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Evaluating your grocery portfolio for optimization
Manually evaluating portfolio performance can be slow and strenuous. To streamline this process, SiteZeus’ Quadrant Recommendations categorizes your locations into four simple categories: Study, Grow, Relocate, or Optimize. Locations are sorted by analyzing their actual sales against projected sales. For instance, a site might currently be performing below average, however, SiteZeus projects that the site could be performing well above average. This site would subsequently be categorized under Optimize, helping quickly highlight opportunities for optimization. While this is just one example, brands use all four recommendation categories to determine their true portfolio potential and guide their optimization strategy. Users can study, test, and act on insights all in one platform.
Retail closure analysis with customer segmentation data
The pandemic forced many multi-unit brands to close their doors. While some sites are beginning to reopen, others will remain permanently closed. As brands analyze whether to close or reopen their existing sites, demographics will play an essential role. However, demographics alone does not depict the whole story. The missing piece? Geosocial customer segmentation data.
Satisfying America’s post-pandemic appetite
When COVID-19 brought the restaurant industry to its knees in February 2020, an interesting phenomenon occurred; everyone from hometown eateries to major multi-unit brands temporarily offered takeout and delivery to survive. Meanwhile, companies with pre-established off-premises systems (i.e. Chipotle), enjoyed increased revenues.
Building a fast and accurate predictive model for your grocery brand
Building a predictive model means gathering, cleaning, analyzing, and testing data; a process that can take months. SiteZeus allows your brand to skip this lengthy process and jump straight into using its highly predictive model. SiteZeus converges multiple datasets (brand data, population, mobile, geosocial, and more) to provide the machine learning with everything it needs to build a highly predictive model. By comparing each site’s predicted and actual revenues, SiteZeus even tests itself for accuracy. Brands are able to simply log in and begin using their predictive model 24/7.
SiteZeus awarded best innovation in artificial intelligence prize at 2020 Devies Awards
The Devies Awards, the definitive award for the Development Technology Industry, has named SiteZeus the winner of their 2020 prize for Best Innovation in Artificial Intelligence and Machine Learning. The award is in recognition of SiteZeus’ groundbreaking achievements in creating an A.I. platform that is able to solve numerous market planning problems faced by the multi-unit brands.
25 Top multi-unit brands leveraging A.I. in 2020
With a new decade under way, multi-unit brands like Kroger, Uniqlo, McDonald's, among many others, are starting to leverage the potential of Artificial Intelligence (A.I.) across various functions of their business.
The future is now: How multi-unit brands are leveraging A.I. today
Whether we realize it or not, Artificial intelligence (A.I.) is starting to become a part of our daily fabric. From electronic assistants like Alexa and Siri to business tools like Salesforce and Gmail, A.I. has proved to be a powerful technology that helps improve the way we work and live. Listed below are ten examples of brands that are harnessing the power of A.I. to solve for some of their business challenges.
Slideshare: How Site Sonar helps with White space analysis
White space analysis, the process that helps brands identify new and existing untapped market potential, used to take months. In this SlideShare, you’ll learn how you can cut that process down to minutes—and get unprecedently precise results—with SiteZeus’ Site Sonar solution.
Slideshare: How multi-unit brands can identify customers in seconds
These days, it is not enough for multi-unit retail brands to classify and find customers with demographics alone. Same goes for psychographics, loyalty data, and even purchase data. There’s something missing from the puzzle…
What makes your customer tick?
One of the fundamental building blocks for any business is knowing who your target customer is. While traditional data sources like demographics and psychographics help to give that customer a face with information, such as age, ethnicity, income, and education levels, these only reveal a part of the picture.
Retail brands look beyond A.I. to solve for locations
“Artificial intelligence is going to change everything, everything, 180 degrees…There is no way to beat the machines, so you’d better bone up on what makes them tick.” Mark Cuban, American businessman, and investor.