The document analyzes Harrah's Entertainment Inc.'s use of real-time CRM in enhancing service within its casino supply chain, detailing strengths such as strong brand identity and a comprehensive rewards program, while addressing weaknesses like outdated technology and potential data security issues. It explores customer segmentation and strategies for engagement, emphasizing the importance of data-driven decision-making and personalized customer experiences. Additionally, the text discusses risks associated with CRM, including data accuracy and impulsive decision-making, alongside recommendations for improvement.

1. HARRAH’S ENTERTAINMENT INC.
Real time CRM in a service supply chain
Debarati Roy | Deep Mondal | Prashant Joshi |
Roshan Ravishankar | Srividya Pinapala | Sreejith Nair.
23rd June, 2018

2. INDUSTRY & COMPANY ANALYSIS
● Marketing Mix Factors
● SWOT Analysis
● Total Rewards Program Overview

3. PRODUCT
• Tangibles
• Lavish casino property
• Resort, spa, restaurants
• Riverboat, Indian
reservation, dockside,
conventional casinos
• Intangibles
• Entertainment destination
• Recognition & offers
• VIP treatment status
• 4 casino brands
PLACE
• 26 casinos
• 13 US states
• >14 Lakh sft. Space
• Good geographical
dispersion
• Regional & destination
properties
PRICE
• Assumed competitive
pricing compared to
other key competition.
• Patrons were visiting
multiple properties of
Harrah’s even before the
reward program was in
place.
PROMOTION
• Centralization – umbrella
program across locations
• Graded – customers
segmented into Gold,
Platinum & Diamond
• Programs like Millionaire
Maker moved customers
to destination properties
• Closed loop CRM for
machine learning
• Real-time offers

4. STRENGTH
• Strong brand identity for
Harrah’s casinos & its
sub-brands
• Seamless digital
handshake across
properties/brands/system
• Presence across
geographies, casino
types in multiple brand
formats
• Active enterprise
experience leading to
high customer retention,
revenues & shareholder
value
WEAKNESS
• Lower investments in
making properties more
lavish
• Est. 1937 – with data on
multiple non-migrated
technology platforms
• Complicated CRM-IT
infrastructure with
incremental modifications
• Reward program hinges
on data availability which
might antagonise data
secure VIPs
• First time users/impulse
users less targeted
OPPORTUNITIES
• Steady increase in
customer spending
• Availability of huge
database of demographic
& playing patterns of
customers
• Improvement in BI &
CRM to increase
differentiation from
competition
THREATS
• Vulnerability to online &
mobile gaming industry
• Taxation of close to 40%
eats into the profit margin
• Negative elasticity to
recession, trade wars,
terrorism
• Risk of competition
coming up with alternate
technology
• Data security &
confidentiality with 3rd
party service providers

5. SALIENT FEATURES OF TOTAL REWARDS PROGRAM
• Comprehensive program covering all touch points
• Only multi-branded loyalty program in the industry till 2000
• Tracks over 15 MN guests across properties
• Segmentation of customers into Gold, Platinum, Diamond
• Simple and easy to understand reward system
• Fungible rewards across sectors
• Data disclosure for rewards, recognition, offers & benefits
• Tracking customer playing patterns & in identifying attrition
• $65mn investment needed to set up
• 3 patents for its real time data technology
TAXONOMY OF CASINO CUSTOMER SEGMENTS
• Prime Customers: Visit the casino twice a week & play an
average of 3 hours per visit, avg. bet of $200
• Mobile Customers: Their relationship with any casino lasts
for 6 years. Visit every 48 hours & avg bet is $5,000
• Valued Customers of Tomorrow (VCT): HNI with avg.
relationship of 6 years. Visit a casino around twice a
month, play for about 3 hours on each visit & their average
bet is $25.
• Incidental Customers: Casual & curious gambler. Bet less
than once a month, average bet is $10.
PRIME CUSTOMERS
(RETAIN)
MOBILE
CUSTOMERS
(RETAIN
OPPORTUNISTICALLY)
VALUED CUSTOMERS
OF TOMORROW
(GROW)
INCIDENTAL
CUSTOMERS
(SERVE IF MARGINAL
REVENUES > SERVICING
COSTS)
Relationship Value
High Low
CustomerProfitability
LowHigh
Source: UNLV Gaming Research & Review Journal • Volume 7, Issue 2

6. CUSTOMER RELATIONSHIP
MANAGEMENT AT HARRAH’S
● Chronology of Events
● CRM Tactics in Use
● Advantages vs. Disadvantages

7. FUZZY CRM: Bill Harrah speaks
to customers & collects feedback.
 Free | Casual | IT independent
 Adhoc | Bias Vulnerable | Unscientific
INDIVIDUAL CRM: Feedback
forms from Phil to slot winners.
 Economical | Data based | No IT need
 Small sample size | Biased | Hypothesis
oriented | No customer facing rewards
SEGREGATED CRM: Player Card
programs at each casino in PDBs.
 Minor data based decision making & RR
 Unleveraged & myopic | Inability to
handle large data volumes & complexity
LEVERAGED CRM: Customer info across stay, gaming &
transactions (IBM+UNIX); total Gold & Harrahs.com run on Winet
 Leveraged data viewing | Segmented R&R | Targeted offers/discounts
 Significant IT investment | Multiple queries overload network | Diverse IT systems
| Perception threat requiring training demos | Reactive analytics
CRM SUITE: Harrahs.com, Total Rewards relaunched. Warehouse
NCR Teradata & Cognos Enterprise Analysis tool track 20mn offers
 Building customer profile | Micro-segmented R&R | Capability to handle huge
volume of data and process it | Predictive analytics
 Significant IT investment | Multiple queries overload network | Diverse IT systems
| Perception threat requiring training demos | No machine learning
CLOSED LOOP & REAL TIME CRM: TIBCO messaging
Middleware & Teradata active data warehouse: ‘active enterprise’
 Individualised profile & real-time offers | Contextual industry data | Prescriptive
analytics | Closed loop & bi-directional data | Lower transitioning costs | Reduced
network traffic | Centralised decision making

