORES ?
Brick & Mortar
Website
Mobile Apps
Various Platforms
Unified
Customer
View
80%
12%
6%
2%
• 80-88% of Retail Transaction in 2020 will happen in Brick & Mortar, Physical Stores
• 90+% of Retail Consumers will research online before buying offline

18. Sherlock for Omni-Channel
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Does customer engagement of different platformsincrease Customer Life Time Value?
Sales Progression
Time series analysis of how the segments
progressed through the months and years
Product Purchase Pattern
Appreciate the top products and different product
purchase patterns of the segments
KPIs of Customers
• Analyze the various KPIs of different customer
segments based on platforms
• Identify customers who shopped on
combination of platforms

19. Sherlock at every stage of Customer Journey
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Enabled with Sherlock understand the different segmentsof customers and entice them
New path to relationship
Old path to purchase
GET HER
ATTENTION
INTRODUCE THEM
TO THE BRAND
GET TO KNOW THEM
LEARN WHAT THEY LIKE
UNDERSTAND THEM
SURPRISE THEM
REASSURE & BUILD
CONFIDENCE IN
YOUR BRAND
ELIMINATE BARRIERS
IN PURCHASING HER
FAVORITE PRODUCT
REFRAIN FROM BEING
TOO PUSHY
OFFER A SUPPORT
PLATFORM
ASPIRE TO BECOME A PART
OF HER LIFE

20. Sherlock for Customer Segmentation
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Be sensitive to the needs of different typesof customers
Sales Progression
Time series analysis of how the segments
progressed through the months and years
Store-wise Contribution
KPIs of the segmentsacross various stores
Product Purchase Pattern
Appreciate the top products and different product
purchase patterns of the segments
KPIs of Customer Segments
Identify the various segmentsbased on Recency,
Frequency, Monetary (RFM) or Behavioral among
other parameters

21. Sherlock for Personal Shopping Assistant
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Be reactive in servicing the customers: Use predictive infoalong with factual info
• Lives in Central
• New customer with more than 2 visits
• Last purchase was done online
• Interested in YXY product
• Potential to visit next Saturday
• Medium Spend Capacity

22. Sherlock for Marketing
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Be sensitive to the needs of different typesof customers
Test/ Control
Statistically assess the impact of the campaigns by
comparing it against a control group.
Campaign ROI
Identify the campaign ROI, through different
stages of interaction with your promotional
campaigns.
Click Through Pattern
Identify and appreciate the differencesin the click-
through patterns for different campaignsand
compare it with normal traffic.
MarketMix Model
Statistically identify the impact of marketing
campaigns be it TV, Radio, PPC, SMS, e-mail.

23. Sherlock for e-Commerce
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Track your customers on your site and integrate with the rest of your business
Landing page with
internal search
Internal search results
Product description
and price
Review/ Payment Checkout Added to cart
Purchase confirmation page

24. Sherlock for e-Commerce
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How do customers interact with your site
Link Click-through/ Heat-map for all pages
Visitors Overview
Traffic Sources & PPC/ Campaign ROI
Location Overview

25. Sherlock for Social Media
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Be sensitive to the needs of different typesof customers
Sales Performance Vs Engagement Levels
How does the Sales contribution vary by the
engagement levels. Understand the $ value of a
positive comment
Influence of your audience on Social Media
Group your audience based on how many of your
customers are influenced by their content
Interaction on Social Media Pages
Sentiment Analysis and word cloud of most used
words in comments
Distribution of Social Media Content
The reach of your social mediacontent, likes,
tweets, fans and followers

26. Merchandising Solution
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Stock the RIGHT product mix in RIGHT quantities
Identify the right products to stock in each store

27. Sherlock for Merchandiser Operations
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Forecast demand and match inventory levels to avoid stock-outs
Sales Forecast
Seasonality, trend and impact of campaigns are
taken into consideration to provide an accurate
forecast
Product Affinity
Using Association Rule Mining, identify the natural
purchase patterns and grouping of products
Product Repeat Purchase Drivers
Identify the key drivers behind the purchase of this
product
Customer Lifetime value indicated by the color of
bar
Product performance
Identify the stores and geographic locations, the
product is bought. Along with the type of
customers interested in the product

28. Sherlock for Product Affinity Analysis
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Forecast demand and match inventory levels to avoid stock-outs
Top Baskets
• Top baskets with the product
• Design relevant ‘combo offers’
Product Affinity
Using Association Rule Mining, identify the natural
purchase patterns and grouping of products

29. Sherlock for identifying Best Selling Price
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Fix the RIGHT price for the RIGHT product
KYC (Key Value Categories)
KYI (Key Value Items)
Transaction Data
Price Perception Data
Merchant Judgment
Value Perception Drivers
Assortment perception drivers
Traffic drivers
Basket Drivers
User Reviews
Social Media
Click Stream Data
Bounce Rate

30. New Store/ Fulfillment center
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What is the OPTIMAL new location for your business and target group of customers
"Careful determination of new sites is critical for most retail and consumer
service businesses.” - Irene Dickey, Dayton's School of Business in Dayton,
Ohio.
Trade Area Analysis
• Network Gap Analysis
• Target Customer Analysis
• Competitor Site Analysis
• Cannibalization

31. Sherlock for Opening A New Location/ Store
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Estimate ROI of opening a new store
New Store Analysis
• Choose a point on the map and your trade
radius,
• See the number of customers, total sales from
the area and other KPIs.
• Get the purchase pattern of customers
• Estimate probable ROI

32. Sherlock for Store Network Optimization
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Be sensitive to the needs of different typesof customers
Store Performance Vs Potential
• Analyze all stores and identify the true potential
• Identify the gap how to achieve true potential
Store Segmentation
• Appreciate various types of stores
• Also analyze various KPIs of these segments
• Identify the difference in sales profile in each of
these segments

33. Store Layout & Operations
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What is the OPTIMAL store layout? Are all stores SIMILAR? Are stores performing at OPTIMAL level?
Visitors
StoreTraffic
Zone Traffic Dwell Times
Purchase
Conversion Rate
• Store Traffic to Zone
Traffic
• Zone Traffic to Product
Dwell Time
• Product Dwell Time to
Purchase

34. Sherlock for Store Operations
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Be sensitive to the needs of different typesof customers
Product Repeat Purchase Drivers
Identify the key drivers behind the purchase of a
repeat visit
Customer Segmentation
Understand the different typesof customers
visiting this store.
Product Purchase Pattern
Identify the top products and the purchase pattern
across product characteristics
Sales Forecast
Seasonality, trend and impact of campaigns are
taken into consideration to provide an accurate
forecast

35. Data Security
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Prevent data leaks of any type
Server – Private Cloud
• Electronic access controlsystem
• 24/7 monitoringof entrances andserverrooms
• Redundant internal networks
• Multiple redundantconnections tothe largest German internetexchange point, DE-CIX, ensure smooth data transfer
• There is a central back-up server tosave backed-up data
• Fire detectionsystem, directly connectedto the local firedepartment
Secure transmission and Sessions
• Connection to the App is via a cryptographic protocol, ensuring our users have a secure connection from their browsers to our
service
• Individual user sessions are identified and re-verified with each transaction, using a unique token created at login
Network Protection
• Perimeter firewalls and edge routers block unused protocols
• Internal firewalls segregate traffic between the application and database tiers
• A third-party service provider continuously scans the network externally and alerts changes in baseline configuration
• PCI DSS compliance ready