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A Longitudinal Study: Casino Gambling Attitudes, Motivations, and Gambling Patterns Among Urban Elders
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A Longitudinal Study: Casino Gambling Attitudes, Casino customer satisfaction survey best practices, and Gambling Patterns Among Urban Elders PMID: A Longitudinal Study: Casino Gambling Attitudes, Motivations, and Gambling Patterns Among Urban Elders Fayetta Martin Wayne State University, School of Social Work, 4756 Cass Avenue, Detroit, MI 48202, USA, Peter A.
Lichtenberg Wayne State University Institute of Gerontology, 87 East Ferry Street, 226 Knapp Building, Detroit, MI 48202, USA, Thomas N.
Templin Wayne State University, College of Nursing, 5557 Cass Avenue Cohn, Room 321, Detroit, MI 48202, USA, Fayetta Martin, Wayne State University, School of Social Casino customer satisfaction survey best practices, 4756 Cass Avenue, Detroit, MI 48202, USA, ; Guided by self-determination theory, the main purpose of this study best boulder strip casino to explore demographic characteristics, attitudes toward casinos, and self-reported intrinsic and extrinsic reasons for casino gambling by urban elders.
The study hypothesized that individuals would more frequently report intrinsic motivations for casino gambling e.
This longitudinal sample included 247 urban elders older who were 60 years and older and who had participated in surveys in 2002 and 2004.
The initial survey consisted of a demographic items, b five items to measure attitudes toward casino gambling, c questions inquiring about motivations for casino gambling, and d questions about gambling frequency.
The follow-up survey was an expanded questionnaire which still included these items.
The sample consisted of the 247 participants, over 200 of whom were African-Americans, 188 were female, and 98 of the participants had a post graduate education.
About half were widowed, and the sample generally reported a low income.
The results supported the theoretical perspective underlying the project.
The hypothesis that more participants would endorse intrinsic motivations for casino gambling rather than extrinsic motivations was supported.
The implications of these findings represent for social workers, gambling counselors and health care services providers an important step toward understanding the attitudes, behaviors, and motivational factors involved in casino gambling among older adults.
Over the past several decades, gambling has become progressively more popular, more widely available, and more socially acceptable in the United States.
As of 2008, only two states Hawaii, Utah did not have some form of legalized gambling ; .
Thirty-seven states and the District of Columbia operate state-sponsored lotteries, 41 states permit para-mutual wagering, and 46 states allow charitable gaming.
Gambling in casinos, including Native-American casinos, is legal in 25 states, and 11 states permit commercial casino gambling.
Recent research shows that casino gambling is the second-most popular form of gambling, trailing only the lotteries AGA.
Gambling in general, and casino gambling in particular, in Detroit and across the country, as well as throughout Canada, has increased dramatically over the past few decades .
Since, the legalization of gambling in Detroit in 1996, the city has seen the expansion of casino capacity, thus providing greater opportunity for the general public, including urban elders, to participate in gambling.
In 1975, only 35% of people 65 years of age or older had gambled during their lifetime.
By 1998, this figure had risen to 80%, equaling the percentage from 18- to 24-year-old gamblers and more than doubling the 1979 percentage of lifetime gambling among older adults .
The AGA has stated that future research priorities should include longitudinal studies and should focus on vulnerable or high-risk subpopulations, such as older adults and people with lower socio-economic status.
When the Baby Boom generation reaches 85 and older in 2050, it is expected to number 19 million, or 5% of the total US population, a 500% increase within 60 years U.
Currently, gambling is the most frequently identified social activity among adults 65 years of age and older.
Between 1975 and 1997 the number of American adults 65 years of age or older who had ever gambled increased by 45%.
Because Detroit is presently the largest city in the United States with casino gambling, ; and because gambling has been identified as the most frequent social activity among adults 65 years of age and older, Detroit provides an ideal location to study casino gambling ; .
There is a scarcity of research on gambling among elderly minority populations, particularly African-Americans.
Theoretical Framework Self-determination theory SDT guided this study on gambling motivations.
Previously, SDT has been used to examine substance abuse and treatment and risky sexual behavior ; ; .
SDT focuses on motivations underlying human behavior and assumes that people have fundamental psychological needs for autonomy, competence, and relatedness; .
Fulfillment of these needs is presumed to result in optimal functioning and psychological well-being and has been associated with increased life satisfaction ; .
