LookStat – Microstock Analytics

As I mentioned in my earlier post, couples were the most popular theme for active senior images. I was interested in the setting for the images (indoors vs. outdoors) and decided to analyze the impact on downloads and downloads per image.

I found the difference is very interesting. Even though there are over three times as many pictures of active seniors in outdoor settings vs. indoor settings, the downloads per image are significantly higher. Indoor shots perform 28% better in terms of downloads per image.

The average for all couple shots is 781.3 downloads per image, so indoors are doing better there too. I think it would be worth adding some indoor compositions to your portfolio if you’re shooting active seniors.

In the Top 60 images (by downloads) of Active Seniors, at Dreamstime, Fotolia & iStock, the most common theme is ‘couples’ – men and women holding hands. I decided to break down the images of couples by setting and the results are below.

Couples in parks account for just under half the number of images of couples but represent 63.5% of the downloads. It’s interesting that even though Parks were the most common setting, they still perform above average for the set. (As an aside, even though ‘home’ & ‘dock’ have extremely high download per image ratios, given that there was only one image in each setting, it’s important to not read too much into those numbers. More data is required.)

Analytics is a big part of helping contributors operate more profitably and we’re making improvements rapidly (contact us to try out the latest upgrades). We have much more we want to do and new features that you’ll see in very short order. However, to keep investing in analytics and improving the service, we need to start charging for it. Our proposed pricing plan is shown below.

Proposed Pricing Plan for LookStat Analytics

Free, as in Free
We always plan to offer a free service and it is a huge step forward from the service that most of you access as LookStat today. The free plan gives you all the metrics that we have added to the system like RPI, Sell-through-rate, images added, downloads, and image level data. You’ll also be able to compare your shoots and collections to see how you are doing and which parts of your portfolio are the most profitable. Your stats will be uploaded less frequently but any improvements we make to core features and any new sites we add will be available to all users, free or paid.

If you have more than 5 collections but choose the free version of the service, we won’t eliminate anything. You’ll still be able to view and explore any collections you have created. For those of you that stick with the free version, you’ll see a much more powerful stats system than the one you’ve grown accustomed to.

Paid Plans
The paid plans increase the number of collections you can have, and give you more ways to slice and dice your data. If you’re a full-time microstock contributor, knowing what’s working and what isn’t and where things are going is critical. Understanding the RPI of one shoot versus another or which models earn the most in your business images versus lifestyle images can make a major difference in earnings.

Users of Pro & Max plans will be able to enter the cost for a collection and then track its ROI and how quickly it becomes profitable. The Pro & Max plans also add custom time periods so you can view how a collection performed in the Summer vs. the Winter, for example. Data update frequency goes up to once daily for Pro and twice daily for Max plan users.

Users who choose the most expensive plan get unlimited access to all features and also get customized insight and analysis. They will also be the first to get access to major new functionality such as benchmarking or keyword sales analysis.

If microstock is a major source of income for you, we think you’ll find that the Max and Pro plans will unlock a lot of value and will be a big help in profitable shoot planning.

We Need Your Input

Our users have always been a huge part of shaping what we do and I’d love your reaction to our proposed pricing. If you haven’t already done so, please contact us to get access to the beta. There is no charge for anything at the moment and you’ll still be able to access any collections you create once we make the transition. I’ll be posting next week about transition plans and how we plan to roll out the new services to everyone. In the meantime, please don’t be shy – tell me what you think.

As part of an ongoing series of posts about active seniors (see part 1 & part 2), I took at look at what the models were doing in the best selling images. The table below shows the Top 60 images (Top 20 @ iStock, Fotolia & Dreamstime) categorized by what people are doing in the photos.

The most common activity by far is hugging. It’s interesting that images of seniors hugging perform slightly worse than average from a downloads per image perspective. Also, I realize that hugging is a loose interpretation of activity, but I’m the messenger here. 14 of 17 images were couples hugging; (2 were friends and 1 was of grandparent/grandson.) Love must get stronger with age

One of the factors I looked at when analyzing 60 best selling images for ‘active seniors’ was whether the subjects were looking at the camera, or elsewhere (e.g. at each other, out at the ocean etc.)

I was pretty blown away by this result – 72% more downloads per image when subjects were looking at the camera? The average for the set was 777.1 so the ‘looking at camera’ group performed well above the mean. This was also true for conversion rate (downloads/views) – Looking at Camera: 11.16% conversion; Looking Elsewhere – 9.24% conversion.

