Select your font size 
 
about us products & services consulting & support news & events contact us
Volume merchants use data-mining techniques to get the upper hand in client and supply chain management. New technologies have the potential to level the playing field for consumers.

Data-Mining for Transaction Patterns - Minnesota

print this article 
 

High-volume merchants, including Walmart, Safeway, Save-on Foods, and others, have already implemented programs to learn more about their clients. Each transaction is stored in a database, where each client should have a unique number. Client participation is encouraged by providing benefits such as lower prices or better credit terms.

Initial, fairly innocuous, applications for the resultant data sets included optimizing the supply chain by arranging for lower inventories, automatically creating purchase orders for just-in-time (JIT) delivery of merchandise, tracking and managing spoilage, and maintaining year-to-year performance statistics.

More controversial applications have included measuring and reacting to the profitability or transaction patterns (favourable or otherwise) of clients. In other words, just as large, nationally regulated, databases are maintained to keep track of credit relationships between lenders and borrowers, which are now used by lenders to grant preference to more profitable and/or less risky borrowers, retailers and high-volume merchants are applying private and mostly unregulated databases to ordinary transactions such as purchases and returns of merchandise.

Several of the methods used by high-volume merchants to maintain customer data lack the property of being able to uniquely identify the client responsible for a transaction. For example, some vendors allow clients to use telephone numbers to get better prices, since it is easier to give a telephone number than to carry a special card. These systems, while sufficient for understanding broad trends and usage patterns, are insufficient for any true accountability, because the telephone number can be guessed easily, and there is no verification that the person making the purchase actually owns that telephone number. Such a system would not be a good candidate for the kind of industry-wide information sharing used in the credit industry.

Kroger stores in North America, and the METRO Group chain of grocery stores in Germany, are two examples of businesses which now use biometric data such as fingerprints to uniquely identify their customers. By taking this step, and acquiring appropriate permissions from their clients, grocery store chains could truly realize the benefits of sharing customer data.

And what are these benefits, one might ask? For instance, the best clients could easily be identified, and better purchase terms (prices, availability, or credit terms) could be offered to these clients. Conversely, clients with unprofitable transaction patterns could also be identified and discouraged from engaging in these patterns. For instance, customers who only purchase loss-leaders, or who routinely purchase clothing only to return the clothing a few weeks later.

Based on the above, it is easy to see that from the consumer point of view, the merchants who are maintaining databases against them seem to have several unfair advantages:

  1. Access to information in database format. This enables the merchants to discern patterns that are not easy to detect when the information is scattered.
  2. Lack of effective regulation that ensures that the information is accurate. Despite privacy laws such as PIPEDA in Canada, it is very difficult to keep track of all of the databases being maintained by merchants, and it may be economically impractical to conduct detailed audits, even of individual accounts.
  3. Merchants have an up-to-date transaction database spanning a large set of clients, but clients would not have a similar kind of database spanning a large set of merchants.

Most Recent Website and Regional Updates

 Research Tools
Measure human resource allocation and collect data with the goal of determining patterns that will bring forward actionable insights which may lead to policy changes, saving money and improving quality of service.

 
 Process Evaluation Questions
Questions to help focus discussion about process improvement

 

Google
 
Web transparen.com

Contact Information

Related Information

Home Buyers Find Attractive Low Interest Mortgage Options
Tens of thousands of dollars can be saved by making use of the mortgage broker industry's leverage. Better rates mean debt can be paid back faster, and mortgages eliminated sooner.
Market-Based Decision Making - Aggregating Good Judgement
Internal stock exchanges may provide key feedback about the relative values of already-identified strategic options by 'automatically promoting' those who exercise good judgement.
Canadian Stocks - Early Research
Early research into Canadian small-cap stocks may reveal companies with solid fundamental growth ratios that are currently under valued in the market.
Researching Canadian Stocks
Conducting unbiased research into Canadian stock performance relative to industry averages can uncover unfairly low valuations likely to yield profitable future stock trades.
Choosing a Discount Brokerage
Stock traders demand speed, risk management, strategy, buying power, information inflows and outflows, a low fee structure, and access from their discount brokerage firms.
News
Updates on the latest developments at Transparen.
Industries - Overview
Transparen's consulting services are useful across a wide number of industries.
XBRL Can Lead to Better Financial Research Insights
Discussion about XBRL - eXtensible Business Reporting Language - with a high-level overview.
   
