Minimum Wage is a frequent topic of political debate. Analyze the pros Essay

Minimum Wage is a frequent topic of political debate. Analyze the pros and cons of such a policy using the relevant theoretical - Essay Example This made it a requirement of all states to set this as their minimum wage limit but this does not make it mandatory because some states exhibit variations of this set minimum. Some states, like California, have higher limits of this wage, which is at $8.00 while others, like Georgia, have wage limits below that federal limit at $5.15 per hour. These differences are made possible, by the municipal and state laws, which make it possible, for individual states to set their own minimum wage limits by exercising their right to enact their own by laws. This enables them to determine the limit of minimum wage, with respect to the economic potential of that a given state because it would not make sense to match the minimum wage with a rich state in terms of resources. This is an analytical discussion about the advantages and disadvantages of the minimum wage policy in the United States of America using a theoretical construct approach. Minimum wage from an economists view is disadvantageous to the market system of demand and supply. This is because when the minimum wage is raised the number of people vying for that job position increase, but the employer’s willingness to offer the position decreases because it is an increase in expenses in terms of salaries. In this scenario, employers would rather delegate the duties to be filled, by the new position to existing employees, than offering the job position. On the other hand, if the minimum wage were reduced, it would give employers an opportunity to create more job opportunities in organizations because they can afford to do so. This would depend on the amount of the wage set because a minimum wage of $1 per hour would not attract anyone, but student workers could consider a $4 per hour. Setting up the minimum wage law disrupted the functioning of supply and demand system because it dictates what employers should pay, instead of letting the two factors standardize the field on their own. Market factors of demand and supply govern the number and type of jobs available along what each job category would pay (Schmidt, 19). Increasing the minimum wage deprives a group of young Americans the much needed life lessons, which can be acquired when one works minimum wage job. This is because these jobs are popular with interns, workers in training and students, which help them, learn early in life how to handle money and relate with people in different circumstances (Schmidt, 16). They instill the values of hard work, responsibility and hard work early in their lives and motivate them to aspire to go to college and acquire advanced skills, which can enable them get better paying jobs in the future. Raising the minimum wage reduces the number of these types of jobs because employers will not be willing to offer these job positions because of increased salaries. This will translate to the emergence of a generation of Americans who have no value for hard work and responsibility, which would be detrimen tal to the economy of the country. It means that most of the American society in the future will lack a driving force that is essential in inculcating work ethics that are vital to a vibrant economy characterized by a work force that knows and understands the benefits of hard work. An increase in the minimum wage will result in a decrease of job opportunities that offer invaluable experience that is a prerequisite in almost all well paying and stimulating jobs in America. New entrants into

3-Methylglutaconic Aciduria Research

3-Methylglutaconic Aciduria Research A distinct type of 3-methylglutaconic aciduria due to a mutation in the Translocase of Inner Mitochondrial Membrane 50 (TIMM50) gene Abstract BACKGROUND: 3-methylglutaconic aciduria biochemically characterized by increased urinary excretion of 3-methylglutaconic acid result from defective leucine metabolism and disorders affecting mitochondrial function though in many cases the cause remains unknown. Recently mutations in mitochondrial TIMM50 gene has been reported in four patients from two unrelated families. We report additional mutations in TIMM50 gene in 6 individuals from two unrelated consanguineous families with a distinctive type of 3-methylglutaconic aciduria. METHODS:Â  We report on three patients of South Asian ancestry with intractable epilepsy, microcephaly, developmental delay, visual deficit spastic quadriplegia and three Caucasian patients of eastern European origin with intellectual disability with or without seizure. Metabolic testing revealed mild lactic acidosis and excretion of large amount of 3-methylglutaconic acid in urine in all patients. Full exome sequencing was performed using genomic DNA isolated from one surviving patient, two healthy siblings and both parents of South Asian family. Exome sequencing was also performed for Caucasian patients of eastern European origin. RESULTS:Â  Exome sequencing identified two homozygous mutation Gly372Ser and Iso392Thr mutations in the gene TIMM50. There were no other candidate alterations in exome that could explain the phenotype in the proband. The mutations are located in the conserved C-terminal domain of the Tim50 protein that interacts with the N-terminal domain of the Tim23 protein in the intermembrane space and regulates mitochondrial protein import of presequence-containing polypeptides Both parents are heterozygous. CONCLUSION: Given the phenotypic similarilty of the patients from two unrelated families and an earlier report of mutations in additional family, we conclude that TIMM50 gene mutation results in a novel mitochondrial disorder with 3-methyl glutaconic aciduria. INTRODUCTION 3-methylglutaconic aciduria (MGCA), an increase in urinary 3-methylglutaconic acid or 3-methylglutaric acid, can be a nonspecific finding in mitochondrial disorders, organic aciduria, urea cycles disease, neuromuscular disorders. but is a consistent abnormality of 3-methylglutaconyl-CoA hydratase deficiency and patients with mutations in TAZ, SERAC1, OPA3, DNAJC19 and TMEM70 gene1. These genes all encode mitochondrial membrane or membrane related proteins. In 3-methylglutaconyl-CoA hydratase deficiency due to mutation in AUH gene , 3-methylglutaconic acid derives from 3-methylglutaconyl CoA (3MG CoA), an intermediate in leucine catabolism1. It has been proposed that in other disorders, 3-methylglutaconic acid derives from aberrant isoprenoid shunting from cytosol to mitochondria via mevalonate pathway or redirection of mitochondrial acetyl CoA toward production of 3MGA due to an increase in the intra-mitochondrial NADH/NAD+ ratio resulting from mutation induced impairment in electron transport chain or Kreb cycle function 2. Examples of mitochondrial include Barth syndrome, a cardioskeletal myopathy with neutropenia, abnormal mitochondria and MGCA. Barth syndrome is caused by X-linked recessive mutations in the TAZ gene which encodes the mitochondrial membrane localized transacylase involved in the maturation of cardiolipin. Autosomal recessive mutations in the OPA3 gene (OMIM: 606580), the mouse ortholog of which encodes a mitochondrial inner membrane protein of unknown function, cause MGCA3 (OMIM: 258501), a neuroopthalmologic syndrome characterized by early-onset bilateral optic atrophy and later-onset spasticity, extrapyramidal dysfunction and cognitive deficit. MGCA5 (OMIM: 610198) is yet another form of MGCA caused by autosomal recessive mutations in the DNAJC19 gene (OMIM: 608977) and in addition to increased urinary excretion of 3-methylglutaconic acid, patients present with infancy or childhood onset dilated cardiomyopathy, microcytic anemia, mild muscle weakness and ataxia. Many patients die of cardiac failure. The DNAJC19 gene encodes the human homolog of the yeast Tim14 which is a part of the Tim23 mitochondrial protein import machinery and hasbeen shown to interact with the mtHsp70 in an ATP-dependent manner to regulate Tim23 function (Davey, 2006). WE report a distinct type of 3-methylglutaconic aciduria resulting from a mutation in mitochondrial TIMM50 gene in 3 sibs from a consanguineous family. We initially reported these xases in abstract form. Recently two different mutations in mitochondrial TIMM50 gene have been reported in four patients with 3 methylglutaconic aciduria, epilepsy, severe intellectual disability and lactic acidosis. Subjects Family 1 Family 1 has three affected sibs of South Asian ancestry with intractable epilepsy, microcephaly, developmental delay, visual deficit spastic quadriplegia. Two affected sibs died unexpectedly when they were visiting families in a remote area of a South Asian country. Metabolic testing had revealed large amount of 3-methylglutaconic acid in urine in all three affected sibs. The patients have a healthy brother and a healthy sister. Mother and father are first cousins. Detailed clinical history, imaging, EEG and metabolic testing were obtained for all affected persons. Full exome sequencing was performed using genomic DNA isolated from one surviving patient, two healthy siblings and both parents. Patient IV-1. Patient IV-1 was the first born child of the parents and was born at 36 weeks gestation after a normal pregnancy and delivery. Her weight at birth was 1.99 kg. Her weight, height and head circumference were always below 5th centile. She also had asthma and frequent episodes