Do terms like “data mining” and “data warehousing” seem both trendy and impersonal, as though you have just walked into a technological maze built by cybernetic engineers and still-wet-behind-the-ears marketing types? Would you feel better with the phrase “up to date methods for analyzing information about your customers and what they want in order to better serve their needs and increase your profits”?
There is really no chasm separating the terms in the first question from the successful store manager and delighted customer in the latter. While you may not use or particularly like the term “data mining,” you do it whenever you hone your strategies to detect patterns in your strategies to detect patterns in your customer data. If you do, however like the idea of wringing all the use possible out of your hard earned information, dig in! Data mining is a gold mine.
Data mining is simply analysis of information about your customers. Different sources insist that the analysis has to take place with different technologies – theirs, of course. What they all do is extract small, precise bits of information out of the glut of data that is generated in today’s business world.
Gregory Bateson, a leading thinker and information theorist of the 19th Century, defined information as “any difference that makes a difference.” Data mining allows us, through the use of new technologies, to see differences that previously would have gone unrecognized. It is partially using an ever more finely grained mesh to filter customer data, but it is far more than simply increasing the level of detail. The technology winnows out, highlights and enables the use of information that would be inaccessible through other means.
The past decade, with its burgeoning growth of Internet and Web access and powerful, low cost desk and laptop computers, has paved the way for even small retailers to precisely process their customer data and engage in targeted marketing.
It’s okay to mine your data
Waine Rodrigues president of POS Solutions in Millersville, MD., a company that helps museum stores set up data mining and customer intelligence operations, stresses that data mining is not akin to mass mailings sorted by income level and zip code. Mining allows managers to target specific preferred customers interested in museum stores’ unique offerings.
Kare Anderson, retail expert (and closing keynote speaker of MSA’s 46th Annual Meeting & Expo), also says that appropriate use of data mining allows stores to move from “dime store displays” where merchandise is organized by category, to display focused on their targeted customers’ situational needs and even extremely personalized targeting.
Tightly focused use of customer data helps retailers maximize sales by stocking and cross selling the right merchandise. This can be accomplished anonymously through large aggregates of data or through tracking individual customer behavior.
By mining data on large amounts of historical data, a store manager might find that sales of hardcover art books selling for $40 to $60 increases by a factor of three when galleries are housing international travel exhibits by women painters. Or the same manager could send out personalized announcements letting the best customers know that pieces from a favorite potter will be put out for display and sale starting the next Monday. You can as high tech or low tech, as impersonal or an individualized as you, the manager, are comfortable with and want to be.
Anderson routinely reassures retailers that although personalized data manipulation might seem invasive of your customers’ privacy, it isn’t if you clearly state what benefit the customer will gain by opting in participation in your “Buyers Club” or your “Elite Service Program.” Benefits might include allowing them to be the first to have access to new merchandise, to win randomly drawn monthly raffles and to be pricy to offsite merchandise that may never make it to your limited display space.
To outsource or go it alone
The primary approaches to data mining are outsourcing or building your own in-house system. These two strategies have a variety of implementation tactics. Completely outsourced data warehousing and mining comprise one end of this continuum. In-house created customer intelligence systems reside at the other end of the spectrum and may be composed of no more than your inventory printouts, a fax machine and your e-mail program. In between are many options with various degrees of equipment and software ownership and with various types of service contracts.
In the totally outsourced approach, a computer program sends encrypted sales and customer information collected during the day to a data-mining vendor. The vendor produces a targeted, easily interpreted report, which is usually e-mailed to the museum director or store manager by the next morning.
Companies like digiMine, started by data mining veteran Dr. Usama Fayyad, Ph.D., serve the information needs of retail companies that don’t want to purchase equipment or constantly train in new versions of software and simply ship out the data. These firms deliver reports at regularly scheduled intervals, usually daily, to you or your retail managers desktop e-mail basket.
