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11 Best Tableau Retail Dashboard Examples

Best Tableau Retail Dashboard Examples will be explained in this article. The use of data visualization software has increased recently. Tools for data visualization and business statistics are widely available. The more well-known ones include Qlikview, Tableau, Power BI, Grafana, and others. The topic of Tableau will be covered in this essay. Most of the top 100 retailers and more than 7,000 retail and consumer goods businesses worldwide use Tableau, one of the top platforms.

The platform helps business and organizational leaders visualize and understand data, and generate actionable insights for improved decision making. Tableau accomplishes this by offering quick and simple methods for examining data, creating dashboards, and running ad hoc analyses.

No matter where you are in your data analytics journey, you can visualize your data and gain a deeper understanding of your company through the Tableau retail dashboards. Additionally, dashboards provide you with the business intelligence you need to have a significant impact on your company and obtain a competitive advantage.

To help you learn how to use visual analytics for competitive advantage and to try them out so you can see the power of visual analytics in action, we’ve put together a collection of Tableau retail dashboard examples.

11 Best Tableau Retail Dashboard Examples

In this article, you can know about 11 Best Tableau Retail Dashboard Examples here are the details below;

1. Store operations

Store operations

Physical stores are still essential for success because they make for a sizable portion of retail sales despite the mobile world having a significant impact on the retail operations.

Store operation dashboards for retail businesses can provide region or store managers, as well as the corporate office, with rich and valuable insights about the performance and execution of the company. With the help of these dashboards, managers can more effectively compare the performance of their stores across an area in terms of foot traffic, sales, average transaction value, year-over-year growth, and units per transaction. Also check directv internet speed

Managers can also compare space efficiency in the store, the performance of the product department, and the top-selling brands, as well as drill down to specific and distinctive store-level operations data.

The store’s activities Tableau’s retail dashboard provides a summary of business operations, including revenue trends and development, customer traffic and conversion rates, and average transaction value. This enables managers to quickly spot underperforming stores by comparing their numerous stores to those of their peers in their particular region.

Indexes of critical performance with current values for important retail metrics A histogram showing the conversion rate and results in relation to conversion A quick look at daily sales for their shops to compare how well sales have performed during different times of the year, events, holidays, weekdays, or weekends To use the right combination of labor during high demand, consider how sales are distributed between weekdays and weekends.

2. Products Availability

The availability of products at current stock levels is one of the biggest problems facing retail shops today. For customers to discover and buy the right product, the stock levels in the right stores must be just right. Retail establishments calculate lost sales when customers are unable to purchase a product due to incorrect inventory levels or being out of supply.

Every time they visit a store, customers of supermarkets in especially want to be able to do all of their shopping underneath one roof.

When this isn’t feasible, the retail store risks losing both the entire basket and any subsequent baskets they would have gotten from the original basket in addition to measuring lost sales.

When compared to other industries, the supermarket and grocery store industry loses 5% of distribution sites, but overall product availability is 95%. Sales loss by this 5 percent could amount to billions.

Retailers typically measure and analyze the product availability in terms of percentages, but this does not correctly highlight the problem when measured in terms of the distribution points that were missed.

Instead of locating the goods and locations that will have the greatest effect, retailers wind up wasting resources trying to repair low sales products with low availability rates or low distribution.

With the aid of this Tableau retail dashboard, retailers can find ways to close efficiency gaps and interactively drill into the specifics, which will help them address the issues of having the appropriate product, inventory levels, and stores.

In order for the retailer to interact and drill into the insights displayed, it also has a color scheme that rapidly draws the user’s attention to the biggest issues.

The following are some of the details you’ll learn from this retail dashboard:

  • Information for various groups
  • The worst issues by merchandise
  • Marks in sample currency on lost revenue
  • Using the worst offenders to filter store areas and products, stores that require more stock can be acted upon.
  • The previous seven days’ availability
  • Product stock information

Additionally, you can work together with your team or export the goods to a.CSV file. Any appropriate team may receive this file and take further action by sharing it with them.

3. Merchandising Assortment

Category managers and merchandisers need a quick method of analyzing the demand data in order to make profitable choices about the products that customers want.

They can examine demand statistics by sales and profit margin performance by sub-categories, departments, or brands using a retail dashboard.

