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By Returnalyze on June 28, 2024

Improve Customer Experiences with AI Insights and Recommendations

Access data-driven recommendations that improve customer experiences and increase revenue with InsightFinderAi

When retailers don’t know their customers, improving the customer experience is difficult, if not impossible. Sadly, it’s not as easy as looking up their purchase history.

Some businesses use analytics or rely on human analysts to comb through massive data sets for customer behavior insights. Not only is this time-consuming and subject to human error but collecting that information is increasingly difficult as access to third-party data declines.

Fortunately, tools like InsightFinderAi can collect, analyze, and automatically generate the kinds of behavior insights necessary to improve customer experiences. 

Since it continuously analyzes tens of millions of data points (zero-party data, returns data, unstructured customer feedback, etc.), it not only provides valuable insights that may have otherwise gone unnoticed, but it also generates data-driven recommendations.

Learn how you can use InsightFinderAi to create more positive customer experiences for greater loyalty and increased revenue.

Optimize Inventory Management and Avoid Stockouts with InsightFinderAi

While inventory management and demand forecasting aren’t necessarily top of mind for customers, their overall satisfaction will quickly decline when the products they want are out of stock. Conversely, excess inventory can lead to increased carrying costs that eat away at revenue as products lose sales velocity over time.

With InsightFinderAi, that’s not an issue. By analyzing customer behavioral insights and historical data, InsightFinderAi can help forecast product demand for more accurate inventory ordering. That means fewer stockouts, reduced carrying costs, and happier customers.

It even monitors return patterns in real time to let retailers make dynamic adjustments to inventory management. 

InsightFinderAi Insights and Recommendations Improve CX | Returnalyze

Size & Fit Recommendations Improve Customer Experiences

One of the biggest contributors to returns is size and fit. If a garment is the wrong size or if a piece of furniture literally won’t fit in a house, it makes sense for a customer to return the item. While this is an acceptable return, minimizing the issues that contribute to these returns is vital to protecting revenue and improving customer experiences. 

In addition to identifying specific sizing issues, InsightFinderAi can recommend data-driven solutions (detailed size charts, additional product details, etc.) that recover revenue and create more positive experiences for shoppers. 

It can even analyze both quantitative and qualitative post-purchase data to provide a more comprehensive understanding of the underlying issue. For example, a customer might select “size and fit” as their return reason, but in a review, they may state, “The material was too stretchy, and it quickly lost its shape.” 

Yes, that’s technically a sizing issue. However, it requires a more specific and possibly more extensive solution—additional descriptions about the material, more product images, or even rethinking the material used during manufacturing. 

The granular data that InsightFinderAi analyzes allows it to identify nuanced issues and make targeted recommendations to address and resolve them directly. This means less time hunting down issues, faster resolutions, and fewer returns.

Product Assortment Insights Can Provide Value to Customers

When customers find a garment style they like, they may want to purchase it in multiple colors. Maybe they enjoy home decor items with specific textiles. Obviously, they’ll want to purchase more products with those features. 

Great, right? Well, only if your product assortment accommodates them. 

When customers can’t find the products they want, not only does it create poor experiences, but it also means they may turn to a competitor. That’s why product assortment recommendations are so valuable.

When InsightFinderAi identifies insights that could inform product assortment, it can make recommendations designed to appeal to customers and increase revenue. This could include adding color variations that encourage bracketing with high keep rates, suggestions about specific materials and hardware, etc. 

Plus, its ability to incorporate returns data and post-purchase behaviors means it will let you know when products should be removed.

While a product variation may initially fly off the shelves, a high return rate can result in poor customer experiences and revenue loss. In this case, removing the product will reduce the poor customer experiences and protect net revenue.

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Enhance Targeted Marketing Personalization with InsightFinderAi

The goal of targeted marketing is to cut through the noise and directly engage with customers. Whether it’s personalized product recommendations, post-sale customer services, or tailored marketing emails, companies that successfully increase the personalization of these efforts generate more revenue.

Not only can InsightFinderAi analyze customer data (browsing and purchase history, items added to cart, demographics, etc.) and then recommend similar products they’ve purchased, but it can also create and integrate product-level and transaction-level scoring.

Analyzing customer data helps improve the customer’s shopping experience, retention, and sales conversions. Additionally, integrating product-level and transaction-level scoring allows it to predict return rates. This, in turn, makes it easier for marketers to understand which customers are likely to provide more value so they can adjust ad spend for specific customers.

For customers, this means being presented with marketing that speaks directly to their wants and needs. Compared to general ads that speak to the masses, customers are much more likely to engage with personalized marketing.

Partner with Returnalyze for AI Insights and Recommendations | Returnalyze

Partner with Returnalyze for Ai-Powered CX Solutions

When behavior insights are leveraged properly, retailers can create positive customer experiences through optimized marketing, customer-centric return policies, channel-specific improvements, and so much more. 

While collecting and analyzing the information necessary for such insights may have been a gargantuan undertaking in the past, InsightFinderAI now makes it easier than ever for you to harness that data. 

Plus, with its recommendations, businesses can easily take corrective action that results in happier customers and increased revenue.

Ready to improve your customer experiences? Schedule a demo or contact our team today.

Published by Returnalyze June 28, 2024