The participation in risky behaviors can be seen as a maladaptive strategy for satisfying these needs.
For example, in the transition to retirement, autonomy may manifest itself in experimentation with gambling and other risk-related behaviors .
Only recently have studies begun to explore self-determination in relation to recreational gambling among older adults ;; .
These studies seem to suggest that more self-determined reasons for gambling e.
In certain forms and contexts, gambling behavior is hypothesized to have positive consequences or reflect well-being .
On the other hand, the current sample is ideal for studying the normative gambling attitudes and behaviors of non-problem gamblers.
According to the literature, gambling can be either intrinsically or extrinsically motivated ; .
McNeilly and Burke found that, in Nebraska, older gambling patrons at commercial and charitable Bingo parlors and at a casino were more likely to gamble to relax and to have fun intrinsic motivationto get away for the day extrinsic motivationand to pass the time or relieve boredom than were older gamblers surveyed in other venues.
According to the study, the two groups did not place emphasis on casino gambling promotions and incentives, such as free transportation, nor on socializing with friends.
In Minnesotaintrinsic motivations of social stimulation and trying something new were much more important 35 and 24% of the sample, respectively than the extrinsic motivation of winning money 6%.
In a Manitoba, Canada telephone survey, stimulation and rewards were the most common reasons reported by older adults; gambling to escape problems and loneliness and to pass the time were reasons that tended to predominate among the problem gamblers in the sample.
Developing a solid understanding of the attitudes, behaviors, and motivational factors involved in gambling by older adults is important to devise and inform prevention and treatment interventions for problem gambling in this population.
Our study represents an important step toward fulfilling that objective.
Also, it presents an opportunity to determine whether gambling attitudes and behaviors have changed over time.
The purpose of this descriptive study was to examine attitudes, motivations, and behaviors of older urban adults who gamble.
The primary objective of this secondary analysis was to describe the relationship between gambling attitudes and behavior and the gambling patterns among urban elders in Detroit.
In particular, this study was designed to a describe demographic characteristics of urban elders who participate in casino gambling in Detroit according to frequency of casino visit, b examine change patterns in frequency of gambling, c examine the attitudes of Detroit urban elders about casinos and casino gambling, and d identify self-reported intrinsic and extrinsic reasons cited by urban elders in Detroit for casino gambling.
Methods This research is a secondary analysis conducted on data collected from 247 adults ages 60 or older residing in Detroit who participated in the 2001 Detroit City-Wide Needs Assessment of Older Adults .
The first study included 1,410 non-institutionalized adults ages 60 and older residing in the city.
The study used a dual-mode stratified sample and addressed several topics important to the living conditions of older persons.
The primary purpose of the original study was to examine the environmental conditions and needs of older adults.
In general, the study asked questions about housing, health, transportation, and service use.
In addition, the survey included questions related to casino use in Detroit, addressing attitudes about casinos and frequency of casino visits; the survey included a standardized tool to assess the risk of pathological gambling in this population.
This data set provided information with which to analyze the expected relationships for this study ; .
Using a random-digit-dial telephone survey and area-probability face-to-face interviews, the stratified sample included 140 participants from each neighborhood area cluster of the ten Community Reinvestment casino customer satisfaction survey best practices Sectors ; .
The final random-digit-dial sample totaled 1,310, with an additional 100 participants from the face-to-face supplement.
This process guaranteed that all areas of the city of Detroit were represented in the research analyses, in proportion to the total population of eligible respondents.
The data emerged from a follow-up of the initial, population-based survey of 1,410 older urban adults in Detroit by Zaranek and Chapleski in 2001 herein identified as Time 1.
The follow-up study herein referred to as Time 2 surveyed a stratified random sample of 247 of those respondents, ages 60 and older, who had self-reported at Time 1 that they had gone to a casino to gamble never, rarely, or monthly or more.
Participants who gambled monthly or more were purposely over-sampled in order to more evenly represent low, middle, and high frequency gamblers.
In the original survey, 42% reported no casino visits in the previous year, 41% reported less than monthly visits, and 17% reported visiting a casino monthly or more.
The distribution in the present study measured 34, 41, and 25%, respectively.
The over-sampling thus resulted in 8% more problem gamblers in the final sample.
This factor was not expected to bias the examination of the relationships in this study.
We measured these variables using fixed-choice items, including a choice of other.
Chi-square was used to measure the association between demographic variables and frequency of gambling at the time of follow-up.
