AI Solutions for Retail

We harvest the power of data by combining internal customer footprint with vast amounts of external knowledge

Up to 25p.p.

improved
forecast accuracy

Up to 30%

decreased
out-of-stocks

Up to 15%

decreased
stock levels

Use cases

Demand forecastingDemand forecasting

Unleash the full potential of your sales with maximized forecast accuracy

  • Better planning thanks to improved accuracy of forecast for every SKU
  • Fast and automated predictions
  • Out-of-stock incidence reduction

Demand forecastingPricing and promotion management

Employ AI to optimize your pricing and boost your promotion activities

  • Optimal pricing strategy based on demand forecast and price elasticity
  • Right promotions at the perfect time based on consumers sentiments
  • Accurate prediction of promotion impact on your sale of each SKU and for other products
  • What-if analysis to try several scenarios

Marketing optimizationMarketing optimization

Maximizing ROI on your marketing activities by implementing machine learning into customer analysis

  • Detecting customers with highest RoI on ads to take the most of your campaigns
  • Optimize your channel mix with advanced attribution models

Supply chain optimizationSupply chain and assortment optimization

Just enough – that’s what your orders will look like thanks to accurate predictions and intelligent stock management

  • Minimize out-of-stocks and make your products always available for your customers
  • Decrease stock levels thanks to just-enough ordering

Let’s connect!

Are you curious if your business challenge can be tackled with AI?
Contact us and we’ll give you a free assessment and a quotation

Contact us!

Case study

Infusing retail analytics with image content extraction

Project challenge:

Thousands of new FMCG products flood the market every month. Nielsen harvests the product information directly from the images of packages. The process of manual extraction and data entry takes about 30 minutes per product.

Handling the task described above required delivering a complex solution consisting of multiple steps performed by several neural networks. Each is performing a separate task that involves image recognition and natural language processing.

Our solution reduces the time needed to gather and validate the data to less than 2 minutes. The deep neural networks-based system localizes the list of ingredients on the label, scans it and puts it into the proper column in the database. At the same time, the data is being cleared from noises and redundancies, delivering standardized information.

About Nielsen:

  • An S&P 500 company
  • $6,5 B revenue
  • 46,000 employees

Project highlights:

  • automatic confidence assessment of the extracted content
  • support for multiple data formats
  • scalable, high-throughput cloud solution

Success stories

Infusing retail analytics with image recognition

    Nielsen Holdings 93% reduction in data gathering time by reducing the amount of manual work Learn more

    #retail#computervision

    Identifying customers with highest ROI on ads

      A CEE leading fashion retailer 2,5x higher uplift from advertising Learn more

      #retail #dataanalytics

      Attribution optimization and strategic data consulting

        A CEE leading fashion retailer Effective online advertising campaigns and significant cost reduction Learn more

        #retail#dataanalytics

        Read more about AI in Retail

        A comprehensive guide to demand forecasting

        May 28, 2019Everything you need to know about demand forecasting - from the purpose and techniques to the goals and pitfalls to avoid.

        Read more

        Powering up demand forecasting with machine learning

        December 6, 2018Demand forecasting is done by analyzing statistical data and looking for patterns and correlations. Machine learning takes the practice to a higher level.

        Read more

        Don’t waste the power. AI supply chain management

        December 13, 2018Just imagine what your business could do if it recouped 6500 man-hours annually.  Or a power supply savings comparable to all the Austin, TX usage?

        Read more

        How to create a product recognition solution

        August 22, 2017Product recognition is a challenging area that offers great financial promise. Automatically detected product attributes in photos should be easy to monetize, e.g., as a basis for cross-selling and upselling.

        Read more

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          Find us
          • deepsense.ai, Inc.
          • 2100 Geng Road, Suite 210
          • Palo Alto, CA 94303
          • United States of America
          • deepsense.ai Sp. z o.o.
          • al. Jerozolimskie 162A
          • 02-342 Warsaw
          • Poland
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