November/December 2004
Digging deeper


Case Study: Using its research capabilities, SIA created the Buying Power Index, which reveals that attendees at the 2004 SnowSports Show represent 80 percent of $2.3 billion in industry revenues. Find out how the association mines its extensive database of exhibitors and attendees and uses the data to increase sales and drive attendance.

By Maxine Golding



In 1998, more than 30 shows crowded the 16-week buy/sell snow sports cycle, burying the March SnowSports Show 21st in line; 70 percent of buyers and 59 percent of suppliers claimed too many shows made the cycle “more costly and less efficient.”

The findings five years ago from a $150,000 project to research the buy-sell process were compelling. “We lost major companies because the show was too late,” says David Ingemie, President, SnowSports Industries America (SIA).

SIA adopted three strategies designed to make itself indispensable to the marketplace:
1. Move the show forward to lead off the buy-sell cycle.
2. Make market research SIA’s centerpiece, rather than a part-time effort.
3. Data mine to drive attendance and exhibits at its annual SnowSports Show. 

Today, SIA’s deep research capabilities and extensive database of exhibitors (distributor and manufacturer members) and attendees (retail owners, managers and buyers) position it as the prime conduit to connect the two, identify emerging market segments, and document changing buy-sell patterns. The show now kicks off the selling season instead of winding it up, while the number of industry shows has shrunk to 19. And since suppliers must be members to exhibit as well as access market data, SIA doesn’t have to bargain for exhibitors; next year’s show sold out ten months in advance.

How SIA got here is a clear testimonial for what data mining can accomplish: improved communication, targeted marketing, research leadership and increased sales.

Power in numbers
When Ingemie came on the scene in 1976 as Marketing Director, SIA was hand-tracking retailer data on cards organized state by state. Initiating an electronic “retail audit” of the industry was an important next step (see The Buying Power Index and Retail Audit, exclusive Web-only content available at the end of the story). But as competitive clouds gathered in the late 1990s, SIA realized it had to dig more deeply to unlock its full value to manufacturer and distributor members. “We think everyone knows everybody in this very small, relationship industry,” says Ingemie, SIA President since 1981. “But that is not always so.”

Putting money into people and technology, SIA powered up a formidable research engine just as its January 2002 show dates took hold. Out came the buying power index, which this year documented the SnowSports Show’s sizable market impact: Attendees represent 80 percent of $2.3 billion in industry revenues.

SIA has not been alone in embracing the advantages of data mining. “It’s smart to find out how market dynamics affect customers and make them more profitable,” agrees David Loechner, Group President at Laguna-Beach, CA-based VNU Expositions Sports Group. The group produces the Outdoor Retailer Summer and Winter Markets (11 percent retailer crossover with SIA) and utilizes data mining to quantify the value of buyer-seller interactions. “Having market insight is the No. 1 reason shows will succeed or fail,” he says.

That’s what makes the SnowSports Show a clear winner for Peggy Kroesch, Trade Marketing Manager, Bushnell Performance Optics. She ranks SIA “far and above the leader” in sourcing the data that Bushnell needs to market such brands as Bollé, Serengeti, H2Optix and Tasco: demographics on snow users, snowboarders vs. skiers, family vs. individual activities, where snow users like to go and how much they like to spend.

Setting goals
Before extracting ultimate value from data, SIA first had to address nuances of the industry’s structure, issues of database infrastructure and choice of information it gathered.

Reaching buyers in the snow sports industry involves a number of complexities. One company may own 80 stores, 40 of which operate under different names. An individual company may have 40 different addresses, plus those for billing, shipping and decision makers. Many shops are closed for part of each year. Some don’t receive mail at street addresses because mail is not delivered in their towns; instead they use post office boxes, to which some vendors refuse to send printed materials.

Knowing this, SIA set two lofty goals for the retailer database: 100 percent of the core population of ski, snowboard, cross-country and resort shops, and 100 percent accuracy. Every single storefront in the United States — management and branches — had to be present and accounted for. This was expanded last year to Canada.