Characteristic and category Never visit f % Rarely visit f % Visit monthly or more f % Age years 60—74 55 44.
Time 2 Never Rarely Monthly or more Total Time 1 Never 67 12 1 80 Rarely 38 51 12 101 Monthly or more 12 22 28 62 Total 117 85 41 243 At Time 1 initial survey25.
At Time 1, 32.
There were two significant changes.
Casinos were perceived as safe 75.
Respondents were equally divided on the other questions The McNemar—Bowker Test a test of marginal homogeneity was used to examine change in gambling frequency from baseline to follow-up and to examine changes in attitudes and perceptions toward casino gambling.
In order to address the research questions, we employed SPSS ® version 17 for data analysis.
Descriptive Analysis The total sample size at Time 2 was 247 older adults who participated in the follow-up; 124 were ages 60—74, 81 were 75—84, and 30 were 85 or over; 220 were female and 27 were male.
In terms of race, 91 were African-American, 17 Caucasian, 4 Hispanic, and 4 other.
Sixty-two reported less than a high school education, 67 were high school graduates, and 88 reported post high school education.
Demographic Characteristics Associated with Casino Visits source Time 1 The first research objective was to measure the relationship between socio-demographic factors and gambling frequency.
As shown inonly education and income levels were significantly related to frequency of area to play slots a casino visits.
Change in Gambling Frequency from Time 1 to Time 2 The second research objective was to examine change in gambling frequency over the preceding year.
At Time 1 25.
At Time 1, 32.
The findings are presented in Change in Attitudes about Casinos and Casino Uk casino app The third research objective was to examine changes in attitudes of Detroit urban elders about casinos and casino gambling.
The findings presented in indicate that respondents generally possessed positive attitudes toward casino gambling.
Casinos were perceived as safe by 75.
Casinos were perceived as good for Detroit by 66.
The respondents were fairly equally divided on the other items.
Self-Reported Intrinsic and Extrinsic Reasons for Casino Gambling The fourth research objective was to identify self-reported more info and extrinsic reasons for casino gambling as reported by urban elders in Detroit.
Results showed that 79.
Among the other intrinsic reasons, 22.
Motivation % Intrinsic Entertainment 79.
While the predominant view that older adults gamble at casinos to have fun and enjoy excitement was supported, other, more troubling, reasons for casino gambling emerged.
Both intrinsic and extrinsic reasons appeared to motivate casino gambling in older adults.
While a great majority of the respondents reported that they went to casinos for entertainment, almost two-third also reported that they went to win money and over one-third went to allay boredom and loneliness.
Perhaps even more startling is that nearly one quarter of those who went to the casino to gamble reported that they did so to avoid feelings of loss or to escape sadness over the death of a loved one.
Contrary to these self-reported reasons, it should be noted that winning money, alleviating boredom, and escaping feelings of loss are unlikely to happen at a casino.
Five questions on attitudes and perceptions were asked at baseline Time 1 and follow-up Time 2.
This finding is consistent with other studies on Detroit older adults and gambling.
Limitations The findings of this study provide an initial profile of urban elders and their attitudes, motivations, and gambling behaviors.
However, certain limitations are recognized.
First, this study included a random sample of adults ages 60 years and older who resided in the city of Detroit.
Therefore, the findings can be generalized only to this specific population.
Second, the random sample was heavily skewed toward African-American females.
The gambling literature suggests that future research focus on special population subgroups, such as women, older adults, and minorities ; ; .
Third, this study used secondary data.
The intention of the researchers was to conduct a needs assessment, so the questions were not developed to address a specific question.
Furthermore, employing gambling questions that were more closely related to the theoretical perspective might have yielded greater ability to test hypotheses, had this been exclusively a gambling study.
While the study did not focus on gambling problems, the literature suggests that gambling behavior is not all positive and that gambling problems exist among older adults.
Casino gambling has become progressively more popular, more widely available, and more socially acceptable in the United States for adults in general and older adults in particular ; .
Conclusions and Practice Implications Our data suggest that given easy access to casinos, urban elders: 1 do not visit the casinos on a regular basis, 2 over time, elders reduced casino participation overall, and 3 over time, elders viewed casinos as less positive for their city.
About 83% of those who reported visiting a casino at Time 1 reported never visiting a casino at Time 2.
We hypothesized that casino gambling participants would report more intrinsic motivation for casino gambling e.
