8.5 Market Knowledge Systems Charting a Path toward Competitive Advantage



  1. ^ Example : Nine West Retail Stores
  2. ^ Godzila Report
  3. ^ What information
  4. ^ What regular marketing decisions
  5. ^ what data
  6. ^ who needs to know ?
  7. ^ when they need to know ?
  8. ^ what sequence and what aggregation level

[1] Example : Nine West Retail Stores

Every Monday morning, each retail director at the headquarters of Nine West Retail Stores, a leading operator of shoe specialty stores, receives the [2] ‘Godzilla Report,’ a tabulation of detailed sales and inventory information about the fastest-selling items in Nine West stores from the prior week.
By style and colour, each director learns which items in his or her stores are selling fast and need to be reordered.

A similar report provides information about all other styles currently in Nine West’s stores, so that slow sellers can be marked down or transferred to stores where those styles are in higher demand.

Additional reports aggregate sales information by style and colour; by merchandise category (e.g., dress or casual); store, area, or region; and for various time periods.

The information provided by these reports constitutes the backbone of Nine West’s decision making about which shoes to offer in which of its stores. Imagine how much more difficult the retail director’s job would be without today’s point-of-sale systems to collect and report such data! Imagine the potential advantage Nine West has over shoe retailers who lack such information.

Nine West retail directors need to know which styles and colours are selling, in which stores, at what rate.
Wal-Mart believes its key suppliers need to know its store-by-store item and category sales data, so it provides password-protected online access to such data to those suppliers.
Telemarketers need to know which callers are producing sales, at what times of day, for which products. Marketers of kitchen gadgets through infomercials on late-night television need to know which ads on which stations in which cities are performing, in order to place media dollars where they will be most productive. Companies selling their wares to industrial markets through outside salesforces need to know not only which products are selling to which customers but also which salespeople are selling how much, at what margins and expense rates, to whom. The salesforce, too, needs information about status of current orders, customer purchasing history, and so on. For

Every marketer, not just retailers, needs information about ‘what’s hot, what’s not.’

Unfortunately, accounting systems generally do not collect such data.

Typically, such systems just track revenue, with no information about which goods or services were sold.

Thus, marketers need
internal records systems to track what is selling, how fast, in which locations, to which customers, and so on.

Providing input on the design of such systems so that the right data are provided to the right people at the right time is a critical marketing responsibility in any company, and we address this issue in considerable detail in
Module 19.

But what constitutes critical marketing information varies from company to company and industry to industry.

For those charged with developing or updating internal record systems in their companies, we provide, in
Exhibit 8.5, a series of questions to help marketing decision makers specify what internally generated sales data are needed, when, for whom, in what sequence, at what level of aggregation.

Questions to ask
Implications for a chain footwear retailer
Implications for an infomercial marketer of kitchen gadgets
[3] What information is key to providing ourcustomers with what they want?
Need to know which shoes sell, in which stores and markets, at what rate
Need to know which gadgets sell, in what markets, at what rate
[4] What regular marketing decisions are critical to our profitability?
Decide which shoes and shoe categories to buy more of, which to buy less of or get rid of, in which stores and markets to sell them
Decide on which specific TV stations, programmes, and times of day to place infomercials for which gadgets
[5] What data are critical to managing profitability?
Inventory turnover and gross margin
Contribution margin (gross margin less media cost) per gadget sold
[6] Who needs to know?
Buyers and managers of merchandise categories
Media buyers, product managers
[7] When do they need to know, for competitive advantage?
For hottest sellers, need to know before competitors, to beat them to the reorder market. For dogs, need to know weekly, to mark them down.
Need to know daily, for prior night’s ads, to reallocate media dollars
[8] In what sequence and at what level of aggregationshould data be reported?
Sequence of report: hot sellers first, in order of inventory turnover
Sequence of report: hot stations/programmes first, in order of contribution margin per gadget sold

Aggregation: by style and colour for buyers, by category for merchandise managers
Aggregation: By stations/programmes for media buyers, by gadget for product managers

  1. client contact systems
  2. collector bias
  3. competitive advantage
  4. competitive intelligence
  5. computerised reorder system
  6. consumer behaviour
  7. data sources
  8. evidence based forecast
  9. experienced user
  10. internal records
  11. just in time
  12. logistical alliance
  13. market potential
  14. market segmentation
  15. market segments
  16. marketing program
  17. marketing research
  18. mass market
  19. mass market strategy
  20. michelin; us west;
  21. micro segmentation
  22. middleman
  23. modified rebuy
  24. multi-functional sales teams
  25. multilevel selling
  26. multiple buying
  27. multiple level relationships
  28. mutual trust
  29. narrow market segment
  30. narrow niche
  31. nationalisation of producers
  32. nerve center
  33. new task buy
  34. nine west group
  35. observation;direct observation' tanzania mobile;
  36. on-time delivery
  37. opportunity; research
  38. order handling
  39. organisation market
  40. organization marketing behaviour
  41. organizational behaviour
  42. organizational customers
  43. organizational demand
  44. organizational market
  45. organizational purchasing behaviour
  46. organizational purchasing process
  47. paperless exchange
  48. parity pricing
  49. personal selling
  50. personal use
  51. political risk
  52. potential market; penetrated market
  53. pre-delivery inspection
  54. pre-sale service
  55. prestige buyer
  56. pretender
  57. primary data
  58. procurement costs
  59. purchasing criteria
  60. qualitative data
  61. qualitative research
  62. quality assurance
  63. quality standards
  64. quantitative data
  65. quantitative research
  66. research objectives
  67. retention programme
  68. routine purchase
  69. sales forecast
  70. semantic differentiation scale
  71. sequence of information
  72. shared costs
  73. short term contracts
  74. social construction
  75. status oriented consumers
  76. stock availability
  77. straight rebuy
  78. supplier bargaining power
  79. supplier performance
  80. supplier reputation
  81. survey
  82. tabulation errors
  83. tanzania mobile
  84. target customers
  85. target market
  86. target marketing
  87. technical experts;
  88. test markets
  89. transaction cost
  90. trend forecasting
  91. trusting patron
  92. underlying consumer demand
  93. unethical demands
  94. unstated but implicit assumptions
  95. users
  96. value analysis
  97. value shopper
  98. vertical integration
  99. visceral thing that cannot be trained
  100. wild guess