What is Retail Merchandising?

The process by which retailers, brands, and other product firms make their goods available in stores is referred to as retail merchandising. Each retail establishment has a unique product line that it sells to customers. The merchandise presentation is crucial when it comes to drawing clients into the store and encouraging them to make purchases.

So why is retail merchandising crucial?

Location intelligence is a critical tool for businesses seeking to optimize their merch mix strategy, particularly in India, where customer preferences can vary widely depending on geographic location. Without location intelligence, businesses risk placing the wrong products in their stores, resulting in suboptimal product visibility and potentially lost sales.

In addition to regional differences in customer preferences, there are often significant variations in affluence levels and demographics within cities. By leveraging location intelligence data, businesses can better understand these local nuances and tailor their merchandising strategies to meet the specific needs of each location.

Failing to leverage location intelligence can lead to serious consequences for businesses, including lost sales, decreased customer loyalty, and ultimately, a negative impact on revenue. Without access to accurate data about customer preferences and local trends, sales executives may suggest the wrong products to customers, resulting in a poor shopping experience and lost sales.

Ultimately, businesses that fail to utilize location intelligence run the risk of falling behind their competitors and losing market share. With so much at stake, it is essential for businesses to leverage the latest location intelligence technologies to ensure that they are making informed decisions about their merch mix strategies.

An essential component of a store’s marketing strategy is retail merchandising. In the following ways, effective retail merchandising can be beneficial:

1. Increased overall sales: Effective retail marketing creates an appealing shopping environment that attracts customers and encourages them to make purchases. Effective merchandising can increase sales and profits by highlighting specific products or product lines, improving product visibility and accessibility, and encouraging impulse purchases.
2. Increased consumer satisfaction: A store with successful retail merchandising has a pleasing appearance. Consumers are more likely to be satisfied when they can find the things they need with ease.
3. Inventory turnaround: It helps retailers manage their inventory and product mix effectively. By tracking sales data and customer preferences, merchandisers can make informed decisions about which products to stock, how much of each product to order, and how to display them in-store or online.

Retailers can make great use of location intelligence to serve clients in a specific catchment region to differentiate themselves from their competitors. A company’s promotional strategies can incorporate location intelligence marketing. Location intelligence marketing is the practice of determining your marketing strategies using relationships between geospatial data. Geotagging makes this approach easier.

It enables the blending of geotagged data with the client, retail, or local demographic information. The outcomes can be understood by overlaying this on a map. The display of this data can assist you in finding new markets to target, contacting leads and prospects, and even enhancing the value of each existing customer by offering individualized care.

How can GeoIQ improve merch-mix?

1.  Optimize the planogram:: Using location data and analytics to adjust the store’s layout can improve product visibility, boosting sales of popular products. Retailers can optimize the planogram by placing top-performing products in high-traffic areas and adjusting placement as needed.

2.  Categorize products: By sorting products based on sales volume and popularity, retailers can optimize inventory management, reducing costs by eliminating underperforming products while ensuring high-demand items remain in stock.

3.  Identify cross-selling opportunities: Leveraging data analytics to identify related products can increase basket size and sales. This can be achieved through personalized recommendations and strategic placement of related items in proximity to each other.

4.  Offer personalized recommendations: Retailers can improve customer experience and increase loyalty by leveraging data analytics to offer tailored recommendations based on previous purchases, preferences, and behavior. This can be achieved through targeted marketing campaigns and personalized product recommendations.

5.  Analyze location data: By examining foot traffic patterns, retailers can identify high-traffic areas and underperforming sections of the store, helping them make informed decisions about product placement and merchandising.

6.  Test and iterate: By continuously testing and iterating on merchandising strategies using data analytics, retailers can stay ahead of the competition and make data-driven decisions. This can be achieved through careful measurement and analysis of the impact of changes to the store’s layout, product offerings, and marketing campaigns.

Improving the merch mix in a retail store with the help of location data and analytics can help retailers optimize their product offerings and increase sales. Here are some points that can be advantageous:

• Analyze the location data: Use location data to understand the foot traffic patterns in the store. Analyze where customers spend the most time and which areas of the store are visited the least. This data can help you identify high-traffic areas and underperforming sections of the store.
• Categorize products: Categorize products based on their popularity and sales volume. Analyze which products are selling the most and which are not. This information can help you determine which products to keep in stock and which ones to discontinue.
• Cross-selling opportunities: Data analytics also helps in identifying cross-selling opportunities. For instance, if customers frequently buy a particular product, consider placing related items nearby. This can help increase the overall basket size and boost sales.
• Planogram optimization: Use location data and analytics to optimize the store’s planogram. The planogram is a visual representation of how products are arranged on shelves and displays. Analyze which products are selling the most and adjust the planogram accordingly.
• Personalized recommendations: Use data analytics to offer personalized recommendations to customers. For instance, if a customer has purchased a specific item before, use that data to suggest other products that are related to their previous purchase.
• Test and iterate: Continuously test and iterate on your merchandising strategies. Use data analytics to measure the effectiveness of your changes and adjust accordingly.