8. HARRAH’S REAL-TIME CRM
● Key USPs.
● Value add to serve customers better.

9. INSTANT RECOGNITION of a customer – not only by
name but also his/her choices and preferences & status
SEGMENTATION & PRIORITIZE customers basis factors
like profitability to identify patterns & offer targeted services
OFFSITE & ONSITE REAL TIME COMMUNICATION that
influences decision making & create top-of-mind recall
ACTIVE LOOP that learns from customer’s reactions &
choices about his changing preferences
ALTERNATIVE CHOICES on offer depending on matching
real-time availability of services with customer preferences
QUICK REMEDIES via additional offers or discounts or
compliments to make good for any dissonance
RELEVANT OFFERS and discounts based on
demographic, transactional, reservation or gaming data.
SIMPLIFIED COMMUNICATION of earn and burn methods
(how to earn the rewards that the customer wants).
SEAMLESS CUSTOMER EXPERIENCE across
geographies & even within departments of a casino
PERSONAL RELATIONSHIP & INDIVIDUALIZATION of
clients that allows isolated targeting at a one-on-one level.
QUICK RESPONSE solutions that values the time of
customers & gives them solutions within a short time frame
BOTTLENECKS & DOWNTIME minimised by having an
agile network that uses a single node messaging system

10. HARRAH’S REAL-TIME CRM
● Key Risk Areas
● Risk Containment Recommendations.

11. DIRTY DATA RISK
• Computation of customer profitability is the skeleton of CRM
• Profitability tracked via a rule engine. E.g.. of a profitability
rule:
(A x {TBV/ΣB} x N/hr. x H)
A = House advantage on a game;
TBV = Total Bet Value; ΣB = sum of number of bets
N/hr. = Number of bets per hour; H = Hours of play per client
• Incorrect data entry can upset the profitability calculation and
jeopardize the value proposition added by the CRM
• Pit managers enter players’ gaming data promptly after the
player leaves the table – the process is manual, based on
observation skills and prone to errors including simple typos.
• Can lead to dirty or incomplete data & hence incorrect
targeting – might take time for the system to course correct
RECOMMENDATIONS
• Minimise manual data entry touch-points.
• Move towards a NewGen Smart Table Management System.
• Capability to automatically & correctly capture players data at
the gaming table just as it is done in slot machines (Fig 1) Fig. 1

12. RISK OF BIG DATA IMPUTATION & ASSUMPTION
• Data captured is only demographic, transactional and gaming
– which is basically spend data patterns/averages
• Doesn’t capture customer lifetime events, viral consumptions,
supervening economical circumstances etc.
• Basically has a blind side on big data and its disruptive impact
on gaming patterns
• Milking profitability/monetization v/s destroying LTV
RECOMMENDATIONS
• Social Relationship Management to intercept additional
customer data about brand interactions, virality buy-ins etc.
• Cloud based architecture for fast data ingestion against
historical & pattern data (against stack tech solutions) (Fig. 3)
• Cloud would also help mobility and experience transgression
between offline and online for customers – (Slide 14)
• Cloud based integrated data analytics which supports quick
prescriptive analytics (Fig 4)
• Cost effective, flexible and secure.
Fig. 1 Fig. 2
Fig.3
Fig. 4

13. RISK OF IMPULSIVE & INSTANT DECISION MAKING
• Customer recognition can be divided into 2 parts: before
presenting the TRCard (info vacuum) & after(info overload)
• VIP customers need more seamless recognition and might
take offence at not being instantly recognised
• As soon as the TRCard is exercised, host is overloaded with a
sudden gush of (transactional and predictive) data.
• Host is forced to make on-the-spot sense of the data & make
impulse decisions in order to interact with the guest.
RECOMMENDATIONS
• Enablement to the host for more even & intuitive flow of
information than a sudden gush of data.
• Face recognition tech to identify customers intuitively for a
more coherent meet & greet experience. (Fig 1)
• Prescriptive analytics support that recommends action to be
taken – mostly determined by the self learning algorithms.
• Covert notification based information pass via wearable tech
that aids conversations without imposing on the guest. (Fig 2)
Fig. 1
Fig. 2

14. MOBILITY SOLUTIONS FOR NEW-TO-CASINO PLAYERS
• For existing customers:
• Since 1998 online gaming industry grew rapidly.
• CRM focus on bringing customer back to the casino.
• Discontinued experience once he leaves the casino.
• Need for offers to create top of mind recall value.
• Higher comm. volume can lead to more spam
• New customers:
• Millennials prefer virtual gaming on-the-go (Fig. 1)
• Need for social interaction or multiplayer gaming
RECOMMENDATIONS
• Mob. players convert 190% faster v/s web players (www.optimove.com)
• Close the experiential loop: online-casino-online. (Fig. 2)
• Continue the experience & earn points/rewards on Mob/Web
• Virtual reality casino for a more immersive experience & better
profitability (spends at VR Casinos are 7% higher) (Fig. 5)
• Server based games & other modern slots to attract millennials.
• Fungibility of TR Points across a larger spectrum of
products/experiences outside the casino world.
Fig. 1 Fig. 2
Fig. 5
Fig. 3 Fig. 4

15. THANK YOU!