of pneumonia presumably due to aspiration, but the family refused G-tube placement. She was severely delayed. She never sat, stand or spoke. She has poor head control, truncal hypotonia but very brisk tendon jerks and sustained clonus. Funduscopy revealed bilateral optic atrophy. She developed seizures at 1 year of age. EEG revealed multifocal spikes arising from both hemispheres. She was treated with phenobarbital and Zonegran but family was noncompliant with medications. She continued to have daily myoclonic jerks. MRI at 2.5 and 5 years of age showed increased T2 signal in basal ganglia and periventricular white matter, brain atrophy, prominent ventricle, increased extraxial fluid. Normal liver en zymes and blood count, normal blood and CSF glucose and a serum ammonia of 21. Several serum lactate levels were mildly elevated. Lactate 2.8, 4.5 (Pyruvate 0.23), 5.4 (normal 0.7 to 2.1) Lactate to pyruvate ratio 20:1. Urine organic acid analysis revealed very high lactic acid, 3-methylglutaconic acid, and 3-methylglutaric acid. Muscle biopsy revealed only scattered atrophic muscle fibers on electron microscopy. Respiratory chain enzyme activities were within normal limits. She died at 7.5 years of age apparently due to complications from an infection while she was visiting families in a remote area of a South Asian country. Patient IV-4 was twin A born at 36 weeks gestation after an uncomplicated twin pregnancy. Her weight, height and head circumference were always below 5th centile. She was severely delayed. She never sat, stand or spoke. She has poor head control, truncal hypotonia but very increased reflexes and spasticity in the limbs. At nine-month-of age, she started to experience several episodes of eye fluttering and body jerking. Her EEG reved slow background, poor sleep architecture and frequent multifocal spike and sharp wave activities coming from both the left and right hemispheres. Her seizures were treated with Zonegran and was poorly controlled but parents refused more aggressive treatment of seizures. Metabolic testing revealed mild elevation of lactate and moderate increase of 3 methylglutaconic, 3 methylglutaric acids in urine. A brain MRI at 11-month-of age revealed diffuse volume loss supratentorially with prominent sulci and extraaxial fluid spaces, mild enlargement of the ventricl es and patchy signal abnormalities in the basal ganglia bilaterally, especially involving the caudate nuclei and putamen. On spectroscopy with voxel placed in the right basal ganglia with short and long TE, there was a lactate peak which inverted on long TE spectrum. Also, the NAA peak was low with NAA to creatinine being 1.15 on short echo and 1.29 on long echo spectrum. Also, the choline was elevated with choline/creatine ratio being 1.00 on short echo and 1.41 on long echo images. She died at 1.5 years of age apparently due to complications of an infection while she was visiting families in a remote area of a South Asian country. Patient IV-5 is a 13 year old female of South Asian ancestry, with 3-methylglutaconic aciduria intractable epilepsy, microcephaly, developmental delay, visual deficit and spastic quadriplegia. She was born at 36 weeks gestation after an uncomplicated twin pregnancy. She was twin B and stayed in NICU for 18 days for feeding issues. Her weight was 1.4 kg and she was not intubated. Patient first presented with seizures at 3 months of age with eyelid fluter and jerking of extremities. Her initial EEG revealed multifoal spikes. Initial biochemical evaluation revealed normal serum and CSF glucose, normal ammonia and liver enzymes. Serum lactate and CSF lactate 4.24 mmol were mildly elevated . Lactate was 2.7. Ammonia 25. Serum amino increased alanine 43.6 micromol/dl (9.9-34.5). Csf lactate 4.24 mmol. CSF alanine 7 micromol/dl (0.6 -4.7). There were also mild elevations of serum and CSF valine, leucine, isoleucine and alanine and lysine. Urine organic analysis revealed moderate increase of 3 methylglutaconic, 3 methylglutaric, glutaric, adipic, suberic, and sebacic acids. MRI of brain at 11 months of age revealed severe atrophic changes involving gray and white matter, predominantly of the cerebrum. Grossly abnormal signal is seen in the basal ganglia, particularly the caudate nucleus and the putamen with relative sparing of the globus pallidus and thalamus. A recent MRI (at age 13 years) reveals severe but stable atrophic changes of the gray and white matter of the supra and infratentorial brain, stable white matter changes of the putamen, caudate nucleus and periventricular white matter, Scattered diffusion restriction in the retrotrigonal white matter, compatible with active demyelination and atrophic changes of the optic nerves. Her seizures were treated with with Keppra, Lamictal, Zonegran and Onfi. She also receives carnitine. She continues to have brief episodes of whole body stiffening each week, but the family was also not very compliant with medications. He r current EEG shows slow background for age, poorly formed sleep spindles indicatvie of diffuse neuronal dysfunction, frequent multifocal interictal spike and wave suggests increased risk of seizures arising from multiple foci and hypsarrhythmia in sleep . She has failure to thrive despite G-tube feeding. At 12 years of age, G-tube was placed due to history of aspirations. Height, weight and head circumference below 5th centile. She is severely delayed. She is nonverbal and never learned to sit independently, stand or walk. She recognizes family members, responds to their voice and looks and smiles at them. Her fundoscopy shows mild optic atrophy. She has bilateral esotropia and dysconjugate gaze. She has poor head control and truncal hypotonia, but her limbs are spastic and her tendon reflexes are very brisk. Family 2 Patient V:1 was the first son of Caucasian consanguineous parents (IV:4 and IV:5) of Eastern European origin. Within the context of an organic acid and amino acid study in young and adult subjects with non-syndromic developmental delay and intellectual disability, he was investigated at the age of 17 years and presented with a developmental language disorder (involving semantic, syntactic, and pragmatic components of the linguistic system), emotional and communicative problems (fearful, aggressive, and loner), and hyperactivity. On neuropsychological testing he showed a short attention span. The child was born at term after an uneventful pregnancy and his birth weight was 2.9 kg. At 4 months of age he was affected by myoclonic jerks that were controlled by administration of valproic acid and lamotrigine. Developmental delay was observed starting from the middle of the first year of life, accompanied by decreased muscle tone. He could walk without support only at 6 years. At last medi cal exam, the patient showed a reduced muscle mass (height 148 cm, Z-score 3.43; weight 38 kg, Z-score 4.21; BMI 17.1 kg/m2, Z-score 2.02) and a head circumference of 51 cm (Z-score 2.76). Due to refusal of parents, no brain imaging studies could be performed. Fundoscopic examination was normal. Laboratory tests, including creatine phosphokinase (CPK), liver enzymes and plasma amino acids, were normal. The profile of urinary organic acids showed a large peak of 3-methylglutaconic acid (113 mmol/mol creatine) and a slightly increased level of 3-methylglutaric acid (17 mmol/mol creatinine). Patient V:3 was the younger brother of V:1, the third child of IV:4 and IV:5. He was investigated at the age of 11 years and presented with a clinical phenotype (developmental delay and intellectual and behavioral disorder) similar to that of his brother. The pregnancy and early postnatal course was unremarkable and birth weight was 3.1 kg. At 3 months he received valproic acid and lamotrigine to control tonic seizures with sudden stiffening movements of arms and legs. The boy walked independently at 4 years. When he was 9 years, his growing parameters were: height 119 cm (Z-score 2.47), weight 22 kg (Z-score 1.91), BMI 15.5 kg/m2 (Z-score 0.38), and head circumference 48 cm (Z-score 3.52). Neuropsychological exam revealed mental retardation and impaired communicative skills, including poor language abilities (few repetitive words with no sentences). Occasionally, the patient is aggressive. Ophthalmologic examination revealed left esotropia. High levels of 3-methylglutaconic acid (15 5 mmol/mol creatine) were identified in urine, together with smaller amounts of 3-methylglutaric acid (22 mmol/mol creatinine). Patient V:5 was the second son of consanguineous parents (IV:9 and IV:10) related to those of patients V:1 and V:3. The girl was delivered by cesarean section because of growth arrest at 37 week. The neonate showed no external malformations. Birth weight was 2.1 kg. In the following years, the clinical phenotype was characterized by delayed developmental milestones, nocturnal enuresis, severe cognitive impairment, speech retardation, and lack of communicative skills. Results of the electroencephalogram were normal. No brain imaging data are available. On a few occasions, levels of ammonia and lactic acid were found to be slightly elevated, but these results could not be confirmed by repeated blood analyses. Plasma levels of amino acids are within normal range. Fundoscopic examination was normal up to 7 years, but since then there is evidence of mild bilateral optic atrophy. Urine levels of of 3-methylglutaconic acid and 3-methylglutaric acid were 176 mmol/mol creatine and 29 mmol/mol creatinine, respectively. DISCUSSION Deleterious