Using Tableau’s merchandising assortment retail dashboard, managers can:

  • Find out quickly how well various categories and their subcategories, including those that can account for a significant portion of sales, have performed in terms of relative sales performance.
  • View the market share of national and private label companies as well as deeper insights into characteristics like color, shape, product category, and style that can increase conversion.
  • A vendor’s costs may be renegotiated if you pay attention to outliers and high volume sales products.
  • Place underperforming products in other shop locations designated for clearance.
  • observe periodic patterns
  • Identify the best-selling items and concentrate on them.
  • Managers can use all of these demand data in real time for decision-making.

4. Waste Manager/Optimization

Data visualization can be used to spot food waste on fresh goods that are discounted or thrown away due to their shelf life running out. Retailers would like to reduce waste and save on them in order to have an effect on profits because waste costs them a lot of money in real revenues. Companies are under enormous pressure to decrease waste as a result of corporate responsibility and sustainability, particularly retailers and quick-serve restaurants. (QSRs).

Fortunately, it is possible to accurately identify wasteful items and get rid of the inconveniences associated with using big text files in spreadsheets. Retailers can take the necessary action by looking at waste at the shop level rather than in aggregate.

Retailers can take corrective action by changing product forecasts, facings, and delisting or removing them entirely from the menu by finding the issues in particular stores where there is high wastage. All of these actions may have an effect on waste reduction, but they may also result in consumer churn.

The information displayed on this Tableau waste manager/optimization retail dashboard is as follows:

  • Items that are in demand
  • The primary reason for the waste issue
  • Determine whether the issue is in one or more store categories by segmenting by store cluster.
  • Consistency of the issue over time, during campaigns, or in connection to particular occasions

The Waste Manager dashboard can be used by retailers to engage with data and identify waste-producing stores and clusters. The data can be exported or shared with the vendor or merchandising team as shops are chosen.

The business can then decide whether to live with waste in order to not inconvenience customers, remove the product from allocation at the risk of alienating or losing customers, or entice customers to choose ready-made products. Other options include lowering prices, engineering cost reductions while keeping margins, reducing pack/case quantities, and reducing stock levels to low-income stores.

5. Retail Scorecard

Since retail data frequently consists of siloed information that is challenging to access, analyze, or use as actionable information, a retail scorecard gathers all the key performance indicator screens in one location. Without switching to a different document or piece of software, top management can view the complete company across all functions.

When the manager accesses the dashboard, a drill-down dashboard designed especially for that task is available. The dashboard displays high-level cards with snapshots of each KPI.

Each card contains a number of filters that, with a single click, display various groups of data. Thanks to JavaScript functions, all of the background dashboards are pre-loaded, allowing each screen to open in under a second.

In this manner, managers can see the state of the company with specific action items and can do so without needing to be highly skilled in Tableau Desktop. However, any client team can create and/or manage the dashboard.

Managers have more time to concentrate on the bottom line thanks to such automated data analyses. The system is straightforward to construct and can be used in all retail situations while keeping speed to insight in mind.

6. Weather Response Predicted Demand

Retailers can forecast extreme product demand spikes, including the locations that will be impacted, the particular goods, and the quantities, with the help of a weather response predicted demand dashboard.

Retailers must cope with consumer change, digitalization, and heightened competition. Extreme weather conditions and how people react to them, though, are essential to take into account. With the help of this Tableau retail dashboard, retailers can more quickly respond to emergencies and incorporate changing customer demands into their supply chain operations.

With machine learning at its core, the dashboard can rapidly analyze and glean insights from more than 73 billion historical NOAA weather data points, psychographics, inventory history, regional demographics, and retail sales history. By doing this, the merchants will have quick summaries of the demand to prepare for emergency weather events such as tornadoes, hurricanes, or floods, among others.

Retailers can obtain a clear summary of predicted and baseline demand, on-hand inventory, remaining gaps in required orders, and orders in transit by combining on-demand weather data with inventory data. This makes it possible for them to effectively allocate inventory and resources to make sure that supplies are supplied at the appropriate time and location.

The data can be drilled down by area, timeframe, and product category to focus on demand at the SKU, product category, day levels, and store levels for larger retailers with store footprints across the country or region. They can gather information this way to make decisions more quickly and mobilize the following actions. In order to ensure that customers receive assistance when they most need it, the data is also helpful in accelerating emergency reaction and recovery efforts.