The database as it existed five years ago recorded “probably 120 percent” of the market, Ingemie recalls ruefully. “We kept finding that a retailer was really a distributor, so we eliminated people who shouldn’t be there.” This cut down the list dramatically, but vastly improved quality and accuracy. And the credibility gained from years of maintaining confidentiality of the data provided to its retail audit greatly strengthened SIA’s hand in expanding its research programs.

Insider Tip #1: Don’t expect to qualify every name, especially buyers, who move so often. There’s never enough money or time. SIA abandoned its quest for 100 percent of hardgoods and softgoods buyers’ names; too many shops will not give these out, and those responsibilities may be shared. Still, SIA claims 99 percent accuracy.

A few tactical decisions paid off handsomely. SIA determined that outsourcing its data management was not effective, so it installed an IS administrator and IS manager full-time. Ingemie calls them “authentic to the industry”; each had worked in ski shops at one time and could talk the same idiom as retailers and suppliers. And by retaining these two individuals over five years, the organization taps into their knowledge and organizational history for fresh ways to mine the database.

SIA hit pay dirt when it moved the IS manager to marketing and sales. Research emphasis shifted to the market needs of those who wanted to rent the database and the critical value of accuracy to the data mining process. Now, more than $150,000 per year is spent on data mining — “and it is never enough,” says Ingemie.

Insider Tip #2: Maintaining the database, although an ongoing challenge, is not as hard as getting to the level you want. Don’t expect to reach an endpoint; it’s an ongoing process that never stops.

Gathering data
SIA knew that the more discrete data points it identified, the better. As a result, what SIA now collects on retailers can spill over four screen pages. What product categories do they carry? Are they members of buying groups? To what organizations do they belong? How many full-time and part-time employees are there? What months are they open? And the must-haves: Web sites, e-mail addresses, and fax numbers.

All of this has been obtained from retailers who have filled out show registration forms or responded to surveys. “We are chasing data every single minute of the day,” says Ingemie.

It’s because SIA “has never compromised” the data’s integrity that Denver-based retailer The Sports Authority has “no difficulty providing it,” says Art Hagan, Senior Vice President. “It’s a nice road map for the industry. The numbers are aggregated so no one knows my individual numbers; if they did, I wouldn’t participate.” He uses the monthly audit reports “all the time,” and even more extensively for a recent new initiative on the East Coast.

Insider Tip #3: Prepopulate the registration form with data, and use e-mail, faxes, mailings and phone calls to update the rest.

One of the best ways to update data, SIA has found, is to prepopulate the show registration form sent to 12,000 retailers post-Labor Day. Since only changes need to be made, the sign-on process is swift. It’s also increasingly digital, as online registration has grown dramatically the past three years to about 50 percent of all attendees (75 percent is the goal). Every bounceback is monitored and checked.

The forms, however, cannot possibly contain all the retailer’s data in SIA’s database. Additional e-mails, print surveys and telephone calls complete the collection. But the real mother lode of data can be found at retailers’ own Web sites. “If not for the Internet,” says Chris Semon, SIA’s National Sales and Products Manager, “we couldn’t do half of what we’re doing.”

Data is input within 24 hours of receipt and coded by method of response: Web, mail or fax. Reports are distributed weekly or at will to SIA management, and more thorough analysis is initiated if registration numbers are not tracking to targets. For example, when Web registration initially lagged last year, the situation was corrected by making the link on the SIA site more prominent.

Turning Data into Attendees
Utilizing its research capabilities, SIA targets:

New markets. While SIA has learned not to dilute the show, it surveys members and retailers to uncover emerging product categories and then pursues those markets aggressively. For example, SIA spots a new trend — ski apparel carried in high-fashion boutiques. The category is discussed during a trade show committee meeting and a decision is made to market to this shop category, which is expected to attend Advanstar’s MAGIC International apparel show. SIA will buy a list, analyze the first 1,000 shops to see how many attended the other show, and promote SIA exhibitors these retailers did not see.