Nature of the TIMM50 gene alteration: TIMM50 NM_001001563 c.1114G>A p.G372S The p.G372S variant (also known as c.1114G>A), located in coding exon 9 of the TIMM50 gene, results from a G to A substitution at nucleotide position 1114. The glycine at codon 372 is replaced by serine, an amino acid with somewhat similar properties. The alteration is not observed in healthy cohorts: Based on data from the NHLBI Exome Sequencing Project (ESP), the TIMM50 c.1114G>A alteration was not observed among 6,503 individuals tested. Allele frequency data for this nucleotide position are not currently available from the 1000 Genomes Project and the alteration is not currently listed in the Database of Single Nucleotide Polymorphisms (dbSNP). Though some variants may appear to be rare due to database-specific ethnic underrepresentation, rare missense alleles commonly exhibit a deleterious effect on protein function (Kryukov, 2007; Tennessen, 2012). The altered amino acid is conserved throughout evolution: The G372 amino acid position is completely conserved in eukaryotes all th e way from the yeast Saccharomyces cerevisiae to humans (Mokranjac, 2003). The alteration is predicted deleterious by in silico models: The p.G372S alteration is predicted to be probably damaging and deleterious by PolyPhen and SIFT in silico analyses, respectively. The amino acid is located in a functionally important protein domain: The p.G372S alteration is located in the conserved C-terminal domain of the Tim50 protein that interacts with the N-terminal domain of the Tim23 protein in the inter membrane space and regulates mitochondrial protein import of presequence-containing polypeptides (Geissler, 2002; Yamamoto, 2002; Guo, 2004). The alteration cosegregated with disease in the family herein: Co-segregation analysis revealed that this alteration is present in a heterozygous form in the mother, father and brother, and absent in the sister. Based on the available evidence, the TIMM50 c.1114G>A (p.G372S) alteration is classified as a likely pathogenic mutation. The TIMM50 gene is not currently known to underlie Mendelian disease (aka clinically novel). The TIMM50 gene function is consistent with the probands clinical presentation: The Translocase of Inner Mitochondrial Membrane 50 (TIMM50) gene (OMIM: 607381) is located on human chromosome 19q13.2 and consists of 11 exons. It encodes the Tim50 protein, a 353 amino acid 40 kDA homolog of the yeast Tim50 protein that functions as an integral part of the mitochondrial Tim23 protein import machinery by linking protein translocation across the outer and inner mitochondrial membranes. This interaction was confirmed by the coprecipitation of Tim50 with an antibody against Tim23 (Geissler, 2002; Yamamoto, 2002; Guo, 2004). The authors further confirmed that the C-terminal domain of Tim50 is located in the inter-membrane space (IMS) where it stably binds to the segment of Tim23 that spans the IMS and regulates its function. Nuclear encoded mitochondrial proteins are synthesized in the cytosol and subsequently imported into the mitochondria through the function of translocators, the TOM complex of the outer mitochondrial membrane (OMM), and the Tim23 and Tim22 complexes of the inner mitochondrial membrane (IMM) (Jensen, 2002). While the Tim22 complex is involved in the transport and insertion of proteins lacking the presequence into the inner membrane, the Tim23 complex is required to process and insert presequence-containing precursor proteins. The IMM generates a proton motive force that is critical for cellular energy synthesis (Stock, 2000) and the permeability barrier of the IMM needs to be maintained during the transport of proteins through the pore-forming Tim23 protein associated with other IMM proteins such as Tim14 (human DNAJC19), Tim17, Tim21, Tim44 and Tim50. Using various yeast IMM protein mutants, Meinecke et al. (2006) demonstrated that tim17 and tim21 mutant mitochondria displayed membra ne potential values that were comparable to wild type mitochondria, whereas tim50 mutant mitochondria showed a drastic reduction of the membrane potential. Further functional studies revealed that the Tim23 channel is tightly regulated by Tim50 in its inactive state to maintain the IMM permeability barrier and is opened only when presequence-containing polypeptide chains need to be translocated into the mitochondrial matrix or the inter membrane space (IMS). Loss of Tim50 function in yeast led to cellular growth arrest and reduced cell viability (Mokranjac, 2003). Knockdown to Tim50 expression in cultured human cells using RNA mediated interference resulted in an increase in the release of cytochrome c and apoptosis in response to cell death stimuli (Guo, 2004). A 50 kDa isoform of the human mitochondrial TIM50, TIM50a, consisting of 456 amino acids has been found to localize in nuclear speckles, specifically in the Cajal bodies, and interact with small nuclear ribonuclear proteins (snRNPs), the coilin protein and the Survival of Motor Neurons (SMN) protein (Xu, 2005) which has been implicated in Spinal Muscular Atrophy (SMA). The protein sequences of the mitochondrial TIM50 and the nuclear TIM50a are identical with the exception of additional 103 amino acids at the N-terminal of TIM50a that are the result of an alternative translational start sequence. This additional N-terminal sequence in TIM50a is thought to contain a putative nuclear localization sequence that allows the Tim50a isoform to display a nucleus specific localization. Based on their results, Xu et al. hypothesized that Tim50a might be involved in the regulation of snRNP biogenesis and possibly the function of the nuclear SMN protein encoded by the SMN1 gene. One of our patien ts had mulsle biopsy. Although there were atrophic changes, no neuropthic pattern was seen. Reference List (1) Wortmann SB, Kluijtmans LA, Rodenburg RJ et al. 3-Methylglutaconic acidurialessons from 50 genes and 977 patients. J Inherit Metab Dis 2013;36:913-921. (2) Ikon N, Ryan RO. On the origin of 3-methylglutaconic acid in disorders of mitochondrial energy metabolism. J Inherit Metab Dis 2016;39:749-756. Legends Legend to Figure 1 Five-generations pedigree of the family with mild 3-methylglutaconic aciduria in which the TIMM50 p.(Ile293Thr) was identified. Subjects V:1, V:3, and V:5 (filled symbols) are patients suffering from intellectual disability and increased urinary excretion of 3-methylglutaconic acid. They are born to consanguineous parents and homozygous for the TIMM50 c.1011T>C mutation predicting the replacement of isoleucine 293 with threonine in the encoded protein. The mutation was inherited by a common ancestor (either I:1 or I:2) and has been identified in the heterozygous state in the clinically and biochemically unaffected subjects III:3, III:4, III:9, IV:2, IV:4; IV:5; IV:9, IV:10, and V:2.

Internet Marketing Privacy Issues Essay -- Internet Security

If a random person came over to you on the street, would you give him your personal information? Would you allow him to follow and record your activities? Most certainly not. Although this answer may be obvious in the physical world, the general populations’ behavior on the Internet is strikingly different. Websites like Facebook, Twitter, and Google retain vast amounts of personal information of their users. Although this practice benefits the user as well, unrestricted profiling can be quite unnerving. Since regulation from the government may impede Internet use, and unless the threat to internet users privacy are shown to exceed the benefits, the government will not regulate the internet, rather we should educate the public how to be more responsible themselves. The most lucrative business on the Internet is marketing. Companies have come up with ingenious ways to generate revenue with very targeted advertising. Each company has their unique method to identify their consumers, some more complicated than others. For example, on a website geared to new mothers the advertisements would reflect that by advertising for baby diapers or formula. This type of targeted advertising is understood and acceptable. The consumer benefits by having advertisements in their interests and the vendor has a higher likelihood of making a sale. The Internet has introduced novel ways to track consumer habits and interests thereby creating smarter advertising. Microsoft employs their browser Internet Explorer using â€Å"cookies† to track user habits. Cookies are pieces of text stored by a user’s web browser, they are sent back and forth every time a user accesses a web page. These can be tracked to follow web surfers’ actions. Cookies are us ed to store... ...egulation may not be a solution, history has proven that the power to resolve this glowing lack of privacy lies within the hands of the people themselves. The manner in which similar issues were resolved in the past, elucidate on the present. The now famous company Truste created the Web Privacy Seal, the little icon that tells you the website is secure. Ten years ago users were to afraid to buy anything in the internet with their credit cards for fear of identity theft, now one can just look for that seal. As mentioned before Facebook’s privacy changes prompted 2.2 million Facebook members to form a group protesting these changes. Consumers are recognizing the threat to their control and in the same way in the past have come up with ingenious ways to protect themselves they will continue to stand up for their rights that will ultimately affect company policies.