Improve merch-mix in-store with location data and analytics:

GeoIQ adds a location data layer to companies’ analytics and intelligence systems to improve decisioning with actionable insights.

Possibilities with Retail IQ:

Let’s take an example of an eyewear brand that is seeking insights on what price, colors, or designs the users prefer. They are using lagging indicators that are time-consuming and yield less accuracy on what a user is searching for. They’re also looking to hook new users in the first go by targeting customers on the basis of where each of their products sells the most which will eventually reduce their bounce rate.

GeoIQ has developed a powerful tool that can accurately predict the expected revenue of a new store in any location across India. This is achieved by leveraging a revenue model that allows for an estimate of what kind of revenue can be expected from a prospective location, thereby helping with the operational budget planning.

Furthermore, GeoIQ’s white-space analysis capability can identify potential locations to expand a company’s operations. These locations are usually high-traffic areas like high streets, malls, etc., where several brands are operating in close proximity.

GeoIQ provides critical information about these potential locations, such as the average restaurant cost for two in the area, the income level of the households in the vicinity, etc. These indicators are discovered by the ML model to have an impact on the performance of a new store. This data helps to understand the spending pattern in the area and to make informed decisions. One can also filter prospective locations by evaluating only areas that provide a certain minimum revenue, thereby reducing the risk of operating in low revenue-generating areas.

The all-inclusive retail system known as RetailIQ takes care of everything from site selection to determining the merchandising mix of each individual store. Forecasting sales and revenue, enabling intelligent reporting, and much more.

City-level Analysis:

Access to street-level hyperlocal intelligence for more than 300 cities across tiers is available. Micro markets are no longer relevant; instead, we provide suggestions for you based on catchments as small as 100m x 100m.

Build your site report:

Generate, analyze, and measure your ideal site location to scale your brand expansion. A one-page report providing a brief about revenue score, demography, and other vital attributes to help you make a data-driven informed decision for your next optimal retail location. Get 20 free credits to derive insights for 20 different locations.

Based on the presence of optimal location characteristics that are shared by successful stores. Similarly, demand prediction algorithms can offer site suggestions and preference scores for the placement of fulfillment facilities. Retail IQ’s ability to deliver timely, accurate, and actionable insights is a key differentiator, helping businesses stay ahead of the competition and drive success.

A store’s locations can be augmented with 3000+ location attributes by GeoIQ. These variables can capture different characteristics of the location from

-Demographics including population, age, income, etc.

-Retail Presence including luxe brand counts, value brand counts, competitors, etc.

-Commercial Indicators which include variables around rents, the average spending on food, etc. spending patterns in the area, income levels of households in the area etc.

Revenue prediction and site economics:

Location data and intelligence allows you to hyper-locally target your marketing campaigns and communications for varying target groups. Forecast revenue with up to 96% accuracy and assign scores by analyzing different attributes like; high density of commercial establishments, population, presence of hospitals, restaurants etc. Geo-locate your target audience and find look-alike locations to reach out to your ideal users. The model is able to identify locations with low revenue potential with an accuracy of 98% and with very high revenue potential with over 85%.

Fleet app/ field assistance:

An application that is simple to use and allows the field force to scout potential areas and communicate with the central teams. The Fleet App enables real-time information flow for business execs., rent decision, floor decision, negotiating power, and more.

Overall, using location data and analytics can help retailers optimize their merch-mix and drive sales. By understanding customer behavior, categorizing products, identifying cross-selling opportunities, optimizing the planogram, offering personalized recommendations, and continuously testing and iterating, retailers can improve their retail merchandising strategies. As recommendations become more relevant, they translate into purchases. Therefore, augmenting your existing recommendation systems with location data and insights will increase the share of revenue coming from recommendations and let you make more informed decisions for your retail merchandising project.

For more details please get in touch with us at hello@geoiq.io, or visit our website https://geoiq.io/.