At the other end of the spectrum are in-house data collection systems. Anderson points out that such home frown data mining systems might only include a PC with-mail, a simple package of statistical software and simple, preprinted forms (with the standard promise of the store and museum to never sell or share any members information). The customer can fill out the form and return it to receive an opt-in marketing newsletter and sale notices.
As the elite group of customers who are the bread and butter of museum retail sales shift into the world of “clicks and mortar,” managers much, as Anderson say, “Have the goal to reach them (customers) wherever they might be.”
She also advises museum stores with limited space to use targeted data practices to sell to established customers who already know what they want without using up valuable display space. Stores can do this by displaying one object and sending daily orders to a direct manufacturer who has agreed to ship the merchandise with your logo sticker attached within 24 hours. Payment of an agreed upon percentage is then sent to the manufacturer monthly.
This is just part of the emerging change in retail, according to Anderson. To stay competitive you need to make use of all resources available to you, even those you may not know about yet, to maximize profit and reduce overhead.
Using the golden data
So how do you build that big, loyal and profitable constituency? After you have identified how you will collect data, the next step, according to Anderson, is to “build your database and know what they want. Treat your top 10 percent like gold.” She reminds us that, once fully integrated, you may reasonably expect the top 10 percent of you customer base to produce 60 to 65 percent of your profits.
Obviously the scale of your operations will somewhat constrain your implementation strategy. A large museum retail business already engaged in extensive data collection with both physical and cyber sales, and with perhaps an extensive catalog sales base as well, may opt into data mining options not available to museums with one counter, a roll out kiosk, one manager and a few dedicated volunteers.
But there is some facet of the new data mining technology that will increase your profit and minimize your overhead. The links in the sidebar (see page 38) will help you delve further into the targeted marketing strategy that is perfect for your store.
No technology is going to replace good old human know-how, but it can help you retain your best customers, attract profitable customers and maximize sales by selling to the right customers. These unique museum customers have higher expectations than the typical customer, says Andrea Snyder of International Product Marketing in Philadelphia.
Also, emergent international markets can be tapped to fill the unique wants and needs that you know about due to data mining, Snyder says. Well-positioned museum stores will be ready to take advantage of increased one to one marketing, something their best customers already expect.
A FEW KEY DATA MINING RESOURCES FOR MUSUEM RETAILERS
Even if you don’t use their product, they have an excellent presentation of what data mining can do for your organization.
Clementine, an SPSS data mining program, was named the No. 1 Web mining tool in KDnuggets poll in the first quarter of 2001.
POS Solutions: www.possolutions.com/
POS Solutions offers data warehousing and mining services and equipment for retailers who really want to know their customer base, want to keep the data in-house but do not want to maintain equipment or software.
See what the grand daddy of software and hardware business solutions is doing in the area of data warehousing and data mining. Many case studies and white papers are available on the site. However, site indexing can be a bit confusing.
“Say It Better” Center: www.sayitbetter.com/
Kare Anderson’s marketing articles are accessible through her web site by clicking on “FREE articles” and then clicking on “Marketing Articles.” The articles will give you some great ideas on what information you should have your customers give you and how to use the informational one you have it.
A data warehousing and date mining company started by one of the original engineers responsible for the groundwork in pattern recognition algorithms, which made data-mining possible.
Read on article about Usama Fayyad, digiMine, and data mining at www.technologyreview.com/magazin/jan01/TR10_fayyad.asp
Like almost every topic under the sun, About.com has a wealth of information on the topic of data mining. All you need do is type the phrase “data mining” into the search box on the main about.com Web page, and you will get a list of several sites related to data mining.
KD Nuggets Newsletter: www.kdnuggets.com/news/index.html
A newsletter to help you keep up with what is happening in the knowledge discovery and data mining area.
Data Mining Group: www.dmg.org/
If you are a real techie and want to dig into standards, trees and nets of the field, you might want to check out this site.
By: Nancy Hill
Source: Museum Store Magazine