This was supported, and we found, as well, that older adults view the casino as a place where they can socialize, escape their loneliness, and escape their grief.
Given that their primary choices of games are slot machines, these social needs, however, may not be getting met.
Some researchers have found that the bus trips to and from the casino may provide an opportunity for older adults to socialize.
Our findings suggest that older adults may not be the best group for whom casinos should market.
This runs counter to our observations of large numbers of older adults in casinos and wellness centers.
It may be worthwhile for church groups to assess the reasons for older adults wanting to go to casinos and helping them to determine how their social needs might be met in a alternative ways.
Additional research could address this issue.
Because heavy gambling continues to be non-normative among this group, older adults may try to hide or deny gambling problems.
They may feel hopeless or ashamed about their habits or they may be unaware that help is available.
For service providers, this research represents an important step toward understanding the unique issues as they relate to attitudes, behaviors, and motivational factors involved in gambling among urban elders.
We found that more highly educated participants with higher incomes were more likely to participate in gambling.
In contrast to the original study, fewer participants are reported to be at risk of problem gambling in this follow-up study.
Perhaps those who had more severe gambling problems chose not to participate in this study.
Our future research will look at health issues and gambling frequency over time.
Future Directions Our future research will look at health issues and gambling frequency over time.
These results suggest that additional research is needed in several areas.
First, investigations of potential motivational differences between social and risky gambling behaviors should be pursued.
Fourth, new studies should examine the role of casino activities in the lives of urban elder adults, particularly with regard to social integration and healthy aging .
This study was supported by a grant from the National Institutes of Health, 5 P30 AG015281, and the Michigan Center for Urban African-American Aging Research.
Contributor Information Fayetta Martin, Wayne State University, School of Social Work, 4756 Cass Avenue, Detroit, MI 48202, USA.
Lichtenberg, Wayne State University Institute of Gerontology, 87 East Ferry Street, 226 Knapp Building, Detroit, MI 48202, USA.
Templin, Wayne State University, College of Nursing, 5557 Cass Avenue Cohn, Room 321, Detroit, MI 48202, USA.
State of the states: The AGA survey of casino casino customer satisfaction survey best practices />Washington, DC: Author; 2008.
Skill versus luck: A motivational analysis of gambling involvement.
Journal of Gambling Studies.
Motivation and gambling involvement.
Journal of Social Psychology.
Facing the future: 2002 City of Detroit needs assessment of older adults: A report for the City of Detroit department of senior citizens.
Detroit: Wayne State Institute of Gerontology Center for Urban Studies Center for Healthcare Effectiveness Research; 2002.
International Journal of Mental Health and Addiction.
Sex differences in the treatment needs and outcomes of problem gamblers.
Research on Social Work Practice.
Intrinsic motivation and self-determination in human behavior.
New York: Plenum; 1985.
Need satisfaction, motivation, and well-being in the work organizations of a former Eastern bloc casino customer satisfaction survey best practices />Personality and Social Psychology Bulletin.
Health correlates of recreational gambling in older adults.
American Journal of Psychiatry.
Older Americans and casino gambling.
Journal of Aging Studies.
Legalized gambling in the United States: The economic and social impact.
New York: Haworth Hospitality Press; 1999.
Self-determination, perception of peer pressure, and drinking among college students.
Journal of Applied Social Psychology.
Gambling and the health of the public: Adopting a public health perspective.
best casino slot of Gambling Studies.
Double jeopardy: Older women and problem gambling.
International Journal of Mental Health and Addiction.
Late life gambling: The attitudes and behaviors of older adults.
Journal of Gambling Studies.
Disposable time and disposable income: Problem gambling behaviors in older adults.
Journal of Clinical Neuropsychology.
Gambling Impact and Behavior Study.
Chicago: University of Chicago; 1999.
Pathological gambling: A critical review.
Washington, DC: National Academy Press; 1999.
Exploring college student gambling motivation.
Journal of Gambling Studies.
Targeting misperceptions of descriptive drinking norms: Efficacy of a computer-delivered personalized normative feedback intervention.
Journal of Consulting and Clinical Psychology.
Are social norms the best predictor of outcomes among heavy-drinking college students?
Journal of Studies on Alcohol and Drugs.
Initial motivations for alcohol treatment: Relations with patient characteristics, treatment involvement, and dropout.
