Analysing Non-Transactional Art Market Data
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This document provides an overview of using non-transactional art market data for market analysis. It discusses the limitations of only using transactional data, as that only reflects the top 3% of the art market. Non-transactional data like exhibition history can provide insights into the full 100% of the market. Specific data sources and analyses are presented, like the Artist Exhibition Career Ranking, comparisons of cities and galleries, and trends in the ages of exhibiting artists. Big data and social media are creating more transparency in the previously opaque art market. Overall, non-transactional data can help identify trends and inform buyers before changes are reflected in auction prices.
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Analysing Non-Transactional Art Market Data
- 1. ART DATA FOR MARKET ANALYSIS WINTER COURSE 2020
- 3. HI, I’M JONAS ALMGREN • 6 months in Berlin • CEO at Artfacts • 7 years in London • CEO at Artfinder • 8 years in NewYork • Founder of VIP Art Fair • 15 years in SiliconValley • A few startups… 3
- 4. OVERVIEW Limitations of transactional data Art world changing with big data and social media Data beyond transactions Market dynamics in detail The artist exhibition ranking Applying data to cities and galleries
- 6. TRANSACTIONAL DATA •Primary Sales (galleries and artists) •Not available •Secondary Sales (auction results) •Available (e.g.Artnet) 6
- 8. BEYOND TRANSACTIONAL MARKET • Is there more to art than price? • Is the value of art the same as price? • Is quality determined by price? • Do we know what will be historically significant? 8
- 9. ARTIST CAREER An artist’s career starts typically when the first gallery is starting to exhibit the artist The next career step is the buyer’s acknowledgment through sales The approval via institutional exhibitions comes last 9
- 10. ARTIST CAREER The art market is hierarchically organised Only the top 3% of market participants are responsible for 80% of turnover The top end of the market can be tracked through auction results Leaving the 97% of market participants with no transparency 10 Top 3%97% of participants
- 11. CONCLUSIONS TRANSACTIONAL DATA Doesn’t measure the dynamics of the art world beyond transactions Only looks at the top 3% of participants 11
- 12. BIG DATA & SOCIAL MEDIA 12
- 13. BIG DATA & SOCIAL MEDIA Increasing availability of big data leads to quantitative standards supporting buyer independence from market interpretation by galleries Social Media provide easy access directly to content producer and artists 13
- 14. CONCLUSIONS BIG DATA & SOCIAL MEDIA Currently the art market has many actors but very few key players.The entry barriers to the top segment are occupied by the leading dealers Buyers are seeking transparency Digitization leads to a complete reinterpretation of the market offering further growth opportunities through new customer base and transparency Instagram becomes the new homepage The artist career starts with finding “own” buyers before first gallery steps in 14
- 15. DATA BEYOND TRANSACTIONS LOOKING AT 100% OF THE MARKET, NOT JUST TOP 3% 15
- 16. Founder Marek Claassen 1996 Built web portal for Berlin Gallery Association. 2001 Founded ArtFacts as a gallery database 2004 Invented the Artist Exhibition Career Ranking 16
- 17. EXHIBITIONS • Exhibitions for over 156 years of art history (1863-2019) • 10 per year between 1863 and 1910 • 100 to 1,000 per year between 1910 and the 60’s • 1,000 to 10,000 per year between 60’s and 90’s • 10,000 to 60,000 per year till today 17
- 18. ARTISTS • over 600,000 artists in the database • from 2,687 living in 1863 • to 130,000 living artists in 2013 18
- 19. MARKET DYNAMICS IN DETAIL 19
- 24. NUMBER OF GALLERIES AND ART FAIRS 24
- 25. NUMBER OF GALLERIES AND ART FAIRS Galleries Overall Galleries At Fairs 25
- 26. CONCLUSIONS MARKET DYNAMICS IN DETAIL The number of artist shown, artfairs and galleries not rising The majority of artists are not shown very much when over 50 The artist shown in exhibitions are getting younger The total number of galleries is declining The surviving galleries go to more and more art fairs The gallery home base is the place to experiment, the fair the place to sell 26
- 28. IT’S A NETWORK CF. GOOGLE PAGE RANK 28
- 29. IT’S A NETWORK 29 • Participants (artists, exhibitions, venues, geo locations, etc.) accumulate points • Points flow through the network • Points are used to calculate the rank • Point depreciate over time
- 31. GEORGIA SAGRI 31
- 32. CONCLUSIONS RANKING EXAMPLES The rank reflects an artist’s prominence in the art world The rank can fluctuate more quickly than art prices, and often precedes an increase/decrease in demand Rank trends can help buyers make purchase decisions Rank visibility allows artists to plan their careers for stable growth 32
- 36. CONCLUSIONS Non transactional analysis is essential to understand the true dynamics of the art world Without non transactional analysis, 97% of the art world is ignored Non transactional data can inform us of trends and artists careers before they show up in transactional auction records Big data and social media creates transparency in a market famous for its opaqueness Increased transparency opens up the art market to new buyers that will be more independent of art world insiders Increased transparency helps artists develop their careers rationally 36