Asset Performance & Conversion Reporting

Some Common Focus Areas When Looking at Asset Performance:

• Recognizable models versus unrecognizable models
• Shooting on-model versus shooting on mannequins
• Costs per shot related to performance
• Visitor path (where did they arrive from on your PDP)
• Styling
• Hero image (trying different angles)
• Videos versus no video
• Additional alts versus no additional alts
• Talent/team responsible for images

The Long-Suffering Tech Stack

Basically, if your tech stack isn't strong (or, at least, modern), this reporting isn't really going to be possible. Product data and associated imagery sometimes has a really long road from conception to production to publishing, and there is data and metadata needed from each step. Which is to say, by the time images end up being published online, they are often pretty removed from the context of how they were produced - unless your systems of record have been quietly recording events and metadata, building a fuller story of each image's path. Useful context is often lost due to the gaps in communication between various systems, making useful reporting on those things impossible. We're talking about things like: did our more expensive assets perform better? Did the assets we shot with the new style guide perform better? Is there a photographer that creates higher performing assets? What about a shooting style? On-model? Off-model?

How are so many studios in a position where they don't have access to answers to these kinds of questions?

For one, accounting software is often not linked to production software, making true costs per sho, or per product, difficult to estimate. Production software is often not linked to publishing software, making it difficult to easily know what the teams and talent were for a particular asset. Even in a good situation, some or all of this information is often buried in metadata, with no one really tying everything together for useful reporting or analysis. There may be a separate project management system, used by producers, or a model booking software used for tracking talent. Or, the majority of this work may be taking place “brute force” style, in spreadsheets.

At the very minimum, you'll want all of your tools to be able to share data, and to be able to produce useful data. For the "sharing data" part, this can be achieved through rolling up multiple systems into a business intelligence platform like Looker or Tableau. You can read more about these systems in Chapter 3: Systems and Data. For the "producing useful data" part, you'll want to be using a modern system for your productions, and structuring your data in a way that it can be extrapolated. While a colorful, hyper-formatted shared spreadsheet might work for one step of this process (say, tracking talent), it's unlikely that you could link this spreadsheet to a BI system and have structured data be exported. In practice, using the talent tracking example, this means your talent is not associated with the images that you produce. Even spreadsheet-esque systems like Monday or Airtable can integrate with data tools (somewhat), assuming they are structured in an organized fashion. That said, if you're working in a tool that's actually made for photography production, you'll have to do less work to wrangle useful data.

In summary: work in modern tools that are built for the job of photo production. And then roll the data from those tools up into one place. This will allow you the context that will be the key to understanding any results of asset performance and conversion testing.

OK, But What Are We Looking For?

So, let's say your tech stack is modern and capable of producing and sharing useful data. Let's also say your organization isn't siloed and cross-functional teams are working together. Now let's talk about the actual things people are looking for when testing asset performance. As we mentioned at the outset, there is a whole art and science behind conversion testing. You don't need to be an expert on this from the studio side, you should be partnered with someone who can lead the technical aspects of this journey.

But you will want to know what the common things people test for are, what their goals are, and where those things interact with your corner of the business. Well, what folks are looking for is simple: conversions. And they're looking for your studio's assets to drive these conversions. We've all probably worked with that horrible Creative Director who just liked to give images a “thumbs up” or “thumbs down” without any explanation of why the images were good or bad. This is an exercise in the exact opposite: let's find out why we think these images work (or don't work). Each asset your studio creates has a number of properties, each of which can be seen as a “lever” to be pulled, and that means a test could be run by pulling this lever. Let's use the example of a brand selling wallets. They could be shot with a model pulling them out a pocket, looking like a “real life” use of the product. One lever you could pull would be to shoot the wallets on plain white tabletops, with no model. Tests are run between the two images, and you get some actionable insight into what works better, which is to say: what converts to a sale.

In addition to the properties an asset has, there are also properties that come from the user journey on the website itself. For example, how did a user arrive on the site? If users who are arriving on the PDP via Instagram links convert at a massive rate, while site users arriving from browser searches do not, your studio may be shooting a lot more social content for IG soon! The combination of these site attributes and asset attributes intersect to create the testing ground for your images.

What About KPIs?

Because testing asset performance is often tied to experimentation and the testing of things that are not necessarily in full production, they make a tricky subject for KPIs. It would be hard for a studio to gauge a team's performance based on video performance on the website when, for example, video is not being used site-wide. That said, a truly ambitious studio team could set a KPI for “image conversion to sales” rate, and aim never to go below it. For example, a goal could be set to “convert at 5% or higher on all 2022 imagery produced in Q4.” The conversion rate would then be a KPI the studio adopted. I can't say I've seen many studios tie KPI's to asset performance, but I absolutely think this will become more common as studio's tech stacks improve and they are rolled into the mainline business more cohesively.

In summary, there are many, many things to test for when discussing asset performance, especially when taking different industries into account. For everyone, though, the first step is having the ability to test, the partners to test with, and the drive to improve based on what you find.