A developmental perspective on alcohol use and heavy drinking during adolescence and the transition to young adulthood.
Journal of Studies on Alcohol.
What is satisfying about satisfying events?
Testing 10 candidate psychological needs.
Journal of Personality and Social Psychology.
American Journal of Psychiatry.
Sixty-five plus in the United States.
Kalamazoo, MI: Author; 1999.
Problem and probable pathological gambling among older adults assessed by the SOGS-R.
Journal of Gambling Studies.
Extrinsic life goals and health-risk behaviors in adolescents.
Journal of Applied Social Psychology.
Senior citizen gaming: More than just buffets.
Worldwide Hospitality and Tourism Themes 1756—1771 2009; 1 4 :344.
Casino gambling among urban elders: Just another social activity?
Journal of Gerontology: Social Sciences.
Urban elders and casino gambling: Are they at risk of a gambling problem?
Journal of Aging Studies.

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(PDF) Service quality perceptions and customer loyalty in casinos | Catherine Prentice - allo-hebergeur.com
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While the key casino customer satisfaction survey best practices business success is creating happy and loyal customers, you still need to get them to generate more revenue.
A good NPS score and low churn rate shows your customers are satisfied but you only benefit when these customers act on their positive feelings.
An article in Harvard Business Review,shows how to convert this satisfaction into profits.
Learn more about your most loyal customers The first key to generate more profits from your loyal customers is to understand them better.
Markey makes the point that companies focus on learning why detractors, or unhappy customers, are dissatisfied but they do not put the same click the following article in understanding why the happy customers are happy.
To maintain that kind of intimate relationship with your most loyal customers, you have to create effective mechanisms for staying in close touch.
Have your account or customer service reps ask customers why they first became enthusiastic.
When sending out NPS surveys, make sure you ask those providing high scores the reason they gave such a score.
Have customers post stories on social media on why they like your offering.
Have events for https://allo-hebergeur.com/best/best-casinos-outside-of-nevada.html top customers and ensure part of the agenda is having customers discuss how they fell in love with your brand.
Use all of your channels not only to help your customers but to learn from them.
Tune your offerings to meet their needs When communicating with your best customers, you will learn both what they like and do not like about your offering.
You will also understand if your competitors are offering something they want that you do not offer.
It may be by providing additional features or more support services.
It could also entail offering your product through new distribution channels or in another format.
The key is understanding what your best customers want from your product but are not getting, then adjusting your product to fill this need so they do not move to competitors.
Help them spread the word Since your most loyal customers by definition love your offering, you want to harness this positive vibe by getting them to promote you to their friends.
As people communicate best via stories, you need to provide them with stories that they can share.
These stories can range from great interaction with your staff maybe customer service, VIP management or on Facebooka great experience with your game or product or even a little bonus you got via email.
Once they have the stories, you need to facilitate them sharing the stories.
This sharing often is by social media but it can be video testimonials on your website or even quotes in your game.
Loyal customers drive profits While it is critical to create incredibly satisfied customers, that is not the end of the battle.
best online casinos and sportsbooks need to learn from them, use this knowledge to make your products even more suited to them and then turn them into advocates.
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A great article in Harvard Business Review — — does a great job of combining the two issues and providing a solution.
The authors begin by pointing out most businesses rely on predictions throughout their organization.
Companies increasingly are using computational algorithms to make these predictions more accurate.
The issue is, if the predictions are inaccurate and although they are computer generated, they are still predictions not facts they can lead you into bad decisions.
Netflix learned this the hard way when its algorithms for recommending movies to DVD customers did not hold when its users moved to streaming.
More relevant to digital marketers, algorithms that generate high click through rates may actually bring in poor users not interested in your underlying game or product.
While a human would understand quickly that an algorithm that gets users that generate no revenue is useless, if the algorithms was just built to maximize the number of users acquired it would continue attracting worthless users.
The problem here is that you do not know when there is incomplete information or what information may be missing.
Once you realize these two limitations of algorithms, you can then develop strategies to combat these problems.
The authors then provide a plan for managing algorithms better.
Be explicit about all of your goals When initiating the creation of an algorithm, you need to understand and state everything you want the algorithm to achieve.
Unlike people, algorithms do not understand the implied needs and trade-offs necessary often to optimize performance.
People understand the end goal and then backward process how to best achieve that eventual goal.
There are also soft goals to most initiatives, and these goals are often difficult to measure and thus input into your algorithms.
