Retail


Retail Analytics

Retailers thrive – or wither – by mastering their supply chain, optimizing pricing, understanding customers, and ultimately selling stuff. As retailers mushroom in size, format, and scope, success will increasingly rely on timely, insightful decisions to do these things exceedingly well.

Lots of data is already available to retailers to make good decisions – from loyalty programs and web analytics to third-party information and point-of-sale details. But there’s a big gap between having the data and putting it to work for you. Tableau’s analytical depth and visualization capabilities can help improve your retail analytics by allowing you to:

  • Create interactive dashboards that support real-time decisions
  • Incorporate geographical-based data for targeted segmentation
  • Blend multiple data sources for more robust analysis

 

Industry Trend

Industry trends at your fingertips

Retail is highly volatile business, particularly during economic recessions. This makes tracking industry trends all the more important to both large and small retailers.

No matter what product segments you operate in, you probably have questions about your industry. How are things going overall? Are we out of the recession yet? What time of the year do people like to shop? How is my product segment doing? Do some product segments perform better than others?

 

 Segmentation

Understand your local customers

What do customers at Store #283 really want? It’s likely to be at least slightly different than those heading to Store #59. Use all the information you have about customers to make informed decisions about your product mix. Urban sites probably sell more small items than suburban stores where customers can fill their trunks with bulky things. And stores catering to an elderly population should carry a different selection than those with a high number of twenty-somethings to optimize customer satisfaction – and sales. This visualization explains who’s who in a store’s neighborhood. Do they buy more hard goods or soft? Is there an age concentration that informs what should be stocked? Does the mix vary as you move towards or away from competitive stores?

 

Pricing and Supply

Make inventory decisions with more insight

Inventory is often the retail KPI that determines success. Getting the balance just right – not too much, not too little – is retail nirvana. How do you create this crystal ball? It relies on aggregating the right data and then visualizing it in a way that lets you make informed decisions.

This visualization offers one way that inventory, shipping, pricing, and sales data can be viewed in one place, driving better pricing and purchasing decisions. What’s the current view on our over/under inventory by product? What happens if we raise – or lower prices.

 

 Planogram Results

Back of the store - or the front? A store’s layout drives competitive differentiation and sales. So how can you determine the best approach? Use data to turn layout decisions from art to science

Retailers are redefining how they prioritize product placement by visualizing their data. By aggregating data about how products perform in a single view, merchandisers can make informed decisions for to boost a store’s sales, which products to promote, and how decisions should vary by store format.

The image provides a view of the shelf and lets you start asking and answering questions about the department's performance in various store formats.

 

 Project Planning

Set priorities and know what’s ahead

Successful retailers master the balance of inventory, pricing, marketing, and supplier relationships to maximize revenue and margins. When the same mentality is applied to a retailer’s project planning, the impact on your team’s time and spending decisions result in big impacts.

Visualizing how projects inter-relate and are prioritized is essential to making good decisions with scarce resources. In the example to the left, team members from executive leadership to individual contributors can quickly understand priorities and next steps. Which are high priorities and which will take the most time?