RetailIQ: Unlock Limitless Growth Opportunities

As retailers strive to maximize sales and demand planning, accessing accurate and relevant data is crucial. It helps in making informed decisions about store expansion and fulfillment centers. Sophisticated location data and intelligence platforms like RetailIQ by GeoIQ provide prompt, precise, and practical insights to aid retailers. This article explores how location data and analytics enhance the retail expansion process. It also delves into the functionalities of RetailIQ by GeoIQ, a comprehensive platform covering site selection and merchandising for individual stores.

Why Consider Location Data and Analytics?

Augmenting the retail expansion process with location data can have a significant impact on a retailer’s ability to make informed decisions by:

1. Identifying high-potential locations: Location data helps retailers identify areas with high foot traffic, population density, and disposable incomes. Retailers can use this information to identify potential store locations and understand customer distribution for strategic decision-making.

2. Optimizing store layouts: Location data can help retailers understand how customers move through their stores and where they spend the most time, allowing them to optimize store layouts and product placements. This can improve the overall shopping experience for customers and increase sales for the retailer.

3. Targeting marketing efforts: Location data can be used to target marketing efforts to specific geographic areas, allowing retailers to tailor their messaging and promotions to local customers. This can increase the effectiveness of marketing campaigns and drive more traffic to stores.

4. Monitoring competition: Location data can help retailers monitor the locations of their competitors and understand how their stores are performing in comparison. This can inform decisions about where to open new stores and how to position products and promotions.

When recommendation engines are backed by location data, brands are able to add another layer to their models and make more pin-pointed decisions. It further filters out the ambiguity when figuring out best-fit products for user segments.

RetailIQ by GeoIQ:

The ultimate ML-backed retail expansion platform’s demand prediction algorithms can offer site suggestions and preference scores for the placement of fulfillment facilities. RetailIQ’s ability to deliver timely, accurate, and actionable insights is a key differentiator, helping businesses stay ahead of the competition and drive success.

  • Quantifying hyperlocal insights in <1 sec.
  • efining search at per sq. km granularity, i.e., substantially more granular than pin codes
  • Field assist application for field force to scout shortlisted locations
  • Revenue prediction with up to 96% accuracy
  • Merch-mix prediction and sales forecast

RetailIQ Functionality:

RetailIQ is an all-encompassing solution for retail that covers everything from site selection to defining the merch mix of each individual store. From sales and revenue forecasting to enabling intelligent reporting and much more.

With a few simple questions, the platform takes into account the line of business, product types, and similar or complementary brands. Competing or complementary brand data is crucial when a retail business is opening its first store and lack historical data due to no existing locations.

1. 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.

Sample Report for GeoIQ, Urbanvault 591, 22nd cross, 15th Main Rd, HSR Layout, Bengaluru, Karnataka 560102
Vital attributes
Insights into demographics and the presence of brands in the area

2. Site Recommendations:

RetailIQ is an ultimate and powerful site selection platform for enabling real-time site recommendations with street-level prioritization. Even if a store is a street away from the ideal location, the impact on the revenue could be massive. It is time that brands eliminate gut work and judgment calls in their expansion decisions.

The brief idea behind optimizing the expansion plan for a business is to identify the best existing stores. This involves finding new locations using real-world data with similar conditions. These conditions include socio-economic factors, demographics, infrastructure level, population density, and more. Look-alike locations that meet these criteria are considered promising spots for setting up new stores. This is because they have the potential to replicate the success of high-performing stores.

If the brand does not have existing stores, another approach can be taken. This involves analyzing the data of a complementary brand. The goal is to identify look-alike locations based on similar criteria. These locations can be highlighted with scores to indicate their potential suitability for the brand’s expansion.

By identifying the geo-characteristics of the addresses that your target group (TG) possesses, a machine learning model can replicate the same learning. This model applies the learned patterns to new locations in order to find regions that resemble the target group.These regions are the ones where you would find new users that match your ideal user persona. We process many kinds of data, break it down to a street level using proprietary algorithms, and provide insights about users from a location perspective.

About GeoIQ:

GeoIQ provides street-level answers for potential sites across all cities within Indian boundaries. Our data and the insights derived from it are dependable. We use customized proprietary algorithms to obtain information from over 600 government and public data sources. This information is classified into more than 3000 location variables, making it simple to review.

data flow for site report
retailiq's recommended locations
Get a list of your recommended locations with detailed insights

3. Shortlist or Reject Locations:

Stakeholders can compare the potential revenue generation of different locations by assigning scores based on the success metrics for each recommended location. Easily shortlist or reject locations from the list of recommended locations. The decision could be based on the location scores and other characteristics critical to the brand. Once the locations are rejected or shortlisted they get bucketed in two categories on the platform as well as the fleet app available with the field teams.

4. Fleet App:

An application that is simple to use and allows the field force to scout shortlisted locations and communicate with the central teams to provide feedback in real time. The Fleet App enables real-time information flow for business executives, rent decisions, floor decisions, negotiating power, and more.

Conclusion:

RetailIQ is an advanced site selection platform that uses hyperlocal insights to provide real-time site recommendations with street-level prioritization. It offers a level of refinement at a per sq. km granularity that is substantially more granular than traditional pin codes. As far as data security is concerned, GeoIQ is also backed with the SOC 2 Type II security designation. This achievement highlights the company’s commitment to maintaining the highest standards of security and data protection. We aim to integrate various channels and expand the use of location data and intelligence tools. By leveraging alternative data sources, we will improve decision-making in optimizing e-commerce deliveries, targeting marketing, segmenting customers, and monitoring demand. These opportunities will enhance our ability to make informed decisions and drive business growth.

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.

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