The Dark Side of Customer Analytics

HBR CASE STUDY AND COMMENTARYHow can these companies leverage the customer data responsibly? The Dark Side of Customer Analytics Four commentators offer expert advice. by Thomas H. Davenport and Jeanne G. Harris Reprint R0705A An insurance company finds some intriguing patterns in the loyalty card data it bought from a grocery chain—the correlation between condom sales and HIV-related claims, for instance. How can both companies leverage the data responsibly? HBR CASE STUDY The Dark Side of Customer Analytics COPYRIGHT  © 2007 HARVARD BUSINESS SCHOOL PUBLISHING CORPORATION. ALL RIGHTS RESERVED. by Thomas H. Davenport and Jeanne G. Harris Laura Brickman was glad she was almost done grocery shopping. The lines at the local ShopSense supermarket were especially long for a Tuesday evening. Her cart was nearly over? owing in preparation for several days away from her family, and she still had packing to do at home. Just a few more items to go: â€Å"A dozen eggs, a half gallon of orange juice, and—a box of Dip & Dunk cereal? † Her sixyear-old daughter, Maryellen, had obviously used the step stool to get at the list on the counter and had scrawled her high-fructose emand at the bottom of the paper in brightorange marker. Laura made a mental note to speak with Miss Maryellen about what sugary cereals do to kids’ teeth (and to their parents’ wallets). Taking care not to crack any of the eggs, she squeezed the remaining items into the cart. She wheeled past the ShopSense Summer Fun displays. â€Å"Do we need more sunscreen? † L aura wondered for a moment, before deciding to go without. She got to the checkout area and waited. As regional manager for West Coast operations of IFA, one of the largest sellers of life and health insurance in the United States, Laura ormally might not have paid much attention to Shop-Sense’s checkout procedures—except maybe to monitor how accurately her purchases were being rung up. But now that her company’s fate was intertwined with that of the Dallas-based national grocery chain, she had less motivation to peruse the magazine racks and more incentive to evaluate the scanning and tallying going on ahead of her. Some 14 months earlier, IFA and ShopSense had joined forces in an intriguing venture. Laura for years had been interested in the idea of looking beyond the traditional sources of customer data that insurers ypically used to set their premiums and develop their products. She’d read every article, book, and Web site she HBR’s cases, whic h are ? ctional, present common managerial dilemmas and offer concrete solutions from experts. harvard business review †¢ may 2007 page 1 H BR C A SE S T UDY †¢Ã¢â‚¬ ¢ †¢T he Dark Side of Customer Analytics Thomas H. Davenport ([email  protected] babson. edu) is the President’s Distinguished Professor of Information Technology and Management at Babson College, in Wellesley, Massachusetts, and the director of research for Babson Executive Education. Jeanne G. Harris (jeanne. g. [email  protected] com) is an executive research fellow and a director of research at the Accenture Institute for High-Performance Business. She is based in Chicago. Davenport and Harris are the coauthors of Competing on Analytics (Harvard Business School Press, 2007). page 2 could ? nd on customer analytics, seeking to learn more about how organizations in other industries were wringing every last drop of value from their products and processes. Casinos, credit card companies, even s taid old insurance ? rms were joining airlines, hotels, and other service-oriented businesses in gathering nd analyzing speci? c details about their customers. And, according to recent studies, more and more of those organizations were sharing their data with business partners. Laura had read a pro? le of ShopSense in a business publication and learned that it was one of only a handful of retailers to conduct its analytics in-house. As a result, the grocery chain possessed sophisticated data-analysis methods and a particularly deep trove of information about its customers. In the article, analytics chief Steve Worthington described how the organization employed a pattern-based approach to issuing coupons. The marketing department understood, for instance, that after three months of purchasing nothing but WayLess bars and shakes, a shopper wasn’t susceptible to discounts on a rival brand of diet aids. Instead, she’d probably respond to an offer of a free doughnut or pastry with the purchase of a coffee. The company had even been experimenting in a few markets with what it called Good-Sense messages—bits of useful health information printed on the backs of receipts, based partly on customers’ current and previous buying patterns. Nutritional analyses of some customers’ most recent purchases were eing printed on receipts in a few of the test markets as well. Shortly after reading that article, Laura had invited Steve to her of? ce in San Francisco. The two met several times, and, after some fevered discussions with her bosses in Ohio, Laura made the ShopSense executive an offer. The insurer wanted to buy a small sample of the grocer’s customer lo yalty card data to determine its quality and reliability; IFA wanted to and out if the ShopSense information would be meaningful when stacked up against its own claims information. With top management’s blessing, Steve and his team had agreed to provide IFA with ten ears’ worth of loyalty card data for customers in southern Michigan, where ShopSense had a high share of wallet—that is, the supermarkets weren’t located within ? ve miles of a â€Å"club† store or other major rival. Several months after receiving the tapes, analysts at IFA ended up ?nding some fairly strong correlations between purchases of unhealthy products (highsodium, high-cholesterol foods) and medical claims. In response, Laura and her actuarial and sales teams conceived an offering called Smart Choice, a low-premium insurance plan aimed at IFA customers who didn’t indulge. Laura was ? ing the next day to IFA’s headquarters in Cincinnati to meet with members of the senior team. She would be seeking their approval to buy more of the ShopSense data; she wanted to continue mining the information and re? ning IFA’s pricing and marketing efforts. Laura understood it might be a tough sell. After all, her industry wasn’t exactly known for embracing radical change—even with proof in hand that change could work. The make-or-break issue, she thought, would be the reliability and richness of the data. â€Å"Your CEO needs to hear only one thing,† Steve had told her several days earlier, while they were comparing notes. Exclusive rights to our data will give you information that your competitors won’t be able to match. No one else has the historical data we have or as many customers nationwide. † He was right, of course. Laura also knew that if IFA decided not to buy the grocer’s data, some other insurer would. â€Å"Paper or plastic? † a young boy was asking. Laura had ? nally made it to front of the line. â€Å"Oh, paper, please,† she replied. The cashier scanned in the groceries and waited while Laura swiped her card and signed the touch screen. Once the register printer had stopped chattering, the cashier curled the long strip of aper into a thick wad and handed it to Laura. â€Å"Have a nice night,† she said mechanically. Before wheeling her cart out of the store into the slightly cool evening, Laura brie? y checked the total on the receipt and the information on the back: coupons for sunblock and a reminder about the importance of UVA and UVB protection. Tell It to Your Analyst â€Å"No data set is perfect, but based on what we’ve seen already, the ShopSense info could be a pretty rich source of insight for us,† Archie Stetter told the handful of executives seated around a table in one of IFA’s recently renovated conference rooms. Laura nodded in agreement, silently cheering on the insurance harvard business review †¢ may 2007 T he Dark Side of Customer Analytics †¢Ã¢â‚¬ ¢ †¢H BR C A SE S T UDY company’s uberanalyst. Archie had been invaluable in guiding the pilot project. Laura had ? own in two days ahead of the meeting and had sat down with the chatty statistics expert and some members of his team, going over results and gauging their support for continuing the relationship with ShopSense. â€Å"Trans fats and heart disease—no surprise there, I guess,† Archie said, using a laser pointer to direct the managers’ attention to a PowerPoint slide projected on the wall. How about this, though: Households that purchase both bananas and cashews at least quarterly seem to show only a negligible risk of developing Parkinson’s and MS. † Archie had at ? rst been skeptical about the quality of the grocery chain’s data, but ShopSense’s well of informati on was deeper than he’d imagined. Frankly, he’d been having a blast slicing and dicing. Enjoying his moment in the spotlight, Archie went on a bit longer than he’d intended, talking about typical patterns in the purchase of certain over-the-counter medications, potential leading indicators for diabetes, and other statistical curiosities. Laura noted that as Archie’s presentation wore on, CEO Jason Walter was jotting down notes. O. Z. Cooper, IFA’s general counsel, began to clear his throat over the speakerphone. Laura was about to rein in her stats guy when Rusty Ware, IFA’s chief actuary, addressed the group. â€Å"You know, this deal isn’t really as much of a stretch as you might think. † He pointed out that the company had for years been buying from information brokers lists of customers who purchased speci? c drugs and products. And IFA was among the best in the industry at evaluating external sources of data (credit histories, demographic studies, analyses f socioeconomic status, and so on) to predict depression, back pain, and other expensive chronic conditions. Prospective IFA customers were required to disclose existing medical conditions and information about their personal habits—drinking, smoking, and other high-risk activities—the actuary reminded the group . The CEO, meanwhile, felt that Rusty was overlooking an important point. â€Å"But if we’re ?nding patterns where our rivals aren’t even looking, if we’re coming up with proprietary health indicators—well, that would be a huge hurdle for everyone else to get over,† Jason noted. arvard business review †¢ may 2007 Laura was keeping an eye on the clock; there were several themes she still wanted to hammer on. Before she could follow up on Jason’s comments, though, Geneva Hendrickson, IFA’s senior vice president for ethics and corporate responsibility, posed a blue-sky question to the group: â€Å"Take the fruit-and-nut stat Archie cited. Wouldn’t we have to share that kind of information? As a bene? t to society? † Several managers at the table began talking over one another in an attempt to respond. â€Å"Correlations, no matter how interesting, aren’t conclusive evidence of causality,† someone said. Ev en if a correlation doesn’t hold up in the medical community, that doesn’t mean it’s not useful to us,† someone else suggested. Laura saw her opening; she