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Frequently Asked Questions

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You can read more about our use cases here to see how we have been able to help our customers. 

[/mkdf_accordion_tab][mkdf_accordion_tab title_tag=”h4″ title=”What sources of data do you use?”]

We utilize a combination of external sources like competitor information, weather patterns and social media conversation and internal data sources like historical sales.  Once we collect, clean, and feed the data into our machine learning algorithms, we can provide essential recommendations on how to improve your business.

[/mkdf_accordion_tab][mkdf_accordion_tab title_tag=”h4″ title=”What kinds of models do you build?”]

We offer two types of predictions – a pre-season model to help buyers and merchandise planners buy smarter and more accurately and an in-season model that forecasts sales out for the next six month period.

[/mkdf_accordion_tab][mkdf_accordion_tab title_tag=”h4″ title=”How accurate is your data?”]

With traditional forecasting methods,  merchandise planners and buyers can take up to six weeks to make predictions for an upcoming season and a 55% average accuracy in identifying best to worst sellers. Alternatively, our algorithms can automate the process and reduce the forecasting calculation time to two hours. and improve the accuracy rate in the best-worst sellers to 85%.

[/mkdf_accordion_tab][mkdf_accordion_tab title_tag=”h4″ title=”What is your limit to data volume or SKU numbers?”]

We do not have any limitations on the number of SKU’s we can model.

[/mkdf_accordion_tab][mkdf_accordion_tab title_tag=”h4″ title=”What countries do you currently support?”]

Currently, we support any English-speaking country, as well as China.

[/mkdf_accordion_tab][mkdf_accordion_tab title_tag=”h4″ title=”What ROI can I expect?”]

On average, brands and retailers that implemented our solution were able to automate many tasks in the merchandise planning process and saw a 9x return on investment. 

[/mkdf_accordion_tab][mkdf_accordion_tab title_tag=”h4″ title=”Do you support offline retailers?”]

Yes, we work with online and offline retailers, as well as omni-channel retailers Our services are ideal for retailers, brands and wholesalers.

[/mkdf_accordion_tab][mkdf_accordion_tab title_tag=”h4″ title=”How safe is my data?”]

As a company that offers predictive analytics services, data privacy and protection is of the utmost importance for us. Read through our Privacy Policy page to get a better idea on our data practices.  

[/mkdf_accordion_tab][mkdf_accordion_tab title_tag=”h4″ title=”Do you work with companies outside of the fashion industry?”]

While we primarily focus on fashion retailers and brands, our services are open to all retailers, provided there is enough data. 

[/mkdf_accordion_tab][mkdf_accordion_tab title_tag=”h4″ title=”What are your system requirements?”]

We house our predictions on our cloud-based platform so you will need a website browser (Safari/Chrome/Firefox) and internet access. 

[/mkdf_accordion_tab][mkdf_accordion_tab title_tag=”h4″ title=”How long does it take to set up and start using your product?”]

When it comes to starting our services, you can begin immediately by first requesting a demo. In regards to the process of getting things set up, we initially go through a 3-month piloting period where we analyze and identify user’s key pain points. To find out more about the details of our process, click here.

[/mkdf_accordion_tab][mkdf_accordion_tab title_tag=”h4″ title=”Can we access your products on mobile or tablet?”]

We currently do not have a mobile or tablet version, however, our application is mobile responsive.

[/mkdf_accordion_tab][mkdf_accordion_tab title_tag=”h4″ title=”Is there a limit to the number of teams that can share a login?”]

We do not restrict the number of users that can share a login as we do not operate on a per-use license model. 

[/mkdf_accordion_tab][mkdf_accordion_tab title_tag=”h4″ title=”How does your machine learning AI leverage price optimization and automation?”]

We start off with a 3-month pilot process where we analyze and identify user’s key pain points. From there, our machine learning algorithms learn and process the mass amounts of data, quickly discovering insights that may have been hidden to the average human eye. 

[/mkdf_accordion_tab][mkdf_accordion_tab title_tag=”h4″ title=”Can users share access to the platform?”]

Yes, multiple users can have their own individual logins as we do not charge based on the number of users.

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