I searched iStock for the Top 100 Best Match results for: African American, Asian, Caucasian, and Hispanic. I recorded the total number of results, and the composition of the Top 100 by Collection.

Total Number of Results:

• The above are the number of results that contain the keyword in question. So, if you looked images that only contained Hispanic models, the number would be lower.

Composition of Top 100 Best Match Results by Collection

Things That Stood Out:

• There were four times as many Caucasian images as there were of the other three ethnicities combined. I expected a disparity, just not one this pronounced. (I’m going to analyze the downloads for each of the searches to see if I find a similar trend.)
• The number of Agency & Vetta images in this dataset surprised me. 272 out of 400 (68%) of these results were in the most expensive collections.
• Top Three Agency Contributors by Number of Images: Blend Images(19), Albany Pictures(18), Rubberball(17)
• Top Three Vetta Contributors by Number of Images: Morganl(11), Uberstock(7), Bortonia(6)

I analyzed the top 50 Best Match results when searching for ‘summer’ and broke out the results by collection:

Number of Images

• Exclusive collections account for 43/50 or 86% of the results.
• The total number of results for the search was: 676,858 (~8% of 8 million total)

Average Age of Image

• This the difference in years between the upload date, and the date of the analysis – May 3, 2011

Average Total Downloads

• This is the average lifetime downloads for the images in each collection.
• Given that Agency exceeds Vetta, it suggests that old images were moved into the Agency Collection.

Average Annual Downloads

• This is the total downloads divided by the age of the image broken out by collection.

Things of Note

• Exclusive+ images in this set were best-sellers that were moved to E+. This analysis doesn’t show what’s happening right now, so the impact of this move is something each person will have to analyze for themselves. (You can do this using LookStat.)
• Agency images in this result set are outperforming Vetta, in terms of downloads. Again, I find this hard to believe and it’s likely being skewed by older images. If it is true, then buyers are indeed price-insensitive, and this is good news.

I searched for ‘business’ on iStockphoto, and analyzed the top 100 results returned for Best Match & Downloads sorts. For each image, I recorded:

• Total Views & Downloads
• Upload Date
• Search Position

Using the data above, I was able to calculate the age of each image, and therefore, calculate the average annual downloads for each image. I used the median instead of the mean for averages, to prevent outliers from skewing the results too badly.

Median Age of Image

• This is the difference between the upload date of each image and the date of the analysis – April 30, 2011.

Median Value for Total Downloads

• This is the median value of the total downloads for each images in the Top 100 search results.

Median Value for Annual Downloads

• This is the Median Value of the Total Downloads divided by the age of each image.

Things That Stood Out to Me

• 46 of the 100 images were present in both Best Match and Downloads sorts.
• I expected a bigger spread in median age of image between Best Match and Downloads.
• I was also surprised by the parity between the median annual downloads in each case.

Over the next few days, I’ll analyze these searches in more detail, and compare them to other subject categories.

If there are topics that interest you, please let me know in the comments.

Our systems should be are updating regularly. Please contact us if you’re still seeing gaps or anomalies.

Our team has been working to resolve the issues, and we expect to return to normal within 2 days. Thank you for your patience.

We’ve had some issues with stats updating which are being compounded by Amazon’s AWS outage. We’re working hard to get things working again and the system will quickly catch up once that happens.

I’m very sorry for the inconvenience and I’ll keep you posted on our progress.

I studied the difference in counts and downloads between people vs. non-people images by running searches on iStock for: business, education, industrial, lifestyle, and medical images. I recorded and analyzed the number of images and also calculated the number of downloads for the Top 200 images.

Image Count

• 7.6% of the images in this sample had nobody in them. (Note: there may be some distortion here due to limited use of the keyword ‘nobody’. But, the ‘No People’ filter includes images of body parts, which I don’t want to count in this analysis).
• 16.4% of the images in the industry category had no people in them (2.3x average).
• I expected business and lifestyle to account for more than 10% of iStock’s eight million or so images, overall.

Average DLs/Image for the Top 200 Images in Each Search

• I obtained the average DLs per image by summing the downloads of the Top 200 images in each search and dividing by 200.
• Overall average DLs/image for the categories shown: 1,153 DLs/image.
• Overall average DLs/image for images with ‘nobody’:    588 DLs/image.

Some Caveats:

• This analysis only applies to the chosen categories. I think the performance of people vs. nobody will be different when looking at subjects like ‘Christmas’.
• I used ‘nobody’ instead of the ‘No People’ filter to exclude images of handshakes, or fingers pointing etc. (Also, the ‘No People’ filter doesn’t work.)
• The reason lifestyle & medical are at exactly 1000 DLs/image is because each of the Top 200 images are in the 1000+ download band.
• Data is cumulative.

The Hispanic and Asian population in the USA grew over 43% from 2000-2010. You can use LookStat collections to explore the impact of this growth on your microstock sales. For example, if you wanted to analyze Hispanic vs. Asian models in business and lifestyle shoots, you would proceed as follows:

1. Create a collection

2. Search for the following terms & add all results.

• HAVING KEYWORDS: business%, hispanic%
• NOT HAVING KEYWORDS: african%, caucasian, asian%, indian%, divers%, mixed%

3. Repeat steps 1 & 2 for Asian models by using the following terms:

• HAVING KEYWORDS: business%, asian%
• NOT HAVING KEYWORDS: african%, caucasian, hispanic%, indian%, divers%, mixed%

4. Analyze the Results:

• LookStat updates collection stats hourly. After that, you can compare the performance of each set of models.
• Pay attention to RPI and Price per download numbers since the collections will likely be of different sizes.

5. Notes:

• The ‘%’ sign symbol is a wild-card character that adds all variations & endings
• Because we’re trying to isolate each group, I’ve added exclusion keywords so each set only contains the relevant models.

Sign up for free today and start using LookStat to make casting decisions that make you more money.

According to the 2010 Census, the Hispanic & Asian populations are the fastest growing ethnic groups in the USA.

• Hispanic: 50.5 million people, +43% growth from 2000-2010
• Asian: 14.7 million people, +43.3% growth from 2000-2010

Together, these groups represent 21% of the total US population in 2010 and accounted for 72% of population growth from 2000-2010.

Conclusions:

• Marketing dollars will follow this growth and this will inevitably impact stock photography.
• You should use LookStat Collections to analyze your shoots by model ethnicity and genre to identify trends.
• You should use these trends to plan future shoots to maximize your return on investment.

Contact us if you have any questions about how to do this — we’re happy to help.

If you don’t have a LookStat account, sign up for free and get started today.

In last week’s post about downloads vs. portfolio size, contributors with 5,000-7,500 images online had the highest number of downloads per photographer, on average.

The Top 10 photographers with 5,000-7,500 images online, (ranked by DLs) accounted for 58% (!) of all downloads for the set:

• Mean (average) DLs: 165,404
• Median DLs: 100,000
• Range: 12,000 – 1,100,000

When analyzing stats in microstock, a few strong performers can skew averages. Look beyond the mean to understand what’s happening.