Geographic areas. In a similar vein, SIA will pull a list of shops in a 25-mile radius of Aspen, CO, knowing every employee wears a uniform (including a parka) that should be bought at the show. It will promote the event, query those who came to the show on the value of attendance and survey non-attendees on why they didn’t come.

History. Those not attending get attention equal to those who do. Spot checks of registrant data help SIA isolate areas, shop segments, or categories of product where the show may be gaining or losing buyers. For example, it will focus on key states, such as Colorado, New York and California, and “if three of 11 top buyers do not attend, something is up,” Ingemie says. 

Promotions. Up to 100 members take advantage of SIA’s offer of free postcards printed with specific exhibit booth information. All the members pay is postage to send these to pre-registrants by category of shop. This promotion is especially effective for new companies to gain the recognition of buyers seeking out “new, cool products at the show,” says Semon.

Registrants. Real-time registration data, provided on a daily basis to exhibitors, enables reps to set up appointments in advance and manufacturers to plan sales meetings, market presentations and product development sessions.

Industry changes. Very detailed post-show attendee surveys further identify how the show needs to change. In recent seasons, SIA noticed a significant increase in women’s products, as well as women in buying positions. SIA responded with a seminar on marketing fashion and equipment to women.

Insider Tip #4: Segment a “top list” (SIA selects 250 shops) for advisory purposes. In quick surveys, ask about a market condition that seems to be emerging, an event you’re planning, or an ad campaign you’re developing. The resulting data will be invaluable.

The tech challenge
Nothing in IT is ever simple, even where SIA’s off-the-shelf database software — first Microsoft’s Access and now Sequel — is concerned.

Take defining or expanding the database’s descriptive codes as markets change. “When naming information, you can end up with obscure terms to outside people,” Semon explains. Fields and data need to properly reflect the market. For example, a field that used to describe six terms has evolved into 36 descriptive terms that “have no meaning to anyone but two of us in the office,” he says. “If we knew then that we would be providing this information, we would have done things differently.”

On the other hand, certain data fields, such as “no mail delivery to that location,” can be very helpful to a supplier marketing to the database. Another is the identification of “common ownership” among retail shops, since 10 shops that attend the show may represent six owners.

Once a new market segment is identified, the database administrator will use phone and e-mail techniques to define it. A new field and links to it can be established in the database within hours and, after testing, implemented in a few days.

Online registration was custom-built for what SIA collects. “We feel we are better off with what we have” than registration packages, says Semon. “It’s not graphically flashy, but gives us infinite flexibility to track what we want.”

Internally, SIA shields the database and limits staff access. Externally, the only work outsourced is a periodic run of the database against the National Change of Address program (NCOA) and area code standardization. “It can be a huge problem to let someone outside work on the database,” says Semon.

From data to dollars
All this research has blossomed into a prized revenue stream. Tapping into the database, though, requires care.

“People often call us to say they want to buy our database. I wish it were that easy,” explains Semon. “They’re not just buying a list, but a lot of options to specifically target who they are looking for.”

Two things are held most sacred: SIA will rent shop names and data, but not divulge e-mail addresses or fax numbers. This protects the data’s integrity and maintains SIA’s control as the valued marketing conduit.

Members willingly pay SIA for e-mail and fax blasts to retailers, Ingemie says, because they feel these efforts are superior to their own. And SIA has a reputation suppliers trust. “Many sales managers of member companies don’t want to use their customer base, but prefer ours,” he says. Indeed, when Kroesch spearheaded a massive lead generation project at Bushnell, she relied much more on SIA’s “very viable” database than on other sources 

Because retailers always want to discover suppliers, new companies — such as last year’s Helmets R Us, which offers safety helmets to retailers and resorts for rental programs — mine the database to build their business plan or prepare for the show. SIA retailer data state by state or county by county also helps a company’s new rep jumpstart a territory. “They say, ‘This is exactly what I’m looking for,’ and it’s always more data than they expect,” notes Semon.