7. Retail Store heat Mapping

Heat maps for retail stores increase sales in ways that grid-based or numbers-only sales flash updates could not. Visual analytics is a tool that modern retailers use to gain more knowledge about their physical shop environments.

Retailers can learn a lot about real store layout and performance using store heat-mapping analytics without wasting time by dispatching teams to each store.

Heat maps eliminate the need for manual guesswork by showing the shop layouts in an optimized manager. These maps use commonly used mapping technology and can receive, analyze, and store CAD maps like:

  • Locator assistance for goods
  • Amounts paid per cubic foot
  • Reset location and results for the season
  • Planogram conformity Sales rate
  • Revenue from fixtures and shelves

8. Regional Manager Dashboard

Improved decision-making based on the regional data and analytics you receive daily, weekly, monthly, quarterly, bi-annually, and annually is one of your top goals as a regional manager. By using these reports, you can gain operational insights from the point-of-sale databases, which can help your region and your company as a whole make decisions.

With the help of this Tableau regional manager dashboard, analysts can create guided visual analytics that are straightforward, basic, and easy to understand. Additionally, they widely spread data over extensive retail networks. Also check how to send large files free

The written analytics in this dashboard make it possible to clarify the context of the visualizations and guarantee that the information is used in a manner compatible with the leadership’s stated goals and strategy.

  • The dashboard combines written and visual analytics to lessen the amount of training required to understand the data.
  • You can benefit greatly from simply establishing a data-driven mindset, whether you share inventory analytics with the supply chain team or give KPIs for sales to physical stores.
  • According to the regional manager dashboard, The overall image of domestic sales and marketing
  • What is happening, as well as an explanation of the larger backdrop for why it occurs and how it is relevant
  • Users can quickly spot events, trends, and KPIs without misinterpreting the data thanks to visual and written analytics for simple data exploration.
  • Role-based insights to provide supervisors with the full context they need to take action
  • Performance of each store in relation to the overall business
  • With all this information, regional managers can pinpoint the underperforming shops and concentrate on the merchandise and divisions that require improvement.

9. Marketing Mix Models and ROI Engines

Combining sales activity and marketing success measurement can be challenging for many organizations. In actuality, these two measures are typically examined independently. To identify the marketing campaigns that have an effect based on direct sales, organizations can determine the actual sales performance and marketing spend together. Businesses can use this dashboard to improve their marketing mix and achieve the highest return on investment by applying machine learning to the underlying combined datasets. (ROI).

It is possible to determine the efficacy of sales and marketing by combining the two different and frequently siloed sources of data. In order for the campaigns to have a greater effect on raising sales revenues, machine learning can be used to maximize the marketing mix and generate ROI.

10. Marketing Consumer Segmentation

Every dollar that retailers expend needs to be examined, scrutinized, justified, and optimized. Additionally, they must be aware of their client’s identity, preferences, needs, and position.

Budgets for marketing are under a lot of pressure right now, so it’s crucial to prioritize certain customer groups and optimize spending. You can enhance the caliber of decision-making with detailed information from Tableau’s marketing customer segmentation dashboard.

KPIs can be measured by the sales effect, the designated market area (DMA), and the type of dominant cluster. This dashboard eliminates guesswork and provides a laser-like focus on important metrics that guarantee marketing gets to optimize every dollar invested, grow important customer segments, or regain the loyalty of clients who may be wavering.

11. Online shopping cart Analysis

Businesses can analyze how marketing campaigns, traffic sources, or the behavior of particular customer groups, among other factors, influence the shopping cart behaviors of their customers using the online shopping cart analysis.

To better comprehend customer behavior, this dashboard details how frequently customers remove things from their shopping carts as well as their motivations. In order for users to concentrate on real outliers, it also displays typical shopping cart removals along with the standard deviation visual band.

Additionally, you get to see details like:

  • Moving patterns in the positive

Determine whether you’ll choose to dropship from a vendor where warehouse inventory is low, raising delivery days, or whether there are any possible problems that could result in strategic price discussions and analysis. Customers choose alternatives and based on how long it takes to receive the merchandise. Also check best xfinity internet for gaming

Wrapping Up

Smart retailers need a data-driven strategy to help them make better decisions in a volatile environment where it’s critical to provide customer-centric experiences and customers’ behavior is constantly changing.

With the assistance of these 11 Tableau retail dashboard examples, retailers can view and comprehend data differently while gaining a strategic competitive advantage that uses granular, useful insights to create significant value.

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