4 Challenges Retail Data Analytics Can Help Solve

In retail, margins are thin and competition is fierce. Every decision your company makes affects current and future performance. No pressure, right? Luckily, using retail data analytics allows leaders to turn to their data rather than going with their gut. Here are four challenges made easier with the right retail analytics software.

Customers Want a More Personalized Experience

Increasingly, customers expect a personalized shopping experience both online and in-person. Failure to deliver a responsive, tailored buying journey from start to finish can cause people to choose a competitor. But the only way to truly understand what customers want and need is to study their behavior: buying patterns, cart abandonment rates, reviews and more.

Using a combination of AI- and search-driven retail business analytics, your teams can get to know customers better than ever before. Then you can modify your sales funnel and branding accordingly.

Customer Service is a Multi-Platform Endeavor

Customer service used to be a telephone-only proposition. Then came email. Then live chat bots. Now, customers expect both public and private replies from brands on social media. This means you need a data analytics solution capable of aggregating data from multiple sources—each with potentially thousands of rows.

ThoughtSpot’s Relational Search Engine and Spot IQ AI Engine can handle this scope of data, still returning insights to end users in seconds.

Return Rates Remain as High as Ever

Returns, though necessary for customer satisfaction, can chip away at your bottom line over time. It’s worthwhile to keep an eye on return rates, reasons for returns, cost-per-return and other metrics.

If your sales data analytics solution doesn’t let you query these important statistics, you’re not getting the whole story. ThoughtSpot’s BI & Visualization Server also returns results as an automatic, interactive data visualization model so it’s easier to digest.

Competition Is Increasing in the Ecommerce Space

Retailers need to understand their own performance, but also their competitors’. A thorough retail industry analysis will allow companies to set healthy benchmarks and monitor KPIs.

Search-driven analytics make it easy to produce and embed reports pertaining to customer turnover and more. AI-driven analytics help end users uncover hidden insights like trends, anomalies and causal relationships, which can ultimately give them the competitive edge.

Implementing retail data analytics from ThoughtSpot addresses many other industry challenges, as well. Learn more with a free demo!



Relational Search: A New Paradigm for Data Analytics

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