Retail

The omnishopper has triggered major changes in the retail industry. This technological evolution has exceeded the needs of today´s businesses and customers, generating the new Retail 4.0 based on:

  • Combining and blending the physical and digital channels
  • Moving from multichanneling to omnichanneling
  • The omnichannel shopping experience: showrooming and webrooming
  • Promotions that are more personalized and complete
  • Loyalty programs with value contribution
  • Customized stores to create faster and more enjoyable shopping
  • Store layouts conceived for customers not the distributor
  • Intelligent shopping carts
  • Fast and efficient payment methods
  • Dynamic and intelligent prices
  • Products, promotions, stock, information… all online

Through knowledge Cognodata has acquired in the retail industry, we are able to offer a wide selection of solutions and services oriented towards the improvement of the customer experience.

New transformation of business models based on new analytic technologies and the needs of the omnishopper.

  • Customer

    Identify the profitable target audience through profiles.

    Develop engagement programs with rewards that go beyond points or general discounts, through the creation of a personalized shopping experience which recognizes each customer and provides differential treatment.

    Attracting new customers requires leverage of personalized omnichannel marketing that uses customer profile blending, loyalty programs, real-time events and social interaction to provide customers with the perfect shopping experience. To accomplish this, it is necessary to redefine customer relationships, and to move from reactive to proactive actions through different channels that are embodied in the commercial plan:

    • Customer Program
    • Customer Experience (CX)
    • Customers Intelligence Journey (CIJ)
    • Segmentation
    • Commercial Plan
  • Product

    Our shopping cart analysis techniques and advanced prediction and simulation models allow us to build recommendation engines, thereby achieving the optimization of the main levers of the business in terms of price, promotions and inventory.

    • Optimization of stock assortment
    • Pricing
    • Promotion Analytics
    • Inventory management: unknown losses, out of stock and expiration date management for fresh products
    • Retail Link: improvement of supplier management
    • Strategy design for brand manufacturer vs. distributor
  • Store

    In-store digitalization and Big Data provide a detailed vision of in-store shopping behavior and enable the optimization of commercial operations to boost brand value and the shopping experience:

    • Geolocate your customers
    • Local marketing and digital signage
    • Point-of-sale (PoS) loyalty
    • Store Intelligence
    • Staff management
  • Marketing

    When we seek to meet the needs of the omnichannel customer with new product offers or marketing promotions, we must deepen our knowledge of the customer through Machine Learning and algorithms that sustain recommendation engines and allow the industrialization of customer management processes:

    • Marketing Studies
    • Analytics and Reporting
    • Personalized Campaigns
    • Media
    • Contact Center Management

Identify the profitable target audience through profiles.

Develop engagement programs with rewards that go beyond points or general discounts, through the creation of a personalized shopping experience which recognizes each customer and provides differential treatment.

Attracting new customers requires leverage of personalized omnichannel marketing that uses customer profile blending, loyalty programs, real-time events and social interaction to provide customers with the perfect shopping experience. To accomplish this, it is necessary to redefine customer relationships, and to move from reactive to proactive actions through different channels that are embodied in the commercial plan:

  • Customer Program
  • Customer Experience (CX)
  • Customers Intelligence Journey (CIJ)
  • Segmentation
  • Commercial Plan

Our shopping cart analysis techniques and advanced prediction and simulation models allow us to build recommendation engines, thereby achieving the optimization of the main levers of the business in terms of price, promotions and inventory.

  • Optimization of stock assortment
  • Pricing
  • Promotion Analytics
  • Inventory management: unknown losses, out of stock and expiration date management for fresh products
  • Retail Link: improvement of supplier management
  • Strategy design for brand manufacturer vs. distributor

In-store digitalization and Big Data provide a detailed vision of in-store shopping behavior and enable the optimization of commercial operations to boost brand value and the shopping experience:

  • Geolocate your customers
  • Local marketing and digital signage
  • Point-of-sale (PoS) loyalty
  • Store Intelligence
  • Staff management

When we seek to meet the needs of the omnichannel customer with new product offers or marketing promotions, we must deepen our knowledge of the customer through Machine Learning and algorithms that sustain recommendation engines and allow the industrialization of customer management processes:

  • Marketing Studies
  • Analytics and Reporting
  • Personalized Campaigns
  • Media
  • Contact Center Management

We are immersed in a business transformation pushed by the current capabilities of technological analytics that gave rise to what we call Retail 4.0. In this scenario, the omnishopper requires a satisfactory shopping experience that interacts with all channels.

Daniel Encinas Oñate Senior partner of the Retail & CPG practice
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