Identify return issues, uncover opportunities, and gain actionable recommendations that increase revenue with the Returnalyze InsightFinderAI.
Trying to resolve returns issues without knowing the right questions to ask, let alone without knowing the answers to those questions, means relying on guesswork. Not only does this cost time and money, but it may not resolve the issue. Essentially, you’re throwing darts at a target without knowing where the target is, and if that wasn’t bad enough, the lights are off.
But what if you could pinpoint specific returns issues? What if additional revenue opportunities were waiting to be discovered? What if you could automatically generate actionable insights that help recapture lost revenue or even generate new revenue?
Questions like these are why we created InsightFinderAI. The Returnalyze AI has been designed specifically for retail returns and continuously analyzes tens of millions of data points. More importantly, the AI analysis doesn’t just tell you what’s going on and why, it tells you exactly what to do next.
If you want crisp, data-driven recommendations on where returns can be reduced and where hidden revenue opportunities exist, read on and explore our InsightFinderAI.
Quickly Identify Product Return Reasons with InsightFinderAI
Not only can InsightFinderAI automatically identify factors that are causing returns, but it can also help you prioritize actions in key contributing areas.
For example, imagine a retailer has noticed high return rates for a specific brand. They want to reduce these returns quickly, so they remove the brand from their product assortment entirely. In doing so, they also remove products with high keep rates, which causes shoppers to find those products with competitors.
Obviously, this scenario is a bit extreme, but it highlights the importance of granular data. Instead of taking a broad action that possibly did more harm, InsightFinderAI would have pinpointed the origin (SKU, variation, etc.) and return reasons (damage, sizing, etc.) to create a targeted solution. That means expending minimal time and money on a data-driven solution that’s much more likely to achieve the desired results. InsightFinderAI takes things a step further, though.
Remember the dart board example from earlier? Not only does InsightFinderAI effectively turn the lights on and direct you toward the target, but it also identifies other factors you may have overlooked.
For example, while stretch fabrics generally have a lower return rate, there are exceptions to everything. A brand that overlooks fabric stretch as a contributing return reason may never discover that shoppers are returning a garment because the fabric actually has too much stretch.
Here’s another good example. It’s generally accepted that existing customers often have a lower return rate compared to new customers since they’re more familiar with a brand. However, one client used InsightFinderAI and discovered that their most valuable customers (those who purchase three or more times a year) actually had the highest return rate. When you compare existing customers who purchase just one time each year to new customers, their return rate is actually lower.
With InsightFinderAI, the client gained valuable information that they might never have uncovered otherwise.
Increase Revenue with Enhanced Customer Behavior Insights
Today, businesses can access vast amounts of data from social media, websites, and even brick-and-mortar stores to interpret customer values, motivations, and shopping preferences. This has led to more targeted marketing efforts, better customer experiences, higher retention rates, etc. Across the board, this increase in knowledge helps businesses increase their revenue.
The issue? The amount of data necessary for these insights is massive. Plus, without the technology to perform sophisticated analytics to identify trends and outliers, businesses have to rely on data analysts. Despite the hurdles, some businesses have been successfully accomplishing this for several years. However, dwindling access to third-party cookies will make this type of data collection increasingly difficult.
Fortunately, InsightFinderAI can collect, analyze, and automatically generate insights much faster. Applying available zero and first-party data with returns analytics can also enhance customer insights and strategies.
For example, imagine that a shoe retailer asks customers to share information about how and how often they use a specific style (running, walking, etc.). InsightFinderAI can cross-reference this information with returns data to determine how this particular style is working for different customer types. If these insights indicate specific customer groups will have a positive experience with that style, businesses can more effectively market that product to targeted customers.
In the above scenario, this would result in greater ad revenue and happier customers. It’s important to note, however, that these insights have applications far beyond marketing. This type of comprehensive understanding allows businesses to optimize and improve the profitability of return policies and loyalty programs, recoup lost revenue by identifying behaviors related to returns abuse, and so much more.
Develop A Returns Opportunity Plan with InsightFinderAI
Without taking action, all the data and insights in the world won’t help a business increase its revenue. That’s why, in addition to its sophisticated analytics capabilities, InsightFinderAI will generate an automated roadmap to deliver targeted revenue impact. This is by no means a complete list of the recommendation types InsightFinderAI can make, but a Returns Opportunity Plan can include the following:
Product assortment recommendations for dimensions such as color, materials, etc.
From adding additional color variations that encourage bracketing with high keep rates to suggestions regarding materials and hardware, InsightFinderAI can provide product assortment recommendations designed to increase revenue.
Comprehensive size & fit recommendations that improve customer experiences.
Sizing is one of the biggest contributing factors when it comes to returns. Fortunately, in addition to identifying specific sizing issues, InsightFinderAI will recommend data-driven solutions (detailed size charts, additional product details, etc.) that recover revenue.
Detecting specific operations issues.
Whether it’s shipping delays or inventory management issues, InsightFinderAI can identify the issue and provide actionable solutions. For example, it has the ability to make recommendations about warehouse staffing. That means minimal staff when products are likely to move slowly and additional staff when appropriate. Overall, the costs associated with labor will be used more efficiently.
Increase Revenue with AI-Driven Actions from Returnalyze
Your returns data contains a wealth of untapped information, and InsightFinderAI now makes it easier than ever for you to harness that data to uncover issues and valuable opportunities. Plus, with its recommendations, businesses can easily take corrective action that results in increased revenue.
In addition, a partnership with Returnalyze comes with step-by-step guidance from our returns experts. We’re immensely proud of InsightFinderAI, but we know how important it is to have an expert in your corner when you need it.
Ready to increase revenue with InsightFinderAI? Schedule a demo or contact our team today.