wanted to get back to Jason’s point about competitive advantage. â€Å"Look at Progressive Insurance,† she began. It was able to steal a march on its rivals simply by recognizing that not all motorcycle owners are created equal. Some ride hard (young bikers), and some hardly ride (older, middle-class, midlife crisis riders). â€Å"By putting these guys into different risk pools, Progressive has gotten the rates right,† she said. â€Å"It wins all the business with the safe set by offering low remiums, and it doesn’t lose its shirt on the more dangerous set. † Then O. Z. Cooper broke in over the speakerphone. Maybe the company should formally position Smart Choice and other products and marketing programs developed using the Shop-Sense data as opt in, he wondered. A lot of people signed up when Progressive gave discounts to customers who agreed to put devices in their cars that would monitor their driving habits. â€Å"Of course, those customers realized later they might pay a higher premium when the company found out they routinely exceeded the speed limit—but that’s not a legal problem,† O. Z. noted. None of the states that IFA did business in had laws prohibiting the sort of data exchange ShopSense and the insurer were proposing. It would be a different story, however, if the company wanted to do more business overseas. At that point, Archie begged to show the group one more slide: sales of prophylactics versus HIV-related claims. The executives continued taking notes. Laura glanced again at the clock. No one seemed to care that they were going a little over. â€Å"Exclusive rights to our data will give you information that your competitors won’t be able to match. No one else has the historical data we have. † page 3 H BR C A SE S T UDY †¢Ã¢â‚¬ ¢ †¢T he Dark Side of Customer Analytics Data Decorum â€Å"Customers find out, they stop using their cards, and we stop getting the information that drives this whole train. † page 4 Rain was in the forecast that afternoon for Dallas, so Steve Worthington decided to drive rather than ride his bike the nine and a half miles from his home to ShopSense’s corporate of? ces in the Hightower Complex. Of course, the gridlock made him a few minutes late for the early morning meeting with ShopSense’s executive team. Lucky for him, others had been held up by the traf? c as well. The group gradually came together in a lightly cluttered room off the main hallway on the 18th ? oor. One corner of the space was being used to store prototypes of regional instore displays featuring several members of the Houston Astros’ pitching staff. â€Å"I don’t know whether to grab a cup of coffee or a bat,† Steve joked to the other s, gesturing at the life-size cardboard cutouts and settling into his seat. Steve was hoping to persuade CEO Donna Greer and other members of the senior team to approve the terms of the data sale to IFA. He was pretty con? dent he had majority support; he had already spoken individually with many of the top executives. In those one-onone conversations, only Alan Atkins, the grocery chain’s chief operations of? cer, had raised any signi? cant issues, and Steve had dealt patiently with each of them. Or so he thought. At the start of the meeting, Alan admitted he still had some concerns about selling data to IFA at all. Mainly, he was worried that all the hard work the organization had done building up its loyalty program, honing its analytical chops, and maintaining deep customer relationships could be undone in one fell swoop. â€Å"Customers ? nd out, they stop using their cards, and we stop getting the information that rives this whole train,† he said. Steve reminded Alan that IFA had no interest in revealing its relationship with the grocer to customers. There was always the chance an employee would let something slip, but even if that happened, Steve doubted anyone would be shocked. â€Å"I haven’t heard of anybody canceling based on any of our other card-driven marketing p rograms,† he said. â€Å"That’s because what we’re doing isn’t visible to our customers—or at least it wasn’t until your recent comments in the press,† Alan grumbled. There had been some tension within the group about Steve’s contribution to everal widely disseminated articles about ShopSense’s embrace of customer analytics. â€Å"Point taken,† Steve replied, although he knew that Alan was aware of how much positive attention those articles had garnered for the company. Many of its card-driven marketing programs had since been deemed cuttingedge by others in and outside the industry. Steve had hoped to move on to the ? nancial bene? ts of the arrangement, but Denise Baldwin, ShopSense’s head of human resources, still seemed concerned about how IFA would use the data. Speci? cally, she wondered, would it identify individual consumers as employees of particular companies? She reminded the group that some big insurers had gotten into serious trouble because of their pro? ling practices. IFA had been looking at this relationship only in the context of individual insurance customers, Steve explained, not of group plans. â€Å"Besides, it’s not like we’d be directly drawing the risk pools,† he said. Then Steve began distributing copies of the spreadsheets outlining the ? ve-year returns ShopSense could realize from the deal. â€Å"‘Directly’ being the operative word here,† Denise noted wryly, as she took her copy and passed the rest around. Parsing the Information It was 6:50 pm, and Jason Walters had canceled his session with his personal trainer— again—to stay late at the of? ce. Sammy will understand, the CEO told himself as he sank deeper into the love seat in his of? ce, a yellow legal pad on his lap and a pen and cup of espresso balanced on the arm of the couch. It was several days after the review of the ShopSense pilot, and Jason was still weighing the risks and bene? ts of taking this business relationship to the next stage. He hated to admit how giddy he was— almost as gleeful as Archie Stetter had been— about the number of meaningful correlations the analysts had turned up. Imagine what that guy could do with an even larger data set,† O. Z. Cooper had commented to Jason after the meeting. Exclusive access to ShopSense’s data would give IFA a leg up on competitors, Jason knew. It could also provide the insurer with proprietary insights into the food-related drivers of disease. The deal was cer tainly legal. And even in the court of public opinion, people understood that insurers had to perform risk analyses. It wasn’t the same as when that harvard business review †¢ may 2007 T he Dark Side of Customer Analytics †¢Ã¢â‚¬ ¢ †¢H BR C A SE S T UDY online bookseller got into trouble for charging ustomers differently based on their shopping histories. But Jason also saw dark clouds on the horizon: What if IFA took the pilot to the next level and found out something that maybe it was better off not knowing? As he watched the minute hand sweep on his wall clock, Jason wondered what risks he might be taking without even realizing it. †¢Ã¢â‚¬ ¢Ã¢â‚¬ ¢ Donna Greer gently swirled the wine in her glass and clinked the stemware against her husband’s. The two were attending a wine tasting hosted by a friend. The focus was on varieties from Chile and other Latin American countries, and Donna and Peter had yet to ? nd a sample they didn’t like. But despite the lively patter of the event and the plentiful food. Donna couldn’t keep her mind off the IFA deal. â€Å"The big question is, Should we be charging more? † she mused to her husband. ShopSense was already selling its scanner data to syndicators, and, as her CFO had reminded her, the company currently made more money from selling information than from selling meat. Going forward, all ShopSense would have to do was send IFA some tapes each month and collect a million dollars annually harvard business review †¢ may 2007 of pure pro? t. Still, the deal wasn’t without risks: By selling the information to IFA, it ight end up diluting or destroying valuable and hard-won customer relationships. Donna could see the headline now: â€Å"Big Brother in Aisle Four. † All the more reason to make it worth our while, she thought to herself. Peter urged Donna to drop the issue for a bit, as he scribbled his comments about the wine they’d just samp led on a rating sheet. â€Å"But I’ll go on record as being against the whole thing,† he said. â€Å"Some poor soul puts potato chips in the cart instead of celery, and look what happens. † â€Å"But what about the poor soul who buys the celery and still has to pay a fortune for medical overage,† Donna argued, â€Å"because the premiums are set based on the people who can’t eat just one? † â€Å"Isn’t that the whole point of insurance? † Peter teased. The CEO shot her husband a playfully peeved look—and reminded herself to send an e-mail to Steve when they got home. What if IFA took the pilot to the next level and found out something that maybe it was better off not knowing? How can these companies leverage the customer data responsibly? †¢ Four commentators offer expert advice. See Case Commentary page 5 T he Dark Side of Customer Analytics †¢ H BR C A SE S T UDY C ase Commentary by George L. Jones How can these companies leverage the customer data responsibly? The message coming from both IFA and ShopSense is that any marketing opportunity is valid—as long as they can get away with it. page 6 Sure, a customer database has value, and a company can maximize that value in any number of ways—growing the database, mining it, monetizing it. Marketers can be tempted, despite pledges about privacy, to use collected information in ways that seem attractive but may ultimately damage relationships with customers. The arrangement proposed in this case study seems shortsighted to me. Neither company seems to particularly care about its customers. Instead, the message coming from the senior teams at both IFA and ShopSense is that any marketing opportunity is valid—as long as they can get away with it legally and customers don’t ? gure out what they’re doing. In my company, this pilot would never have gotten off the ground. The culture at Borders is such that the managers involved would have just assumed we wouldn’t do something like that. Like most successful retail companies, our organization is customer focused; we’re always trying to see a store or an offer or a transaction through the customer’s eyes. It was the same way at both Saks and Target when I was with those companies. At Borders, we’ve built up a signi? cant database through our Borders Rewards program, which in the past year and a half has grown to 17 million members. The data we’re getting are hugely important as a basis for serving customers more effectively (based on their purchase patterns) and as a source of competitive advantage. For instance, we know that if somebody buys a travel guide to France, that person might also be interested in reading Peter Mayle’s A Year in Provence. But we assure our customers up front that their information will be handled with the utmost respect. We carefully control the content and frequency of even our own ommunications with Rewards