Customer Success

Building an Analytics-Driven Retail Machine

Valentine’s Day is approaching, and love e-commerce is in the air. The National Retail Federation (NRF) predicts shoppers will spend close to $5 billion online for gifts for the holiday this year, up from $3 billion last year.

Not exactly breaking news––we spent more than $1 billion in sales over 31 days this past holiday season, and most of us see (the slightly excessive) Amazon packaging more often than we see the inside of a mall––but these trends and conversations serve as a reminder that the way we shop has changed.

So how can retailers adapt?

The key is putting the wealth of data generated by shoppers, products, and our changing behaviors directly into the hands of the business users who can do something with it.

Here's how one top retailer is making it happen. 

What if your merchandise managers were their own data analysts?

Retailers today have only a few seconds to make an impact on a customer, so presenting the right content or product in the moment can make the difference between a happy customer and a lost sale.

So when merchants at one of the world’s largest retailers found themselves struggling to manage product assortments across thousands of SKUs, they risked losing a lot. These merchants relied on weekly data dumps from a data warehouse into their old BI system, which meant each individual spent hours per week preparing data from the top performing products. When you only focus on the top performers, a lot gets overlooked. Managing a full assortment is nearly impossible. On top of that, their legacy analytics portal only delivered static reports, so ad-hoc queries were out of the question.

What they really needed was a solution that could:

  1. Open up easy access to data for non-technical merchants, and
  2. Handle and analyze massive amounts of data from web, mobile, and in-store systems...

...all in seconds.

With ThoughtSpot, these merchants can ask questions throughout the day and get instant answers about thousands of SKUs and product categories with year-over-year compares for any date range. For example, merchants can now identify which SKUs are performing best each week and use that information to adjust assortments and improve revenue.

Improved access to data has translated to 950 hours saved per week. Merchants can use this additional time to focus on buying and improving long tail sales performance.

How to democratize your data

But merchandise managers aren’t the only employees who benefit from a simple analytical search experience. ThoughtSpot opens up the last mile of data access for everyone. It can be useful for:

  • Store associates to analyze sales and transaction volumes by region and store in seconds to accurately forecast employee staffing and customer demand against company benchmarks.
  • Brand managers to get instant answers about product, customer, and sales data to deliver personalized experiences across every channel.
  • Merchandise planners to improve planning and optimize every store inch with instant access to sales and warehouse inventory levels across thousands of SKUs.
  • Operations managers to maximize efficiency with instant access to store staffing data and hourly order volumes to improve employee productivity.

Our digital universe is a growing at an insane rate. It’s doubling every two years and is expected to reach 44 zettabytes (or 44 trillion gigabytes) by 2020. How will you manage your corner? By taking the employee guesswork out of your retail operations, you can get the full picture of your assortment and deliver a more personalized shopping experience

To see ThoughtSpot in action, check out a 3-minute retail demo here.

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