There could also be a goal of fairness, for casino customer satisfaction survey best practices a bank using an algorithm to optimize loan behavior may not provide enough loans in areas where it feels a moral obligation to do so.
Another example could be where you may want to optimize your business units sales but the behavior could negatively impact overall sales of your company.
The key is to be explicit about everything you hope to achieve.
Ask everyone involved to list their soft goals as well as the primary objective.
Ask people to be candid and up-front.
This process may entail extending the objective to include multiple outcomes, weighted by importance.
Minimize myopia Algorithms tend to be myopic, they focus on the data at hand and that data often pertains to short-term outcomes.
There can be casino customer satisfaction survey best practices tension between short-term success and long-term profits and broader corporate casino customer satisfaction survey best practices />People understand this, computer algorithms do not.
The authors use the example of a consumer goods company that used an algorithm to decide to sell a fast-moving product from China in the US.
While initial sales were great, they ended up suffering a high level of returns and negative customer satisfaction that impacted the brand and overall company sales.
The authors suggest that this problem can be solved at casino customer satisfaction survey best practices objective-setting phase by identifying and specifying long-term goals.
I recommend using NPS to balance out short term objectives with the long-term health of the product and company.
I have written before about which is probably the most powerful tool to measure customer satisfaction.
It is also highly correlated with growth and success.
By ensuring you keep your NPS high, you are providing a great way to look holistically at the success of specific initiatives.
Chose the right data inputs Using the right data can make your algorithms much more effective.
When looking casino customer satisfaction survey best practices a game like Candy Crush, you can create levels by looking at when people abandon the game and decompose the levels before abandonment.
However, by adding social media posts to the your data, you could get a more holistic view of which levels players are enjoying and thus build a more compelling resort grand slots sierra best />The authors also point to an example with the City of Boston.
By adding Yelp reviews to what health inspectors use to determine what restaurants to inspect, they were able to maintain their exact same performance but with 40 percent fewer inspectors.
Thus, the new data source had a huge impact on productivity.
Rather than focusing on more data, the amount of data you know about each customer determines the width.
Leveraging comprehensive data is at the heart of prediction.
Text documents are a great source of wide data, for instance; each word is a clue.
Similar to your investment strategy, you should use data sources that are largely uncorrelated.
If you use data that moves closely to your data sources, you will have the illusion of using multiple data sources but really only be looking at one angle of the data.
If each data set has a unique perspective, it creates much more value and accuracy.
Understand the limitations As with anything, it is also critical to understand the limitations of algorithms.
Knowing what your algorithm will not do is equally important as understanding how it helps.
Algorithms use existing data to make predictions about what might happen with a slightly different setting, population, time, or question.
Suppose that an algorithm predicts that short tweets will get retweeted more often than longer ones.
This does not in any way suggest that you should shorten your tweets.
This is a prediction, not advice.
It works as a prediction because there are many other factors that correlate with short tweets that make them effective.
This is also why it fails as advice: Shortening your tweets will not necessarily change those other factors.
Algorithms are increasingly powerful and central to business success.
Whether you are predicting how consumers will react with a feature, where to launch your product or who to hire, algorithms are necessary to get great results.
Given the central importance of these algorithms, however, it is even more crucial to use them correctly and optimize their benefit to your company.
Given the central importance of these algorithms it is even more crucial to use them correctly and optimize their benefit to your company.
Bad profits are revenues earned at the expense of customer relationships.
These bad profits are generated usually with short-term revenue goals that over a longer period make your customers more likely to churn.
Examples of bad profits As a consumer, you probably have many examples you can list of bad profits.
Some of these are banks charging late payment or bounced check fees not in line with their costs.
It could also be rental car agencies charging you more per gallon if you do not return your vehicle with a full tank of gasoline than you would pay for a fine French Bordeaux.
It could be a wireless phone company charging you crazy international roaming fees.
And it could be a free to play game company tricking players into spending premium currency by creating misleading buttons.
Remember how AOL made you jump through about twenty agents to cancel its service?
Unfortunately, these examples are too numerous to list.
Although I have written many times about customer satisfaction and how good experiences positively impact customer lifetime value, I have not presented a good way to measure it.
As we all know, if you do not measure something, it usually does not get done.
What is the Net Promoter Score?
For such a powerful metric, the net promoter score is very straightforward.
