When you look at sales data for your ecommerce DTC store, it’s about more than just crunching numbers. It’s about finding the stories within your data that give you insight into how the market is responding to your product or how your customers reacted to a new offer. Every time you make a change to your product, pricing, marketing strategy, or really anything that affects your ecommerce site, the resulting data will inform you on what actions you should repeat compared to what strategies need adjustments.
This is why Peel brings your data to life. Our goal from the outset has been to provide you with new ways of looking at your data with visualization that makes the story jump off the screen. When you have a seasonal spike in sales for a certain product, or you gain more subscriptions after making tactical changes to product bundles, or you see a dip in average order value (AOV) for a given month, your data is trying to tell you something. Peel provides your data with the megaphone it needs to give you a louder push in the right direction.
So, when it comes to finding the stories that live within your data, we thought about what could give you more control. What new features could we add to Peel to give you more autonomy to dig into your automated analytics and find new segments and slices of data that speak to your story?
The result is our Customization release, which has added 3 new features to Peel that give you more flexibility for data segmentation and more:
Let’s jump into the new features that you can use right now, in Peel, to discover new narratives in your data and more avenues for growth.
Data segmentation can make or break the quality of your analysis. That’s why our new custom segmentation update allows more flexibility in the way you group and analyze your data. You can forget the pre-conceived attributes that you may be used to; this update allows you to create completely custom segments based on your needs.
For example, if you want to look at your first-purchase data by different regions, you don’t have to stick to segmenting by cities or states, you can come up with more tailored groupings like “Midwest” or “Southern California” or really anything you can think of. By tagging your products accordingly in your Shopify store, you’ll have a completely new and custom set of data that better informs your store’s individual needs.
From there, you can dig into those segments and get into customer lifetime value (CLV), AOV, repurchase rate, and any other metrics you're used to using in Peel. You can combine this with your tagged attribution channels to understand your marketing channel performance and more. This empowers your team to bring your imagination to even the most advanced metrics in the platform. Despite this, our core ethos remains the same with this update: you don’t have to be a data analyst or expert to use Peel.
In the past, our team has worked directly with our users to help them create custom segments. This update puts the power in your hands to easily create those data segments without losing depth. In our time working with DTC ecommerce brands, we’ve learned that their savviness and entrepreneurial spirit drives a desire for innovation. So, instead of putting you in a box with rigid tools for your data segmentation, Peel rewards your ingenuity with constant updates for more flexibility.
You don’t need special upgrades to use these features. The idea here is that we’re democratizing your data and putting more power in the hands of your entire team without the need for a technical expert or “owner” of your data. You’ve poured time and resources into your company to carve out your unique business model; now you have the power to find more granular data and stories in your metrics to drive growth.
One of the biggest values in choosing Peel as your automated analytics partner is that you can visit the Shopify App Store, find us, and install us in a single click. But what about data that lives outside of Peel? Sure, all of your sales data is automatically pulled into the platform for you, but what about extra data that may be important to your business but isn’t part of that automation?
If you have a relevant set of data living in a different location, we’ve added a CSV drag and drop feature to easily incorporate that information into Peel. This not only helps with new avenues for analyzing data that would not usually be in the platform, but it also helps reinforce the use of Peel as your central repository for data and analysis. There’s nothing worse than having important data live in disparate locations.
Data silos = danger of losing important information. CSV drag and drop gives you an opportunity to diversify your data and find new and highly specific ways of analyzing important data.
For example, we work with clothing brands that find value in creating print catalogs and look books. This is an offline marketing technique that exists in the physical world, right in the hands of your customers. Sometimes it pays to have a physical way to engage your customers in their offline space.
Any data attached to a print media feature like this will not inherently live in Peel. But there may be some really relevant analysis that could come along with incorporating that data into the platform.
The CSV drag and drop feature now allows those brands to take any of that relevant data and drop their spreadsheet right into Peel. This opens the door to better understanding the ROI of something like a print catalog in relation to all the other metrics you have access to in the platform. Fashion catalogs take countless hours of design, styling, art direction, and photography. Associating a cost with that and then using Peel to analyze customer behavior can tell you the true performance of that media.
Do the customers who receive my catalog have a higher AOV than those who don’t? Does exposure to the catalog show a trend of higher lifetime value (LTV)? How about repurchase rate? Do my customers make their next purchase faster if they see our new season in the catalog? These are highly relevant questions that the CSV drag and drop feature can help solve, giving you a more robust picture of your catalog’s impact on your business.
The same applies for just about any other data that lives outside of Peel that you’d benefit from looking at closer with cohort analysis.
As we mentioned earlier, to get the most out of Peel, you don’t have to be a data analyst or numbers expert. We want our solution to remove the blockers of relying on a single person or specialized team to get data insights. With that said, we do understand that there may be people in your organization (or other stakeholders) who may benefit from raw data.
So, this update allows you the freedom to download your raw data from Shopify and other sources. We recognize that our tech-savvy users benefit from access to raw datasets that we use to compute our metrics. Files of this nature are a boon for data scientists, but can be an absolute pain to reload and verify. Sometimes there’s a need to share metrics in good old spreadsheet form.
With the addition of the CSV drag and drop feature along with the raw data download, we’ve updated the control you have over the way data flows in and out of Peel.
It’s true. We love when our customers come up with new, unique ways of arriving at the metrics that will help their growth. Custom data segmentation and new ways of bringing data in and out of the platform are just the beginning of our updates.
We encourage you to come to us with your most unique forms of tagging customers, experimental lists and more. Peel will help you bring that information into context, empowering you to always make the next move informed by data that’s tailored to you.
If you haven’t already, drop by the Shopify App Store to start your free, 15-day Peel trial.