members. We don’t want any offers we present to have negative connotations—for instance, we avoid bombarding people with e-mails about a product they may have absolutely no interest in. I honestly don’t think these companies have hit upon a responsible formula for mining and sharing cust omer data. If ShopSense retained control of its data to some degree—that is, if the grocer and IFA marketed the Smart Choice program jointly, and if any offers came from ShopSense (the partner the customer has built up trust with) rather than the insurance company (a stranger, so to speak)—the relationship could work. Instead of ceding complete control to IFA, ShopSense could be somewhat selective and send offers to all, some, or none of its loyalty card members, depending on how relevant the grocer believed the insurance offer would be to a particular set of customers. A big hole in these data, though, is that people buy food for others besides themselves. I rarely eat at home, but I still buy tons of groceries—some healthy, some not so healthy— for my kids and their friends. If you looked at a breakdown of purchases for my household, you’d say â€Å"Wow, they’re consuming a lot. † But the truth is, I hardly ever eat a bite. That may e an extreme example, but it suggests that IFA’s correlations may be ? awed. Both CEOs are subjecting their organizations to a possible public relations backlash, and not just from the ShopSense customers whose data have been dealt away to IFA. Every ShopSense customer who hears about the deal, loyalty card member or not, is going to lose trust in the company. IFA’s customers might also think twice about their relationship with the insurer. And what about the employees in each company who may be uncomfortable with what the companies are trying to pull off? The corporate cultures suffer. What the companies are proposing here is ery dangerous—especially in the world of retail, where loyalty is so hard to win. Customers’ information needs to be protected. George L. Jones is the president and chief executive officer of Borders Group, a global retailer of books, music, and movies based in Ann Arbor, Michigan. harvard business review †¢ may 2007 T he Dark Side of Customer Analytics †¢ H BR C A SE S T UDY C ase Commentary by Katherine N. Lemon How can these companies leverage the customer data responsibly? Customer analytics are effective precisely because firms do not violate customer trust. harvard business review †¢ may 2007 As the case study illustrates, companies will o on be able to create fairly exhaustive, highly accurate pro? les of customers without having had any direct interaction with them. They’ll be able to get to know you intimately without your knowledge. From the consumer’s perspective, this trend raises several big concerns. In this ? ctional account, for instance, a shopper’s grocery purchases may directly in? uence the availability or price of her life or health insurance products—and not necessarily in a good way. Although the customer, at least tacitly, consented to the collection, use, and transfer of her purchase data, the real issue here is the nintended and uncontemplated use of the information (from the customer’s point of view). Most customers would probably be quite surprised to learn that their personal information could be used by companies in a wholly unrelated industry and in other ways that aren’t readily foreseeable. If consumers lose trust in ? rms that collect, analyze, and utilize their information, they will opt out of loyalty and other data-driven marketing programs, and we may see more regulations and limitations on data collection. Customer analytics are effective precisely because ? rms do not violate customer trust. People believe that retail and other organizations will use their data wisely to enhance their experiences, not to harm them. Angry customers will certainly speak with their wallets if that trust is violated. Decisions that might be made on the basis of the shared data represent another hazard for consumers—and for organizations. Take the insurance company’s use of the grocer’s loyalty card data. This is limited information at best and inaccurate at worst. The ShopSense data re? ect food bought but not necessarily consumed, and individuals buy food at many stores, not just one. IFA might end up drawing rroneous conclusions—and exacting unfair rate increases. The insurer’s general counsel should investigate this deal. Another concern for consumers is what I call â€Å"battered customer syndrome. † Market analytics allow companies to identify their best and worst customers and, consequently, to pay special attention to those deemed to be the mo st valuable. Looked at another way, analytics enable ? rms to understand how poorly they can treat individual or groups of customers before those people stop doing business with them. Unless you are in the top echelon of customers— those with the highest lifetime value, say—you ay pay higher prices, get fewer special offers, or receive less service than other consumers. Despite the fact that alienating 75% to 90% of customers may not be the best idea in the long run, many retailers have adopted this â€Å"top tier† approach to managing customer relationships. And many customers seem to be willing to live with it—perhaps with the unrealistic hope that they may reach the upper echelon and reap the ensuing bene? ts. Little research has been done on the negative consequences of using marketing approaches that discriminate against customer segments. Inevitably, however, customers will ecome savvier about analytics. They may become less tolerant and take their business (and information) elsewhere. If access to and use of customer data are to remain viable, organizations must come up with ways to address customers’ concerns about privacy. What, then, should IFA and ShopSense do? First and foremost, they need to let customers opt in to their data-sharing arrangement. This would address the â€Å"unintended use of data† problem; customers would understand exactly what was being done with their information. Even better, both ? rms would be engaging in trust-building—versus trust-eroding—activities with customers. The esult: improvement in the bottom line and in the customer experience. Katherine N. Lemon (kay. [email  protected] edu) is an associate professor of marketing at Boston College’s Carroll School of Management. Her expertise is in the areas of customer equity, customer management, and customer-based marketing strategy. page 7 T he Dark Side of Customer Analytics †¢ H BR C A SE S T UDY C ase Commentary by David Norton How can these companies leverage the customer data responsibly? Would customers feel comfortable with the data-sharing arrangement if they knew about it? page 8 Transparency is a critical component of any loyalty card program. The value proposition must be clear; customers must know what they’ll get for allowing their purchase behavior to be monitored. So the question for the CEOs of ShopSense and IFA is, Would customers feel comfortable with the data-sharing arrangement if they knew about it? ShopSense’s loyalty card data are at the center of this venture, but the grocer’s goal here is not to increase customer loyalty. The value of its relationship with IFA is solely ? nancial. The company should explore whether there are some customer data it should exclude from the transfer—information that could be perceived as exceedingly sensitive, such as pharmacy and lcohol purchases. It should also consider doing market research and risk modeling to evaluate customers’ potential reaction to the data sharing and the possible downstream effect of the deal. The risk of consumer backlash is lower for IFA than for ShopSense, given the information the insurance company already purchase s. IFA could even put a positive spin on the creation of new insurance products based on the ShopSense data. For instance, so-called healthy purchases might earn customers a discount on their standard insurance policies. The challenge for the insurer, however, is that there is no proven correlation between the urchase of certain foods and fewer health problems. IFA should continue experimenting with the data to determine their richness and predictive value. Some companies have more leeway than others to sell or trade customer lists. At Harrah’s, we have less than most because our customers may not want others to know about their gaming and leisure activities. We don’t sell information, and we don’t buy a lot of external data. Occasionally, we’ll buy demographic data to ? ne-tune our marketing messages (to some customers, an offer of tickets to a live performance might be more interesting than a dining discount, for example). But we think the internal transactional data are much more important. We do rely on analytics and models to help us understand existing customers and to encourage them to stick with us. About ten years ago, we created our Total Rewards program. Guests at our hotels and casinos register for a loyalty card by sharing the information on their driver’s license, such as their name, address, and date of birth. Each time they visit one of our 39 properties and use their card, they earn credits that can be used for food and merchandise. They also earn Tier Credits that give them higher status in the program and ake them eligible for differentiated service. With every visit, we get a read on our customers’ preferences—the types of games they play, the hotels and amenities they favor, and so on. Those details are stored in a central database. The company sets rules for what can be done with the information. For instance, managers at any one of our properties can execute th eir own marketing lists and programs, but they can target only customers who have visited their properties. If they want to dip into the overall customer base, they have to go through the central relationship-marketing group. Some of the information captured in ur online joint promotions is accessible to both Harrah’s and its business partners, but the promotions are clearly positioned as opt in. We tell customers the value proposition up front: Let us track your play at our properties, and we can help you enjoy the experience better with richer rewards and improved service. They understand exactly what we’re capturing, the rewards they’ll get, and what the company will do with the information. It’s a win-win for the company and for the customer. Companies engaging in customer analytics and related marketing initiatives need to keep â€Å"win-win† in mind when collecting and andling customer data. It’s not just about what the information can do for you; it’s about what you can do for the customer with the information. David Norton ([email  protected] com) is the senior vice president of relationship marketing at Harrah’s Entertainment, based in Las Vegas. harvard business review †¢ may 2007 T he Dark Side of Customer Analytics †¢ H BR C A SE S T UDY C ase Commentary by Michael B. McCallister How can these companies leverage the customer data responsibly? When the tougher, grayarea decisions need to be made, each person has to have