It is the answer to one question, on a scale of 1-10: How likely is it that you would recommend the company to a friend?
Those who are answer with a 9 or 10 are considered loyal enthusiasts who will keep buying and refer others.
Those who answer 7 or 8 are passives, satisfied but unenthusiastic customers who are vulnerable to churning.
Those with a score of 0-6 are considered detractors, unhappy customers who can damage your brand and impede growth through negative word-of-mouth.
Customer service is a function that is usually neglected in the tech or game space.
The article points out that customer satisfaction is the most widely used metric to measure and manage customer loyalty because companies assume highly satisfied customers are good for business.
The article points out that the reality is not as simple as the belief that high customer satisfaction optimizes profitability.
Another actually shows a negative relationship.
Although you can poke holes in these studies, overall the relationship between customer spending and customer satisfaction is very weak.
Because of this and similar research, many consultants and authors have argued that achieving customer satisfaction is a waste of money.
The authors, however, conducted extensive research and uncovered three critical issues that keep customer satisfaction from generating higher revenue.
By understanding these three issues, any tech or game company which I think will find them very familiar can create a better customer service strategy.
Avoid money losing delighters Strong customer service CS scores are normally considered universally good for business but the data is not as clear-cut.
There is a downside to devoting resources continually to raise customer satisfaction levels.
As companies cannot usually quantify the costs associated with raising customer satisfaction levels, you cannot determine the value of an increase.
Often, the return on investment for improving customer satisfaction is trivial or negative.
Although higher satisfaction scores can increase revenue, the costs of getting the higher scores frequently outweigh the benefits.
Pricing is a great example of this phenomenon.
One key factor that drives customer satisfaction is low prices, as satisfaction and price are almost inversely related.
Thus, lowering price tends to be one of the easiest ways to casino customer satisfaction survey best practices satisfaction levels in the game industry, which could be the same as giving away premium currency.
The problem is that most companies and products, low prices are often bad for business and there is not much room to drop prices and remain profitable.
The authors used examples of a large financial services institution and to illustrate this point.
With the financial institution, the majority of customers were highly satisfied.
Unfortunately, over two-thirds of these highly satisfied customers were also unprofitable for the company.
Each time the company underpriced its offer, these customers bought in large quantities.
The problem was exacerbated as the more they spent, the more additional services they expected.
With Groupon, there is a usually negative relationship between customer satisfaction and merchant profitability.
Four of the six top performing categories of Groupon offers in terms of satisfaction were money losers for the merchants.
These examples show that customer satisfaction and profitability are often not aligned.
There are other ways to improve customer satisfaction, a better customer experience or more innovative products.
However, not all alternatives will be profitable.
Moreover, not all customers can be profitably satisfied; some will not pay the necessary price for the level of service being offered.
Others demand a level of service that more than offsets any revenue they provide.
The point of this issue: you must understand the profit impact of efforts to improve customer satisfaction.
They use some very obvious examples to make their point.
Target, Sears and JC Penney all consistently outperform Wal-Mart on customer satisfaction but there sales and profits fall way behind.
Thus, smaller niche companies can better serve their customers while companies with large market share must serve a more diverse set of customers.
This data suggests you should not necessarily benchmark against the companies in your space with the highest customer satisfaction levels, they are probably niche players that by design are tailored to best machines kansas star casino individual audience.
It also shows that you a focus on improving your score may not improve your profitability.
The research, however, shows virtually no correlation between satisfaction and wallet share.
They hypothesize this occurs because customers now have divided loyalty they are not committed to a single brandmore customers partially defect than completely defect from a business or brand.
This is particularly true in the free to play game space, where players will partially defect to another game or app.
The weak relationship between satisfaction and wallet share leaves many companies unable to identify what they can do to capture a greater share of customer spending.
They tend to believe that customers who consider themselves completely satisfied are more likely to give the bulk of their spending in the category to their brand.
The goal then becomes to get that number up.
Customers this web page divide their spending among multiple competing games or brands.
Satisfaction is relative to competitive alternatives.
How to succeed with customer satisfaction While focusing simply on high customer satisfaction is not a profitable strategy, using it appropriately has huge benefits.
The definitive book on customer lifetime value,is now available in both print and Kindle formats on Amazon.
By understanding this metric, you can predict how changes to your product will impact the value of each customer.
You will also learn how best poker vegas apply this simple yet powerful method of predictive analytics to optimize your marketing and user acquisition.
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