As a Product Marketer, how would you use Experience Analytics here? 3 tips inspired by Julie Osborne’s article
Back in 2020, Productmarketingalliance.com published a great article by Julie Osborne with tips for the product marketing of apps based on her work as a product marketer for Etsy’s app.
Julie’s article didn’t touch on whether or how digital experience analytics could be used for making some of her best practice tips easier to accomplish. So, I am taking the opportunity to piggyback on Julie’s best practice tips. This post is about the way that many brands use experience analytics to help accomplish the ideas that she shared.
Disclaimer: This article and author is in no way affiliated with Etsy, Julie Osborne, or the product marketing alliance. This author has no inside view into Etsy’s practices or the analytics they are using. The original article was simply a source of inspiration for this post.
”There is no such thing as a growth strategy that you can’t measure”
This is my favored statement in Julie’s article, of course. And she continues that:
“you can have a real impact with pretty straightforward tactics if they’re executed well.”
But, I will also add “and if they are the right tactics.” And these are both the areas where digital experience analytics come in to help.
- Inform and prioritize the best new tactics to invest in that are most likely to move the needle in a lasting way.
- Understand whether and why tactics are working / not. How to tune them for performing better.
Example:
A tried and proven trick: Compare completed vs. abandoned journeys.
When you compare journeys that completed a given goal vs. didn’t, it quickly jumps out where some users get lost and how to best help them. Let’s see an example from another brand here, namely De Beers.
De Beers need no introduction. They are the world brand specializing in diamond mining, diamond sourcing, diamond retail, diamond trading and industrial diamond manufacturing sectors
In the De Beers case study on Contentsquare.com, we see that the brand used Journey Analysis to illuminate the paths of customers that exit their journeys prior to completing a conversion.
Note: How to read this Sunburst-style Journey Analysis
- It’s read from the inside out.
- The Innermost ring are the most common landing pages
- Every subsequent ring is the next step in the interaction
- The colors represent different types of page types
- Black represents where users exit
- This visual is filtered for customers that exit without completing a transaction
What unexpected behaviors jump out?
There is looping between the pink and purple pages, i.e. PDP and PLP. Potential customers are going back and forth between the PDP and PLP, viewing different potential products (in this case engagement rings).
Answer the why: Why are customers looping? Is there an issue?
The case study continues to answer that question using in-page analytics. It shows that customers were actually very engaged with each of the potential engagement rings, carefully viewing and considering their different options.
In-page analytics span a variety of visualizations. In the image example, Zone-based heatmaps show the degree of engagement with various content elements across a user population. Session replays provide anecdotal examples of an individual experience. These visuals are based on completely anonymous data, i.e. no personally identifiable information (PII) is captured nor visualized.
Derive a hypothesis for the best tactic (e.g. A/B test) to invest in
This triggered a hypothesis about the next-best tactic to invest in. Namely, bridal customers are clearly seeing a lot of options for their engagement ring and aren’t quite sure which one to choose. So, … what would be the most human thing to offer them?
That’s right, a helping hand!
And it’s exactly what De Beers invested in. Namely, a small offer on the lower left of the screen to video chat with one of their experts.
The result?
Based on the case study this resulted in a 27% increase in conversion.
Talk about having “a real impact with pretty straightforward tactics if they’re executed well.”, as Julie Osborne wrote in her article about her own work at Etsy.
What else?
Julie’s article has many other examples of where experience analytics are typically used to speed things up. For example, the following ones:
Advertising the App
“We also added a section dedicated to the app in the footer of our homepage, which I know may sound pretty basic, but it actually drove a tonne of downloads. This was really unexpected for us because we thought that no one would scroll down to the bottom of the homepage, but it’s been a great example of a high impact, low effort kind of project. “
Perfect for experience analytics. For example, scrolling heatmaps show how many customers are exposed to the bottom of pages after scrolling. When you see that, you can make a decision informed by data, no more need to be surprised or randomly testing.
Reminding users of the app
“Another thing that you need to do is find the right mobile web pages to show the banner. Perhaps a home-screen listing page, but, for instance, you may not want to show mobile web banners on the checkout page because users are just so close to buying an item you don’t want to distract them from completing a purchase. Something that works is to show a banner after they completed their purchase, and say something”
“Sometimes you have to take a short term hit to gain long term value, and introduce friction in the shopping journey to drive app downloads that will have a positive return on investment long term”
Weighing these tradeoffs and fine tuning the tactic for promoting additional offers is one of the most common use cases for experience analytics. There are so many examples at so many brands. For example for …
- Optimizing cross-sell offers during checkout
- Optimizing free sample offers during cosmetics checkout
- Optimizing placement of a loyalty program banner
- Optimizing upgrade offers on a travel & hospitality website or app
- etc.
For example, in Julie’s case they resolved on promoting the app after a completed purchase: “Thank you for your purchase. Maybe you can track your shipment in the app. Download the app here.”
Understanding what users love the app for
“I also learned that buyers prefer using the app compared to other platforms for lots of actions beyond buying things. They like to save items for later, they like to ‘favorite items’, they like to create lists of favorites, they like to create a card sometimes just to save an item but not necessarily to purchase it right away, they like to take screenshots to share with their friends and family. So they do a lot of actions beyond buying. I also learned that buyers preferred to use their desktop and laptops to compare multiple items on Etsy. ”
Another perfect area where experience analytics speeds insights up.
- Journey Analysis and in-page analytics reveal user behavior and intent
- For example, using the cart as a wish list is a very common observation that many retailer have have discovered for their apps or sites
- The use of in-page functionality such as a compare functions is also easy to spot with Zone-based heatmaps. Its impact is then evaluated with Impact Quantification
Optimizing the app experience
“Now that your users have your app installed on their phones, you may think, ‘great, my job here is done,’ but that’s not true. Actually, you’re just getting started. Simply downloading the app is not enough to ensure usage. You need to really compel app downloaders with enticing quickly to make sure that right away, after they install the app, users find some value in it. ”
Exactly what experience analytics is used for, i.e. understanding how users want to be browsing the app and making those journeys as easy, exciting, and seamless as possible.
The moral of the story
As Julie quotes:
“I remember Jane Butler, who’s a managing director at Google, said at the conversion summit in New York, ‘Put the consumer at the heart of everything you do – remember that you’re competing, not just with the other folks in your category, but with the best experience that consumer has ever had.’”
When you become conscious of this fact, you see how high the bar is. So, trying to do this without experience analytics would be like trying to do pole vaulting … without a pole to help you.
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