The Eyes Have It

According to this eye tracking study, viewers look at people’s eyes and they look where people are looking. As a result, I’m fairly sure that images of people looking at the camera are more engaging in search results and lead to higher click through and ultimately more downloads. This may also work in ads whereby people find eyes more engaging and arresting and therefore stop to look.

A Potential Problem

As you can see from the screen shot above (which is from the above-linked study), people look where the models are looking. If the model is looking at your text, more people read your text. As a result, the problem is the following:

• Model Looking at Camera -> Arresting ad, people look at it BUT they don’t read about your brand.
• Model Looking Sideways -> Less arresting ad BUT those who look will likely read your ad copy.

We may be caught in a little trap where buyers purchase images that engage them, produce ads that grab attention but make the customer look at the model, not at the product being advertised.

Conclusions

• Looking at the Camera images had more downloads per image and better conversion than images where people were looking elsewhere.

• It’s possible that even though these images are more engaging, they may lead to less effective ads.

• I think this is only something that can be answered by A/B testing, but I’d love to hear what you think. Also, if you create collections to explore this in your own data, I’d love to know what you find. I’ll be looking at this factor as I analyze more categories for future posts.

• Microstock photographers should shoot both.

• Maybe the ideal ad has two people – one looking at the camera to engage the viewer and another to look at the copy to get the viewer to read it   What do you think?

About This Post

This post is the first in a two part series analyzing the top 20 best-selling images for ‘active seniors’ from iStock, Dreamstime & Fotolia. There’s too much data for one post hence my decision to split them up into a series. (By way of information, the image above is the best-selling image for ‘active seniors’ on iStock and has over 4,300 downloads.)

Part 1 will focus on the number of people in the images, ethnicity & common themes. Part 2 will focus on where they are, what they are doing and cross segmentation.

PS: If you want the spreadsheet with the raw data (which contains image IDs, sites, views data, pivot tables and charts for your own use), please tweet about this post or share it on Facebook and I’ll email you a download link.

Methodology

I collected data for the Top 20 most downloaded images from iStock, Dreamstime & Fotolia and categorized them by theme to see which factors were shared across the best-sellers. I’m not a photo editor, so this is not an aesthetic assessment; it’s an analytical look at trends across the best-selling images. I scored the images in the following ways:

• Number of men, women & children
• Ethnicity of Models
• Theme – e.g. couples, grandparents, friendship
• Location & Setting – indoors vs. outdoors etc
• Activities
• Where People are Looking
• Views & Downloads

Note, that in this post, I’m highlighting correlation, but not causation. This is an exploration of the data associated with the Top 20 images from 3 sites. Also, given the small image counts in certain categories, outliers may have a disproportionate impact on the data.

The above caveats aside, I think it’s very instructive to look at your images in this way. You can do this on LookStat by using our ‘Collections’ feature. I’ll have a post on how to do this soon.

Number of People

The chart above is sorted by downloads per image based on the number of people in the image. As you can see, two people shots dominate both in terms of total views & downloads as well as in terms of downloads per image.

Digging further in to the 45 images with two people in them, 82% were of couples. (The others were 2 friends & a grandparent & grandchild.) The downloads per image for these subgroups were: Couples – 781.3, 2 Friends – 877.8, Grandparent & grandchild – 1079.3.

Ethnicity

As you can see from the charts above, while there are significantly more downloads associated with images of Caucasian models, the downloads per image data for both African American & shots of groups is significantly higher than the mean for the set which was 777.1 downloads per image. One of the challenges here is that analyzing all-time data in this way doesn’t give you a sense for velocity. I’m a little surprised that there isn’t more diversity in terms of ethnic backgrounds in the best-selling images.

Common Themes

Points to note:

• Couples refer to a man and woman and they are typically hugging or holding hands. (more on this in Part 2)
• Friendship images were typically those involving 2 women. I was surprised that there were no images of 2 men in a photo together.

Conclusions

• Two is the most common number of people in best-selling images for active seniors. Of those images, 80+% are of couples, but the images with the highest Downloads per Image are those of a grandparent with a grandchild. (Couples – 781.3, 2 Friends – 877.8, Grandparent & grandchild – 1079.3)
• There were no images of two men together engaged in any activity in the top 60 best sellers; the 5 images of friendship were typically of two female friends.
• 92% of the images in the top 60 were of ‘Caucasian’ models only. While the numbers are small, the downloads per image data suggest that there is an opportunity to explore ‘active senior’ themes with more ethnic diversity.

Analyzing this at the site level is great, but one thing you can do with LookStat is to set up collections to analyze all this. Since images can live in more than one collection, setting up overlapping segments is straightforward and you can then start to compare your data with bestsellers. I’ll post more on how to do this next week. Some of the features in our new beta really take this sort of thing to another level and I’m excited to share it with you all.