Much of the database marketing done through SIA, such as e-mail product announcements year-round, has nothing to do with the show. For example, a supplier’s recent e-blast alerted retailers to a large stolen shipment of specialty eyewear coming to market.

Still, no organization wants to be accused of bombarding customers with too many data requests or promotions. SIA watches the schedule closely and adjusts the timing of e-blasts, mailings and customer contacts. “We can’t let 25 members buy an e-blast in one week,” Ingemie says.

And SIA clearly lays out the options retailers can choose to opt in or out of receiving newsletters, show information and marketing communication from members. “People can, in a moment of frustration, demand to be taken off the database,” Semon points out. “But do they really want to get nothing from us?”

For its own part, SIA mines the data for new products. SnowTrak datamaps all retailers in a particular state or county and charts such data as the number of shops, product category sales (percentage of alpine sales, for example), number of in-store reps and instructors, and number of sports participants (skiers and snowboarders). An annual Intelligence Report covers the snow sports industry from top to bottom. And Brand Share Reports help retailers and suppliers make key marketing and tactical decisions.

No wonder SIA bills itself as “the intelligent partner of the snow sports industry.” 

Maxine Golding has reported extensively on the meetings industry during a 25-year career as editor, writer and publisher. 

Sidebar (Web only): A One-Two Punch: The Buying Power Index and Retail Audit

What if…you had tools that clearly measure the buying power of your industry and the attendees walking your show floor? They would be priceless, wouldn't they?

That's what the Retail Audit and Buying Power Index mean to SnowSports Industries America (SIA). They are neither easy nor cheap to do. But their effectiveness in documenting the organization's reach and the show's purchasing might is unmatched.

The History: SIA and an outside service provider jointly developed 25 years ago an electronic system to track and analyze retail checkout data. Its current partner is Boulder, CO-based Leisure Trends Group.

The Audit Panel: 1,259 retailers, a geographically balanced national sample of independent specialty and sporting good chain retail storefronts within the snow industry market.

The Data: Actual point-of-sale transactions covering six categories and 36 product segments. Reports are delivered via the SIA Web site through secure passwords.

The Challenge: Every manufacturer numbers each of its products differently than the retailer, which assigns its own distinct SKUs to the products it sells. Leisure Trends' gargantuan task is to take every SIA member's catalog and match each retailer's SKU back to the original product. (One manufacturer may have 13,000 discrete products.)

The Measures: Total industry sales projections; aggregated sales volume -- every transaction to the penny; market share and brand leaders in product categories; average retail selling price (for example, $585 for the Rossignol Viper, a $700 list ski); numbers shipped and remaining in inventory.

The Outputs: Six audit reports cover the complete selling season - August-October, October -November, November-December, January-February, February-March, and Year-end.

The Corrections: To ensure that the algorithm in use remains accurate, a distribution study every three years charts changes; revisions are made to the number and type of stores on the panel. In addition, SIA conducts a sales and orders census of every shipment members make to retail. These numbers, never disclosed, are used to spot anomalies in the audit that might call for a distribution study to be done sooner. For example, a trend this year of skis being sold with bindings on them caused a misreading of the individual totals of skis and bindings sold.

The Index: Data from the Retail Audit is used to establish an algorithm for each state's snow sports revenues. The registration list is matched against state lists, and the algorithm applied to estimate total retail revenues represented at the SnowSports Show.

The Value: The numbers tell "the quality and volume of business present at the show," Ingemie emphasizes. "We look for the key 20 percent of retailers representing 80 percent of the business. If they're missing, we have a problem." The same is true of suppliers. If the top brands pinpointed in market share reports are not at the show, SIA must get them there. For example, apparel represents 6 percent of the market, and SIA uses this to show prospective exhibitors that if they're selling into the market, they need to exhibit. "When we show them just how much business they've lost by not being at the last three shows," Ingemie adds, "that hits home.