How I spent my summer vacation JESSE ALLEVA Saving the family auction business an auction house built upon failure Grubstake Auction was founded in 1980 and specializes in real estate, heavy equipment, and vehicle auctions. Throughout the years, we’ve established ourselves as the largest auction company in the state and sell everything from diamonds to dumptrucks. Some of our most exciting auctions are bankruptcy liquidations. Growing up in the auction business, I’ve seen and learned how many different businesses in Alaska have failed. Either failed to innovate or innovated too fast and ultimately exploded. The key to Grubstake’s success, and what I would say is ingrained in me from all my experience, is quickly learning market dynamics of various sectors to find buyers for these failing businesses’ assets. It take a curious and agile mind to run an auction business as inventory is constantly changing. However, in recent years, Grubstake was starting to go the way of the businesses it helped liquidate; consigners and bidders fled to online and rival companies, overhead costs soared, and the business model broke. If problems weren’t addressed, Grubstake itself could be next on the auction block. regular auctions bankruptcy auctions real estate brewery heavy equipment airliner vehicles jewelry store (CLICK HERE) THE PROBLEMS Losing market share and customers to online and local competitors IT and web presence stuck in 1990s Lack of quality and quantity of information on website for users Slow customer check-out and outdated auction processes PROBLEM SOLVING METHODS gut instinct data analytics gut instinct data analytics my 20+ years in the auction business guided what was wrong and pathways to solutions gut instinct can only go so far… what can data tell us about: customers wanted: up-to-date information on inventory and auctions faster check-in/check-out at auctions great deals the auction business: why are we losing market share to online and local competitors? • • • • • • • • problems: it and web presence stuck in 1990s lack of quality and quantity of information on website outdated auction operations • • • • • • possible solutions: redesign website and online auction site upgrade it and new auction software solutions marketing campaign and brand redesign • • • • customers: what are the different demographics of auction goers? how are their needs unmet? how best to market to these demographics? inventory: what predicts final bid prices? what kinds of bidders buy what kinds of items? data informed solutions: smart marketing campaigns pricing models forecasting tools problem: outdated webiste banner ads difficult to navigate calendar difficult to update aol image search sourced clip art too many calls to action no hierarchy to design lack of design to users needs SOLUTION: WEBSITE DESIGN adobe muse prototype Cleaner design • Easier to navigate • Hierarchy to customer needs: • Joining e-mail list • Viewing auction calendar • Consigning items to Grubstake’s auctions • Price appraisals Problems with Adobe Muse prototype: • Extremely different from original website • Very off-putting to old users when testing • Designed to my tastes instead of to the taste of our customers • Difficult to update quickly • squarespace final version • • • • • • Easier to update than Adobe Muse prototype Dynamically resizes across different devices Easy to maintain by novice webmaster Similar design to old website Excellent integration with e-mail marketing program Excellent analytics to track customers and page views E-MAIL AND WEBSITE ANALYTICS after launch of new website c 102 26% 86% 274% 231% New users/week E-Mail list growth Open rate growth Click rate growth Web traffic growth DATA ANALYTICS customers, cars, and marketing HISTORICAL CAR AUCTION DATA 3064 1751 DATA POINTS BIDDER PROFILES 56 CAR MAKES 354 CAR MODELS 3 “In God we trust; all others must bring data” W. Edwards Deming YEARS OF DATA QUESTIONS TO BE ANSWERED TO HELP INCREASE REVENUE AT CAR AUCTIONS: • what are the best predictors of car price? • what are the different segments of customers? • how are they different? • what are the best marketing channels to reach these segments? DATA ANALYTICS End User Re-Seller most sold vehicle bidder profiles # of Auctions Attended: Average Price Paid for Car: Average Age: % of Cars Purchased by Group: Increase in Price of Car per Bidder: Typical Intended Use for Car: Marketing Channel: * 1-2 3+ $812 $620 35 57 22% +$40.54 Daily driver TV, E-Mail 77% 1994 Ford Explorer Current Retail Price: $4200 Avg. Auction Price: $662 *pricing model year price 1951-1995 $424.50 1996-1998 $724.40 1999-2004 $1207 2005-2014 $2884 +$0 Re-sale or parts Newspaper MANUFACTURE YEAR BEST PREDICTOR OF WINNING BID PRICE MARKETING CAMPAIGNS (CLICK HERE) newspaper television • • • • • • • Targeted to “Nascar Dads” NASCAR NFL games MLB games Fox News Jeopardy Late Night online & newsletter • • Most Grubstake customers still check classified section Must use newspaper to satisfy contracts with government agency clients • • • YouTube ad conversion rate absymal Twitter page remains unfollowed Much better results with Facebook ads RESULTS OF MARKETING CAMPAIGN $900.00 $825.00 $750.00 $675.00 $600.00 29 No v 15 No v 1 No v 25 ct O O ct 11 4 ct O 27 Se pt Se pt 6 $375.00 30 Increase in End Users $450.00 Au g 62% $525.00 average weekly price of vehicle sold at auction problem: customer experience OLD PROCESS 3-5 Min. 1-2 Days 37 Hours Average customer wait time Processing time for new inventory Additional man-hours to set up and run auction OLD PROCESS pre-auction Inventory Specialist types inventory list into computer Pictures of inventory are taken Photos imported into computer Customer bids and win an items Customer waits for clerk’s sheet to be delivered Manually copy inventories and pictures to auction computers Exports and uploads inventory to website Customer waits for cashier to enter clerk sheet information into computer Customer waits for background check auction Customer hand writes information for bidder card Customer waits for information to be typed into the computer by cashier Customer pays for and receives item $ Bid # 87 Cashier checks auction computer to make sure the inventory specialist updated inventories Cashier types information into computer Cashier generates bid card from customer’s information Clerk writes winning bidder number and price paid on sheet Clerk delivers “clerk sheet” to cashier every 10 items Cashier types information from clerk sheet into computer If necessary, cashier performs background check on winning bidder via telephone NEW PROCESS pre-auction Inventory Specialist loads inventory list into Cloud Pictures taken using tablet and attach to inventory in the Cloud auction Inventory automatically updates to all auction computers running Cloud client Items automatically post to online auction website Online bidder done simultaneously to live bidding Customer hands ID to cashier Customer bids on items Customer wins item Customer can immediately check out Bid # 87 Customer pays for and receives items won $ Bid # 87 Cashier accesses auction data from Cloud Cashier scans customer’s ID, autopopulates fields and stores information in Cloud Cashier generates bid card from customer’s information Clerk enters winning customer’s bid number and bid into tablet. Tablet wireless transmits to cashier’s station. Auction software calculates purchases and total due by customer If necessary, background check is completed automatically via internet NEW PROCESS RESULTS 20 Sec. 10 Min. 35 Hours Average customer wait time Processing time for new inventory SAVED man-hours to set up and run auction
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