Feedback Request

Please comment and let me know if you think this sort of post is helpful & valuable to you. Also, if you have thoughts on whether downloads per image is a relevant proxy for opportunity, I’d be curious to hear about that as well.

One of the core features of LookStat is automated image-level stats. When you create a LookStat account, our system builds a complete picture of your sales history for each image. Once this is complete, you can group images into collections and then start tracking performance of things like shoots, concepts, models etc.

Image Detail Screenshot

The screenshot above shows the earnings by week of the image above for last year. Clearly, this is a seasonal image for fall/thanksgiving and you can see how this plays out in the earnings chart. The image starts really selling in July (week 32) and then peaks in October (week 42) and drops down from there.

The lines on the chart are:

• Earnings – Weekly earnings of the image. This is the default time period when viewing a year, but you can also choose to view the data by month or by day.

• Downloads – Weekly downloads of the image. As stated above.

• T30 Earnings - This is the red line in the chart above and is the trailing 30 day moving average of the image’s earnings. This shows the overall trend line and is especially useful when viewing daily or weekly sales.

• Total Earnings – This is the cumulative earnings of the image over it’s entire lifetime. This should always be increasing. As you can see from the chart above, when the image isn’t selling, this line is flat.

• $/DL – This is the weekly earnings divided by the weekly downloads for the image. This line gives you a sense for the image sizes being downloaded. You can see above that the $/DL line peaks before the sales peak which is in line with the idea that print buyers use larger sizes

Transaction Register

In addition to the image charts, there is a transaction register that lists all transactions associated with that image. You can drill down by month and then by day to look at individual transactions.

Sign Up for the Beta

We’re expanding our beta program, so please contact us and we’ll get you activated. We’re really excited about the new functionality and we’d love to know what you think of it.

We’ve been getting some great feedback from our initial set of beta users and we have been making improvements.

Some recent changes:

• Addition of monthly RPI. This is calculated by taking the earnings for a month, divided by the image count at the end of the month and then averaging over the time period being viewed. I’d love some feedback from you on if this approach lines up with what you would expect.

• Addition of all-time Sell Through Rate. Our system already shows the percentage of images that sell each day on average. We are also going to add in all-time Sell Through Rate so you can see how things are looking overall. This is currently a placeholder, but we’ll have it in there soon. This is currently live. The number depicted is the sell-through rate for the period you are viewing.

• Sortable columns. All column headings can now be used to sort lists. So, for example, if you want to sort your collections by RPI, just click.

All these metrics are also available by collection so you can compare your shoots.

We’ve been working hard to significantly upgrade our analytics product and we’re getting very close to releasing it to our users. The system is about to enter a limited beta so we can get feedback on what’s working and what isn’t.

We are really excited about this upcoming upgrade and the potential it will have to help our users figure out which shoots are working and where to spend their time. There are many new changes and metrics available and I’ll be talking about them all over the next few days and weeks. Some highlights:

• True Daily RPI calculations
• Earnings, Downloads, Images online
• Sell-through rate
• Collection RPIs – compare your shoots apples to apples!
• lots more to come!

It has been too long since we’ve updated our stats product and this has changed. I hope you’re going to be excited about what you see and I’m confident the data will give you an edge that will help you sell more microstock!

As I mentioned, we will be reaching out to a small group of users and will be running a very tightly controlled beta. If you’re interested in trying out the service, please contact us and we’ll add you to our list!

To the many users that have trusted us so far, thanks for your support and please help us spread the word.

Two very interesting charts from www.marketingcharts.com, a site that provides easily digestible snapshots on media and advertising. Both of the charts below focus on display advertising i.e. some form of banner ad. This is where you’re most likely to see microstock & stock photography in action.

Top Online Advertisers by Category – Feb 2010

It’s quite clear that financial services at, 22% of total, is the leader of the pack in terms of ad impressions. This also lines up with business imagery being one of the top selling categories in microstock in general.

Top Financial Services Advertisers – Feb 2010

This too is a fascinating list. Online trading, credit scores, insurance, taxes, retirement – a rich array of conceptual categories worth exploring in your finance shoots if you’re not doing it already. Tax searches are highly seasonal as you would expect, with a steady increase in search volume from Jan-March followed by a dramatic spike during the week of April 15.

Food for Thought – Seasonality

I often think of seasonal events as being more related to holidays and greeting cards, but as the tax example shows, there are often seasonal cycles in other aspects as well. This isn’t something I’d explicitly considered when thinking about categories like business or medical shoots, but it does make sense.