LookStat – Microstock Analytics

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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.

“It is true that you can succeed best and quickest by helping others to succeed.” – Napoleon Hill

Although Napoleon Hill wasn’t talking about microstock, his advice remains relevant. If you focus on helping image buyers succeed, you’ll make more money in microstock.

One way you can do this is by studying how images are used in ads. A recently launched site, Moat.com, let’s you do just that. (Moat also intends to provide engagement analytics, but you’ll have to wait, and pay for that service.)

I searched for some major advertisers on Moat and found a range of ads that are worth examining.

From right to left, we have Netflix, Pfizer, Aetna, and Lifelock. Netflix is demonstrating their service, while the others are selling peace of mind.

Some Observations:

• Images are horizontal, and subjects are off-center in 3 out of 4 ads to leave room for copy.
• Models are looking directly at the camera in 2 out of 3 of the ‘peace of mind’ ads. Eye contact does suggest trust, so this makes sense.
• Netflix’s models are pointing at the ad, and the ad is directly above the ‘Click Here’ button. (This makes sense since we read from left to right in English.)
• Models in portrait style shots are looking at the camera, but their shoulders are at an angle. (I don’t know if this is significant, but I think it’s interesting.)

This isn’t a statistical analysis, but I think studying how buyers pair images with concepts will tune you in to their needs. In turn, this will help you plan your shoots and produce more salable images.

Other Examples:

To save you time, here are links to some of the brands I searched for:

• Healthcare: Aetna, Pfizer, United Healthcare.
• Financial: Citigroup, Lifelock.
• Travel: Princess Cruises, Travelocity, Westin Hotels.
• Lifestyle: Kohl’s, Netflix, Target.

NB: Product retailers use their own products, but I think it’s still instructive. Service providers seem to use more stock imagery.

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.

The chart below shows the Top 10 Leisure Activities in the USA based on number of female participants in 2009.

The chart below shows the Top 10 Leisure Activities in the USA based on the % of participants that are women. This data will help you ensure your shoots are realistic.

The actual number of participants for the above activities are shown below to help you prioritize your efforts. For example, gymnastics and roller-blading appeal to a much smaller segment of the population than walking, working out the gym, or yoga.

Source: National Sporting Goods Association

Points to Note:

• Yoga is close to 80% female, growing, and ranked #11 in terms of total participants. When casting yoga shoots, you should keep this mix in mind.
• I was surprised that walking is 60% female in terms of participation. I normally think of this as a couples concept but the data would suggest women walking together would be a worthwhile concept.

Last year, I posted about the Top 10 Leisure Activities to help with lifestyle shoot planning for the summer. To help with this year’s shoots, I charted updated data from 2001-2009 for the top activities based on 2009 participation numbers.

Source: National Sporting Goods Association – 10 Year Participation Report

Points to Note:

• The Top 5 fastest growing over this period were: Workout at Club, Weight Lifting, Running/Jogging, Exercising w/ Equipment, and Hiking.
• Although Yoga didn’t make the cut (15.7 million participants), it was one of the fastest growing in the last year. Also, 79.4% of yoga participants were female.

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.

While analyzing data for my last post on downloads per contributor, I became curious about the relationship between downloads per image and portfolio size.

Chart: Total Downloads per Image

• I was surprised to see the spike in downloads per image in the middle band.
  • I blame exceptional performers, rather than a magic trend favoring those with 5,000-7,500 images online.
• Downloads per image decline (mostly) as portfolio size increases, but at a slower rate.

Conclusions:

If you keep uploading, your earnings will rise, but at a slower rate than your portfolio does. Although this seems depressing, it shouldn’t be.

• You’ll make more as you upload more.
• You can fight the trend by improving your skills and analyzing your portfolio to uncover better opportunities.

The strong performers in the middle tier are proof that it’s possible.