 
E C M | © 2003-2007 Transparen Corp.      

Standardized Services: Data Recovery Service / Creative Services / Premium Web Hosting Services / System Administration Tech Support Services
Recent Projects: Full-Service Mortgage and Financing Company / System to manage flights from Vancouver to Tofino / Photo exchange verification service
Our Vancouver BC Server Proudly Hosts: automated parking and revenue control systems, leafside lane at southlands, cost effective alternative power sources, Higher Grade Learning Centres, pacific forage bag supply, sunburst medical, neosonic design, roger mahler photography - passionate, intriguing, desirable, the connection between east and west, affordable flights to victoria and tofino, low interest mortgage brokers in vancouver, richmond, surrey, toronto, Toronto Calgary and Vancouver IT staffing and talent search
* Ada * Adams * Adrian * Afton * Aitkin * Akeley * Albany * Alberta * Albert Lea * Albertville * Alden * Aldrich * Alexandria * Alpha * Altura * Alvarado * Amboy * Andover * Annandale * Anoka * Appleton * Apple Valley * Arco * Arden Hills * Argyle * Arlington * Ashby * Askov * Atwater * Audubon * Aurora * Austin * Avoca * Avon * Babbitt * Backus * Badger * Bagley * Balaton * Barnesville * Barnum * Barrett * Barry * Battle Lake * Baudette * Baxter * Bayport * Beardsley * Beaver Bay * Beaver Creek * Becker * Bejou * Belgrade * Bellechester * Belle Plaine * Bellingham * Beltrami * Belview * Bemidji * Bena * Benson * Bertha * Bethel * Bigelow * Big Falls * Bigfork * Big Lake * Bingham Lake * Birchwood Village * Bird Island * Biscay * Biwabik * Blackduck * Blaine * Blomkest * Blooming Prairie * Bloomington * Blue Earth * Bluffton * Bock * Borup * Bovey * Bowlus * Boyd * Boy River * Braham * Brainerd * Brandon * Breckenridge * Breezy Point * Brewster * Bricelyn * Brooklyn Center * Brooklyn Park * Brook Park * Brooks * Brookston * Brooten * Browerville * Brownsdale * Browns Valley * Brownsville * Brownton * Bruno * Buckman * Buffalo * Buffalo Lake * Buhl * Burnsville * Burtrum * Butterfield * Byron * Caledonia * Callaway * Calumet * Cambridge * Campbell * Canby * Cannon Falls * Canton * Carlos * Carlton * Carver * Cass Lake * Cedar Mills * Center City * Centerville * Ceylon * Champlin * Chandler * Chanhassen * Chaska * Chatfield * Chickamaw Beach * Chisago City * Chisholm * Chokio * Circle Pines * Clara City * Claremont * Clarissa * Clarkfield * Clarks Grove * Clearbrook * Clear Lake * Clearwater * Clements * Cleveland * Climax * Clinton * Clitherall * Clontarf * Cloquet * Coates * Cobden * Cohasset * Cokato * Cold Spring * Coleraine * Cologne * Columbia Heights * Comfrey * Comstock * Conger * Cook * Coon Rapids * Corcoran * Correll * Cosmos * Cottage Grove * Cottonwood * Courtland * Cromwell * Crookston * Crosby * Crosslake * Crystal * Currie * Cuyuna * Cyrus * Dakota * Dalton * Danube * Danvers * Darfur * Darwin * Dassel * Dawson * Dayton * Deephaven * Deer Creek * Deer River * Deerwood * De Graff * Delano * Delavan * Delhi * Dellwood * Denham * Dennison * Dent * Detroit Lakes * Dexter * Dilworth * Dodge Center * Donaldson * Donnelly * Doran * Dover * Dovray * Duluth * Dumont * Dundas * Dundee * Dunnell * Eagan * Eagle Bend * Eagle Lake * East Bethel * East Grand Forks * East Gull Lake * Easton * Echo * Eden Prairie * Eden Valley * Edgerton * Edina * Effie * Eitzen * Elba * Elbow Lake * Elgin * Elizabeth * Elko * Elk River * Elkton * Ellendale * Ellsworth * Elmdale * Elmore * Elrosa * Ely * Elysian * Emily * Emmons * Erhard * Erskine * Evan * Evansville * Eveleth * Excelsior * Eyota * Fairfax * Fairmont * Falcon Heights * Faribault * Farmington * Farwell * Federal Dam * Felton * Fergus Falls * Fertile * Fifty Lakes * Finlayson * Fisher * Flensburg * Floodwood * Florence * Foley * Forada * Forest Lake * Foreston * Fort Ripley * Fosston * Fountain * Foxhome * Franklin * Frazee * Freeborn * Freeport * Fridley * Frost * Fulda * Funkley * Garfield * Garrison * Garvin * Gary * Gaylord * Gem Lake * Geneva * Genola * Georgetown * Ghent * Gibbon * Gilbert * Gilman * Glencoe * Glenville * Glenwood * Glyndon * Golden Valley * Gonvick * Goodhue * Goodridge * Good Thunder * Goodview * Graceville * Granada * Grand Marais * Grand Meadow * Grand Rapids * Granite Falls * Grant * Grasston * Greenbush * Greenfield * Green Isle * Greenwald * Greenwood * Grey Eagle * Grove City * Grygla * Gully * Hackensack * Hadley * Hallock * Halma * Halstad * Hamburg * Ham Lake * Hammond * Hampton * Hancock * Hanley Falls * Hanover * Hanska * Harding * Hardwick * Harmony * Harris * Hartland * Hastings * Hatfield * Hawley * Hayfield * Hayward * Hazel Run * Hector * Heidelberg * Henderson * Hendricks * Hendrum * Henning * Henriette * Herman * Hermantown * Heron Lake * Hewitt * Hibbing * Hill City * Hillman * Hills * Hilltop * Hinckley * Hitterdal * Hoffman * Hokah * Holdingford * Holland * Hollandale * Holloway * Holt * Hopkins * Houston * Howard Lake * Hoyt Lakes * Hugo * Humboldt * Hutchinson * Ihlen * Independence * International Falls * Inver Grove Heights * Iona * Iron Junction * Ironton * Isanti * Isle * Ivanhoe * Jackson * Janesville * Jasper * Jeffers * Jenkins * Johnson * Jordan * Kandiyohi * Karlstad * Kasota * Kasson * Keewatin * Kelliher * Kellogg * Kennedy * Kenneth * Kensington * Kent * Kenyon * Kerkhoven * Kerrick * Kettle River * Kiester * Kilkenny * Kimball * Kinbrae * Kingston * Kinney * La Crescent * Lafayette * Lake Benton * Lake Bronson * Lake City * Lake Crystal * Lake Elmo * Lakefield * Lake Henry * Lakeland * Lakeland Shores * Lake Lillian * Lake Park * Lake St. Croix Beach * Lake Shore * Lakeville * Lake Wilson * Lamberton * Lancaster * Landfall * Lanesboro * Laporte * La Prairie * La Salle * Lastrup * Lauderdale * Le Center * Lengby * Leonard * Leonidas * Le Roy * Lester Prairie * Le Sueur * Lewiston * Lewisville * Lexington * Lilydale * Lindstrom * Lino Lakes * Lismore * Litchfield * Little Canada * Little Falls * Littlefork * Long Beach * Long Lake * Long Prairie * Longville * Lonsdale * Loretto * Louisburg * Lowry * Lucan * Luverne * Lyle * Lynd * Mabel * McGrath * McGregor * McIntosh * McKinley * Madelia * Madison * Madison Lake * Magnolia * Mahnomen * Mahtomedi * Manchester * Manhattan Beach * Mankato * Mantorville * Maple Grove * Maple Lake * Maple Plain * Mapleton * Mapleview * Maplewood * Marble * Marietta * Marine on St. Croix * Marshall * Mayer * Maynard * Mazeppa * Meadowlands * Medford * Medicine Lake * Medina * Meire Grove * Melrose * Menahga * Mendota * Mendota Heights * Mentor * Middle River * Miesville * Milaca * Milan * Millerville * Millville * Milroy * Miltona * Minneapolis * Minneiska * Minneota * Minnesota City * Minnesota Lake * Minnetonka * Minnetonka Beach * Minnetrista * Mizpah * Montevideo * Montgomery * Monticello * Montrose * Moorhead * Moose Lake * Mora * Morgan * Morris * Morristown * Morton * Motley * Mound * Mounds View * Mountain Iron * Mountain Lake * Murdock * Myrtle * Nashua * Nashwauk * Nassau * Nelson * Nerstrand * Nevis * New Auburn * New Brighton * Newfolden * New Germany * New Hope * New London * New Market * New Munich * Newport * New Prague * New Richland * New Trier * New Ulm * New York Mills * Nicollet * Nielsville * Nimrod * Nisswa * Norcross * North Branch * Northfield * North Mankato * North Oaks * Northome * Northrop * North St. Paul * Norwood Young America * Oakdale * Oak Grove * Oak Park Heights * Odessa * Odin * Ogema * Ogilvie * Okabena * Oklee * Olivia * Onamia * Ormsby * Orono * Oronoco * Orr * Ortonville * Osakis * Oslo * Osseo * Ostrander * Otsego * Ottertail * Owatonna * Palisade * Parkers Prairie * Park Rapids * Paynesville * Pease * Pelican Rapids * Pemberton * Pennock * Pequot Lakes * Perham * Perley * Peterson * Pierz * Pillager * Pine City * Pine Island * Pine River * Pine Springs * Pipestone * Plainview * Plato * Pleasant Lake * Plummer * Plymouth * Porter * Pratt * Preston * Princeton * Prinsburg * Prior Lake * Proctor * Quamba * Racine * Ramsey * Randall * Randolph * Ranier * Raymond * Red Lake Falls * Red Wing * Redwood Falls * Regal * Remer * Renville * Revere * Rice * Richfield * Richmond * Richville * Riverton * Robbinsdale * Rochester * Rock Creek * Rockford * Rockville * Rogers * Rollingstone * Ronneby * Roosevelt * Roscoe * Roseau * Rose Creek * Rosemount * Roseville * Rothsay * Round Lake * Royalton * Rush City * Rushford * Rushford Village * Rushmore * Russell * Ruthton * Rutledge * Sabin * Sacred Heart * St. Anthony * St. Anthony * St. Augusta * St. Bonifacius * St. Charles * St. Clair * St. Cloud * St. Francis * St. Hilaire * St. James * St. Joseph * St. Leo * St. Louis Park * St. Martin * St. Marys Point * St. Michael * St. Paul * St. Paul Park * St. Peter * St. Rosa * St. Stephen * St. Vincent * Sanborn * Sandstone * Sargeant * Sartell * Sauk Centre * Sauk Rapids * Savage * Scanlon * Seaforth * Sebeka * Sedan * Shafer * Shakopee * Shelly * Sherburn * Shevlin * Shoreview * Shorewood * Silver Bay * Silver Lake * Skyline * Slayton * Sleepy Eye * Sobieski * Solway * South Haven * South St. Paul * Spicer * Springfield * Spring Grove * Spring Hill * Spring Lake Park * Spring Park * Spring Valley * Squaw Lake * Stacy * Staples * Starbuck * Steen * Stephen * Stewart * Stewartville * Stillwater * Stockton * Storden * Strandquist * Strathcona * Sturgeon Lake * Sunburg * Sunfish Lake * Swanville * Taconite * Tamarack * Taopi * Taunton * Taylors Falls * Tenney * Tenstrike * Thief River Falls * Thomson * Tintah * Tonka Bay * Tower * Tracy * Trail * Trimont * Trommald * Trosky * Truman * Turtle River * Twin Lakes * Twin Valley * Two Harbors * Tyler * Ulen * Underwood * Upsala * Urbank * Utica * Vadnais Heights * Vergas * Vermillion * Verndale * Vernon Center * Vesta * Victoria * Viking * Villard * Vining * Virginia * Wabasha * Wabasso * Waconia * Wadena * Wahkon * Waite Park * Waldorf * Walker * Walnut Grove * Walters * Waltham * Wanamingo * Wanda * Warba * Warren * Warroad * Waseca * Watertown * Waterville * Watkins * Watson * Waubun * Waverly * Wayzata * Welcome * Wells * Wendell * Westbrook * West Concord * Westport * West St. Paul * West Union * Whalan * Wheaton * White Bear Lake * Wilder * Willernie * Williams * Willmar * Willow River * Wilmont * Wilton * Windom * Winger * Winnebago * Winona * Winsted * Winthrop * Winton * Wolf Lake * Wolverton * Woodbury * Wood Lake * Woodland * Woodstock * Worthington * Wrenshall * Wright * Wykoff * Wyoming * Zemple * Zimmerman * Zumbro Falls * Zumbrota