the company’s core principles and values in ind. harvard business review †¢ may 2007 Companies that can capitalize on the information they get from their customers hold an advantage over rivals. But as the ? rms in the case study are realizing, there are also plenty of risks involved with using these data. Instead of pulling back the reins, organizations should be nudging customer analytics forward, keeping in mind one critical point: Any collection, anal ysis, and sharing of data must be conducted in a protected, permission-based environment. Humana provides health bene? t plans and related health services to more than 11 million embers nationwide. We use proprietary datamining and analytical capabilities to help guide consumers through the health maze. Like IFA, we ask our customers to share their personal and medical histories with us (the risky behaviors as well as the good habits) so we can acquaint them with programs and preventive services geared to their health status. Customer data come to us in many different ways. For instance, we offer complimentary health assessments in which plan members can take an interactive online survey designed to measure how well they’re taking care of themselves. We then suggest ways they can reduce their health risks or treat their existing conditions more effectively. We closely monitor our claims information and use it to reach out to people. In our Personal Nurse program, for example, we’ll have a registered nurse follow up with a member who has ? led, say, a diabetes-related claim. Through phone conversations and e-mails, the RN can help the plan member institute changes to improve his or her quality of life. All our programs require members to opt in if the data are going to be used in any way that would single a person out. Regardless of your industry, you have to start with that. One of the biggest problems in U. S. health care today is obesity. So would it be useful for our company to look at grocery-purchasing patterns, as the insurance company in the case study does? It might be. I could see the upside of using a grocer’s loyalty card data to develop a wellness-based incentive program for insurance customers. (We would try to ? nd a way to build positives into it, however, so customers would look at the interchange and say â€Å"That’s in my best interest; thank you. †) But Humana certainly wouldn’t enter into any kind of datatransfer arrangement without ensuring that our customers’ personal information and the ntegrity of our relationship with them would be properly protected. In health care, especially, this has to be the chief concern—above and beyond any patterns that might be revealed and the sort of competitive edge they might provide. We use a range of industry standard security measures, including encryptio n and ? rewalls, to protect our members’ privacy and medical information. Ethical behavior starts with the CEO, but it clearly can’t be managed by just one person. It’s important that everyone be reminded often about the principles and values that guide the organization. When business opportunities come along, they’ll be screened according to those standards—and the decisions will land right side up every time. I can’t tell people how to run their meetings or who should be at the table when the tougher, grayarea decisions need to be made, but whoever is there has to have those core principles and values in mind. The CEOs in the case study need to take the â€Å"front page† test: If the headline on the front page of the newspaper were reporting abuse of customer data (yours included), how would you react? If you wouldn’t want your personal data used in a certain way, chances are your customers wouldn’t, either. Michael B. McCallister ([email  protected] com) is the president and CEO of Humana, a health benefits company based in Louisville, Kentucky. Reprint R0705A Case only R0705X Commentary only R0705Z To order, call 800-988-0886 or 617-783-7500 or go to www. hbrreprints. org page 9 To Order For Harvard Business Review reprints and subscriptions, call 800-988-0886 or 617-783-7500. Go to www. hbrreprints. org For customized and quantity orders of Harvard Business Review article reprints, call 617-783-7626, or e-mail [email  protected] harvard. edu www. hbrreprints. org U. S. and Canada 800-988-0886 617-783-7500 617-783-7555 fax

External Influence on Ayam Brand

Reference groups have a high influence to the primary target audience, which are the housewives. The closest groups of people to housewives are the husbands and the children. Since housewives are the mothers for the children, they need to decide on which product of food or fruit to buy for their children for consumption. According to Gourmet Retailer (2008), mothers are concerned with feeding their little one the most nutritious diet possible. Thus, they sake the decision to purchase â€Å"Maya Brand† canned fruits because it contains no preservatives and MS (Maya brand, 2009). Maya Brand† also provides a large variety of fruits, which are mainly pineapple fruits, mixture of fruit cocktails like peach, pears, grapes, cherries and fruits snacks as well. Children are usually very fond of all these, because what children want Is different products throughout the time of consumption, and not the same or similar product over and over again. Social class is the hierarchical ca tegorization of people into distinct status classes, so hat members of each class share similar values, Interest and behavior (Chaffinch, et al. , 2008). Social class Is divided into upper class, middle class and lower class.It Is determined by a complex set of variables: household Income level, occupational prestige and educational achievement. Income directly affects ones attitude towards a particular purchase. For upper class people, they usually work in a big company, meaning they will have a busy working hours for almost everyday. Due to their occupation, they will not have time to shop for fresh fruits in the market. With once of health at the same time, they will purchase ‘Maya Brand' canned fruits as It's a very popular brand, with no preservatives and MS, and Is available In almost all convenient store or embitterment, Tort example, â€Å"Gallant Hypermarket†.Meanwhile, for the lower class people, they usually have a lower household income level. As ‘Maya Brand' canned fruits are cheap in price and it is value for money, they will choose to purchase it to satisfy basic needs. For instance, Gap, Ralph Lauren and United Colors of Benton understand how parents reflect the brand choices in the children's market (Koala, 2007). Parents especially are influential in apparel purchases because children are unable to pay for their own expenses of a purchase due to high cost. In addition, social group and peer influences are considered as the significant reference groups.Research shows as the age of a child increases, peers become more influential on apparel decision- making and not their parents anymore (Bridges & Burgess, 2010). Teens nowadays, make the purchase decision on their outfit, based on the interaction within the peer group. They enjoy making decision on themselves, while taking consideration into there friends' opinion (Grant and Stephan, 2006). 2. 2. 2 Social class that members of each class share similar values, interest and beh avior (Coffman, et al. , 2008). Social class is determined by a complex set of variables: household income level, occupational prestige and educational achievement.Income directly affects of ones attitude towards a particular purchase. Thus, the motivation of people in upper class is stronger in owning the latest fashion trends compared to the motivation of people in middle and lower social class (Peter & Olson, 1999), Upper lass people are concern on the body image and self-image whereas middle or lower class people tend to evaluate products in terms of functionality rather than the style of the garments. Higher social class associates clothing as wealth and luxury thus, they tend to dress in expensive and high in quality of apparels (See & Lee, 2008).Such high fashion retail store includes, Gucci and Airman Exchange. In the contrary, people in the lower class will consider whether the clothing is comfortable, reasonable in price whereas fashion trend is the least important aspect (Kennel, 1976). It) Message framing ii) advertising appeal Advertising can help companies develop consumers' awareness to an unmet need or introduce a product that consumers may see as valuable. This influence is often present when new products enter the market. Customer awareness is often low for these items until companies promote them and attempt to drive customer demand through advertising.Companies may also need to use advertising to stave off the popularity of a competitor's products in the economic market. This will result in advertisements that will influence consumers to change their buying behavior and witch products for specific reasons, such as cost or quality. (Vitae, 2010) â€Å"Maya Brand† advertise its' company on Faceable to enhance its' fame to the public as well as the people around the world. As Faceable is a social networking service. It allows â€Å"Maya Brand† to market Its prattle Ana products to lots AT networks . En AT ten advertising appealed used by â€Å"Maya Brand† is by organizing a ‘Community Care Campaign 201 1†², which one free canned food is given with Just one â€Å"like† button (Diagram 5. 1). Their mission is to provide donation of canned food to 40 charity home in 2 months. They have successfully supplied 3663 cans for the moment. In this case, its generosity will result in its brand name sinking in consumers' mind. As housewives are mothers of the children, they tend to be attracted to this brand as the campaign is helping the children who need strong support in terms of food.They understand how children will be without care. Besides, if â€Å"Maya Brand† can sponsor its products to so many charity homes, meaning its products have trusted quality. This is because if it does not have the required quality, it might spoil its own image by doing so. Thus, housewives or mothers will feel that â€Å"Maya Brand† is more trusted in terms of its quality. Www. Oho. Com For examp le, advertising on faceable. Read more: The Influence of Advertising on Consumer Buying Behavior I oho. Com http://www. Oho. Com/facts_6948058_influence-advertising-consumer-buying- behavior. HTML#sizzle Alfonzo behavior. HTML#sizzle Ladings ‘v) Humor in advertising. Www. allaboutmedicalsales. Com Some Definition of Humor in Advertising: ‘Humor' in the dictionary means a quality – being amusing or comic but in advertising it is serious business. In advertising, humor is more than Just making a munch of people laugh. Some of the best brands in India have leveraged humor to such an extent that the viewers look forward for newness in humor each time they see a new commercial from that brand. To illustrate, Officio has been one of those brands which have used humor so intelligently and subtly that it remains in people's minds.Here again one needs to closely view the product and the category before applying humor to sell your product. According to David Googol 30 per c ent of advertising is based on humor. Humor sells if used creatively with a strong idea and great execution. Claude Hopkins, the father of modern advertising had a different view on this. He was of the opinion that people don't buy from clowns. But in India over the last two decades humor has been drawing lot of attention for communicating a product. Also the conventional wisdom of thinking among our people is that when you buy products it should deliver some value and benefits.These could be nutritious for a health beverage, labor saving for a washing machine or a dishwasher. Humor in the dictionary means a quality of being amusing or comic but in advertising it is serious business. In advertising, humor is more than lust making a Duncan AT people laugh. Humor tenant a strong idea and great execution. (.NET. COM) Using Humor In Advertising Advertising Is Not A Funny Business s uses creatively Walt First, a warning. Professional Advertising does not recommend that you use humor in y our advertising. A lot of people simply don't have a sense of humor.You lose them immediately, and the potential size of your market shrinks. And humor is in the eye of the beholder. It is commonly misinterpreted. Many people will not get the Joke. Your market size Just shrunk again. And humor often insults someone. They may simply get angry because they don't get the Joke. This is fire we are playing with. Your market Just shrunk again. Is it worth the risk? Laugh Out Loud – Advertising Humor Yes, humor in advertising is risky. It can also be devastatingly effective. When done right, humor works – really, really well. Advertising is about getting attention.The best ways to get attention with advertising are with strong visuals, sex, powerful headlines, and humor. Let's look at how to use [or not use] humor in advertising. Advertising humor is wonderful for getting attention. As you look at some of our ample ads, we hope you get a good idea of what we mean. Advertising humor can be extraordinarily effective when it is used correctly. People will actually look for your ads, and talk about them if they are good. But there are rules about using humor in advertising to represent your company, and following them is probably a good idea. First, people like funny things.They relax and pay attention when they know you have a sense of humor. It puts them in a good mood, and it creates a more comfortable atmosphere and a more positive image for your company. It makes you easy to approach, and easy to remember. Advertising humor works best with established and commonly purchased products. Humor in advertising works for business services, familiar items, and products we all know. But corporate image and industrial advertising are serious business. Unknown, KY, expensive, or sensitive products are not normally salute to ten lighter toucan AT advertising humor.Advertising humor also needs to be well suited to its audience. If your customers don't get the Joke, then the Joke will be on you. A sophisticated audience will understand your irony, satire, and puns, but a young audience may only understand lipstick comedy or a silly cartoon caricature. Inside Jokes can be effective if the recipient understands that it was done for them, but nobody else will get it. And advertising humor can backfire. If you make a Joke at the expense of any one group, you will surely alienate them.Everyone loved the â€Å"Where's the Beef† commercials done by Wendy – everyone, that is, except the senior citizens who did not like being portrayed as grumpy old people. Advertising humor also needs to be product specific. We have all seen funny ads we liked so much that we forgot what was being sold. Advertising humor must relate erectly to your business or products if you want to be remembered. And advertising humor has a relatively short life. The first time we see it we may laugh out loud. But after a while, although we still may smile at the Joke, it's not so funny any more. Funny ads need to be replaced periodically.Will advertising humor work in your ads? Absolutely – if you can make it appropriate to your products and customers, if they understand it, if it is related to your business or message, and if you change your ads frequently enough so that they don't wear out. K, here's the punch line. Advertising humor definitely gets attention. And if your ads don't get attention first, they will be anything but funny. But when done right, advertising humor can send your ads light years ahead of the competition, and that's what Professional Advertising is all about. Www. myprofessionaladvertising . Mom Power of humor in advertising V Sympathy, GM 20:20 Media The role of humor dates back to many years when all of us used to view films like the Charlie Chaplin, Laurel and Hardy. These actors and characters really made all of us laugh when we sat and watched their movies. Even all our Hindi and regional ivies in India alway s had a comedian to play a very important role and provide the movie a touch of humor to give the audience some fun and Joy. Every Hindi movie had an actor like Method, Seepage, Devon Versa or an Saran who played a very important role in making the movie entertaining and thrilling.The same strategy is used by many advertisers in India into their advertising to get noticed and stand out in the clutter with memorable humor which remains sticky in ten blower's Milan. In Tact news papers Like ten Limes AT IANAL nave made every reader smile early morning with R. K. Legman's cartoon. Even individual personality or celebrities try and use humor to position themselves differently in the people's minds. One such example that is top of mind is our Railway Minister Aloe Parkas Hydra. His witty and funny speeches and replies have positioned him differently amongst other politicians.So humor as a tool has been a strong weapon for many brands to draw the customers' attention. Different view on th is. He was of the opinion that people don't buy from clowns. But or a dishwasher. Role of Humor: With more and more channels mushrooming, clutter has become a significant problem for most brands. Hence to beat the clutter and break the ice, humor has been used by many brands to answer the problem. Over a period of time humor has been proved to be one of the best techniques to keep the customer laughing and grab his attention with some sticky and creative idea.The proof of the pudding for any humor based on advertising remains in forcing the audience watch, laugh and most importantly is able to recall the brand easily. Brands must ensure that if they are using humor to sell a product then the connect and the equity of the brand should not be diluted. According to some research humorous ads are recalled fast ND easily and it also elevates the consumer's happiness and mood. Finally humor captures the viewer's attention, cuts through the ad clutter and enhances recall. If not crafted pr operly humor can also backfire at times.Product and Brand connect: It sometimes so happens that a Joke in an advertisement is so powerful that the consumer tends to forget the brand. Hence it is important that there should be a strong connect between the product and the humor that you are trying to convey. The Pizza world ad showing a hosepipe being used to cool off someone who Just had a spicy plaza Is a good Ana relevant example wanly connects Walt ten Drain Ana really communicates that when you ask for a spicy pizza we deliver it with full pride. Understanding the nuances of the brand and the audience is very important.Overindulgence of humor can put down the audience and the brand if not executed in the right taste. The Maul undergarments ads which tried to use humor and sex to sell their brand never went off well with many consumers. The brand did get some publicity due to controversy but did not win the hearts of the target audience. Hence it is important to base your Joke on the core values of the product and the service proposition the brand is offering. No product connect means no effectiveness. All these results in huge wastage of the marketing budget.Types of Humor in advertising: Using a comedian: Here instead of building humor in the advertising one can use a comedian actor to promote the brand. One's choice of comedian has to match the values of the brand. One of the most memorable advertisements that have used a comedian well has been Charlie Chaplin for Cherry Blossom shoe polish. The most recent one in this space using an Indian comedian which has been noticeable and successful is Domino's Pizza which has plugged in Parses Rival very cleverly. Capitalizing on the current topics : Use the current hot topic in all walks of life which is funny, sticky, memorable and controversial.Maul Butter has been doing these for several years. The advertising deployed has been very humorous and are always based on the current topics with a tongue-in-cheek app roach. People never get fatigued watching the Maul ads. People eagerly wait for what Maul Butter outdoor campaigns by constantly looking at the prime hoarding points where Maul butter is visible. Strong idea based humor: Here the strong creative idea is carefully blended with subtle humor. The case in example is Officio. The powerful idea with humor helps in beating the clutter.Centre Shock electric gum is another good example where a strong advertising idea (Idea sprung up from the product) with the help of humor helped in translating into a great piece of campaign. Saint Goblin glass is another wonderful example of how humor has been used subtly. The restaurant advertisement (where the water is thrown) created by the company is so refreshing that one never gets bored of viewing it. Using the right type humor in advertising will be determined by clearly defining your objectives and positioning of your product.This, supported with a strong idea ill further help you to create good ad vertising which can be sticky and memorable for a long time. Humor will help if it is relevant: Mostly humor is used in products which is low in investment and which has high impulse purchase. (Candy, beer and mosquito repellents). One cannot totally generalize this, as consumer durable products have also used humor effectively. Humor may not work in category like condoms, sanitary napkins as tense products need to explain ten Detentes AT ten product more clearly. Similarly cars and diamonds may also not use humor as the decision process to purchase is long.Finally we need to remember that humorous campaigns are difficult to design and create. Over exaggeration of humor may have negative effect on the brand. People may remember the Joke but not the message and the brand. It can upset individuals if not done tastefully. Products can also flop and brand equity may erode. While humor is a strong and interesting route to create a great advertising campaign, one must also keep in mind th at the imagery, core values of the brand and the positioning does not deviate. If your positioning is perfect then humor with a great idea can do wonders for the brand. Www. .NET. Com